U.S. patent application number 14/775190 was filed with the patent office on 2016-02-18 for kinematic and parameterized modeling for patient-adapted implants, tools, and surgical procedures.
The applicant listed for this patent is CONFORMIS, INC.. Invention is credited to Philipp Lang, Klaus Radermacher, Daniel Steines.
Application Number | 20160045317 14/775190 |
Document ID | / |
Family ID | 51537926 |
Filed Date | 2016-02-18 |
United States Patent
Application |
20160045317 |
Kind Code |
A1 |
Lang; Philipp ; et
al. |
February 18, 2016 |
Kinematic and Parameterized Modeling for Patient-Adapted Implants,
Tools, and Surgical Procedures
Abstract
Patient-adapted articular repair systems, including implants,
instruments, and surgical plans, and methods of making and using
such systems, are disclosed herein. In particular, various
embodiments include methods of selecting and/or designing
patient-adapted surgical repair systems using parameterized models
and/or multibody simulations.
Inventors: |
Lang; Philipp; (Lexington,
MA) ; Radermacher; Klaus; (Aachen, DE) ;
Steines; Daniel; (Lexington, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
CONFORMIS, INC. |
Bedford |
MA |
US |
|
|
Family ID: |
51537926 |
Appl. No.: |
14/775190 |
Filed: |
March 15, 2014 |
PCT Filed: |
March 15, 2014 |
PCT NO: |
PCT/US14/30001 |
371 Date: |
September 11, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61801865 |
Mar 15, 2013 |
|
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|
Current U.S.
Class: |
700/98 ;
703/1 |
Current CPC
Class: |
A61B 2034/105 20160201;
A61F 2002/30948 20130101; A61B 2034/2051 20160201; A61F 2002/30943
20130101; A61B 2034/108 20160201; G05B 2219/35134 20130101; A61B
2017/00526 20130101; A61F 2240/001 20130101; G05B 19/4099 20130101;
A61F 2/30942 20130101; A61B 34/10 20160201; A61B 17/15 20130101;
A61F 2002/30955 20130101; A61B 2034/2055 20160201 |
International
Class: |
A61F 2/30 20060101
A61F002/30; G05B 19/4099 20060101 G05B019/4099 |
Claims
1. A method of making an implant and/or jig for a patient, the
method comprising: receiving patient-specific image data;
segmenting at least a portion of the patient-specific image data;
performing a shape search of a case database of original implant
designs and/or jig designs; and if an original implant design is
found by the shape search that is a good match, selecting the
original implant design and/or a corresponding original jig design
for making the implant and/or jig for the patient.
2. The method of making an implant and/or jig of claim 1, further
comprising: if no original implant design that is a good match is
found by the shape search, designing a new implant design and/or a
new jig design based, at least in part, on the patient-specific
image data.
3. The method of making an implant and/or jig of claim 1, further
comprising: if no implant design that is a good match is found by
the shape search, deriving a statistical model match; adapting one
or more shape parameters of a parameterized model based on the
derived statistical model match; evaluating the adapted shape
parameter model a first time in a multibody simulation; if the
results of the first multibody simulation are good, generating an
implant design and/or jig design for making the implant and/or jig
for the patient from the adapted shape parameter model; if the
results of the of the first multibody simulation are not good,
subsequently adapting one or more shape parameters and evaluating
the subsequently adapted shape parameter model in a subsequent
multibody simulation; if the results of the subsequent multibody
simulation are good, generating an implant design and/or jig design
for making the implant and/or jig for the patient from the
subsequently adapted shape parameter model; and if the results of
the of the subsequent multibody simulation are not good, repeating
the steps above of subsequently adapting and evaluating the
subsequently adapted shape parameter model until the results of the
subsequent multibody simulation are good.
4. A method of making a patient-specific implant according to a
process as shown in FIG. 31.
5. A method of generating an optimized implant model according to a
process as shown in FIG. 32.
6. A method of performing a finite element analysis on an implant
model according to a process as shown in FIG. 33.
7. A method of selecting and/or designing an implant design and/or
a jig design for a patient according to a process as shown in FIG.
35.
8. A method of making a patient-specific implant according to a
process as shown in FIG. 36.
9. An implant produced according to the method of claim 1, 2, 3, 4,
5, 7, or 8.
10. A system for treating a patient comprising an implant produced
according to the method of claim 1, 2, 3, 4, 5, 7, or 8 and a jig
produced according to the method of claim 1, 2, 3, or 7.
Description
RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 61/801,865, entitled "Modeling, Analyzing And Using
Anatomical Data For Patient-Adapted Implants, Designs, Tools And
Surgical Procedures" and filed Mar. 15, 2013, the disclosure of
which is incorporated herein by reference in its entirety.
TECHNICAL FIELD
[0002] This application relates to improved methods of modeling,
designing and selecting patient-adapted (e.g., patient-specific
and/or patient-engineered) implant designs, including the use of
novel kinematic modeling systems and techniques in the design,
manufacture, testing and surgical planning for joint replacement
procedures.
BACKGROUND AND SUMMARY
[0003] Recently, the joint repair and replacement field has come to
embrace the concept of "patient-specific" and "patient-engineered"
implant systems. With such systems, the surgical implants and
associated surgical tools and procedures are designed or otherwise
modified to account for and accommodate one or more features of the
individual anatomy of the patient undergoing the surgical
procedure. Such systems typically utilize non-invasive imaging
data, taken of the individual pre-operatively, to guide the design
and/or selection of the implant, surgical tools, and the planning
of the surgical procedure itself. Various objectives of these newer
systems include: (1) reducing the amount of bony anatomy removed to
accommodate the implant, (2) designing/selecting an implant that
replicates and/or improves the function of the natural joint, (3)
increasing the durability and functional lifetime of the implant,
(4) simplifying the surgical procedure for the surgeon, (5)
reducing patient recovery time and/or discomfort, and (6) improving
patient outcomes.
[0004] Advantages of the various embodiments described herein can
include better fit, more natural movement of the joint, reduction
in the amount of bone removed during surgery and less invasive
surgical procedures. If desired, patient-adapted articular implants
can be selected, designed and/or created from images of the
patient's joint and/or other anatomical structures. Based on the
images, patient-adapted implant components can be selected and/or
designed to include features (e.g., surface contours, curvatures,
widths, lengths, thicknesses, and other features) that match
existing features in the single, individual patient's joint as well
as features that approximate an ideal and/or healthy feature that
may not exist in the patient prior to a procedure. Moreover, by
altering the design and/or selection approach to address various
potential and actual implant design issues, non-traditional design
approaches have been identified that offer improvements over
traditional implant designs and surgical procedures.
[0005] Patient-adapted features can include patient-specific
features as well as patient-engineered features. Patient-specific
(or patient-matched) implant component or guide tool features can
include features adapted, designed, modified and/or manufactured to
match or substantially match one or more of the patient's
biological features, for example, one or more biological/anatomical
structures, alignments, kinematics, and/or soft tissue features.
Patient-engineered (or patient-derived) features of an implant
component can include features adapted, designed, modified and/or
manufactured (e.g., preoperatively designed and manufactured) based
at least partially on patient-specific data in combination with
various other data sources and/or various engineering and design
principles to substantially enhance or improve one or more of the
patient's anatomical and/or biological features.
[0006] In various exemplary embodiments described herein, the
design, selection, manufacture, testing and surgical planning
associated with patient-specific implant designs can be further
improved or refined by various combinations of soft tissue and/or
kinematic modeling methods, techniques and considerations. Such
approaches represent a quantum leap in the development of joint
replacement implants and associated surgical procedures.
[0007] In various embodiments, the techniques, methods, implant
components, tools and surgical procedures described can be can be
applied to any joint, including, without limitation, a spine,
spinal articulations, an intervertebral disk, a facet joint, a
shoulder, an elbow, a wrist, a hand, a finger, a hip, a knee, an
ankle, a foot, or a toe joint. Moreover, the implant components can
be selected and/or designed to accommodate any number and/or shape
of prepared anatomical support surfaces, including accommodating no
prepared surfaces (i.e., attaching to and/or abutting against the
pre-existing surfaces of the patient's articular anatomy).
[0008] It is to be understood that the features of the various
embodiments described herein are not mutually exclusive and may
exist in various combinations and permutations.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] The foregoing and other objects, aspects, features, and
advantages of embodiments will become more apparent and may be
better understood by referring to the following description, taken
in conjunction with the accompanying drawings, in which:
[0010] FIG. 1 is a flow chart illustrating a process for generating
a model of a patient's joint (and/or a resection cut, guide tool,
and/or implant component);
[0011] FIGS. 2A and 2B are front and side views of a surface
outline for a patient's femur and tibia;
[0012] FIG. 3 depicts a flowchart of steps in certain embodiments
of a deformable segmentation method;
[0013] FIGS. 4A through 41 depict various views of a display
interface for one embodiment of a computer program that applies a
deformable segmentation method;
[0014] FIG. 30 is an illustrative flow chart showing exemplary
steps taken by a practitioner in assessing a joint and selecting
and/or designing a suitable replacement implant component;
[0015] FIG. 31 is a flowchart depicting an exemplary embodiment for
using eigen modes to select and deform implant designs to create a
patient-specific implant;
[0016] FIG. 32 is a flowchart depicting an exemplary embodiment for
employing multibody simulation to optimize kinematics of an implant
model;
[0017] FIG. 33 is a flowchart depicting an exemplary embodiment for
performing a FEA analysis on an implant design;
[0018] FIG. 34 is a flowchart depicting an exemplary embodiment for
using muscle and ligament models to adapt implant component
features;
[0019] FIG. 35 is a flowchart depicting exemplary embodiments of
using shape matching, parameterized models, and/or multibody
simulations for selecting and/or designing personalized implant and
jig design; and
[0020] FIG. 36 is a flowchart depicting an exemplary embodiment of
using eigen modes to select and/or design an implant.
HEADINGS
[0021] The headings used herein are for convenience only. The
headings do not purport to define, limit, or extend the scope or
intent of the language of the sections and/or the paragraphs to
which they pertain.
Incorporation by Reference
[0022] The entire disclosure of each of the publications, patent
documents, and other references referred to herein is incorporated
herein by reference in its entirety for all purposes to the same
extent as if each individual source were individually denoted as
being incorporated by reference.
DETAILED DESCRIPTION
Imaging, Computer Modeling and Software
[0023] Pre-operative imaging of patient anatomy is constantly
improving in accuracy, sensitivity and availability, and the use of
such imaging techniques continues to expand and become commonplace.
Concurrently, the availability and capabilities of automated and/or
semi-automated computing systems have significantly increased,
while the cost of such systems has reduced. This convergence
creates a significant opportunity for orthopedic implant designers
and manufacturers to improve the durability and/or performance of
their implants as well as simplify and diversify the surgical
implantation procedures associated with such devices.
[0024] Various embodiments described herein include the use of
automated and/or semi-automated computing systems to obtain,
quantify, classify and/or model patient anatomical image data for
use in selecting and/or designing surgical tools, implants and/or
surgical procedures to repair and/or replace portions of a
patient's anatomy. The models created can include actual and/or
approximate models of the patient's existing anatomy as well as
models of optimal, desired, undesired and/or unacceptable anatomy
derived using, at least in part, the patient's existing anatomical
data. The derived models can be created using a wide variety of
tools, techniques and/or data sources.
[0025] The image data, derived models and/or actual models can be
utilized to select, design and/or manufacture surgical tools,
implants and surgical techniques that, when utilized on the
patient, create an optimal and/or otherwise acceptable repair
and/or replacement of the relevant patient anatomy. These models
will also desirably facilitate the creation of highly durable
implant components that can be easily implanted using less invasive
and/or least invasive surgical techniques. Various embodiments will
desirably increase the availability, performance, convenience,
suitability and/or cost of orthopedic implants.
[0026] An initial step in repairing and/replacing one or more
anatomical features of a patient is to assess the size, shape
and/or condition of the relevant patient anatomy. For an orthopedic
implant, this process typically includes obtaining one or more
images of the patient's joint and/or other relevant patient anatomy
(e.g., adjacent anatomical areas and/or other features of interest)
using, for example, non-invasive imaging modalities (as well as
other imaging and/or anatomical derivation techniques known in the
art). The raw electronic image data can be used to create one or
more representations or "models" of the patient's anatomy. These
representations can include electronic models as well as
2-Dimensional images and/or 3-Dimensional physical reproductions of
the patient anatomy.
[0027] In various embodiments, the models can be used to select
and/or design an orthopedic implant appropriate for the patient's
anatomy. In other embodiments, the models can be processed and/or
modified to generate one or more modified versions of the patient
anatomy, including portions of a joint and/or surfaces within or
adjacent to the joint, with the derived model(s) representing
desired (and/or undesired) conditions of the joint at various
stages, including after surgical repair and/or replacement. In
various embodiments, the raw image data can be used to create
models that can be used to analyze the patient's existing joint
structure and kinematics, and to devise and evaluate a course of
corrective action.
[0028] If desired, the data and/or models can be used to design an
implant that replaces the existing component having one or more
patient-specific features, such as a surface or curvature. In
alternative embodiments, the various models described herein can be
utilized to plan a surgical procedure as well as to design and/or
select surgical tools useful during the procedure. In various
embodiments, the models can be optimized or otherwise modified
using a wide variety of techniques and/or data sources, to create
one or more desired models that represent one or more desired
"improvements" or outcomes of a surgical repair and/or
replacement.
Obtaining and Modeling Data
[0029] One initial step in many embodiments is to obtain image data
of a patient's anatomy. As illustrated in FIG. 1, a method of
generating a model of a patient's joint or other biological feature
can include one or more of the steps of obtaining image data of a
patient's biological structure 910; analyzing or segmenting the
image data 930; combining the segmented data 940; and presenting
the data as part of a model 950.
[0030] Image data can be obtained 910 from near or within the
patient's biological structure(s) of interest. For example, pixel
or voxel data from one or more radiographic or tomographic images
of a patient's joint can be obtained, for example, using computed
or magnetic resonance tomography. A wide variety of imaging
modalities known in the art can be used, including X-ray,
ultrasound, laser imaging, MRI, PET, SPECT, radiography including
digital radiography, digital tomosynthesis, cone beam CT, and
contrast enhanced imaging. Image data can also include electronic
image data derived from physical image "films" or "plates" through
scanning or other capture techniques.
[0031] The one or more pixels or voxels (as well as other
electronic values representing the image data) can be converted
into one or a set of values. For example, a single pixel/voxel or a
group of pixels/voxels can be converted to coordinate values, e.g.,
a point in a 2D or 3D coordinate system. The set of values also can
include a value corresponding to the pixel/voxel intensity or
relative grayscale color. Moreover, the set of values can include
information about neighboring pixels or voxels, for example,
information corresponding to relative intensity or grayscale color
and or information corresponding to relative position.
[0032] Then, the image data can be analyzed or segmented 930 to
identify those data corresponding to a particular biological
feature of interest. For example, as shown in FIG. 2A, image data
can be used to identify the edges of a biological structure, in
this case, the surface outline for each of the patient's femur and
tibia. As shown, the distinctive transition in color intensity or
grayscale 19000 at the surface of the structure can be used to
identify pixels, voxels, corresponding data points, a continuous
line, and/or surface data representing the surface or other feature
of the biological structure. This step can be performed
automatically (for example, by a computer program operator
function) or manually (for example, by a clinician or technician),
or by a combination of the two.
[0033] Optionally, the segmented data can be combined 940. For
example, in a single image, segmented and selected reference points
(e.g., derived from pixels or voxels) and/or other data can be
combined to create one or more lines representing the surface
outline of a biological structure. Moreover, as shown in FIG. 2B,
the segmented and selected data from multiple images can be
combined to create a 3D representation of the biological structure.
Alternatively, the images can be combined to form a 3D data set,
from which the 3D representation of the biological structure can be
derived directly using a 3D segmentation technique, for example an
active surface or active shape model algorithm or other model based
or surface fitting algorithm.
[0034] Optionally, the 3D representation of the biological
structure can be generated, manipulated, smoothed and/or corrected,
for example, by employing a 3D polygon surface, a subdivision
surface or parametric surface such as, for example, a non-uniform
rational B-spline (NURBS) surface. For a description of various
parametric surface representations see, for example Foley, J. D. et
al., Computer Graphics: Principles and Practice in C;
Addison-Wesley, 2nd edition (1995). Various methods are available
for creating a parametric surface. In various embodiments, the 3D
representation can be converted directly into a parametric surface
by connecting data points to create a surface of polygons and
applying rules for polygon curvatures, surface curvatures, and
other features. Alternatively, a parametric surface can be best-fit
to the 3D representation, for example, using publicly available
software such as Geomagic.RTM. software (Research Triangle Park,
N.C.).
[0035] Then, the data can be presented as part of a model 950, for
example, a patient-specific virtual model that includes the
biological feature(s) of interest. The data can be utilized to
create multiple models, representing different anatomical features
(i.e., individual models representing bone surfaces, bone structure
variations or interfaces, articulating surfaces, muscles and/or
connective tissues, the patient's skin surface, etc.) or a single
model can incorporate multiple features of interest.
[0036] As will be appreciated by those of skill in the art, one or
more of these steps 910, 930, 940, 950 can be repeated 911, 931,
941, 951 as often as desired to achieve the desired result.
Moreover, the steps can be repeated reiteratively 932, 933, 934. If
desired, the practitioner can proceed directly 933 from the step of
segmenting image data 930 to presenting the data as part of a model
950.
Deformable Segmentation and Models
[0037] In various embodiments, individual images of a patient's
biological structure can be segmented individually and then, in a
later step, the segmentation data from each image can be combined.
The images that are segmented individually can be one of a series
of images, for example, a series of coronal tomographic slices
(e.g., front to back) and/or a series of sagittal tomographic
slices (e.g., side to side) and/or a series of axial tomographic
slices (e.g., top to bottom) of the patient's joint. In some cases,
segmenting each image individually can create noise in the combined
segmented data. As an illustrative example, in an independent
segmentation process, an alteration in the segmentation of a single
image may not alter the segmentation in contiguous images in a
series. Accordingly, an individual image can be segmented to show
data that appears discontinuous with data from contiguous images.
To address this issue, certain embodiments include methods for
generating a model from a collection of images, for example,
simultaneously, rather than from individually segmented images. One
such method is referred to as deformable segmentation.
[0038] In the deformable segmentation method, a template model
having a surface data representation, such as for example a
parametric surface, a subdivision surface or a meshed surface, can
be deformed to fit a collection of multiple images. By fitting the
template model to a collection of images, alterations to one
location in the template model can be carried across the model and,
therefore, connect information corresponding to various images in
the collection, thus preserving continuity and smoothness of the
surface model. For example, in certain embodiments, a template
model includes a parametric surface that includes multiple patches
or sections. During deformation, the patches can maintain a set of
properties, such as continuity, curvature, and/or other properties
within each patch and/or across patch boundaries with neighboring
patches. These properties also can be reinforced during deformation
so that the integrity of the model is maintained.
[0039] FIG. 3 shows a flowchart of steps in certain embodiments of
a deformable segmentation method. The steps include one or more of
collecting multiple images of a patient's biological structure
19460; optionally approximating a biological feature of interest
19464; applying a template model to the approximate biological
feature of interest 19468; optionally roughly fitting the template
model to the approximate biological feature 19472 (e.g., by
performing global adjustments); and precisely fitting the template
model to the collection of multiple images 19476. Similar to other
methods described herein, one or more of these steps 19460, 19464,
19468, 19472, 19476 can be repeated 19461, 19465, 19469, 19473,
19477 as often as desired to achieve the desired result. Moreover,
the steps can be repeated reiteratively 19462, 19466, 19470, 19474,
19478. FIGS. 4A-40 show exemplary images from a computer program
that applies an embodiment of the deformable segmentation
method.
[0040] In one step 19460, multiple images can be collected for
processing together, for example, the images can be processed
together in a single event rather than individually. As illustrated
in FIG. 4A, a computer program can be used to load and view the
multiple images as one or more views into one or more 3D image data
stacks, for example coronal, sagittal or axial views. In the
figure, a series of coronal image slices 19480 and a series of
sagittal image slices 19482 can be viewed as separate stacks or
decks of 2D images. These stacks of images can result from separate
image scans or can be different views of the same scan. In
addition, any two or more images can be combined 19484 to provide a
3D image.
[0041] In another step 19464, a biological feature of interest is
approximated from the multiple images. FIG. 4B illustrates the
approximated biological features of a femoral surface 19486 and a
tibial surface 19488. The approximated surface can be provided by
the method described above, for example, by detecting edges in each
image based on relative grayscale or intensity changes, and then
combining the image data. In various embodiments, this step can be
optional.
[0042] In another step 19468, a template model is applied to the
approximate biological feature or directly to the combined image
data stack. FIG. 4C illustrates a femoral template model 19490
applied to the approximate femoral surface 19486. In applying a
template model, the operator or user of the software can select one
or more initial best fit template models. Template models can be
available from a library of models, for example, collected from one
or more previous assessments.
[0043] As shown by the template outline 19492 in the 2D images, the
femoral template 19490 initially is not a substantial match for the
approximate femoral surface 19486. This match can be improved by
making global and local adjustments. Global adjustments align the
template by performing operations such as rotating, translating or
scaling. Local adjustments deform the surface representation of the
template in certain subregions. In an optional step 19472, an
operator or a user or the software can roughly fit the template
model to the biological feature of interest or directly to the
image data stack. FIG. 4D-4G illustrate the femoral template model
19490 being roughly adjusted to best-fit the approximate femoral
surface 19486. As shown in the figures, a user can perform the
adjustments using a control panel 19494. Adjustments can include,
for example, adjusting the location of the template in one or more
dimensions; adjusting the scale (e.g., size) of the template in one
or more dimensions; and adjusting the rotation of the template in
one or more dimensions. User-controlled knobs, as shown in the
control panel 19494, can be used to induce position changes
relative to their initial center positions. FIG. 4D illustrates a
user adjustment to the location of the template model in the x axis
(e.g., in the M-L direction). FIG. 4E illustrates a user adjustment
to the location of the template model in the z axis (e.g., in the
proximal-distal direction). FIG. 4F illustrates a user adjustment
to the scale (i.e., size) of the template model in the x axis. FIG.
4G illustrates a user adjustment to rotation of the template model
about the z-axis (the axis perpendicular to the view). These or
other adjustments can be performed in any order and repeated as
desired to achieve the best rough fit of the template with the
approximate biological feature. In other embodiments, the software
can automatically determine the initial best fit of the template
model to the biological feature of interest or the image data. This
can be achieved by finding the scaling, rotation and translation
parameters that result in the closest fit of the template to the
structure of interest, for example using a multidimensional
optimization algorithm. FIG. 4H illustrates the rough fit of the
template to the approximate surface following these
adjustments.
[0044] In another step 19476, the model template can be precisely
fit to the collection of multiple images (rather than independently
processing each image, which can optionally be accomplished using
many of the various methods described herein). As shown in FIG. 4I,
the surface quadrangles or "patches" of surface data representation
of the femoral template 19490 can be deformed to match the
surface(s) across the entire collection of images. In certain
embodiments, the template patches can be deformed to directly fit
the radiographic or tomographic image data (e.g., voxel data)
rather than any subsequently processed data, for example, data
points representing multiple voxels or data compatible with a
computer monitor. If desired, radiographic or tomographic images
can include much higher gray value resolution (e.g., can assign one
of a much greater number of unique shades of gray to each pixel or
voxel) than data compatible with a computer monitor. Accordingly,
by deforming the template to directly fit the radiographic images,
a high degree of resolution can be maintained, which can provide a
highly precise model.
[0045] The points or dots shown in association with the template
outline 19492 represent control points that can be used by a
technician to manually alter the outline and surface of the
template. By moving a control point, the user can manually alter
and deform adjacent sections of the surface data representation of
the template, and the resulting alterations and deformations appear
in both the 2D outline view and in the 3D view of the template. In
another embodiment, the software can optimize the position of the
control points and thus the fit of the surface automatically using
various criteria, for example gray values or gray value gradients
in the image data or smoothness and continuity constraints in the
surface data representation.
[0046] In various embodiments, the global transformations and local
deformations may be determined by the software, at least in part,
based on external design constraints pertinent to a particular
implant design. This can include, for example, specific surface
curvature radii, minimum distance between structures such as
anchoring elements and/or minimum or maximum thickness or length or
width dimensions of the implant or parts thereof. The
transformations can also be optimized to minimize bone cuts.
[0047] In further embodiments, the model can be fit to the
patient's anatomy after the axis alignment of the joint, for
example the anatomical or biomechanical axis, has been corrected.
The fitting, optimization or deformation of the model can then be
performed taking the corrected axis into account. Alternatively,
the axis alignment is corrected after the model has been fitted.
The model can then undergo further adjustments as the alignment
correction is performed. Thus, the position or shape of the joint
bearing surfaces and other anatomical structures can be determined
based on the corrected axis information.
[0048] In various embodiments, the virtual model can include, in
addition to or instead of the surface model representation, one or
more geometric reference structures. This can include, for example,
planes, axes, curves or surfaces that can be used as construction
parameters for one or more implants, guide tools and/or surgical
procedures. The geometric reference structures can be used to
define the position and shape of anatomical surfaces as well as the
location and direction of any potential anatomical support
structures, bone cuts and/or drill holes needed to position
implants and/or surgical tools. Similar to the way the surface data
representation can be adjusted using global transformations and
local deformations as described above to match the individual
patient's anatomy, the position, direction, scale and/or shape of
the geometric reference structures can be adjusted
accordingly--i.e. the software can selectively apply the same
global transformations and local deformations applied to the
surface model to the geometric reference structures as well. During
this process, the position, direction, scale and/or shape of the
geometric reference structures can be adjusted as well based on the
transformations and deformations of the virtual shape model.
Adjusting the position, direction, scale and shape of the geometric
reference structures can be performed automatically by the software
or based on user or operator input or a combination thereof.
Reference Points and Features
[0049] In various embodiments, information collected from a patient
or patient group, including the image data and/or models described
herein, can include points, surfaces, and/or landmarks,
collectively referred to herein as "reference points." In certain
embodiments, the reference points can be selected and used to
derive a varied or altered surface, such as, without limitation, an
ideal surface or structure.
[0050] In various embodiments, reference points can be used to
create a model of the patient's relevant biological feature(s)
and/or one or more patient-adapted surgical steps, tools, and
implant components. For example the reference points can be used to
design a patient-adapted implant component having at least one
patient-specific or patient-engineered feature, such as a surface,
dimension, or other feature.
[0051] Sets of reference points can be grouped to form reference
structures used to create a model of a joint, an implant design,
and/or a tool design. Designed implant and/or tool surfaces can be
derived from single reference points, triangles, polygons, or more
complex surfaces, such as parametric or subdivision surfaces, or
models of joint material, such as, for example, articular
cartilage, subchondral bone, cortical bone, endosteal bone or bone
marrow. Various reference points and reference structures can be
selected and manipulated to derive a varied or altered surface,
such as, without limitation, an ideal surface or structure.
[0052] The reference points can be located on or in the joint that
will receive the patient-adapted implant. For example, the
reference points can include weight-bearing surfaces or locations
in or on the joint, a cortex in the joint, cortical and/or
cancellous wall boundaries, and/or an endosteal surface of the
joint. The reference points also can include surfaces or locations
outside of but related to the joint. Specifically, reference points
can include surfaces or locations functionally related to the
joint.
[0053] For example, in embodiments directed to the knee joint,
reference points can include one or more locations ranging from the
hip down to the ankle or foot. The reference points also can
include surfaces or locations homologous to the joint receiving the
implant. For example, in embodiments directed to a knee, a hip, or
a shoulder joint, reference points can include one or more surfaces
or locations from the contralateral knee, hip, or shoulder
joint.
[0054] In certain embodiments, imaging data collected from the
patient, for example, imaging data from one or more of x-ray
imaging, digital tomosynthesis, cone beam CT, non-spiral or spiral
CT, non-isotropic or isotropic MRI, SPECT, PET, ultrasound, laser
imaging, and/or photo-acoustic imaging, is used to qualitatively
and/or quantitatively measure one or more of a patient's biological
features, one or more of normal cartilage, diseased cartilage, a
cartilage defect, an area of denuded cartilage, subchondral bone,
cortical bone, endosteal bone, bone marrow, a ligament, a ligament
attachment or origin, menisci, labrum, a joint capsule, articular
structures, and/or voids or spaces between or within any of these
structures. The qualitatively and/or quantitatively measured
biological features can include, but are not limited to, one or
more of length, width, height, depth and/or thickness; curvature,
for example, curvature in two dimensions (e.g., curvature in or
projected onto a plane), curvature in three dimensions, and/or a
radius or radii of curvature; shape, for example, two-dimensional
shape or three-dimensional shape; area, for example, surface area
and/or surface contour; perimeter shape; and/or volume of, for
example, the patient's cartilage, bone (subchondral bone, cortical
bone, endosteal bone, and/or other bone), ligament, and/or voids or
spaces between them.
[0055] In certain embodiments, measurements of biological features
can include any one or more of the illustrative measurements
identified in Table 1.
TABLE-US-00001 TABLE 1 Exemplary patient-specific measurements of
biological features that can be used in the creation of a model
and/or in the selection and/or design of an implant component
Anatomical feature Exemplary measurement Joint-line, joint gap
Location relative to proximal reference point Location relative to
distal reference point Angle Gap distance between opposing surfaces
in one or more locations Location, angle, and/or distance relative
to contralateral joint Soft tissue tension Joint gap distance
and/or balance Joint gap differential, e.g., medial to lateral
Medullary cavity Shape in one or more dimensions Shape in one or
more locations Diameter of cavity Volume of cavity Subchondral bone
Shape in one or more dimensions Shape in one or more locations
Thickness in one or more dimensions Thickness in one or more
locations Angle, e.g., resection cut angle Cortical bone Shape in
one or more dimensions Shape in one or more locations Thickness in
one or more dimension Thickness in one or more locations Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Endosteal bone Shape in
one or more dimensions Shape in one or more locations Thickness in
one or more dimensions Thickness in one or more locations Angle,
e.g., resection cut angle Cartilage Shape in one or more dimensions
Shape in one or more location Thickness in one or more dimensions
Thickness in one or more location Angle, e.g., resection cut angle
Intercondylar notch Shape in one or more dimensions Location Height
in one or more locations Width in one or more locations Depth in
one or more locations Angle, e.g., resection cut angle Medial
condyle 2D and/or 3D shape of a portion or all Height in one or
more locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness in one or more
locations Curvature in one or more locations Slope in one or more
locations and/or directions Angle, e.g., resection cut angle
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Lateral
condyle 2D and/or 3D shape of a portion or all Height in one or
more locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness in one or more
locations Curvature in one or more locations Slope in one or more
locations and/or directions Angle, e.g., resection cut angle
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Trochlea 2D
and/or 3D shape of a portion or all Height in one or more locations
Length in one or more locations Width in one or more locations
Depth in one or more locations Thickness in one or more locations
Curvature in one or more locations Groove location in one or more
locations Trochlear angle, e.g., groove angle in one or more
locations Slope in one or more locations and/or directions Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Medial trochlea 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Slope in one or more locations and/or directions
Angle, e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Central trochlea 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Groove location in one or more locations Tochlear
angle, e.g., groove angle in one or more location Slope in one or
more locations and/or directions Angle, e.g., resection cut angle
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Lateral
trochlea 2D and/or 3D shape of a portion or all Height in one or
more locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness in one or more
locations Curvature in one or more locations Slope in one or more
locations and/or directions Angle, e.g., resection cut angle
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Entire tibia
2D and/or 3D shape of a portion or all Height in one or more
locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness in one or more
locations Curvature in one or more locations Slope in one or more
locations and/or directions (e.g., medial and/or lateral) Angle,
e.g., resection cut angle Axes, e.g., A-P and/or M-L axes
Osteophytes Plateau slope(s), e.g., relative slopes medial and
lateral Plateau heights(s), e.g., relative heights medial and
lateral Bearing surface radii, e.g., relative radii medial and
lateral Perimeter profile Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Medial tibia 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness or height in one or more locations Curvature in
one or more locations Slope in one or more locations and/or
directions Angle, e.g., resection cut angle Perimeter profile
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Lateral
tibia 2D and/or 3D shape of a portion or all Height in one or more
locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness/height in one or
more locations Curvature in one or more locations Slope in one or
more locations and/or directions Angle, e.g., resection cut angle
Perimeter profile Portions or all of cortical bone perimeter at an
intended resection level Resection surface at an intended resection
level Entire patella 2D and/or 3D shape of a portion or all Height
in one or more locations Length in one or more locations Width in
one or more locations Depth in one or more locations Thickness in
one or more locations Curvature in one or more locations Slope in
one or more locations and/or directions Perimeter profile Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Medial patella 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Slope in one or more locations and/or directions
Angle, e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Central patella 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Slope in one or more locations and/or directions
Angle, e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Lateral patella 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Slope in one or more locations and/or directions
Angle, e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended ended resection level Resection surface at
an intended section level Femoral head 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Slope in one or more locations and/or directions
Angle, e.g., resection cut angle Anteversion or retroversion
Portions or all of bone perimeter at an intended resection level
Resection surface at an intended resection level Femoral neck 2D
and/or 3D shape of a portion or all Height in one or more locations
Length in one or more locations Width in one or more locations
Depth in one or more locations Thickness in one or more locations
Angle in one or more locations Neck axis in ore or more locations
Curvature in one or more locations Slope in one or more locations
and/or directions Angle, e.g., resection cut angle Anteversion or
retroversion Leg length
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Femoral
shaft 2D and/or 3D shape of a portion or all Height in one or more
locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness in one or more
locations Angle in one or more locations Shaft axis in one or more
locations Curvature in one or more locations Angle, e.g., resection
cut angle Anteversion or retroversion Leg length Portions or all of
cortical bone perimeter at an intended resection level Resection
surface at an intended resection level Acetabulum 2D and/or 3D
shape of a portion or all Height in one or more locations Length in
one or more locations Width in one or more locations Depth in one
or more locations Thickness in one or more locations Curvature in
one or more locations Slope in one or more locations and/or
directions Angle, e.g., resection cut angle Anteversion or
retroversion Portions or all of cortical bone perimeter at an
intended resection level Resection surface at an intended resection
level Glenoid 2D and/or 3D shape of a portion or all Height in one
or more locations Length in one or more locations Width in one or
more locations Depth in one or more locations Thickness in one or
more locations Curvature in one or more locations Slope in one or
more locations and/or directions Angle, e.g., resection cut angle
Anteversion or retroversion Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Humeral head 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Curvature in one or
more locations Slope in one or more locations and/or directions
Angle, e.g., resection cut angle Anteversion or retroversion
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Humeral neck
2D and/or 3D shape of a portion or all Height in one or more
locations Length in one or more locations Width in one or more
locations Depth in one or more locations Thickness in one or more
locations Angle in one or more locations Neck axis in one or more
locations Curvature in one or more locations Slope in one or more
locations and/or directions Angle, e.g., resection cut angle
Anteversion or retroversion Arm length Portions or all of cortical
bone perimeter at an intended resection level Resection surface at
an intended resection level Humeral shaft 2D and/or 3D shape of a
portion or all Height in one or more locations Length in one or
more locations Width in one or more locations Depth in one or more
locations Thickness in one or more locations Angle in one or more
locations Shaft axis in one or more locations Curvature in one or
more locations Angle, e.g., resection cut angle Anteversion or
retroversion Arm length Portions or ail of cortical bone perimeter
at an intended resection level Resection surface at an intended
resection level Ankle joint 2D and/or 3D shape of a portion or all
Height in one or more locations Length in one or more locations
Width in one or more locations Depth in one or more locations
Thickness in one or more locations Curvature in one or more
locations Slope in one or more locations and/or directions Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Elbow 2D and/or 3D shape of a portion or
all Height in one or more locations Length in one or more locations
Width in one or more locations Depth in one or more locations
Thickness in one or more locations Curvature in one or more
locations Slope in one or more locations and/or directions Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended section level Wrist 2D and/or 3D shape of a portion or all
Height in one or more locations Length in one or more locations
Width in one or more locations Depth in one or more locations
Thickness in one or more locations Curvature in one or more
locations Slope in one or more locations and/or directions Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Hand 2D and/or 3D shape of a portion or
all Height in one or more locations Length in one or more locations
Width in one or more locations Depth in one or more locations
Thickness in one or more locations Curvature in one or more
locations Slope in one or more locations and/or directions Angle,
e.g., resection cut angle Portions or all of cortical bone
perimeter at an intended resection level Resection surface at an
intended resection level Finger 2D and/or 3D shape of a portion or
all Height in one or more locations Length in one or more locations
Width in one or more locations Depth in one or more locations
Thickness in one or more locations Curvature in one or more
locations Slope in one or more locations and/or directions Angle
Portions or all of cortical bone perimeter at an intended resection
level Resection surface at an intended resection level Spine 2D
and/or 3D shape of a portion or all Height in one or more locations
Length in one or more locations Width in one or more locations
Depth in one or more locations Thickness in one or more locations
Curvature in one or more locations Slope in one or more locations
and/or directions Angle, e.g., resection cut angle Portions or all
of cortical bone perimeter at an intended resection level Resection
surface at an intended resection level Spinal facet joint 2D and/or
3D shape of a portion or all Height in one or more locations Length
in one or more locations Width in one or more locations Depth in
one or more locations Thickness in one or more locations Curvature
in one or more locations Slope in one or more locations and/or
directions Angle, e.g., resection cut angle
[0056] Depending on the clinical application, a single or any
combination or all of the measurements described in Table 1 and/or
known in the art can be used. Additional patient-specific
measurements and information that can be used in the evaluation can
include, for example, joint kinematic measurements, bone density
measurements, bone porosity measurements, soft and connective
tissues structures, skin, muscles, identification of damaged or
deformed tissues or structures, and patient information, such as
patient age, weight, gender, ethnicity, activity level, and overall
health status. Moreover, the patient-specific measurements may be
compared, analyzed or otherwise modified based on one or more
"normalized" patient model or models, or by reference to a desired
database of anatomical features of interest. For example, a series
of patient-specific femoral measurements may be compiled and
compared to one or more exemplary femoral or tibial measurements
from a library or other database of "normal" (or other reference
population) femur measurements. Comparisons and analysis thereof
may concern, but is not limited to, one or more or any combination
of the following dimensions: femoral shape, length, width, height,
of one or both condyles, intercondylar shapes and dimensions,
trochlea shape and dimensions, coronal curvature, sagittal
curvature, cortical/cancellous bone volume and/or quality, etc.,
and a series of recommendations and/or modifications may be
accomplished. Any parameter mentioned in the specification and in
the various Tables throughout the specification, including
anatomic, biomechanical and kinematic parameters, can be utilized,
not only in the knee, but also in the hip, shoulder, ankle, elbow,
wrist, spine and other joints. Such analysis may include
modification of one or more patient-specific features and/or design
criteria for the implant to account for any underlying deformity
reflected in the patient-specific measurements. If desired, the
modified data may then be utilized to select and/or design an
appropriate implant and/or tool to match the modified features, and
a final verification operation may be accomplished to ensure the
selected and/or designed implant and/or tool is acceptable and
appropriate to the original unmodified patient-specific
measurements (i.e., the selected and/or designed implant and/or
tool will ultimately "fit" the original patient anatomy). In
alternative embodiments, the various anatomical features may be
differently "weighted" during the comparison process (utilizing
various formulaic weightings and/or mathematical algorithms), based
on their relative importance or other criteria chosen by the
designer/programmer and/or physician.
[0057] In addition to (or optionally in place of) the
above-mentioned measurements, it may be desirable to obtain
measurements of the targeted joint (as well as surrounding
anatomical areas and or other joints of the patient's anatomy) in a
load-bearing or otherwise "real-world" condition. Such measurements
can potentially yield extremely useful data on the alignment and/or
movement of the joint and surrounding structures (as well as the
loading conditions of the various joint components)--information
which may be difficult to obtain or model from standard imaging
techniques (i.e., sitting or lying X-rays, CT-scans and/or MRI
imaging). Such load-bearing measurements can include imaging of the
patient standing, walking and/or carrying loads of varying sizes
and/or weights.
[0058] It may also be desirable to model various patient
measurements (including non-load-bearing measurements as described
above) to simulate the targeted joint and surrounding anatomy
virtually. Such simulations can include virtually modeling the
alignment and load bearing condition of the joint and surrounding
anatomical structures for the patient standing and/or moving (i.e.,
walking, running, jumping, squatting, kneeling, walking up and down
stairs or inclines/declines, picking up objects, etc.). Such
simulations can be used to obtain valuable anatomical,
biomechanical and kinematic data including the loaded conditions of
various joint components, component positions, component movement,
joint and/or surrounding tissue anatomical or biomechanical
constraints or limitations, as well as estimated mechanical axes in
one or more directions (i.e., coronal, sagittal or combinations
thereof). This information could then be utilized (alone or in
combination with other data described herein) to design various
features of a joint resurfacing/replacement implant. This method
can be incorporated in the various embodiments described herein as
additional patient measurement and anatomical/joint modeling and
design data. This analysis is applicable to many different joints,
including those of a medial condyle, a lateral condyle, a trochlea,
a medial tibia, a lateral tibia, the entire tibia, a medial
patella, a lateral patella, an entire patella, a medial trochlea, a
central trochlea, a lateral trochlea, a portion of a femoral head,
an entire femoral head, a portion of an acetabulum, an entire
acetabulum, a portion of a glenoid, an entire glenoid, a portion of
a humeral head, an entire humeral head, a portion of an ankle
joint, an entire ankle joint, and/or a portion or an entire elbow,
wrist, hand, finger, spine or facet joint.
Modeling Proper Limb Alignment
[0059] Proper joint and limb function typically depend on correct
limb alignment. For example, in repairing a knee joint with one or
more knee implant components, optimal functioning of the new knee
will often depend, at least partially, on the correct alignment of
the anatomical and/or mechanical axes of the lower extremity.
Accordingly, an important consideration in designing and/or
replacing a natural joint with one or more implant components is
proper limb alignment or, when the malfunctioning joint contributes
to a misalignment, proper realignment of the limb. Alignment can
include static alignment in various orientations as well as
alignment throughout portions and/or all of a range of motion of
the joint.
[0060] Certain embodiments described herein include collecting and
using data from imaging sources and/or tests to virtually
determine, in one or more planes, one or more anatomic axes and/or
one or more mechanical axes of a joint or extremity and the related
misalignment of a patient's limb. The misalignment of a limb joint
relative to the axis can identify the degree of deformity, for
example, varus or valgus deformity in the coronal plane or genu
antecurvatum or recurvatum deformity in the sagittal plane. Then,
one or more of the patient-specific implant components and/or the
implant procedure steps, such as bone resection, can be designed to
help correct the misalignment.
[0061] Imaging data can be used to virtually determine a patient's
axis and misalignment, anatomic reference points and/or limb
alignment, including alignment angles within the same and between
different joints or to simulate normal limb alignment. Any anatomic
features related to the misalignment can be selected and imaged.
For example, in certain embodiments, such as for a knee or hip
implant, the imaging test can include data from at least one of, or
several of, a hip joint, knee joint and ankle joint. The imaging
test can be obtained in lying, prone, supine or standing position.
The imaging test can include only the target joint, or both the
target joint and also selected data through one or more adjoining
and/or opposing joints.
[0062] Using the image data, one or more mechanical or anatomical
axes, angles, planes or combinations thereof can be determined. In
certain embodiments, such axes, angles, and/or planes can include,
or be derived from, one or more of a Whiteside's line, Blumensaat's
line, transepicondylar line, femoral shaft axis, femoral neck axis,
acetabular angle, lines tangent to the superior and inferior
acetabular margin, lines tangent to the anterior or posterior
acetabular margin, femoral shaft axis, tibial shaft axis,
transmalleolar axis, posterior condylar line, tangent(s) to the
trochlea of the knee joint, tangents to the medial or lateral
patellar facet, lines tangent or perpendicular to the medial and
lateral posterior condyles, lines tangent or perpendicular to a
central weight-bearing zone of the medial and lateral femoral
condyles, lines transecting the medial and lateral posterior
condyles, for example through their respective centerpoints, lines
tangent or perpendicular to the tibial tuberosity, lines vertical
or at an angle to any of the aforementioned lines, and/or lines
tangent to or intersecting the cortical bone of any bone adjacent
to or enclosed in a joint. Moreover, estimating a mechanical axis,
an angle, or plane also can be performed using image data obtained
through two or more joints, such as the knee and ankle joint, for
example, by using the femoral shaft axis and a centerpoint or other
point in the ankle, such as a point between the malleoli.
[0063] As one example, if surgery of the knee or hip is
contemplated, the imaging test can include acquiring data through
at least one of, or several of, a hip joint, knee joint or ankle
joint. As another example, if surgery of the knee joint is
contemplated, a mechanical axis can be determined. For example, the
centerpoint of the hip, knee and ankle can be determined. By
connecting the centerpoint of the hip with that of the ankle, a
mechanical axis can be determined in the coronal plane. The
position of the knee relative to said mechanical axis can be a
reflection of the degree of varus or valgus deformity. The same
determinations can be made in the sagittal plane, for example to
determine the degree of genu antecurvatum or recurvatum. Similarly,
any of these determinations can be made in any other desired
planes, in two or three dimensions. A desired alignment throughout
a desired range of motion may be derived using individual
measurements and/or a combination of multiple measurements along
multiple planes.
Establishing Normal or Near-Normal Joint Kinematics
[0064] In certain embodiments, a computer program simulating
biomotion of one or more joints, such as, for example, a knee
joint, or a knee and ankle joint, or a hip, knee and/or ankle
joint, can be utilized. In certain embodiments, imaging data as
previously described, which can include information related to the
joint or extremity of interest as well as information regarding
adjacent anatomical structures, can be entered into the computer
program. In addition to (or in place of) patient-specific image
data, patient-specific kinematic data, for example obtained in a
gait lab, can be entered into the computer program. Alternatively,
patient-specific navigation data, for example generated using a
surgical navigation system, image guided or non-image guided, can
be entered into the computer program. This kinematic or navigation
data can, for example, be generated by applying optical or RF
markers to the limb and by registering the markers and then
measuring limb movements, for example, flexion, extension,
abduction, adduction, rotation, and other limb movements.
[0065] Optionally, other data including anthropometric data may be
added for each patient. These data can include but are not limited
to the patient's age, gender, weight, height, size, body mass
index, and race. Desired limb alignment and/or deformity correction
can be added into the model. The position of bone cuts on one or
more articular surfaces as well as the intended location of implant
bearing surfaces on one or more articular surfaces can be entered
into the model.
[0066] A patient-specific biomotion model can be derived that
includes combinations of parameters listed above. The biomotion
model can simulate various activities of daily life, including
normal gait, stair climbing, descending stairs, running, kneeling,
squatting, sitting and any other physical activity (including
activities relevant to other joints of interest). The biomotion
model can start out with standardized activities, typically derived
from reference databases. These reference databases can be
generated, for example, using biomotion measurements using force
plates and motion trackers using radiofrequency or optical markers
and video equipment.
[0067] The biomotion model can then be individualized with use of
patient-specific information including at least one of, but not
limited to, the patient's age, gender, weight, height, body mass
index, and race, the desired limb alignment or deformity
correction, and the patient's imaging data, for example, a series
of two-dimensional images or a three-dimensional representation of
the joint for which surgery is contemplated.
[0068] An implant shape including associated bone cuts generated in
various optimizations and/or modifications discussed herein, for
example, limb alignment, deformity correction and/or bone
preservation on one or more articular surfaces, can be introduced
into the model. Table 2 includes an exemplary list of parameters
that can be measured in a patient-specific biomotion model.
TABLE-US-00002 TABLE 2 Parameters measured in a patient-specific
biomotion model for various implants Joint implant Measured
Parameter knee Medial femoral rollback during flexion knee Lateral
femoral rollback during flexion knee Patellar position, medial,
lateral, superior, inferior for different flexion and extension
angles knee Internal and external rotation of one or more femoral
condyles knee Internal and external rotation of the tibia knee
Flexion and extension angles of one or more articular surfaces knee
Anterior slide and posterior slide of at least one of the medial
and lateral femoral condyles during flexion or extension knee
Medial and lateral laxity throughout the range of motion knee
Contact pressure or forces on at least one or more articular
surfaces, e.g., a femoral condyle and a tibial plateau, trochlea
and a patella knee Contact area on at least one or more articular
surfaces, e.g., a femoral condyle and a tibial plateau, a trochlea
and a patella knee Forces between the bone-facing surface of the
implant, an optional cement interface and the adjacent bone or bone
marrow, measured at least one or multiple bone cut or bone-facing
surface of the implant on at least one or multiple articular
surfaces or implant components. knee Ligament location, e.g., ACL,
PCL, MCL, LCL, retinacula, joint capsule, estimated or derived, for
example using an imaging test. knee Ligament tension, strain, shear
force, estimated failure forces, loads for example or different
angles of flexion, extension, rotation abduction, adduction, with
the different positions or movements optionally simulated in a
virtual environment. knee Potential implant impingement on other
articular structures, e.g., in high flexion, high extension,
internal or external rotation, abduction or adduction or any
combinations thereof or other angles/positions/ movements. Hip,
shoulder or Internal and external rotation of one or more articular
other joint surfaces Hip, shoulder or Flexion and extension angles
of one or more articular other joint surfaces Hip, shoulder or
Anterior slide and posterior slide of at least one or more other
joint articular surfaces during flexion or extension, abduction or
adduction, elevation, internal or external rotation Hip, shoulder
or Joint laxity throughout the range of motion other joint Hip,
shoulder or Contact pressure or forces on at least one or more
other joint articular surfaces, e.g., an acetabulum and a femoral
head, a glenoid and a humeral head Hip, shoulder or Forces between
the bone-facing surface of the implant, other joint an optional
cement interface and the adjacent bone or bone marrow, measured at
least one or multiple bone cut or bone-facing surface of the
implant on at least one or multiple articular surfaces or implant
components. Hip, shoulder or Ligament location, e.g., transverse
ligament, other joint glenohumeral ligaments, retinacula, joint
capsule, estimated or derived, for example using an imaging test.
Hip, shoulder or Ligament tension, strain, shear force, estimated
failure other joint forces, loads for example for different angles
of flexion, extension, rotation, abduction, adduction, with the
different positions or movements optionally simulated in a virtual
environment. Hip, shoulder or Potential implant impingement on
other articular other joint structures, e.g., in high flexion, high
extension, internal or external rotation, abduction or adduction or
elevation or any combinations thereof or other angles/positions/
movements.
[0069] The above list is not meant to be exhaustive, but only
exemplary. Any other biomechanical parameter known in the art can
be included in the analysis.
[0070] The resultant biomotion data can be used to further optimize
the implant and/or procedure design with the objective to establish
normal or near normal kinematics. The implant optimizations can
include one or multiple implant components. Implant and/or
procedure optimizations based on patient-specific data, including
image-based biomotion data, include (but are not limited to):
[0071] Changes to external, joint-facing implant shape in coronal
plane [0072] Changes to external, joint-facing implant shape in
sagittal plane [0073] Changes to external, joint-facing implant
shape in axial plane [0074] Changes to external, joint-facing
implant shape in multiple planes or three dimensions [0075] Changes
to internal, bone-facing implant shape in coronal plane [0076]
Changes to internal, bone-facing implant shape in sagittal plane
[0077] Changes to internal, bone-facing implant shape in axial
plane [0078] Changes to internal, bone-facing implant shape in
multiple planes or three dimensions [0079] Changes to one or more
bone cuts, for example with regard to depth of cut, orientation of
cut
[0080] Biomotion models for a particular patient can be
supplemented with patient-specific finite element modeling,
population-specific finite element modeling and/or other
biomechanical models known in the art. In many cases, bony anatomy
may be readily imaged and/or defined for a given patient's anatomy,
but the muscles and connective tissues of the body (and a variety
of other such "softer" tissues) may not be so readily identified
from anatomical image data. In such cases, additional biomechanical
models of softer tissues can be obtained that provide a readily
available and accurate source of data for incorporation into the
patient's bony anatomical model. The soft tissue models can
supplement the bony anatomy models at a wide variety of simulation
levels, from "gross movement" anatomical models having low modeling
complexity (i.e., only major muscle groups being modeled, with
simple lines of action and limited choice of tissue connection
points) to highly complex models (i.e., modeling of multiple tissue
groups, including muscles, tendons, ligaments, fatty tissues,
articular cartilage, etc, with complex lines of action and
connection points, including the potential to simulate the actual
bony connection points from anatomical images to further refine the
combined model).
[0081] Using such combined modeling, resultant forces, motions and
kinematics of various joints, such as the knee joint, can be
calculated for each component for each specific patient. Modeling
can include static and dynamic modeling, and can allow simulation
of a patient's joint structures at a variety of alignments and/or
loading conditions. If desired, an implant can be engineered to
accommodate such models, as well as the patient's load and force
demands for a variety of conditions. For instance, in one
embodiment a 1251b. patient may not need a tibial plateau as thick
as a patient with 280 lbs. Similarly, in various embodiments one or
more polyethylene inserts and/or components in various implants can
be adjusted in shape, thickness and material properties for each
patient. For example, a 3 mm polyethylene insert can be used in a
light patient with low force and a heavier or more active patient
may need an 8 mm polymer insert or similar device.
Selecting and/or Designing Implants, Tools and/or Procedures
[0082] Once one or more desired models has been created using the
various techniques described above, the models (optionally with
information from other data sources) can be utilized to select
and/or design appropriate implant components and/or surgical tools,
as well as to plan the surgical procedure.
Templates and Deformable Models
[0083] In various embodiments, various aspects of the models and
systems described herein, including the virtual model, can include
(in addition to or instead of the surface model representation), a
template for one or more implants and/or guide tools, including the
position and shape of hard and soft tissues, bearing surfaces, and
the location and direction of bone cuts and/or drill holes needed
to position the implants. Similar to the way the surface data
representation is adjusted using global transformations and local
deformations as described herein to match the individual patient's
anatomy, the shape of the implants and/or guide tools can be
adjusted accordingly, i.e., the software applies similar global
transformations and/or local deformations, as applied to the
surface model, to the implants and/or guide tools as well. During
this process, the position and shape of the bearing surfaces as
well as the position and direction of bone cuts and/or drill holes
can be adjusted based on the transformations and deformations of
the virtual shape model. Adjusting the position and shape of
bearing surfaces and the position and direction of bone cuts and/or
drill holes can be performed automatically by the software or based
on user or operator input or a combination thereof.
Library/Databases of Repair Systems
[0084] In various embodiments, an articular repair system (e.g.,
resection cut strategy, guide tools, and implant components) can be
formed or selected from a library or database of systems of various
sizes, including various medio-lateral (ML), antero-posterior (AP),
and supero-inferior (SI) dimensions, curvatures, and thicknesses.
The articular repair system may be formed or selected such that it
achieves various parameters, such as, for example, a near anatomic
fit or match with the surrounding or adjacent cartilage, cortical
bone, trabecular bone, subchondral bone, menisci, and/or cut bone
(including bone cut before or after preparing an implantation
site). The shape of the repair system can be based on the analysis
of an electronic image. If the articular repair system is intended
to replace an area of diseased cartilage or lost cartilage, the
near anatomic fit can be achieved using a method that provides a
virtual reconstruction of the shape of healthy cartilage in an
electronic image. These systems can be pre-made or made to order
for an individual patient.
[0085] In order to control the fit or match of the articular repair
system with the surrounding or adjacent cartilage, cortical bone,
trabecular bone, subchondral bone, cut bone and/or menisci and
other tissues preoperatively, a software program can be used that
projects the articular repair system over the anatomic position
where it will be implanted. Suitable software is commercially
available and/or can be readily modified or designed by a skilled
programmer. In some embodiments, an articular surface repair system
can be projected over the implantation site prior to, during or
after planning or simulating the surgery virtually using one or
more 3-D images. The cartilage, cortical bone, trabecular bone,
subchondral bone, cut bone, menisci, and/or other anatomic
structures are extracted from a 3-D electronic image such as an MRI
or a CT using manual, semi-automated and/or automated segmentation
techniques. In select embodiments, segmentation is not necessary
and data are directly displayed using the grayscale image
information. Optionally, a 3-D representation of the cartilage,
cortical bone, trabecular bone, subchondral bone, cut bone,
menisci, and/or other anatomic structures as well as the articular
repair system is generated, for example, using a polygon or
non-uniform rational B-spline (NURBS) surface or other parametric
surface representation. For a description of various parametric
surface representations see, for example, Foley, J. D. et al.,
Computer Graphics: Principles and Practice in C; Addison-Wesley,
2nd edition (1995).
[0086] The 3D representations of the cartilage, cortical bone,
trabecular bone, subchondral bone, cut bone, menisci, and/or other
anatomic structures and the articular repair system can be merged
into a common coordinate system. The articular repair system can
then be placed at the desired implantation site. The
representations of the cartilage, cortical bone, trabecular bone,
subchondral bone, cut bone, menisci, and/or other anatomic
structures and the articular repair system can be rendered into a
3-D image in application programming interfaces (APIs), such as,
for example, OpenGL.RTM. (standard library of advanced 3-D graphics
functions developed by SG, Inc.; available as part of the drivers
for PC-based video cards, for example from www.nvidia.com for
NVIDIA video cards or www.3dlabs.com for 3Dlabs products, or as
part of the system software for Unix workstations) or DirectX.RTM.
(multimedia API for Microsoft Windows.RTM. based PC systems;
available from www.microsoft.com). The 3-D image can be rendered
showing the cartilage, cortical bone, trabecular bone, subchondral
bone, cut bone, menisci and/or other anatomic objects and the
articular repair system from varying angles, e.g., by rotating or
moving them interactively or non-interactively, in real-time or
non-real-time.
[0087] In various embodiments, articular repair systems (e.g.,
including resection cut strategy, guide tools, and implant
components) can be formed or selected to achieve various parameters
including a near anatomic fit or match with the surrounding or
adjacent cartilage, subchondral bone, menisci and/or other tissue.
The shape of the repair system can be based on the analysis of an
electronic image. If the articular repair system is intended to
replace an area of diseased cartilage or lost cartilage, the near
anatomic fit can be achieved using a method that provides a virtual
reconstruction of the shape of healthy cartilage in an electronic
image.
Virtual and Physical Models
[0088] In certain embodiments, models can be generated to show
defects of interest in a patient's joint. Computer software
programs to generate models of patient-specific renderings of
implant assembly and defects (e.g., osteophyte structures),
together with bone models, to aid in surgery planning can be
developed using various publicly available programming environments
and languages, for example, Matlab 7.3 and Matlab Compiler 4.5, C++
or Java. In certain embodiments, the computer software program can
have a user interface that includes, for example, one or more of
the components including a 3D render canvas, a data path selector,
an ID listbox, a report views selection, a scan selection, a
generate report button, a generate views button, an image display,
and an image slice slider. Alternatively, one or more off-the-shelf
applications can be used to generate the models, such as
SolidWorks, Rhinoceros, 3D Slicer or Amira.
[0089] If desired, in various embodiments a patient-specific
bone-surface model can be obtained and/or rendered. The bone
surface model can provide basic patient-specific features of the
patient's biological structure and serve as a reference for
comparison against a model or value that includes the defect(s) of
interest. As an illustrative example, previously generated
patient-specific files, for example, STL files exported from
"SOLID" IGES files in SolidWorks, can be loaded as triangulation
points with sequence indices and normal vectors. The triangles then
can be rendered (e.g., using Matlab TRISURF function) to supply or
generate the bone-surface model. The bone surface model can include
corrections of defects, such as osteophytes removed from the bone.
In a similar fashion, one or more guide tool models can be obtained
and/or rendered.
[0090] If desired, models can be used to detect interference
between any defect volume and the placement of one or more guide
tools and/or implant components. For example, guide tool model
triangulation points can be transformed onto an image volume space
to obtain a binary representation of the guide tool. The binary
structure then can be manipulated (e.g., dilated and eroded using
voxel balls having pre-set diameters) to obtain a solid field mask.
The solid field mask can be compared against the defect volume, for
example, the osteophyte binary volume, to identify interfering
defect volume, for example, interfering osteophyte binary volume.
In this way, interfering defect volume and non-interfering defect
volume can be determined (e.g., using Matlab ISOSURFACE function),
for example, using representative colors or some other
distinguishing features in a model. The resulting model image can
be rendered on a virtual rendering canvas (e.g., using Matlab
GETFRAME function) and saved onto a computer-readable medium.
Deformity Correction and Optimizing Limb Alignment
[0091] In certain embodiments, the degree of deformity correction
that is necessary to establish a desired limb alignment can be
calculated based on information from the alignment of a virtual
model of a patient's limb. The virtual model can be generated from
patient-specific data, such 2D and/or 3D imaging data of the
patient's limb. The deformity correction can correct varus or
valgus alignment or antecurvatum or recurvatum alignment. In a
preferred embodiment, the desired deformity correction returns the
leg to normal alignment, for example, a zero degree biomechanical
axis in the coronal plane and absence of genu antecurvatum and
recurvatum in the sagittal plane, or various other user-defined
alignment(s) can be designated and obtained.
[0092] Once the proper and/or desired alignment of the patient's
extremity has been determined virtually, one or more surgical steps
(e.g., resection cuts) may be planned and/or accomplished, which
may include the use of surgical tools (e.g., tools to guide the
resection cuts), and/or implant components (e.g., components having
variable thicknesses to address misalignment). Various features of
the patient-adapted implant components and/or the planned surgical
steps, including bone cut angles, bone cut slopes, bone cut number,
implant thickness in one or more portions, joint facing curvature,
implant component thickness, and other features, can be selected
and/or designed, at least in part, to optimize the parameter of
deformity correction and/or limb alignment, for example, using the
virtual alignment method described herein. Optionally, one or more
other parameters can simultaneously be factored into the selection
and/or design of implant component features and/or surgical
procedure. For example, in addition to limb alignment, the implant
component and/or surgical procedure features also can be selected
or designed meet one or more of the following parameters: (1)
preserving, restoring, or enhancing the patient's joint kinematics;
(2) deformity correction; (3) maximizing preservation of bone
cartilage, or ligaments (e.g., resulting from the resection); (4)
maximizing preservation and/or optimization of other features of
the patient's anatomy, such as trochlea and trochlear shape; (5)
restoration or optimization of joint-line location and/or joint gap
width, and (6) preservation, restoration, or enhancement of other
target features.
[0093] If desired, an implant design can alter the kinematics of
the patient knee as desired, such as, for example, by altering a
condyle location and/or surface to alter the implant motion and
ultimately the kinematics of the patient's limb. In a similar
manner, a surgical procedure plan can include modified resection
and bone cut planes that reposition and/or reorient the various
surfaces of a predetermined implant design, thereby altering the
location and/or orientation of articulating surfaces of a condyle
implant to desirably alter the implant motion and ultimately the
kinematics of the patient's limb.
Matching to Reference Databases
[0094] In various embodiments, one or more measured anatomical
features may be modeled, derived and/or modified using information
from one or more reference databases. For example, existing patient
information can be obtained from patient measurements through the
various methods described herein. Such information can include
various information regarding a targeted femur, tibia and patella
of a targeted knee joint, which in this case includes information
regarding the patient's femoral/tibial/patellar shape, length,
width, condyle dimensions, features and slopes, angles, e.g.,
trochlear angles, Q angle, trochlea characteristics, tibial
characteristics, tibial tuberosity, medial/lateral slopes, tibial
spine height, coronal curvatures, sagittal curvatures and general
joint dimensions, as well as any number of biomechanical or
kinematic parameters as described in the various sections and
Tables herein as well as those known in the art. The information
can also include anatomical and biomechanical axes, angles and
other information from the patient's opposing joint and well as
information regarding adjacent joint structures (i.e., hip and/or
ankle information) from the treated leg or the opposing leg or
both. Additional information collected can include body weight,
race, gender, activity level, health conditions, other disease or
medical conditions, etc. If desired, weighting parameters may be
assigned to various measurements or series of measurements (or
other collected or derived information), as well as to one or more
joint surfaces, including opposing joint surfaces.
[0095] Various disclosed embodiments contemplate utilizing various
of the collected and/or derived patient-specific information (as
well as any optional weighting parameters), which methods can
include identifying one or more "matching subjects" from one or
more reference databases, comparing features from the matching
subject to the patient-specific information, and optionally
creating a comparison or "weighting score" to evaluate and display
the results of the various comparisons (relative to individual
feature comparisons and/or an overall composite score for the
comparison of each subject). The databases can comprise information
from various sources, including cadaveric data, imaging,
biomechanical or kinematic data, historic data and/or data
regarding previous knee implant cases from various manufacturers,
including ConforMlS-specific case data. Such data can be specific
to gender, age, weight, health, size, etc., or can be selected
based on weighting (as previously described) or other criteria.
[0096] Next, the method manually or automatically selects one or
more anatomic shapes or features from one or more matching subjects
to create one or more "derived anatomic matches" and/or to modify
the patient-specific data. The "derived anatomic matches" may
comprise the features from one or more subjects, or may comprise a
composite anatomy derived from such shapes and/or subjects (which
may also be identified and/or derived utilizing a weighting score,
if desired). In addition, or if place of, this step, the method may
utilize the matching subject data to normalize or "smooth" the
patient-specific data and/or model, which can desirably correct or
normalize the patient-specific data and potentially correct the
patient-specific data for inherent deformities like osteophytes,
axis deformity and/or cartilage degradation.
[0097] In various alternative embodiments, one or more databases
may be created that include anatomical information of multiple
individuals, with preplanned surgical steps/tools and/or
pre-designed implant components associated with relevant anatomical
information. The associated information may be compiled from
records of previous surgeries and/or may be created by designers
and/or physicians using patient anatomical information from
specific patients and/or from general population groups and/or
averages. If desired, an automated and/or semi-automated system may
search these one or more databases using various data from a
prospective patient (utilizing one or more of any data sources
described herein, including actual anatomical data, variations,
reference points and features and/or models) and identify one or
more matches (or other relationships, such as similarities of
various relevant component features of individual anatomy) to one
or more individuals. The preplanned surgical steps/tools and/or
pre-designed implant components associated with such anatomy may
then be assessed, evaluated, rated and/or combined (if desired),
and the resulting information may be utilized to design and/or
select an appropriate implant and surgical plan/tools for the
prospective patient.
Using Parameters to Assess Implants, Tools and Procedures
[0098] Correcting a joint deformity and/or a limb alignment
deformity can include, for example, generating a virtual model of
the patient's joint, limb, and/or other relevant biological
structure(s); virtually correcting the deformity and/or aligning
the limb; and selecting and/or designing one or more surgical steps
(e.g., one or more resection cuts), one or more guide tools, and/or
one or more implant components to physically perform and/or
accommodate the correction.
[0099] Certain embodiments described herein include generating
and/or using a model, for example, a virtual model, of the
patient's joint that includes selected parameters and/or parameter
measurements and virtually selecting and/or designing one or more
implant components, and optionally resection cuts and/or guide
tools to fit the virtual model in accordance with the selected
parameters and/or parameter measurements. This approach allows for
iterative selection and/or design improvement and can include steps
to virtually assess fit relative to the selected parameters and/or
parameter measurements, such as (1) correction of a joint
deformity; (2) correction of a limb alignment deformity; (3)
preservation of bone, cartilage, and/or ligaments at the joint; (4)
preservation, restoration, or enhancement of one or more features
of the patient's biology, for example, trochlea and trochlear
shape; (5) preservation, restoration, or enhancement of joint
kinematics, including, for example, ligament function and implant
impingement; (6) preservation, restoration, or enhancement of the
patient's joint-line location and/or joint gap width; and (7)
preservation, restoration, or enhancement of other target
features.
Software for Testing/Verification of Component Suitability
[0100] In various embodiments, it is important to ensure that
optimization, correction and/or modifications of the joint,
implant, tools and/or procedure in one given manner do not
adversely and/or unacceptably affect the implant components or
joint in some other manner. In various embodiments, this
cross-checking or cross-referencing of proposed individual
modifications to the joint, implant, tools and/or surgical
procedure can be accomplished using software and automated and/or
semi-automated systems.
[0101] For example, an implant component may be selected and/or
adapted in shape so that it stays clear of (i.e., avoids incidental
and/or long-term contact with) important ligament structures
(either or both during the surgical insertion procedure as well as
after implantation). Imaging data can help identify or derive shape
or location information on such ligamentous structures.
[0102] As will be appreciated by those of skill in the art, the
process of selecting and/or designing an implant component feature
and/or feature measurement, resection cut feature and/or feature
measurement, and/or guide tool feature and/or feature measurement
can be tested against the information obtained regarding the
patient's biological features and/or other models, for example,
from one or more MRI or CT or x-ray images from the patient, to
ensure that the features and/or feature measurements are optimum
with respect to the selected parameter targets or thresholds.
Testing can be accomplished by, for example, superimposing the
implant image over the image for the patient's joint. In a similar
manner, load-bearing measurements and/or virtual simulations
thereof may be utilized to optimize or otherwise alter a derived
implant design. For example, where a proposed implant for a knee
implant has been designed, it may then be virtually inserted into a
biomechanical model or otherwise analyzed relative to the
load-bearing conditions (or virtually modeled simulations thereof)
it may encounter after implantation. These conditions may indicate
that one or more features of the implant are undesirable for
varying reasons (i.e., the implant design creates unwanted
anatomical impingement points, the implant design causes the joint
to function in an undesirable fashion, the joint design somehow
interferes with surrounding anatomy, the joint design creates a
cosmetically-undesirable feature on the repaired limb or skin
covering thereof, FEA or other loading analysis of the joint design
indicates areas of high material failure risk, FEA or other loading
analysis of the joint design indicates areas of high design failure
risk, FEA or other loading analysis of the joint design indicates
areas of high failure risk of the supporting or surrounding
anatomical structures, etc.). In such a case, such undesirable
features may be accommodated or otherwise ameliorated by further
design iteration and/or modification that might not have been
discovered without such analysis relative to the "real world"
measurements and/or simulation.
[0103] Such load-bearing/modeling analysis may also be used to
further optimize or otherwise modify the implant design, such as
where the implant analysis indicates that the current design is
"over-engineered" in some manner than required to accommodate the
patient's biomechanical needs. In such a case, the implant design
may be further modified and/or redesigned to more accurately
accommodate the patient's needs, which may have an unintended (but
potentially highly-desirable) consequence of reducing implant size
or thickness, reducing the required amount of bony support material
removal, increasing or altering the number and/or type of potential
implant component materials (due to altered requirements for
material strength and/or flexibility), increasing estimate life of
the implant, reducing wear and/or otherwise altering one or more of
the various design "constraints" or limitations currently
accommodated by the present design features of the implant and/or
surgical procedure.
[0104] In various embodiments, a finite element analysis can be
conducted on device components as one parameter in the optimization
of the features of an implant, which can include analyses of
multiple or "competing" potential designs for a given implant
component. In various alternative embodiments, implant components
such as a tibial tray can comprise sections of varying thickness.
If desired, the modeling software may conduct FEA or other load
analysis on the tibial tray (incorporating various patient-specific
information, including patient weight and intended activity levels,
among other factors) and determine if specific areas of the
intended implant design at are an undesirable risk of failure or
fatigue. Such areas can be reinforced, thickened or otherwise
redesigned (if desired) to accommodate and/or alleviate such risks
(desirably before actual manufacture of the implant). In a similar
manner, areas of lower stress/fracture risk can be redesigned (if
desired) by removal of material, etc., which may improve the fit
and/or performance of the implant in various ways. Of course,
either or both of the upper and lower surfaces of the tibial tray
may be processed and/or redesigned in this manner.
Software and Data Libraries
[0105] Data and models can be collected in one or more libraries
for subsequent use for the same patient or for a different patient
(e.g., a different patient with similar data). In certain
embodiments, a library can be generated to include images from a
particular patient at one or more ages prior to the time that the
patient needs a joint implant. For example, a method can include
identifying patients eliciting one or more risk factors for a joint
problem, such as low bone mineral density score, and collecting one
or more images of the patient's joints into a library. In certain
embodiments, all patients below a certain age, for example, all
patients below 40 years of age can be scanned to collect one or
more images of the patient's joint. The images and data collected
from the patient can be banked or stored in a patient-specific
database. For example, the articular shape of the patient's joint
or joints can be stored in an electronic database until the time
when the patient needs an implant. Then, the images and data in the
patient-specific database can be accessed and a patient-specific
and/or patient-engineered partial or total joint replacement
implant using the patient's original anatomy, not affected by
arthritic deformity yet, can be generated. This process results in
a more functional and more anatomic implant.
[0106] In a similar manner, pre-existing implant designs and/or
implant components can be selected from, catalogued in, and/or
stored in a library. The library can include a virtual library of
implants, or components, or component features that can be combined
and/or altered to create a final implant. The library can include a
catalogue of physical implant components. In certain embodiments,
physical implant components can be identified and selected using
the library. The library can include previously-generated implant
components having one or more patient-adapted features, and/or
components with standard or blank features that can be altered to
be patient-adapted. Accordingly, implants and/or implant features
can be selected from the library.
[0107] A virtual or physical implant component can be selected from
the library based on similarity to prior or baseline parameter
optimizations, such as one or more of (1) deformity correction and
limb alignment (2) maximum preservation of bone, cartilage, or
ligaments, (3) preservation and/or optimization of other features
of the patient's biology, such as trochlea and trochlear shape, (4)
restoration and/or optimization of joint kinematics, and (5)
restoration or optimization of joint-line location and/or joint gap
width. Accordingly, one or more implant component features, such as
(a) component shape, external and/or internal, (b) component size,
and/or (c) component thickness, can be determined precisely and/or
determined within a range from the library selection. Then, the
selected implant component can be designed or engineered further to
include one or more patient-specific features.
[0108] Accordingly, in certain embodiments an implant can include
one or more features designed patient-specifically and one or more
features selected from one or more library sources. For example, in
designing an implant for a total knee replacement comprising a
femoral component and a tibial component, one component can include
one or more patient-specific features and the other component can
be selected from a library.
[0109] The process can include generating and/or using a model, for
example, a virtual model, of the patient's joint that includes the
selected measurements and virtually fitting one or more selected
and/or designed implants into the virtual model. This approach
allows for iterative selection and/or design improvement and can
include steps to virtually assess the fit, such as virtual
kinematics assessment.
Modeling and Uses of Blanks and Blank Libraries
[0110] If desired, various components may be constructed as a
"standard" or "blank" in various sizes or may be specifically
formed for each patient based on their imaging data and anatomy.
Computer modeling may be used and a library of virtual standards
may be created for each of the components. A library of
physical
[0111] In various embodiments, the surgical alteration can be
simulated on a computer and the insert blank can then be shaped
based on the result of the simulation.
Surgical Repair and Kinematics Optimization
[0112] The modeling of a patient's anatomy, and the surgical repair
and/or replacement of a patient's anatomical features, provides the
surgeon and implant manufacturers with an opportunity to modify,
correct and/or otherwise optimize/enhance at least a portion of the
patient's anatomy. Many of the embodiments described herein relate
to improvements, alterations, optimizations and/or modifications to
the patient's biological features and/or to articular repair
systems (including implant components, tools/jigs and/or surgical
procedures), with an ultimate objective being the modification of
and/or improvement to joint and/or extremity alignment and/or
kinematics. Various embodiments include implant components that
incorporate various patient-engineered features optimized from
patient-specific data. Such patient-engineered features can include
(but are not limited to) one or more implant component surfaces,
such as surface contours, angles or bone cuts, and dimensions, such
as thickness, width, depth, or length of one or more aspects of the
implant component. Some embodiments can include alterations or
modifications to surgical tools/jigs and/or various surgical
procedure steps to modify the underlying anatomical support
surfaces in one or more desirable manners. Additional embodiments
can include inserts, spacers or other components to modify and/or
enhance the positioning, orientation and/or performance of the
implant, as well as the performance, kinematics and/or alignment of
the joint and/or extremity. Various combinations of the above
embodiments are contemplated as well, with varying results.
[0113] Preservation or restoration of the patient's joint
kinematics can include, for example, selecting and/or designing one
or more surgical steps (e.g., one or more resection cuts), one or
more guide tools, and/or one or more implant components so that the
patient's post-operative joint kinematics substantially match the
patient's pre-operative joint kinematics and/or substantially match
the patient's healthy joint kinematics (e.g., as identified from
previous images of the patient's joint when it was healthy or from
an image of the patient's contralateral healthy joint).
[0114] Enhancing the patient's joint kinematics can include, for
example, selecting and/or designing one or more surgical steps
(e.g., one or more resection cuts), one or more guide tools, and/or
one or more implant components that provide healthy joint
kinematics estimated for the particular patient and/or that provide
proper joint kinematics to the patient. Optimization of joint
kinematics also can include optimizing ligament loading or ligament
function during motion.
[0115] Enhancing the patient's joint-line location and/or joint gap
width can include, for example, selecting and/or designing one or
more surgical steps (e.g., one or more resection cuts), one or more
guide tools, and/or one or more implant components that provide a
healthy joint-line location and/or joint gap width and/or estimated
for the particular patient and/or that provide proper kinematics to
the patient.
Patient Anatomy Modeling
[0116] As described herein, a computer program or other automated
processing equipment can be utilized in effectuating the various
methods and systems described herein. An initial step in assessing
one or more anatomical features of a patient is to obtain
information about the size, shape and/or condition of the relevant
patient anatomy. For an orthopedic implant, this process typically
includes obtaining one or more images of the patient's joint and/or
other relevant patient anatomy (i.e., adjacent anatomical areas
and/or other features of interest) using, for example, non-invasive
imaging modalities or scans (including those previously described,
as well as those known in the art). The raw electronic image data
can be used to create one or more representations or "models" of
the patient's anatomy. These representations can include electronic
and/or virtual models as well as 2-Dimensional images and/or
3-Dimensional physical reproductions of the patient anatomy.
[0117] In various embodiments, the models can include anatomic
reference points and/or limb alignments, including alignment angles
within the same and between different joints as well as comparisons
to simulated normal limb alignment(s). Any anatomic features,
including those related to alignment and/or misalignment, can be
selected and imaged. For example, in certain embodiments, such as
for a knee or hip implant, the imaging test can include data from
at least one of, or several of, a hip joint, knee joint and ankle
joint. The imaging test can be obtained in lying, prone, supine or
standing position. The imaging test can include only the target
joint, or both the target joint and also selected data through one
or more adjoining joints as well as data from opposing joints
and/or structures adjacent thereto.
[0118] The models (as well as the raw anatomical information) can
be used to simulate biomotion of one or more joints and/or
extremities, such as a knee joint, or a knee and ankle joint, or a
hip, knee and/or ankle joint. In various embodiments, the computer
can model the existing patient anatomy for various uses, including
(1) to create patient-specific imaging data and/or models thereof,
(2) to identify deficiencies in the existing anatomy, (3) to
determine if replication of the existing patient anatomy would
create a desired or acceptable outcome for the joint
repair/replacement procedure, (4) to derive, identify and/or plan
modifications or alterations to the existing anatomy to create one
or more desired anatomical features for the patient's anatomy, (5)
to design joint repair/replacement implant components, surgical
tools and surgical procedures for treating the relevant patient
anatomy, and/or (6) to plan surgical repair and replacement
procedures for display to and/or further use by surgeons and/or
patients.
[0119] Various additional information can be incorporated into the
model(s), including patient-specific kinematic data, such as
obtained in a gait lab. If desired, patient-specific navigation
data, for example generated using a surgical navigation system,
image guided or non-image guided can be fed into the computer
program. This kinematic or navigation data can, for example, be
generated by applying optical or RF markers to the limb and by
registering the markers and then measuring limb movements, for
example, flexion, extension, abduction, adduction, rotation, and
other limb movements. Optionally, other data including
anthropometric data may be added for each patient. These data can
include but are not limited to the patient's age, gender, weight,
height, size, body mass index, and race. Desired limb alignment
and/or deformity correction can also be added into the model.
[0120] A patient-specific biomotion model can be derived that
includes combinations of parameters listed above. The biomotion
model can simulate various activities of daily life including
normal gait, stair climbing, descending stairs, running, kneeling,
squatting, sitting and any other physical activity. The biomotion
model can start out with standardized activities, typically derived
from reference databases. These reference databases can be, for
example, generated using biomotion measurements using force plates
and motion trackers using radiofrequency or optical markers and
video equipment. If desired, the biomotion model can subsequently
be modified and/or queried by the inclusion of patient-specific
activities, such as golfing, mountain climbing, swimming, scuba
diving, etc.
[0121] In addition to (or in place of) the above-mentioned
measurements, it may be desirable to obtain measurements of the
targeted joint (as well as surrounding anatomical areas and or
other joints of the patient's anatomy) in a load-bearing or
otherwise "real-world" condition. Such measurements can potentially
yield extremely useful data on the alignment and/or movement of the
joint and surrounding structures (as well as the loading conditions
of the various joint components)--information which may be
difficult to obtain or model from standard imaging techniques
(i.e., sitting or lying X-rays, CT-scans and/or MRI imaging). Such
load-bearing measurements can include imaging of the patient
standing, walking and/or carrying loads of varying sizes and/or
weights.
[0122] It may also be desirable to model various of the patient
measurements (especially non-load-bearing measurements as described
above) to simulate the targeted joint and surrounding anatomy
virtually. Such simulations can include virtually modeling the
alignment and load bearing condition of the joint and surrounding
anatomical structures for the patient standing and/or moving (i.e.,
walking, running, jumping, squatting, kneeling, walking up and down
stairs or inclines/declines, picking up objects, etc.). Such
simulations can be used to obtain valuable anatomical,
biomechanical and kinematic data including the loaded condition of
various joint components, component positions, component movement,
joint and/or surrounding tissue anatomical or biomechanical
constraints or limitations, as well as estimated mechanical axes in
one or more directions (i.e., coronal, sagittal or combinations
thereof). This information could then be utilized (alone or in
combination with other data described herein) to design various
features of a joint resurfacing/replacement implant. This method
can be incorporated in the various embodiments described herein as
additional patient measurement and anatomical/joint modeling and
design data. This analysis is applicable to many different joints,
including a medial condyle, a lateral condyle, a trochlea, a medial
tibia, a lateral tibia, the entire tibia, a medial patella, a
lateral patella, an entire patella, a medial trochlea, a central
trochlea, a lateral trochlea, a portion of a femoral head, an
entire femoral head, a portion of an acetabulum, an entire
acetabulum, a portion of a glenoid, an entire glenoid, a portion of
a humeral head, an entire humeral head, a portion of an ankle
joint, an entire ankle joint, and/or a portion or an entire elbow,
wrist, hand, finger, spine or facet joint.
[0123] The biomotion model can then be individualized with use of
patient-specific information including at least one of, but not
limited to the patient's age, gender, weight, height, body mass
index, and race, the desired limb alignment or deformity
correction, and the patient's imaging data, for example, a series
of two-dimensional images or a three-dimensional representation of
the joint for which surgery is contemplated.
Modeling and Model Correction/Modification
[0124] At any point in the design and/or selection procedure,
including any point before or after initial design and/or selection
of implant components, tools and/or surgical procedure planning has
been completed, biomotion models for a particular patient can be
supplemented with patient-specific finite element modeling,
kinematic modeling and/or other biomechanical models known in the
art. Anticipated motion and/or resultant forces in the knee joint
can be calculated for each component or combination of components
for each specific patient. The implant and/or surgical procedure
can be engineered to the patient's load and force demands. For
instance, in one embodiment a patient weighing 125 lbs. may not
need a tibial plateau as thick as a patient weighing 280 lbs.
Similarly, the polyethylene can be adjusted in shape, thickness and
material properties for each patient. For example, a 3 mm
polyethylene insert can be used in a light lite patient with low
force, and a heavier or more active patient may need an 8 mm
polymer insert or similar device. Such considerations may require
and/or recommend changes to the initially designed and/or selected
implant components, tools and/or surgical procedure steps.
[0125] From a three-dimensional perspective, the lower extremity of
the body ideally functions within a single plane known as the
median anterior-posterior plane (MAP-plane) throughout the
flexion-extension arc. In order to accomplish this, the femoral
head, the mechanical axis of the femur, the patellar groove, the
intercondylar notch, the patellar articular crest, the tibia and
the ankle will desirably remain within the MAP-plane during the
flexion-extension movement. During movement, the tibia rotates as
the knee flexes and extends in the epicondylar axis, which is
perpendicular to the MAP-plane.
Using Kinematics to Plan Implants/Procedure Steps
[0126] Once one or more reference points, measurements, structures,
surfaces, models, or combinations thereof have been determined,
selected, varied, deformed, altered or derived, the resulting
models and/or features can be used to select and/or design one or
more implant components having an ideal or optimized feature or
shape, e.g., corresponding to the measured, deformed, altered
and/or corrected joint feature(s) or shape(s). For example, one
application of this embodiment could create an ideal or optimized
implant shape that reflects the shape of the patient's joint before
he or she developed arthritis.
[0127] In various embodiments, the comparison, analysis and/or
modifications may include modification of one or more
patient-specific features and/or design criteria for the implant to
account for any underlying deformity reflected in the
patient-specific measurements. If desired, the modified data may
then be utilized to choose or design an appropriate implant to
match the modified features, and a final verification operation may
be accomplished to ensure the chosen implant is acceptable and
appropriate to the original unmodified patient-specific
measurements (i.e., the chosen implant will ultimately "fit" the
original patient anatomy). In alternative embodiments, the various
anatomical features may be differently "weighted" during the
comparison process (utilizing various formulaic weightings and/or
mathematical algorithms), based on their relative importance or
other criteria chosen by the designer/programmer and/or
physician.
[0128] In various exemplary embodiments, such as shown in FIG. 30,
after a model representation of a joint is generated 2730, the
practitioner optionally can generate a projected model
representation of the target joint in a corrected condition 2740,
e.g., based on a previous image of the patient's joint when it was
healthy, based on an image of the patient's contralateral healthy
joint, based on a projected image of a surface that
negatively-matches the opposing surface, based on one or more
database images of various patient or population-matched "normal"
or "healthy" joints, or various combinations thereof. This step can
be repeated 2741, as necessary or as desired. Using the difference
between the topographical condition of the joint and the projected
image of the joint, the practitioner can then select a joint
implant 2750 that is suitable to achieve the corrected joint
anatomy. As will be appreciated by those of skill in the art, the
selection and/or design process 2750 can be repeated 2751 as often
as desired to achieve the desired result. Additionally, it is
contemplated that a practitioner can obtain a measurement of a
target joint 2710 by obtaining, for example, an x-ray, and then
selects a suitable joint replacement implant 2750.
[0129] In various embodiments, virtual models of a patient's
misaligned lower limb can be virtually corrected. In particular,
the patient's lower limb may be misaligned in the coronal plane,
for example, a valgus or varus deformity. The deformity correction
can be achieved by designing and/or selecting one or more of a
resection dimension, an implant component thickness, and an implant
component surface curvature that adjusts the mechanical axis or
axes into alignment in one or more planes. For example, a lower
limb misalignment can be corrected in a knee replacement by
designing or selecting one or more of a femoral resection
dimension, a femoral implant component thickness, a femoral implant
component surface curvature, a tibial resection dimension, a tibial
implant component thickness, a tibial implant component insert
thickness, and a tibial implant component surface curvature to
adjust the femoral mechanical axis and tibial mechanical axis into
alignment in the coronal plane.
[0130] Information regarding the misalignment and the proper
mechanical alignment of a patient's limb can be used to
preoperatively design and/or select one or more features of a joint
implant and/or implant procedure. For example, based on the
difference between the patient's misalignment and the proper
mechanical axis, a knee implant and implant surgical procedure can
be designed and/or selected preoperatively to include implant
and/or resection dimensions that substantially realign the
patient's limb to correct or improve a patient's alignment
deformity. In addition, the process can include selecting and/or
designing one or more surgical tools (e.g., guide tools or cutting
jigs) to direct the clinician in resectioning the patient's bone(s)
in accordance with the preoperatively designed and/or selected
resection dimensions.
[0131] In certain embodiments described herein, an implant or
implant system can include one, two, three, four or more components
having one or more patient-specific features that substantially
match one or more of the patient's biological features, for
example, one or more dimensions and/or measurements of an
anatomical/biological structure, such as bone, cartilage, tendon,
or muscle; a distance or space between two or more aspects of a
biological structure and/or between two or more different
biological structures; and a biomechanical or kinematic quality or
measurement of the patient's biology. In addition or alternatively,
an implant component can include one or more features that are
engineered to optimize or enhance one or more of the patient's
biological features, for example, (1) deformity correction and limb
alignment (2) preserving bone, cartilage, and/or ligaments, (3)
preserving and/or optimizing other features of the patient's
anatomy, such as trochlea and trochlear shape, (4) restoring and/or
optimizing joint kinematics or biomechanics, and/or (5) restoring
and/or optimizing joint-line location and/or joint gap width. In
addition, an implant component can be designed and/or manufactured
to include one or more standard (i.e., non-patient-adapted)
features.
Designing Implants/Procedures to Alter Kinematics
[0132] There are several advantages that a patient-specific implant
designed and/or engineered to meet or improve one of more of these
parameters can have over a traditional implant. These advantages
can include, for example: improved mechanical stability of the
extremity; improved fit with existing or modified biological
features; improved motion and kinematics, and other advantages.
[0133] In various embodiments, an implant component (such as a
tibial component) can be designed either before or after virtual
removal of various features of the underlying anatomical support
structure (i.e., a tibial bone) have been accomplished. In one
embodiment, the initial design and placement of a tibial tray and
associated components can be planned and accomplished utilizing
information directly taken from the patient's natural anatomy. In
various other embodiments, the design and placement of the tibial
components can be planned and accomplished after virtual removal of
various bone portions, including the removal of one or more cut
planes (to accommodate the tibial implant) as well as the virtual
removal of various potentially-interfering structures (i.e.,
overhanging osteophytes, etc.) and/or the virtual filling of voids,
etc. Prior virtual removal/filling of such structures can
facilitate and improve the design, planning and placement of tibial
components, and prevent anatomic distortion from significantly
affecting the final design and placement of the tibial components.
For example, once one or more tibial cut planes has been virtually
removed, the size, shape and rotation angle of a tibial implant
component can be more accurately determined from the virtual
surface, as compared to determining the size, shape and/or tibial
rotation angle of an implant from the natural tibial anatomy prior
to such cuts. In a similar manner, structures such as overhanging
osteophytes can be virtually removed (either alone or in addition
to virtual removal of the tibial cut plane(s)), with the tibial
implant structure and placement (i.e., tibial implant size, shape
and/or tibial rotation, etc.) subsequently planned. Of course,
virtually any undesirable anatomical features or deformity,
including (but not limited to) altered bone axes, flattening,
potholes, cysts, scar tissue, osteophytes, tumors and/or bone spurs
may be similarly virtually removed and then implant design and
placement can be planned.
Kinematic Libraries
[0134] As part of the selection and/or design process, a virtual or
physical implant component can be selected from a library based on
similarity to prior or baseline parameter optimizations, such as
one or more of (1) deformity correction and limb alignment (2)
maximum preservation of bone, cartilage, or ligaments, (3)
preservation and/or optimization of other features of the patient's
biology, such as trochlea and trochlear shape, (4) restoration
and/or optimization of joint kinematics, and (5) restoration or
optimization of joint-line location and/or joint gap width.
Accordingly, one or more implant component features, such as (a)
component shape, external and/or internal, (b) component size,
and/or (c) component thickness, can be determined precisely and/or
determined within a range from the library selection. Then, the
selected implant component can be designed or engineered further to
include one or more patient-specific features. For example, a joint
can be assessed in a particular subject and a pre-existing implant
design having the closest shape and size and performance
characteristics can be selected from the library for further
manipulation (e.g., shaping) and manufacturing prior to
implantation. For a library including physical implant components,
the selected physical component can be altered to include a
patient-specific feature by adding material (e.g., laser sintering)
and/or subtracting material (e.g., machining).
[0135] In certain embodiments, the library could be generated to
include images from the particular patient (or a similar patient or
patient population) at one or more ages prior to the time that the
patient needs a joint implant. Then, the images and data in the
patient-specific database can be accessed and a patient-specific
and/or patient-engineered partial or total joint replacement
implant using the patient's original anatomy, not affected by
arthritic deformity yet, can be generated. This process could
result in an implant with improved kinematics and/or alignment as
compared to the patient's current condition.
Modeling Procedural Steps to Alter Kinematics
[0136] In certain embodiments, bone cuts and/or implant shape
including at least one of a bone-facing surface of the implant can
be designed or selected to achieve normal and/or desired joint
kinematics. For example, in certain embodiments, the joint-facing
surface of an implant component is designed to match the shape of
the patient's articular cartilage. If desired, the joint-facing
surface can substantially positively-match one or more features of
the patient's existing cartilage surface and/or healthy cartilage
surface and/or a calculated cartilage surface, on the articular
surface that the component replaces. Alternatively, it can
substantially negatively-match one or more features of the
patient's existing cartilage surface and/or healthy cartilage
surface and/or a calculated cartilage surface, on the opposing
articular surface in the joint.
[0137] If desired, corrections can be performed to the shape of
diseased cartilage by designing surgical steps (and, optionally,
patient-adapted surgical tools) to re-establish a normal or near
normal cartilage shape that can then be incorporated into the shape
of the joint-facing surface of the component. These corrections can
be implemented and, optionally, tested in virtual two-dimensional
and three-dimensional models. The corrections and testing can
include kinematic analysis and/or surgical steps.
Modeling Exemplary Designs to Alter Kinematics
[0138] A wide variety of implant component designs and/or
selections can be employed to alter, modify and/or optimize the
kinematics and/or performance of a patient's joint and joint
replacement implant. Moreover, it is often possible to attain a
desired extremity alignment through a variety of implant and
surgical procedure designs and/or selections. For example, a
desired change in the alignment of a knee implant can accomplished
by using an implant component specifically designed to create a
specific alignment of one or more articulating surfaces. As an
alternative approach, surgical resection cuts can be planned such
that, in conjunction with a standard implant component, the
specific alignment of one or more articulating surfaces of the
standard implant can be attained. In a similar manner, a desired
alteration of the alignment of medial and lateral condyles of a
tibial implant component (relative to a femoral implant component)
can be obtained via numerous approaches and techniques, including
(1) by increasing the height of the medial component relative to
the lateral component, (2) by decreasing the height of the lateral
component relative to the medial component, (3) by altering the
angle and/or thickness of the tibial tray, (4) by altering the
tibial cut surfaces and/or angulations, and (5) by altering the
surfaces of the opposing femoral component condyles, etc.
Kinematic Balancing in Various Joints
[0139] The use of techniques similar to those discussed herein can
be applied to a wide variety of joints, some of which may be
modified or altered to varying degrees to account for unique or
dissimilar anatomical features. For example, in some embodiments,
imaging data can initially be obtained and analyzed, either
manually or with computer assistance, to determine the patient
specific parameters relevant for placing an implant component in a
particular anatomical location. The parameters can include patient
specific articular dimensions and geometry and also information
about ligament location, size, and orientation, as well as
potential soft-tissue impingement, and, optionally, kinematic
information for the particular joint or anatomy of interest.
Guide Tools and Surgical Jigs
[0140] A variety of traditional guide tools are available to assist
surgeons in preparing a joint for an implant, for example, for
resectioning one or more of a patient's biological structures
during a joint implant procedure. However, these traditional guide
tools typically are not designed to match the shape (contour) of a
particular patient's biological structure(s). Moreover, these
traditional guide tools typically are not designed to impart
patient-optimized placement for the resection cuts. Thus, using and
properly aligning traditional guide tools, as well as properly
aligning a patient's limb (e.g., in rotational alignment, in varus
or valgus alignment, or alignment in another dimension) in order to
orient these traditional guide tools, can be an imprecise and
complicated part of the implant procedure.
Kinematic Modeling of Soft Tissues
[0141] In an effort to improve the design and/or selection of
implant components, tools and/or surgical procedures for a given
patient, the accurate modeling and reproduction of in vivo joint
kinematics can include the incorporation of soft tissue modeling.
Because the constraints provided by soft tissues are very complex
in nature, and can include the application of nonlinear force
displacement characteristics and axis coupled behavior, inclusion
of such information in a joint model can significantly alter the
anticipated quantity and direction of loading or other forces that
may be experienced by one or more joint resurfacing/replacement
implant components over a wide range of joint motion. The proper
consideration and/or use of such information has the potential to
significantly improve the clinical outcomes of joint arthroplasty
procedures.
[0142] In various embodiments, a kinematic profile and/or model of
a joint can include biomechanical modeling, e.g., of muscles,
ligaments and other soft tissues associated with the joint. If
desired, this modeling can be in addition to kinematic modeling of
the hard tissue structures and/or articulating surfaces of the
joint, and such models can include hybrid models incorporating
various features of both hard and soft tissue structures. Such
"hybrid" biomechanical models can be built with generic information
(e.g., related to the muscles, ligaments or other soft tissues), or
can include patient-specific information (e.g., information derived
from a patient's image data or non-image derived patient-specific
information), or various combinations thereof. Such
patient-specific image data can include different joint positions,
motion imaging and motion analysis. Such non-image derived
patient-specific information can include biomechanical properties
of the muscles, e.g., contractile response (e.g., force produced or
changes in muscle length, width or other dimensions during a
contractile response) of the muscles.
[0143] A hybrid kinematic model as described herein can include
muscle simulations including muscle activation and ligament
simulations. The muscle data and/or ligament data can be selected
from a pre-existing database. Alternatively, the patient's scan
data can be used to introduce muscle data or ligament data of the
patient or combinations thereof. For example, the location of a
muscle, its width and volume can be introduced into the hybrid
kinematic model, for example for purposes of estimating muscle
strength and forces. The moment arms can be determined based on the
location of the muscles and their tendons. Tendon location, width,
length, thickness can be introduced into the hybrid model, for
example derived from the patient's scan data. Tendons can be
directly visualized on the scan and segmented and introduced into
the model. Alternatively, the tendon origin and insertion can be
identified on the scan and can be used for kinematic modeling.
[0144] In various embodiments, the results of such hybrid kinematic
modeling can be utilized to assess and/or modify the design and/or
selection of one or more patient-adapted implants, surgical tools
and/or surgical procedure plans. For example, a hybrid kinematic
model incorporating soft tissue modeling may be utilized to
determine a maximum material stress throughout the entirety of a
joint implant's range of motion, which may indicate that the
implant design is under-designed to accommodate some portion of the
anticipated loading. In contrast, a static kinematic model of the
same joint and implant components in pure flexion and/or extension
(without soft tissue modeling information included) could
potentially conclude that the implant component is adequately
designed to accommodate the anticipated forces. By including soft
tissue modeling, therefore, it can be possible to more accurately
estimate the various loading conditions experienced by implant
components, and anticipate and/or accommodate undesired loading
conditions revealed therewith.
[0145] In various embodiments, an implant component position and/or
orientation could be adjusted in a hybrid kinematic model to
achieve desired post-implantation joint kinematics or biomotion
patterns or performance. Bone cuts or reaming or drilling or other
surgical interventions could be simulated and/or adjusted to change
the implant position, for example in a knee joint, a hip joint or a
shoulder joint. The adjustment or optimization of the implant
position and orientation and any related surgical interventions
could be performed manually, with optionally re-assessment of the
kinematic or biomotion pattern or performance after adjustment. The
adjustment or optimization of the implant position and orientation
and any related surgical interventions could also be performed
automatically or semi-automatically, e.g. with optional manual user
interaction or input. By utilizing the patient's anatomic
information to select an implant and by optionally utilizing the
patient's demographic, anatomic, axis, biomechanical and/or hybrid
kinematic information, it can be possible to optimize implant
placement/position and orientation on one or more articular sides
or portions thereof, thereby potentially improving the
postoperative kinematic results. In one exemplary embodiment, the
optimizations could be focused towards achieving a postoperative,
e.g. post implantation, condition for a given patient that would
result in a natural or near natural state of joint kinematics or
biomotion similar to a health, unoperated state.
[0146] In various embodiments, the hybrid kinematic model with one
or more implant components incorporated therein could also include
information about the patient's bone quality parameters, bone
stock, bone shape, cartilage shape, articular curvatures, slopes as
well as ligament and muscle information.
[0147] In a given hybrid kinematic model, the position and/or
orientation of one or more implant components could be adjusted by
adjusting the position of one or more patient-adapted guide tools
or templates or by adjusting the position of drill guides or cut
guides or other guides within these molds or attached to these
molds, thereby adjusting the implant position or orientation.
Exemplary parameters of implant position or orientation that could
be influenced or optimized in this manner could include parameters
based on database information, pre-operative scan measurements
and/or scan data, as well as intraoperative measurements including,
but not limited to: [0148] Implant position, e.g. AP, ML, SI [0149]
Implant position to avoid notching, e.g. in knee implants [0150]
Implant orientation [0151] Implant rotation, e.g. internal or
external [0152] Implant flexion [0153] Implant extension [0154]
Implant anteversion [0155] Implant retroversion [0156] Implant
abduction [0157] Implant adduction [0158] Implant joint line, e.g.
between a femoral component and a tibial component
[0159] In various embodiments, a hybrid kinematic model could
include data obtained by moving a joint through a range of motion,
which can include pre-operative imaging of the joint as well as
intraoperative imaging of the joint with a trial or actual implant
or implant component in place, but not permanently affixed yet to
the joint. Various such measurements could be obtained, including:
[0160] Preoperative [0161] Active [0162] Passive [0163] With
optional stress testing [0164] Intraoperative prior to performing
surgical steps, i.e. on the unaltered joint [0165] Active, e.g.
before anesthesia [0166] Passive [0167] Passive with optional
stress testing [0168] Intraoperative after performing surgical
steps [0169] Passive [0170] Passive with optional stress testing
[0171] Intraoperative with trial implant in place [0172] Passive
[0173] Passive with optional stress testing [0174] Intraoperative
with definitive implant in place, not affixed yet. [0175] Passive
[0176] Passive with optional stress testing [0177] Intraoperative
with definitive implant in place, affixed to joint/bone [0178]
Passive [0179] Passive with optional stress testing
[0180] In various embodiments, the same or similar measurements
could be obtained for a given joint from a contralateral joint,
pre-operatively or intraoperatively. Alternatively, a database of
the same of contralateral joints from a given patient and/or
patient population may be queried and/or utilized.
[0181] Based on joint kinematics assessment and hybrid modeling,
the position or orientation of a guide tool could optionally be
adjusted as a technique for adjusting the position or orientation
of the implant after placement in order to achieve a better or more
desired kinematic result. The position or orientation of a guide
within a guide tool could similarly and/or alternatively be
optionally adjusted as a technique for adjusting the position or
orientation of the implant after placement in order to achieve a
better or more desired kinematic result. The position or
orientation of both a guide tool and a guide within a guide tool
could be optionally adjusted as a technique of adjusting the
position or orientation of the implant after placement in order to
achieve a better or more desired kinematic result. A wide variety
of improved and/or desired kinematic results could be obtained,
including: [0182] improvements in ligament balancing, e.g.
optimization of flexion and extension gap or balancing; [0183]
improvements in range of motion, e.g. flexion and extension; [0184]
improvements in joint stability, e.g. as a means of reducing the
possibility of subluxation or dislocation; [0185] improvements in
performance for select daily activities, e.g. stair climbing or
going downstairs; [0186] avoidance or reduction of well know
problems with joint replacement, e.g. mid-flexion instability.
[0187] In various embodiments described herein, thereof, one can
measure joint motion prior to implantation (e.g. pre-operatively or
intra-operatively) or after performing select surgical steps.
Preoperative (e.g. via a virtual simulation of joint kinematics
optionally including patient data including scan data) and
intraoperative measurements can include measurements of one or more
dimensions of the joint (e.g. in an AP, ML, SI or oblique planes),
one or more curvatures of the joint (e.g. of cartilage or
subchondral bone), one or more slopes of the joint (e.g. from a
medial to a lateral condyle), measurements of distances (e.g. a
condylar length or height or width of a notch), and measurements or
estimations of ligaments, ligament locations, strength, insertion,
origin, muscle location, strength, insertion, origin and the like.
Any of these simulations and/or models, both pre-operatively and
intraoperatively, can also include finite element modeling, for
example for estimating the stress or forces exerted on an implant
(e.g. in select implant locations or along a chamfer cut). The
finite element data can be augmented with patient specific data
(e.g., data obtained from the patient's scan including also for
example bone mineral density or structure) or any of the parameters
mentioned above and throughout the specification.
[0188] If kinematic optimizations are simulated pre-operatively,
they can be used to adjust the position or orientation of a mold or
guide or combinations thereof used during surgery. This can,
optionally, result in a change of the physical shape of the guide
or the mold. If kinematic measurements are performed during the
surgical procedure, for example by measuring marker motion during a
range of motion prior to placing an implant, the position or
orientation of a patient specific mold or guide included therein or
attached thereto can be adjusted intraoperatively. Such adjustments
can be, for example, performed with use of shims, spacers, spacer
blocks, ratchet-like mechanisms, dial-like mechanisms, electronic
mechanisms, and other mechanisms known in the art or developed in
the future. Alternatively, the guide tool can include more than one
guide so that the position of a drill hole, a peg hole or a cut can
be adjusted intraoperatively. Alternatively, the guide tool can
allow for attachment of a block, e.g. for drilling or cutting,
either in multiple different locations for kinematic optimization,
or the position of the guide tool can be adjusted by inserting, for
example, shims or spacers between the guide tool and the block.
[0189] Thus, while patient adapted guide tools will typically place
an implant in a fixed position and orientation, for example
relative to one or more anatomic or biomechanical axes or anatomic
landmarks, the methods described herein allow for optimization of
implant position for a desired, improved kinematic result.
[0190] A wide variety of possible adjustments for implant
components are contemplated in the various embodiments discussed
herein, including: adjustment of implant flexion (or extension)
relative to one or more anatomic or biomechanical axes (e.g.
femoral component flexion in a knee prosthesis); adjustment of
implant rotation (e.g. internal or external) relative to one or
more anatomic or biomechanical axes or landmarks (e.g. femoral
component rotation for flexion and/or extension balancing), or
tibial component rotation; adjustment of anterior or posterior
implant position (e.g. femoral component position--for flexion
balancing) or tibial component position relative to one or more
anatomic or biomechanical axes or landmarks; adjustment of medial
or lateral implant position (e.g. femoral component position or
tibial component position relative to one or more anatomic or
biomechanical axes or landmarks); and/or adjustment of superior or
inferior implant position (e.g. femoral component position or
tibial component position relative to one or more anatomic or
biomechanical axes or landmarks--optionally performed via
recuts).
[0191] The various adjustments contemplated herein can include
repositioning and/or rotating an AP cut guide on a distal femur, in
order to rotate the implant position. A flexion spacer or cut guide
can be rotated or changed in position, for example with a spacer or
shim, in order to change implant position or orientation, for
example for flexion balancing. A tibial guide can be rotated, for
example for controlling varus or valgus or for controlling tibial
component rotation.
[0192] In various embodiments, an ultrasound scan can be obtained.
The ultrasound scan can be obtained in 1D, 2D and 3D. The scan can
include information about the curvature of the joint, e.g. a
cartilage or subchondral bone, and its surface shape. This
information can be used to generate a patient adapted guide tool
with at least one portion including a patient specific surface
derived from the scan.
[0193] In various embodiments, 4D imaging can be employed, as it
can be a preferred mode for imaging of joint motion, with the three
dimensions being space and the 4th dimension being time or motion.
Joint motion that can be measured can include, but is not limited
to: translation of one articular surface relative to the other;
rotation of one articular surface relative to the other during:
Flexion; Extension; Abduction; Adduction; Elevation; Internal
rotation; External rotation; and other joint movements.
[0194] In various embodiments, the resultant kinematic scan data
(3D or 4D) can be used to assess joint motion prior to surgery.
Such ultrasound based kinematic data can be captured for the joint
that will be operated or for the contralateral joint. A surgical
procedure, e.g. a ligament repair (e.g. ACL), an osteotomy or an
implant placement can then be simulated on the data. If an implant
placement is performed, optionally virtual cuts, drilling or
reaming can be introduced. The implant surfaces can be superimposed
and the kinematics or biomotion after implant placement can be
assessed and compared to the unoperated state.
[0195] Many simulations and optimizations can be performed in order
to achieve postoperative kinematics that closely resemble the
preoperative kinematics or in the case of severe arthritis that
resemble the kinematics of the patient in the pre-arthritic state.
These simulations or optimizations can include: [0196] Selection of
an implant size; [0197] Selection of implant shape(s), e.g. on a
femur or a tibia or a tibial insert shape (including, for example,
sagittal curvature, coronal curvature of femoral component(s),
tibial component, insert height etc.) [0198] Selection of an
implant position; [0199] Selection of an implant orientation;
[0200] Selection of a resection height or level, e.g. on a femur or
a tibia or a glenoid or an acetabulum or a femoral neck in order to
maintain a joint line location after implantation similar to the
unoperated state.
[0201] If a patient specific implant is employed as part of the
various embodiments described herein, any of the parameters in
Table 1 can be adapted or changed in order to optimize the
kinematic result relative to the preoperative simulation (based on
ultrasound, other scans or databases or combinations thereof).
Muscle Kinematics
[0202] Various embodiments described herein can include the
modeling of muscle kinematics as part of a hybrid kinematics
analysis and modeling technique to facilitate a joint arthroplasty
procedure. A human body typically includes four muscle regions:
head and neck; trunk, front and back; brachium, antebrachium and
hand; thigh, leg and foot. Each muscle region includes certain
muscle groups, and each muscle group includes certain muscles with
their own origins and insertions, as well as distinct functions. As
described below, various muscle groups and/or component muscles
therein may be modeling and included in a hybrid kinematic
model:
TABLE-US-00003 Muscle Muscle Region Group Muscle Origin Insertion
Action Head Suboccipital Obliquus spinous transverse rotates the
head and capitis process of axis process of atlas to the contracted
Neck inferior (C2) (C1) side Obliquus transverse between superior
bilaterally capitis process of and inferior extends the superior
atlas (C1) nuchal line of head; laterally occiput flexes to the
contracted side Rectus spinous inferior nuchal bilaterally capitis
process of axis line (lateral to extends the posterior (C2) minor)
head; rotates the major head to the contracted side Rectus
posterior inferior nuchal bilaterally capitis tubercle of line
(adjacent to extends the posterior atlas (C1) midline) head minor
Prevertebral Longus colli lower anterior anterior vertebral flexes
the head vertebral bodies and and neck bodies and transverse
transverse processes processes several segments above Longus upper
anterior anterior vertebral flexes the head capitis vertebral
bodies and and neck bodies and transverse transverse processes
processes several segments above Rectus anterior base occipital
bone flexes the head capitis of the anterior to anterior transverse
foramen magnum process of the atlas Rectus transverse jugular
process of bends the head capitis process of the the occipital bone
laterally lateralis atlas Anterolateral Anterior anterior 1st rib
if transverse Neck scalene tubercles of process fixed: transverse
elevates the ribs processes of for respiration; C3-C6 if ribs
fixed: rotates to side opposite of contraction laterally flexes to
the contracted side bilaterally flexes the neck Scalenus anterior
1st rib and/or if transverse minimus tubercles of supraplural
process fixed: transverse membrane elevates the ribs processes of
for respiration; C6 & 7 if ribs fixed: rotates to side opposite
of contraction laterally flexes to the contracted side bilaterally
flexes the neck Middle transverse 1st rib (behind if transverse
scalene processes of anterior scalene) process fixed: all cervical
elevates the ribs vertebrae for respiration; if ribs fixed: rotates
to side opposite of contraction laterally flexes to the contracted
side bilaterally flexes the neck Posterior posterior 2nd and/or 3rd
rib if transverse scalene tubercles of process fixed: transverse
elevates the ribs processes of for respiration C5 & C6 if ribs
fixed, rotates to side opposite of contraction laterally flexes to
the contracted side bilaterally flexes the neck Superficial
Sternocleid (two heads) mastoid process rotates to side Neck
omastoid manubrium of of temporal bone opposite of sternum;
contraction medial portion laterally flexes to of clavicle the
contracted side bilaterally flexes the neck Platysma subcutaneous
invests in the skin depress skin over widely over the mandible and
delto-pectoral mandible lower lip tenses region the skin over the
lower neck Anterior Neck Sternohyoid posterior body of hyoid
depresses hyoid aspect of & larynx acts manubrium eccentrically
with sternal end of the suprahyoid clavicle muscles to provide them
a stable base Omohyoid superior belly: both bellies meet depresses
hyoid hyoid bone at the clavicle & & larynx acts (lateral
to are held to the eccentrically with sternohyoid) clavicle by a
the suprahyoid inferior belly: pulley tendon muscles to superior
provide them a scapular stable base border (medial to suprascapular
notch) Sternothyroid posterior oblique line of depresses hyoid
aspect of thyroid cartilage & larynx; acts manubrium
eccentrically with the suprahyoid muscles to provide them a stable
base Thyrohyoid oblique line of body of hyoid depresses hyoid;
thyroid may assist in cartilage larynx elevation Stylohyoid styloid
process lateral margin of pulls the hyoid of temporal hyoid (near
superiorly & bone greater horn) posteriorly during swallowing
fixes the hyoid bone for infrahyoid action Digastric post belly:
both bellies meet open mouth by mastoid and attach at the
depressing process of lateral aspect of mandible; temporal bone;
body of hyoid by fixes hyoid bone anterior belly: a pulley tendon
for infrahyoid digastric fossa action of internal mandible
Mylohyoid inner surface body of hyoid elevates the of mandible off
along midline at hyoid bone; the mylohyoid mylohyoid raphe raises
floor of line mouth (for swallowing); depresses mandible when hyoid
is fixed Geniohyoid inner surface body of hyoid elevates the of the
(paired muscles tongue; depress mandible off separated by a the
mandible; the mental septum) works with spines mylohyoid Epicranial
Occipitalis lateral 2/3 of galea draws back the (2 bellies)
superior aponeurosis, scalp to raise the nuchal line; over the
occipital eyebrows and external bone wrinkle the brow occipital
protuberance Frontalis (2 galea skin above the draws back the
bells) aponeurosis, nose and eyes scalp to raise the anterior to
the eyebrows and vertex wrinkle the brow Muscles of Orbicularis
orbital portion: circumferentially powerfully closes Facial oculi
nasal process around orbit the eye Expression of frontal bone;
meeting in palpebral palpebral raphe portion: palpebral ligament;
lacrimal portion: lacrimal crest of lacrimal bone Corrugator
frontal bone skin of the medial draws the supercilii just above the
portion of the eyebrows nose eyebrows downward and medially
Orbicularis alveolar border circumferentially closes the lips; oris
of maxilla; around mouth; protrudes the lateral to blends with
other lips midline of muscles mandible Levator frontal process
upper lip elevates the labii of maxilla muscles; upper lip; flares
superioris nasal cartilage the nostrils alaeque nasi Levator medial
1/2 of upper lip muscles elevates the labii infraorbital upper lip
superioris margin Zygomaticus zygomatic skin of the upper elevates
the minor bone, posterior lip upper lip to maxillary zygomatic
suture Zygomaticus anterior to modiolus (angle lifts and draws
major zygomatic- of the mouth) back the temporal angle(s) of the
suture mouth (as in smiling) Risorius parotid fascia modiolus
(angle draws the mouth of the mouth) laterally (as in smiling)
Levator maxilla, modiolus (angle lifts the angle(s) anguli oris
inferior to of the mouth) of the mouth (as infraorbital in smiling)
foramen Buccinator posterior modiolus compresses the alveolar
cheek(s) process of maxilla; posterior alveolar process of
mandible; along the pterygomandi bular raphe Depressor along the
modiolus lowers the anguli oris oblique line of angle(s) of the
mandible; mouth (as in lateral aspect frowning) of mental tubercle
of the mandible Depressor mandible, skin of the lower draws the
lower labii between lip lip downward inferioris symphysis and and
laterally mental foramen; along oblique line of the mandible
Muscles of This group includes: Masseter; Medial pterygoid; Lateral
pterygoid; Mastication their actions relate to movement of jaw and
mouth. Extraocular This musculature group includes: Levator
palpebrae superioris;
Lateral rectus; Medial rectus; Superior rectus; Inferior rectus;
Superior oblique; Inferior oblique; their actions are related to
eyelid and eye movements. Laryngeal This musculature group
includes: sternothyroid; thyrohyoid; stylopharyngeus;
palatopharyngeus; posterior cricoarytenoid; arytenoid, oblique;
arytenoid, transverse; aryepiglottic; cricothyroid; lateral
cricoarytenoid; thyroarytenoid; thyroepiglottic; vocalis;
constrictor, inferior pharyngeal; cricopharyngeus. Trunk,
Superficial Trapezius external posterior, lateral elevates front
Back occipital 1/3 of clavicle; scapula; and protuberance;
acromion; upward rotation back along the superior spine of of the
scapula medial sides of scapula (upper fibers); the superior
downward nuchal line; rotation of the ligamentum scapula (lower
nuchae fibers); (surrounding retracts scapula the cervical spinous
processes); spinous processes of C1-T12 Latissimus spinous lateral
lip of the adduction of dorsi process of T7- intertubercular
humerus; L5; groove medial rotation upper 2-3 of the humerus;
sacral extension from segments; flexed position; iliac crest;
downward lower 3 or 4 rotation of the Ribs scapula Pectoral
Subclavius first rib about lower surface of assists in the junction
of clavicle stabilizing the bone and clavicle cartilage Pectoralis
medial 1/3 of lateral lip of adducts major clavicle; bicipital
groove to humerus; anterior aspect the crest of the medially
rotates of manubrium greater tubercle; humerus; & length of
clavicular fibers flexion of the body of insert more arm from
sternum; distally; sternal extension cartilaginous fibers more
(clavicular attachments of proximally portion) upper 6 ribs;
external oblique's aponeurosis Pectoralis outer surface medial
aspect of depresses & minor of ribs 2-5 or coracoid process
downwardly 3-5 or 6 of the scapula rotates the scapula; assists in
scapular protraction from a retracted position; stabilizes the
scapula Shoulder Levator transverse superior angle of elevates the
Girdle scapulae processes of scapula toward scapula; C1-C3 or C4
the scapular extends and/or spine laterally flexes the head
Rhomboid spinous medial margin of retract scapula minor process of
C7 the scapula at the & T1; medial angle ligamentum nuchae;
supraspinous ligament Rhomboid spinous medial scapula retract
scapula major processes of from the scapular T2-T5; spine to the
supraspinous inferior angle ligament Serratus fleshy slips costal
aspect of protract scapula; anterior from the outer medial margin
of stabilize scapula; surface of the scapula assists in upper 8 or
9 upward rotation ribs Deltoid lateral, anterior deltoid tuberosity
abducts arm; 1/3 of distal of humerus flexion and clavicle; medial
rotation lateral boarder (anterior of the portion); acromion;
extension and scapular spine lateral rotation (posterior portion)
Supraspinatus supraspinous uppermost of abduction of arm fossa;
three facets of (first 15-20.degree.); muscle fascia the greater
stabilizes tubercle of glenohumeral humerus joint Infraspinatus
infraspinous middle facet of external rotation fossa; greater
tubercle of the humerus; muscle fascia of humerus stabilizes the
glenohumeral joint Teres middle half of lowest of three lateral
rotation of minor the scapula's facets of the the humerus; lateral
margin greater tubercle stabilizes the of humerus glenohumeral
joint Teres inferior, lateral crest of lesser assists in major
margin of the tubercle (just adduction of arm scapula medial to the
assists in medial insertion of rotation of arm latissimus dorsi)
assists in extension from an flexed position Subscapularis
subscapular lesser tubercle of medial rotation fossa humerus of the
humerus; stabilizes the glenohumeral joint Splenius Splenius lower
portion superior nuchal bilateral capitis of ligamentum line;
contraction: nuchae; mastoid process extend head & spinous of
temporal bone neck; processes of unilateral C3-T3(4) contraction:
Splenius spinous posterior rotate and cervicis process of T3
tubercles of laterally bend T6 transverse head & neck to
processes of C2- the contracted C4 (same) side Erector Iliocostalis
common lower border of bilateral: Spinae lumborum tendinous angles
of ribs extension of origin: (same (5)6-12 vertebral for all lower
column; erector spinae) maintenance of sacrum; iliac erect posture
crest; (pneumonic = I spinous Like Standing); processes of
stabilization of lower thoracic vertebral column & most lumbar
during flexion, vertebrae acting in contrast Iliocostalis upper
border lower border of to abdominal thoracis of ribs 6-12 angles of
ribs 1-6 muscles and the (medial to I. (sometimes action of
gravity; lumborum's transverse unilateral: insertion.) process of
C7) lateral bend to Iliocostalis angles of ribs transverse same
side; cervicis 1-6 processes of C4- rotation to same C6 side;
Longissimus common transverse opposite thoracis tendinous processes
of all muscles contract origin: (see thoracic eccentrically for
above) vertebrae; stabilization all ribs between tubercles and
angles; transverse processes of upper lumbar vertebrae Longissimus
transverse transverse cervicis processes of processes of C2-
T1-T5(6) C6 Longissimus transverse and posterior aspect capitis
articular of mastoid processes of process of middle and temporal
bone lower cervical vertebrae; transverse processes of upper
thoracic vertebrae Spinalis common spinous thoracis tendinous
processes T3(4) origin: (see T8(9) above) Spinalis spinous Spinous
cervicis processes of processes of C2 C6-T2 (and possibly extend to
C3 or C4) Spinalis spinous between superior capitis processes of
& inferior nuchal lower cervical lines of occipital & upper
bone thoracic vertebrae Transverso- Semispinalis transverse spinous
bilaterally spinal thoracis processes of processes of extends
T6-T12 upper thoracic & vertebral vertebrae lower cervical
column, vertebrae especially head and neck; controls lateral
flexion to side opposite contraction (eccentric for stability);
maintains head posture Semispinalis transverse spinous bilaterally
cervicis processes of processes of C2- extends T1-T6 T5(6)
vertebral vertebrae and column, can go down especially head to
lower and neck; thoracic controls lateral flexion to side opposite
contraction (eccentric for stability); maintains head posture
Semispinalis transverse between superior bilaterally capitus
processes of & inferior nuchal extends T1-T6; lines of
occipital vertebral articular bone column, processes of especially
head C4-C7 and neck; controls lateral flexion to side opposite
contraction (eccentric for stability); maintains head posture
Multifidus cervical spinous process bilaterally region: from of all
vertebrae extends articular extending from vertebral processes of
L5-C2 (skipping column; lower cervical 1-3 segments) controls
lateral vertebrae; flexion to side thoracic opposite region: from
contraction transverse (eccentric for processes of stability); all
thoracic unilaterally rotate vertebrae; vertebral bodies lumbar
region: (column) to lower portion opposite side of dorsal sacrum;
PSIS; deep surface of tendenous
origin of erector spinae; mamillary processes of all lumbar
vertebrae Long transverse skips one rotate to rotators process of
one vertebra to insert opposite side; vertebra on the base of
bilateral spinous process extension of vertebra above Short
transverse base of spinous rotate to rotators process of one
process of opposite side; vertebra vertebra bilateral immediately
extension above Segmental Interspinalis spinous to the spinous
extension of the processes of process of vert. vertebrae each
vertebra immediately segments above Intertransversi cervical
cervical region: laterally flexes region: to the anterior each
respective from the tubercle pair of vertebrae; anterior
immediately (also eccentric tubercle of above; to the muscle
transverse posterior tubercle contraction process; immediately
provides from the above; stability) posterior thoracic region:
tubercle of (poorly transverse developed); process; lumber region:
thoracic lateral aspect of region: (poorly the transverse
developed); process lumbar region: immediately lateral aspect
above; to the of the accessory transverse process on the process;
vertebra mamillary immediately process above
[0203] Various additional muscle groups can be modeled as of a
hybrid kinematics analysis and modeling technique to facilitate
joint arthroplasty procedures. Such muscle groups can include the
following and information regarding the, including:
[0204] Brachium to Hand Musculature--this region includes four
muscle groups: Brachium; Antebrachial Flexors; Antebrachial
Extensors; Hand & Wrist.
[0205] The Brachium Musculature includes:
[0206] Coracobrachialis: [0207] Origin: coracoid process of the
scapula; [0208] Insertion: medial shaft of the humerus at about its
middle [0209] Action: flexes the humerus; assists to adduct the
humerus
[0210] Biceps Brachii: [0211] Origin: long head-supraglenoid
tubercle and glenohumeral labrum; short head-tip of the coracoid
process of the scapula [0212] Insertion: radial tuberosity;
bicipital aponeurosis [0213] Action: flexes the forearm at the
elbow (when supinated); supinates forearm from neutral; stabilizes
anterior aspect of shoulder; flexes shoulder (weak if at all)
[0214] Brachialis: [0215] Origin: lower 1/2 of anterior humerus;
both intermuscular septa [0216] Insertion: ulnar tuberosity;
coronoid process of ulna slightly [0217] Action: elbow flexion
(major mover)
[0218] Triceps Brachii: [0219] Origin: long head--infraglenoid
tubercle of the scapula; lateral head--upper half of the posterior
surface of the shaft of the humerus, and the upper part of the
lateral intermuscular septum; medial head--posterior shaft of
humerus, distal to radial groove and both the medial and lateral
intermuscular septum (deep to the long & lateral heads) [0220]
Insertion: posterior surface of the olecranon process of the ulna;
deep fascia of the antebrachium [0221] Action: long--adducts the
arm, extends at the shoulder, and a little elbow flexion; [0222]
lateral--extends the forearm at the elbow; medial--extends the
forearm at the elbow
[0223] Anconeus: [0224] Origin: posterior surface of the lateral
epicondyle of the humerus [0225] Insertion: lateral aspect of
olecranon extending to the lateral part of ulnar body [0226]
Action: extends the forearm at the elbow; supports the elbow when
in full extension
[0227] The Antebrachial Flexor Musculature Includes:
[0228] Pronator Teres: [0229] Origin: humeral head: upper portion
of medial epicondyle via the CFT (common flexor tendon), medial
brachial intermuscular septum; ulnar head--coronoid process of
ulna, antebrachial fascia [0230] Insertion: lateral aspect of
radius at the middle of the shaft (pronator tuberosity) [0231]
Action: pronates forearm (during rapid or forced pronation); weakly
flexes the elbow
[0232] Flexor Carpi Radialis: [0233] Origin: medial epicondyle via
the CFT (common flexor tendon); antebrachial fascia; [0234]
Insertion: base of the 2nd and sometimes 3rd metacarpals [0235]
Action: flexes the hand at the wrist; radially deviates the wrist;
may assist to pronate the forearm
[0236] Palmaris Longus: [0237] Origin: medial epicondyle via the
CFT (common flexor tendon); antebrachial fascia [0238] Insertion:
central portion of the flexor retinaculum; superficial portion of
the palmar aponeurosis; [0239] Action: flexes the hand at the
wrist
[0240] Flexor Carpi Ulnaris: [0241] Origin: humeral head--medial
epicondyle via the CFT (common flexor tendon); ulnar [0242] head:
medial aspect of olecranon; proximal 3/5 of dorsal ulnar shaft;
antebrachial fascia [0243] Insertion: pisiform & hamate bones
(via the pisohamate ligament); base of the 5th metacarpal (via the
pisometacarpal ligament) [0244] Action: flexes the hand at the
wrist; ulnarly deviates the wrist; stabilizes wrist to permit
powerful thumb motion
[0245] Flexor Digitorum Superficialis: [0246] Origin: humeral-ulnar
head: medial epicondyle via the CFT (common flexor tendon), medial
boarder of base of coronoid process of ulna, medial (ulnar)
collateral ligament, antebrachial fascia; radial head: oblique line
of radius along its upper anterior boarder Insertion: both sides of
the base of each middle phalanx of the 4 fingers [0247] Action:
flexes the proximal and middle phalanges; flexes the wrist if
fingers are extended
[0248] Flexor Digitorum Profundus: [0249] Origin: anterior &
medial surface of upper 3/4 ulna; adjacent interosseous membrane;
[0250] Insertion: distal phalanx of medial 4 digits (through FDS
tunnel) [0251] Action: flexes the distal IP joints and in so doing
flexes the proximal and middle IP joints; flexes the wrist if
fingers are extended
[0252] Flexor Pollicis Longus: [0253] Origin: middle anterior
surface of the radius; interosseous membrane (may also originate
from lateral boarder of coronoid process or medial epicondyle)
[0254] Insertion: palmar aspect of base of the distal phalanx of
thumb (deep to flexor retinaculum) [0255] Action: flexes the distal
phalanx of the thumb (IP joint); flexes the other joints to the
wrist (McP, CMc and weakly at the wrist)
[0256] Pronator Quadratus: [0257] Origin: distal 1/4 anteriomedial
surface of ulna [0258] Insertion: distal 1/4 anteriolateral surface
of radius [0259] Action: pronates the forearm and hand
[0260] The Antebrachial Extensor Musculature includes:
[0261] Brachioradialis: [0262] Origin: upper lateral supracondylar
ridge of humerus (between the triceps and brachialis muscles);
lateral intermuscular septum of humerus [0263] Insertion: superior
aspect of styloid process of radius; lateral side of the distal 1/2
to 1/3 of the radius; antebrachial fascia [0264] Action: flexes the
forearm at the elbow; pronates the forearm when supinated;
supinates the forearm when pronated
[0265] Extensor Carpi Radialis Longus: [0266] Origin: lower lateral
supracondylar ridge (below the brachioradialis); lateral
intermuscular septum of humerus [0267] Insertion: base of 2nd
metacarpal [0268] Action: extends the hand at the wrist; radially
deviates the hand at the wrist; weakly flexes the forearm at the
elbow; weakly supinates the forearm
[0269] Extensor Carpi Radialis Brevis: [0270] Origin: lateral
epicondyle via the CET (common extensor tendon); radial collateral
ligament; antebrachial fascia [0271] Insertion: base of 3rd
metacarpal [0272] Action: extends the hand at the wrist; radially
deviates the hand at the wrist
[0273] Extensor Digitorum: [0274] Origin: lateral epicondyle via
the CET (common extensor tendon); antebrachial fascia [0275]
Insertion: base of middle phalanx of each of the four fingers
(central band); base of distal phalanx of each of the four fingers
(2 lateral bands) [0276] Action: extends the four medial digits;
extends the wrist if fingers flexed; abducts the digits (spreads
the digits as it extends them)
[0277] Extensor Digiti Minimi: [0278] Origin: lateral epicondyl via
the CET (common extensor tendon); antebrachial fascia; ulnar aspect
of extensor digitorum [0279] Insertion: base of middle phalanx of
the 5th digit (central band); base of distal phalanx of the 5th
digit (2 lateral bands) [0280] Action: extends the 5th digit;
abducts the 5th digit
[0281] Extensor Carpi Ulnaris: [0282] Origin: 1st head--lateral
epicondyle via the CET (common extensor tendon); 2nd
head--posterior body of ulna; antebrachial fascia [0283] Insertion:
medial side of base of the 5th metacarpal [0284] Action: extends
the hand at the wrist; ulnarly deviates the hand at the wrist
[0285] Supinator: [0286] Origin: lateral epicondyle of humerus;
supinator crest of ulna; radial collateral ligament; annular
ligament; antebrachial fascia [0287] Insertion: proximal portion of
anteriorlateral surface of the radius [0288] Action: supinates the
forearm
[0289] Abductor Pollicis Longus: [0290] Origin: posterior surfaces
of ulna and radius; interosseous membrane; antebrachial fascia
[0291] Insertion: lateral aspect of base of 1st metacarpal [0292]
Action: abducts the 1st metacarpal; assists to extend & rotate
the thumb; radially deviates the hand at the wrist; flexes the hand
at the wrist
[0293] Extensor Pollicis Brevis: [0294] Origin: posterior surfaces
of radius (below abductor pollicis longus); interosseous membrane;
antebrachial fascia [0295] Insertion: base of proximal phalanx of
thumb (often a slip inserts into extensor pollicis longus tendon)
[0296] Action: extends the proximal phalanx and 1st metacarpal of
the thumb; radially deviates the hand at the wrist
[0297] Extensor Pollicis Longus: [0298] Origin: posterior surface
of ulna; interosseous membrane; antebrachial fascia [0299]
Insertion: distal phalanx of thumb [0300] Action: extends distal
phalanx of thumb; extends proximal phalanx of thumb; assists to
extend the hand at the wrist (if fingers flexed)
[0301] Extensor Indicis:
[0302] Origin: posterior surface of ulna (distal to extensor
pollicis longus); interosseous membrane; antebrachial fascia [0303]
Insertion: base of middle and distal phalanx of the index finger
[0304] Action: extends the 2nd digit (McP & IP joints); adducts
the 2nd digit; assists to extend the hand at the wrist; stabilizes
McP joint for flexion of IP solely
[0305] The Hand and Wrist Musculature Includes:
[0306] Abductor Pollicis Brevis: [0307] Origin: distal border of
flexor retinaculum; trapezium (may be variable) [0308] Insertion:
lateral aspect of base of proximal phalanx of the thumb; may also
send a slip to the tendon of extensor pollicis longus [0309]
Action: abducts thumb (at the McP joint); participates to flex the
thumb (at the McP joint); if attached to extensor pollicis longus,
it might assist to extend the thumb
[0310] Flexor Pollicis Brevis: [0311] Origin: superficial head:
distal border of flexor retinaculum, trapezium; deep head: floor of
carpal tunnel, indirectly to scaphoid & trapezium [0312]
Insertion: base of proximal phalanx of thumb; can also attach to
the lateral sesamoid bone at the McP joint [0313] Action:
powerfully flexes the thumb (at the McP joint)
[0314] Opponens Pollicis: [0315] Origin: distal border of flexor
retinaculum; trapezium [0316] Insertion: lateral aspect of the 1st
metacarpal [0317] Action: opposes the thumb to the fingers
[0318] Adductor Pollicis: [0319] Origin: transverse head: 3rd
metacarpal; oblique head: base of 1st, 2nd and 3rd metacarpals;
floor of carpal tunnel [0320] Insertion: medial aspect of the base
of proximal phalanx; medial sesamoid at McP [0321] Action: adducts
the thumb; may assist to flex the thumb (at the McP joint)
[0322] Palmaris Brevis: [0323] Origin: medial margin of palmar
aponeurosis [0324] Insertion: skin of ulnar border of palm; may
insert on the pisiform [0325] Action: tenses the skin on the ulnar
side, which is used in a grip action
[0326] Abductor Digiti Minimi: [0327] Origin: pisiform & tendon
of flexor carpi ulnaris [0328] Insertion: medial aspect of the base
of proximal phalanx of the 5th digit; may send a slip to the ulnar
side of the dorsal expansion [0329] Action: abduct 5th digit
(requires pisiform stabilized by FCU); assists to flex the 5th
digit (at McP); may assist in extension of 5th digit (at IP due to
slips to extensor digitorum)
[0330] Flexor Digiti Minimi Brevis: [0331] Origin: distal border of
flexor retinaculum; hook of the hamate [0332] Insertion: medial
aspect of the base of proximal phalanx [0333] Action: flexes the
5th digit (at the McP joint)
[0334] Opponens Digiti Minimi [0335] Origin: distal border of
flexor retinaculum; hook of the hamate [0336] Insertion: medial
aspect of the 5th metacarpal [0337] Action: opposes the 5th digit
with the thumb; assists to "cup" the palm
[0338] Palmar Interossei: [0339] Origin: from the side of the
metacarpal that faces the midline--to adduct them [0340] Insertion:
on the base of the proximal phalanx of the digit of origin (same
side toward the midline); extensor hood of the same digit(s) [0341]
Action: adducts the fingers; flexes the fingers (at the McP while
IP joints are extended)
[0342] Dorsal Interossei: [0343] Origin: between each metacarpal
[0344] Insertion: directly distal to the origin on the base of the
proximal phalanx closest to the midline (to abduct them); extensor
hood of the same digit(s) [0345] Action: abducts the fingers (hint:
DAB); flexes the fingers (at the McP while IP joints are
extended)
[0346] Lumbricals: [0347] Origin: tendon of flexor digitorum
profundus; 1 & 2 have a single head of origin (from radial
aspect of tendon); 3 & 4 have two heads of origin (each head
from an adjacent tendon) [0348] Insertion: extensor hood of digits
2-5 [0349] Action: flexes the fingers (at the McP joints); extend
IPs
[0350] Thigh to Foot Musculature [0351] Muscle Groups within this
Region includes: Gluteal; Posterior Thigh; Adductor Thigh; Anterior
Thigh; Posterior Leg; Anterolateral Leg; Foot
[0352] The Gluteal Musculature includes:
[0353] Tensor Fascia Lata: [0354] Origin: anterior aspect of iliac
crest; anterior superior iliac spine (ASIS) [0355] Insertion:
anterior aspect of IT band, below greater trochanter [0356] Action:
hip flexion; medially rotate & abduct a flexed thigh; tenses IT
tract to support femur on the tibia during standing
[0357] Gluteus Maximus: [0358] Origin: outer rim of ilium (medial
aspect); dorsal surface of sacrum and coccyx; sacrotuberous
ligament [0359] Insertion: IT band (primary insertion); gluteal
tuberosity of femur [0360] Action: powerful extensor of hip;
laterally rotates thigh; upper fibers aid in abduction of thigh;
fibers of IT band stabilize a fully extended knee
[0361] Gluteus Medius: [0362] Origin: outer aspect of ilium
(between iliac crest and anterior and posterior gluteal lines);
upper fascia (AKA gluteal aponeurosis) [0363] Insertion: superior
aspect of greater trochanter [0364] Action: anterior and lateral
fibers abduct and medially rotate the thigh; posterior fibers may
laterally rotate thigh; stabilizes the pelvis and prevents free
limb from sagging during gait
[0365] Gluteus Minimus: [0366] Origin: outer aspect of ilium
(between anterior and inferior gluteal lines) [0367] Insertion:
greater trochanter (anterior to medius); articular capsule of hip
joint [0368] Action: abduct and medially rotate the thigh;
stabilizes the pelvis and prevents free limb from sagging during
gait
[0369] Piriformis: [0370] Origin: pelvic surface of sacrum
(anterior portion) [0371] Insertion: medial surface of greater
trochanter (through greater sciatic foramen) [0372] Action: lateral
rotation of extended thigh; abducts a flexed thigh
[0373] Superior Gemellus: [0374] Origin: ischial spine [0375]
Insertion: medial aspect of greater trochanter via upper tendon of
obturator internus [0376] Action: laterally rotates femur; abducts
thigh when flexed
[0377] Obturator Internus: [0378] Origin: internal aspect margins
of obturator foramen; obturator membrane [0379] Insertion: medial
aspect of greater trochanter (through lesser sciatic foramen)
[0380] Action: laterally rotates femur; abducts thigh when
flexed
[0381] Inferior Gemellus: [0382] Origin: Ischial Tuberosity [0383]
Insertion: medial aspect of greater trochanter via lower tendon of
obturator internus [0384] Action: laterally rotates femur
[0385] Quadratus Femoris: [0386] Origin: lateral aspect of ischial
tuberosity [0387] Insertion: quadrate line (along posterior aspect
of femur and intertrochanteric crest) [0388] Action: laterally
rotates femur
[0389] Posterior Thigh Musculature Includes:
[0390] Semitendinosus:
[0391] Origin: ischial tuberosity [0392] Insertion: medial aspect
of tibial shaft; contributes to the pez anserine [0393] Action:
extends hip; flexes knee; medially rotates tibia
[0394] Semimembranosus: [0395] Origin: ischial tuberosity [0396]
Insertion: posterior medial aspect of medial tibial condyle; fibers
join to form most of oblique popliteal ligament (& medial
meniscus) [0397] Action: flexes knee; extends hip; medially rotates
tibia; pulls medial meniscus posterior during flexion
[0398] Biceps Femoris: [0399] Origin: long head: ischial
tuberosity; short head: lateral lip of linea aspera and the lateral
intermuscular septum [0400] Insertion: head of fibula; maybe to the
lateral tibial condyle [0401] Action: flexor at the knee (mainly
short head); laterally rotates thigh if flexed at the knee; extends
hip (long head)
[0402] Adductor magnus: posterior fibers are sometimes considered
part of this group. Its information is listed below with the other
thigh adductors.
[0403] Adductor Thigh Musculature Includes:
[0404] Adductor Longus: [0405] Origin: anterior surface of pubis,
just inferior to the pubic tubercle [0406] Insertion: medial lip of
linea aspera on middle half of femur [0407] Action: adducts thigh;
flexes thigh; may laterally rotate thigh at the hip
[0408] Adductor Brevis: [0409] Origin: body & inferior ramus of
pubis [0410] Insertion: superior portion of linea aspera [0411]
Action: adducts thigh (major); aids in flexion of thigh; may
laterally rotate thigh at the hip
[0412] Adductor Magnus: [0413] Origin: anterior fibers: inferior
pubic ramus; oblique fibers: ischial ramus; posterior fibers:
ischial tuberosity [0414] Insertion: proximal 1/3 of linea aspera;
adductor tubercle [0415] Action: adducts the thigh; posterior
fibers also extend and laterally rotate thigh
[0416] Gracilis: [0417] Origin: body of pubis & inferior pubic
ramus [0418] Insertion: medial surface of proximal tibia, inferior
to tibial condyle; contributes to the pez anserine [0419] Action:
adducts thigh; flexes knee; medially rotates tibia
[0420] Obturator Externus: [0421] Origin: medial surface of
obturator foramen; external surface of obturator membrane
Insertion: trochanteric fossa of femur [0422] Action: laterally
rotates thigh; assists in flexion of hip joint
[0423] Anterior Thigh Musculature Includes:
[0424] Sartorius: [0425] Origin: anterior superior iliac spine
(ASIS) [0426] Insertion: upper medial surface of body of tibia;
contributes to pez anserine [0427] Action: flexes hip and knee;
laterally rotates thigh if flexed at the hip
[0428] Rectus Femoris: [0429] Origin: anterior head: anterior
inferior iliac spine (AIIS); posterior head: ilium just above the
acetabulum [0430] Insertion: common quadriceps tendon into patella;
tibial tuberosity via patellar ligament [0431] Action: extends
knee; flexes hip
[0432] Vastus Lateralis: [0433] Origin: greater trochanter; lateral
lip of linea aspera; lateral intermuscular septum [0434] Insertion:
common quadriceps tendon into patella; tibial tuberosity via
patellar ligament [0435] Action: extends knee; can abnormally
displace patella
[0436] Vastus Intermedius: [0437] Origin: anterior lateral aspect
of the femoral shaft [0438] Insertion: common quadriceps tendon
into patella; tibial tuberosity via patellar ligament [0439]
Action: extends knee
[0440] Vastus Medialis: [0441] Origin: intertrochanteric line of
femur; medial aspect of linea aspera [0442] Insertion: common
quadriceps tendon into patella; tibial tuberosity via patellar
ligament [0443] Action: extends knee
[0444] Articularis genus: [0445] Origin: distal portion of anterior
femoral surface, close to the knee; off the deep fibers of the
vastus intermedius [0446] Insertion: synovial membrane of the knee
joint [0447] Action: pulls the synovial membrane of the knee
superior with knee extension; prevents impingement of the synovial
membrane between patella and the femur
[0448] Psoas Major: [0449] Origin: transverse processes of L1-L5;
vertebral bodies of T12-L4 and the intervening intervertebral discs
[0450] Insertion: iliopsoas tendon to the lesser trochanter of the
femur [0451] Action: hip flexion; lateral rotation
[0452] Illiacus: [0453] Origin: inner surface of upper iliac fossa
[0454] Insertion: iliopsoas tendon to the lesser trochanter of the
femur [0455] Action: powerful hip flexion; lateral rotation
[0456] Pectineus: [0457] Origin: pectineal line of the pubis;
superior pubic ramus [0458] Insertion: the pectineal line of the
femur (just below the lesser trochanter on the posterior aspect of
the femur) [0459] Action: flexes hip; adducts thigh; medially
rotates thigh
[0460] Posterior Leg Musculature Includes:
[0461] Gastrocnemius: [0462] Origin: medial head: just above medial
condyle of femur; lateral head: just above lateral condyle of femur
[0463] Insertion: calcaneus via lateral portion of calcaneal tendon
[0464] Action: plantarflex the ankle; knee flexion (when not weight
bearing); stabilizes ankle & knee when standing
[0465] Soleus: [0466] Origin: upper fibula; soleal line of tibia
[0467] Insertion: calcaneus via medial portion of calcaneal tendon
[0468] Action: plantarflex the foot
[0469] Plantaris: [0470] Origin: above the lateral head of
gastrocnemius on femur [0471] Insertion: calcaneus, medial to
calcaneal tendon, or blending with the calcaneal tendon [0472]
Action: like a weak gastrocnemius
[0473] Popliteus: [0474] Origin: lateral femoral condyle; arcuate
popliteal ligament; lateral meniscus; knee joint capsule [0475]
Insertion: posterior tibial surface above the soleal line [0476]
Action: insertion fixed: laterally rotates femur on tibia &
unlocks knee; origin fixed: medially rotates tibia on femur &
unlocks knee
[0477] Flexor Digitorum Longus: [0478] Origin: posterior surface of
tibia; crural fascia [0479] Insertion: plantar surface of bases of
the 2-5th distal phalanges [0480] Action: primarily flexes 2nd-5th
toes; weak plantarflexor; weak inversion & adduction of
foot
[0481] Tibialis Posterior: [0482] Origin: posterior, proximal
tibia; interosseous membrane; medial surface of fibula [0483]
Insertion: navicular tuberosity (principle); all 3 cuneiforms
(plantar surface); bases of 2nd-4th metatarsals; cuboid;
sustentaculum tali of calcaneus [0484] Action: stabilizes ankle;
inversion & adduction of foot; prevents hyperpronation while in
gait; weak plantarflexion of ankle
[0485] Flexor Hallucis Longus: [0486] Origin: posterior, inferior
2/3 of fibula; interosseous membrane; crural fascia & posterior
intermuscular septum [0487] Insertion: plantar surface of distal
phalanx of hallux [0488] Action: flexes big toe (hallux); weak
plantarflexion of the foot; weak inversion & adduction of
foot
[0489] Anterolateral Leg Musculature Includes:
[0490] Peroneus Longus: [0491] Origin: head of the fibula; proximal
2/3 of lateral fibula; adjacent intermuscular septum [0492]
Insertion: plantar surface of cuboid; base of 1st & (2nd)
metatarsal; plantar surface of medial cuneiform [0493] Action:
eversion & abduction of the foot; weak plantarflexion of the
foot at the transverse tarsal joint
[0494] Peroneus Brevis: [0495] Origin: distal 2/3 of lateral
fibula; posterior and anterior intermuscular septum [0496]
Insertion: tuberosity on lateral aspect of base of 5th metatarsal
[0497] Action: eversion & abduction of the foot; weak
plantarflexion of foot
[0498] Tibialis Anterior: [0499] Origin: lateral tibial condyle;
proximal 2/3 of anteriolateral surface of tibia; interosseous
membrane; anterior intermuscular septum & crural fascia [0500]
Insertion: medial & plantar surface of base of 1st metatarsal;
medial & plantar surface of the cuneiform [0501] Action:
strongest dorsiflexor; inverts & adducts the foot
[0502] Extensor Hallucis Longus: [0503] Origin: medial aspect of
the fibula; interosseous membrane; crural fascia [0504] Insertion:
dorsal surface of base of proximal and distal phalanx of hallux
[0505] Action: extends distal phalanx of big toe; weak dorsiflexor;
weak inversion & adduction
[0506] Extensor Digitorum Longus: [0507] Origin: lateral condyle of
the tibia; upper anterior surface of fibula; interosseous membrane;
crural fascia [0508] Insertion: dorsal surface of the bases of the
middle & distal phalanxes of the 2nd-5th rays (via 4 tendons
and giving a fibrous expansion) [0509] Action: extends the lateral
4 toes; weak dorsiflexor & everts foot
[0510] Peroneus Tertius: [0511] Origin: distal 1/3 of anterior
fibula; distal & lateral aspect of extensor digitorum [0512]
Insertion: dorsal surface of base of 5th metatarsal [0513] Action:
extends the 5th toe; weak dorsiflexor & everts foot
[0514] Foot Musculature Includes:
[0515] Abductor Halluces: [0516] Origin: medial process of
calcaneal tuberosity; flexor retinaculum; plantar aponeurosis;
medial intermuscular septum [0517] Insertion: medial aspect of base
of proximal phalanx of hallux [0518] Action: flexes the big toe
(primary action); may assist in abduction of big toe
[0519] Flexor Digitorum Brevis: [0520] Origin: medial process of
calcaneal tuberosity; plantar aponeurosis [0521] Insertion: both
sides of the bases of the middle phalanx of rays 2-5 (each of the 4
tendons splits forming tunnel for FDL) [0522] Action: flexes toes
2-5
[0523] Abductor Digiti Minimi: [0524] Origin: lateral & medial
processes of the calcaneal tuberosity; plantar aponeurosis; lateral
intermuscular septum [0525] Insertion: lateral aspect of base of
proximal phalanx of 5th ray [0526] Action: abducts 5th toe; aids in
flexing
[0527] Abductor Ossis Metatarsi Quinti: [0528] Origin: from fibers
of abductor digiti minimi [0529] Insertion: into the 5th metatarsal
[0530] Action: abducts the 5th ray
[0531] Quadratus Plantae: [0532] Origin: medial head: medial
calcaneus; lateral head: lateral calcaneus & long plantar
ligament [0533] Insertion: lateral margin of tendon of flexor
digitorum longus (FDL); may send slips into the distal tendons
[0534] Action: assists FDL in flexing the distal phalanxes of
2nd-5th toes; corrects FDL from pulling toes medially
[0535] Lumbricals: [0536] Origin: from tendons of FDL: 1st: medial
aspect of tendon to 2nd ray; 2nd-4th: two heads between the tendons
in which they lie [0537] Insertion: extensor tendons of EDL on
dorsal foot [0538] Action: flex proximal phalanges at MTP; extend
middle & distal phalanges at IP
[0539] Flexor Hallucis Brevis: [0540] Origin: medial aspect of the
cuboid; lateral cuneiform [0541] Insertion: medial aspect of base
of proximal phalanx of hallux; lateral aspect of base of proximal
phalanx of hallux [0542] Action: flexes hallux at MTP
[0543] Adductor Halluces:
[0544] Origin: oblique head: base of 2nd-4th metatarsals & long
plantar ligament; transverse head: deep transverse metatarsal
ligament & plantar ligaments at MTP joints [0545] Insertion:
lateral aspect of base of proximal phalanx of hallux [0546] Action:
adduction of hallux at MTP; flexes hallux at MTP
[0547] Flexor Digiti Minimi Brevis: [0548] Origin: base of 5th
metatarsal; digital sheath of peroneus longus [0549] Insertion:
lateral aspect of base of proximal phalanx of 5th ray [0550]
Action: flexes the 5th toe at MTP
[0551] Plantar Interossei (3 Muscles): [0552] Origin: medial aspect
of 3rd-5th metatarsals (each muscle has a single head) [0553]
Insertion: medial aspect of base of proximal phalanx of the same
ray (of 3rd-5th rays) [0554] Action: adduct toes 3-5; flex toes 3-5
at MTP
[0555] Dorsal Interossei (4 Muscles): [0556] Origin: from both
metatarsals between which they lie [0557] Insertion: base of
proximal phalanx closest to the axis of the foot (2nd ray) [0558]
Action: abduct toes 2-4; flexes toes 2-4 at MTP
[0559] Extensor Hallucis Brevis: [0560] Origin: upper anterolateral
calcaneus; inferior extensor retinaculum [0561] Insertion: base of
proximal phalanx of hallux [0562] Action: extends hallux
[0563] Extensor Digitorum Brevis: [0564] Origin: upper
anterolateral calcaneus; inferior extensor retinaculum [0565]
Insertion: middle & distal phalanges of 2nd-4th rays (via EDL)
[0566] Action: extends 2nd-4th rays
Examples of Muscle Measurements and Modeling
[0567] A wide variety of techniques can be employed to incorporate
muscle and other soft tissue (i.e., tendons, ligaments, other
connective tissues, fascia, fat, skin, etc.) information in a
kinematic model of a joint and/or extremity. In some embodiments, a
hybrid kinematic model of a joint can include information relating
to adjacent joint structures (i.e., a knee model can include ankle
and/or hip modeling data) as well as relevant soft tissue
structures such as muscles and the like. In one exemplary
embodiment, an upper extremity model can include modeling data
relevant to the various extremity joints (i.e., shoulder, elbow,
forearm, wrist, thumb and index finger/other digits) as well as the
various muscle compartments (i.e., 50 or more individual muscle
compartments) crossing each of these joints. The kinematics of each
joint and the force-generating parameters for each muscle can be
derived from any combinations of actual patient-specific data,
experimental data, databases of relevant patients and/or
mathematical approximations. The various models can estimate
muscle-tendon lengths and movement arms for each of the muscles
over a wide range of postures, movements and/or degrees of freedom.
Given a modeled pattern of muscle activations, the hybrid kinematic
model can estimate muscle forces, joint movements and
surface/subsurface forces and stresses experienced by joint support
structures and/or articulating surfaces (including implant
component designs therefor).
[0568] Depending upon a wide variety of modeling constraints, a
more physiologically-accurate hybrid kinematic model can be created
and utilized. For example, "coupling" between various joints (i.e.,
passive finger flexion and wrist extension) can be included in a
hybrid kinematic model, if desired. Moreover, various models can
accommodate and/or account for differentiation in the "pose" and
"tone" (i.e., the stiffness and/or tension of an individual muscle
or group of muscles in a given portion of the musculoskeletal
system) of various muscles in an extremity and/or joint model.
Various models could incorporate data regarding the ability of
human and other animals to coactivate agonist and antagonist
muscles to increase stiffness while maintaining pose, which can
mitigate instability under external loads and/or increase the
accuracy of limbs in motor tasks. In various embodiments, the
various levels of stress and/or strain in a muscle and/or muscle
group modeled may indicate relevant information for the model, such
as a value that exceeds a specified threshold and indicates the
potential for injury and/or pain generation in a given muscle based
upon a certain implant design and/or procedure, which may be
important information to a clinician seeking to avoid such an
occurrence in a patient during and after surgical recovery.
[0569] Where a complete hybrid model of a given joint might be
prohibitively complex, or utilize excessive computing capacity, a
modified hybrid model can be evaluated that employs kinematic data
from major or unique muscle groups and/or other soft tissues, while
minor or peripheral groups can be estimated, combined and/or
ignored. Similarly, a model may include data from various
combination of muscle types based on subcutaneous depth and/or
attachment, including skeletal muscles, "deep" muscles,
"intermediate" muscles and "superficial" muscles. Depending upon
the number and complexity of muscles modeled, as well as the number
of bones spanned by each muscle, various muscles and/or muscle
groups (as well as bony attachment points) may be disregarded in
order to simplify the relevant model, if necessary.
[0570] In various alternative embodiments, hybrid kinematic models
could include hybrid modeling of joint structures that account for
damage and/or disruption to soft and/or connective tissues as a
result of the surgical intervention (i.e., damage along a given
surgical path, tissue releases, muscle separation and/or joint
capsule removal) and/or that could account for previous, present
and/or future damage and/or the formation of scar tissues. In
various embodiments, the modeling data may reveal a preferred
access path that minimizes and/or accounts for such
damage/disruption during the surgical procedure, which may also
mandate some change and/or alteration to the implant design and/or
surgical procedure to accommodate the altered kinematics.
[0571] A wide variety of techniques for modeling anatomical systems
can be incorporated into a hybrid kinematic model that can be
useful, to varying degrees, in facilitating the design and/or
selection of a patient-specific implant, tools and surgical
procedure. For example, US Application Publication No. 20110137138
teaches that motion exercise is adapted to provide a degree of
muscle tone or muscle relaxation of said patient based on said
measurement data, and wherein accelerometers are adapted to provide
said measurement data for determination of said degree of muscle
tone or muscle relaxation. US Application Publication No.
20070137307 discloses an electromechanical force sensor uses a
rotating element that aligns with the force and may carry a force
magnitude sensor simplifying and providing more accurate
measurement of force-angle and force-magnitude. The ability to
detect simply force-angle and force-magnitude enables a variety of
training and exercise devices, as well as modeling thereof.
[0572] US Application Publication No. 20060286522 discloses systems
and methods for animating a character with activation-driven muscle
deformation. External loads can be estimated through an iterative
joint torque estimation process, and the external loads reflected
in a physical model. Kinematic motion and the physical model
reflecting external loads can be used to estimate joint torques.
Muscle activations can be determined from the joint torques, and a
character can be animated with muscle deformation responsive to the
muscle activations. Employing these techniques, various types of
kinematic motion models and physical models can be created to
estimate joint torques that include external loads. Muscle
activations can be determined from the estimated joint torques, and
a character model can be animated with muscle deformation
responsive to the muscle activations. External loads and muscle
activations can be estimated through a two-step joint torque
determination process. A first set of estimated joint torques can
be estimated from the kinematic motion and the physical model. The
first set of estimated joint torques can include an artificial
external load (also called an "artificial load"). An artificial
external load can be an apparent load that is caused by a force
and/or torque acting on an object, but without a naturally
occurring source in the environment. A non-zero artificial load
will typically indicate the presence of unaccounted for external
loads. This artificial external load from the first set of
estimated joint torques can be redistributed to various points on
the body to estimate physically-realizable external loads, which
can be explained as physical interactions with the environment
(i.e., contact forces with the ground). The external load can be
applied to the physical model to produce a loaded physical model,
and a second set of estimated joint torques can be estimated from
the kinematic motion and the loaded physical model. The second set
of estimated joint torques can include the effects of the external
loads on the physical system, making them more physically
realistic. Muscle activations can be determined from the second set
of estimated joint torques, and a character model can be animated
with muscle deformation responsive to the muscle activations. By
including the effect of external loads and accelerations in the
muscle activations, convincing character models with lifelike
muscle deformations can be animated. Various of such models for
alternative joint implant designs and/or placements can then be
queried and/or compared to determine desired and/or undesired
implant component features and/or kinematic effects.
[0573] In various alternative embodiments, a modeling system such
as LifeMOD.TM. (commercially available from LifeModeler, Inc. of
San Clement, Calif.) can be employed that models ligaments and
muscles as force-producing soft tissues available in tension
forces. Ligaments can be modeled as passive spring/dampers and may
or may not be included in a generic full body tissue set. Muscles
can be the primary soft tissues used in LifeMOD.TM. to produce
tension forces between bone attachments. As described in US
Application Publication No. 20110045952: a major objective of a
biomechanical simulation tool is to determine the physiologically
relevant muscle forces required for a given muscular-skeletal model
performing a prescribed kinematic profile. Examples of kinematic
profiles include the flexion of elbow or knee. However, kinematic
profiles may also be more complex. For example, a kinematic profile
may include the motion of walking. For many models and kinematic
profiles there are multiple muscle activations that are possible.
The goal of the simulation then becomes choosing the set of muscle
activations, or muscle recruitment patterns, that best match what
is expected for human motion. Some biomechanical simulations of
muscular-skeletal systems have used a PID control scheme, e.g.
LifeMOD.TM., for determining muscle forces required to meet a
pre-determined kinematic profile. This is done by using a sensor of
the muscle kinematics, e.g. muscle length, muscle velocity, or
joint angle, which is compared to a target signal. Output of the
control system can be a muscle control force that may further be
modified to physiological limitations based on maximum force,
velocity, etc. Once various models have been created using data for
one or more implant component designs and/or orientations, these
models can then be queried and/or compared to determine desired
and/or undesired features and/or kinematic effects.
Flowcharts and Modeling Techniques
[0574] Various embodiments described herein include a variety of
techniques and systems for obtaining and/or usaing biomotion
modeling data to improve the design, selection, manufacture and use
of patient-specific implant, tool, jigs and surgical
techniques.
* * * * *
References