U.S. patent application number 17/307719 was filed with the patent office on 2022-03-10 for system and method for performing virtual surgery.
The applicant listed for this patent is Alan Bao-Chan Dang, United States Government as Represented by the Department of Veterans Affairs. Invention is credited to Alan Bao-Chan Dang, Liang Ge, Mark B. Ratcliffe.
Application Number | 20220076591 17/307719 |
Document ID | / |
Family ID | |
Filed Date | 2022-03-10 |
United States Patent
Application |
20220076591 |
Kind Code |
A1 |
Ratcliffe; Mark B. ; et
al. |
March 10, 2022 |
SYSTEM AND METHOD FOR PERFORMING VIRTUAL SURGERY
Abstract
A method and system are presented for performing virtual surgery
simulations. The computer system includes a processor and a memory.
The method includes receiving user input from a user via a user
interface. The user input includes input representing surgical
operations or non-surgical invasive procedures. The method also
includes processing the user input and utilizing the input to
generate or modify a computational model. The method also includes
running simulations using the computational model in accordance
with the user input. After running the simulations, the method
further includes determining results from the simulations. The
results correspond to probable effects or outcomes of performing
real life surgical operations or non-surgical invasive procedures
corresponding to the user input. Last, the method includes
presenting the results to the user via the user interface.
Inventors: |
Ratcliffe; Mark B.;
(Piedmont, CA) ; Ge; Liang; (Foster City, CA)
; Dang; Alan Bao-Chan; (Orange, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Dang; Alan Bao-Chan
United States Government as Represented by the Department of
Veterans Affairs |
Washington |
DC |
US
US |
|
|
Appl. No.: |
17/307719 |
Filed: |
May 4, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15424070 |
Feb 3, 2017 |
11043143 |
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17307719 |
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14211452 |
Mar 14, 2014 |
9601030 |
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15424070 |
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61801000 |
Mar 15, 2013 |
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International
Class: |
G09B 23/28 20060101
G09B023/28; G09B 5/00 20060101 G09B005/00; G09B 9/00 20060101
G09B009/00 |
Claims
1. A method comprising: determining one or more loading conditions
and one or more material properties associated with a surgical
mesh; receiving, via a user interface, one or more user inputs
wherein the one or more user inputs comprise at least one surgical
action; determining, based on the at least one surgical action and
at least one loading condition of the one or more loading
conditions and at least one material property of the one or more
material properties, a surgical outcome; comparing the surgical
outcome to an optimal surgical outcome; and outputting, based on
the comparison, a notification.
2. The method of claim 1, wherein the one or more loading
conditions comprise at least one of: blood pressure, age, height,
weight, or lab test results.
3. The method of claim 1, wherein the one or more material
properties comprise at least one of: an indication of tissue
softness or an indication of tissue hardness.
4. The method of claim 1, wherein determining the surgical outcome
comprises: receiving one or more surgical actions associated with
the surgical mesh; and determining, via fine element analysis, the
surgical outcome.
5. The method of claim 1, wherein the notification comprises an
indication of a the surgical outcome.
6. The method of claim 1, further comprising: determining clinical
imaging information; and converting the clinical imaging
information into the surgical mesh.
7. The method of claim 6, wherein the clinical imaging information
comprises at least one: an x-ray, magnetic resonance imaging,
computed tomography, or ultrasound.
8. An apparatus comprising: one or more processors; and memory
storing processor executable instructions that, when executed by
the one or more processors, cause the apparatus to: determine one
or more loading conditions and one or more material properties
associated with a surgical mesh; receive, via a user interface, one
or more user inputs wherein the one or more user inputs comprise at
least one surgical action; determine, based on the at least one
surgical action and at least one loading condition of the one or
more loading conditions and at least one material property of the
one or more material properties, a surgical outcome; compare the
surgical outcome to an optimal surgical outcome; and output, based
on the comparison, a notification.
9. The apparatus of claim 8, wherein the one or more loading
conditions comprise at least one of: blood pressure, age, height,
weight, or lab test results.
10. The apparatus of claim 8, wherein the one or more material
properties comprise at least one of: an indication of tissue
softness or an indication of tissue hardness.
11. The apparatus of claim 8, wherein processor executable
instructions, when executed by the one or more processors, cause
the apparatus to: receiving one or more surgical actions associated
with the surgical mesh; and determine, via fine element analysis,
the surgical outcome.
12. The apparatus of claim 8, wherein the notification comprises an
indication of a the surgical outcome.
13. The apparatus of claim 8, wherein processor executable
instructions, when executed by the one or more processors, cause
the apparatus to: determine clinical imaging information; and
convert the clinical imaging information into the surgical
mesh.
14. The apparatus of claim 13, wherein the clinical imaging
information comprises at least one: an x-ray, magnetic resonance
imaging, computed tomography, or ultrasound.
15. A system comprising: a computing device configured to:
determine one or more loading conditions and one or more material
properties associated with a surgical mesh; receive, via a user
interface, one or more user inputs wherein the one or more user
inputs comprise at least one surgical action; determine, based on
the at least one surgical action and at least one loading condition
of the one or more loading conditions and at least one material
property of the one or more material properties, a surgical
outcome; compare the surgical outcome to an optimal surgical
outcome; send a notification; and a display device configured to:
receive the notification; and output the notification.
16. The system of claim 15, wherein the one or more loading
conditions comprise at least one of: blood pressure, age, height,
weight, or lab test results.
17. The system of claim 15, wherein the one or more material
properties comprise at least one of: an indication of tissue
softness or an indication of tissue hardness.
18. The system of claim 15, wherein the computing device is
configured to determine the surgical outcome by: receiving one or
more surgical actions associated with the surgical mesh; and
determining, via fine element analysis, the surgical outcome.
19. The system of claim 15, wherein the computing device is
configured to determine the surgical outcome by: determine clinical
imaging information; and convert the clinical imaging information
into the surgical mesh.
20. The system of claim 19, wherein the clinical imaging
information comprises at least one: an x-ray, magnetic resonance
imaging, computed tomography, or ultrasound.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of and claims the benefit
of U.S. application Ser. No. 15/424,070, filed Feb. 3, 2017, which
is a continuation of and claims the benefit of U.S. application
Ser. No. 14/211,452, filed Mar. 14, 2014, and issued as U.S. Pat.
No. 9,601,030, issued Mar. 21, 2017, and claims the benefit of U.S.
Provisional Application No. 61/801,000, filed Mar. 15, 2013, all of
which are herein incorporated by reference in their entireties for
all purposes.
TECHNICAL FIELD
[0002] The disclosed embodiments relate generally to computational
modeling and simulations in computer systems.
BACKGROUND
[0003] Currently, practicing surgeons, clinicians, medical device
engineers, scientists and trainees work with physical models or
cadavers when developing novel surgical operations and non-surgical
invasive procedures, training to perform surgeries or non-surgical
invasive procedures, or developing instruments or implants related
to those surgeries or non-surgical invasive procedures. Physical
simulators made of rubber/plastic material in a "shoebox" are used
by educators to evaluate how a trainee sutures or cuts. However,
physical simulators and models have many limitations. More
specifically, physical models made from materials such as plastic,
rubber, latex, foam, metal, ceramics, or other manufactured
materials do not provide the ability to fully replicate the
consistency, texture, and physical properties of human tissue.
Cadavers have many limitations as well. More specifically, cadavers
do not allow the ability to compare the effects of one procedure
with another procedure given that no two cadavers are identical.
Additionally, a cadaver cannot fully replicate living human tissue
due to the change in physical properties that occurs during the
preparation and preservation of the tissue to prevent decomposition
and the inherent inability for a cadaver to mimic living tissue
such as muscle, which contracts. Thus, there exists a need for
using computational modeling to simulate surgical operations and
non-surgical invasive procedures. These same limitations to
physical models and cadaver specimens affect medical device
engineers in the development of new or refinement of existing
instruments or implants. Additionally, practicing surgeons develop
their surgical plan for an individual patient using "historical"
information based upon their personal experience gained during
training or while in practice from similar patients or published
studies in medical literature reporting the outcome of a procedure
from similar patients. The systems and method presented in the
present disclosure allow for clinicians to predict the outcome of
their surgery or non-surgical invasive procedure in advance, using
computational modeling to simulate surgical operations and
non-surgical invasive procedures, for their individual
patients.
SUMMARY
[0004] In one aspect of the present disclosure, a method to be
performed by a computer system is provided. The computer system
includes a processor and a memory. The method includes receiving
user input from a user via a user interface. The user input
includes input representing surgical operations or non-surgical
invasive procedures. The method also includes processing the user
input and utilizing the input to generate or modify a computational
model. The method also includes running simulations using the
computational model in accordance with the user input. After
running the simulations, the method further includes determining
results from the simulations. The results correspond to probable
effects or outcomes of performing real life surgical operations or
non-surgical invasive procedures corresponding to the user input.
Last, the method includes presenting the results to the user via
the user interface.
[0005] In another aspect of the present disclosure, a system is
provided. The system includes a user interface and a computer. The
computer includes a processor and memory, and is configured to
receive user input from the user interface, wherein the user input
includes input representing surgical operations or non-surgical
invasive procedures. The computer is further configured to process
the user input and utilize the input to generate or modify a
computational model. The computer is further configured to run
simulations using the computational model in accordance with the
user input. In addition, the computer is configured to also
determine results from the simulations, wherein the results
correspond to probable effects or outcomes of performing real life
surgical operations or non-surgical invasive procedures
corresponding to the user input. Last, the computer is configured
to present the results to the user via the user interface.
[0006] In some embodiments of the present disclosure, processing
the user input includes pre- and post-processing of data provided
to a solver module.
[0007] In some embodiments, the user input is pre-processed before
being received. In some embodiments, the method is performed
dynamically while the user is performing steps of a surgery or
non-surgical invasive procedure simulation. In some embodiments,
the user input includes input from a keyboard, mouse, camera,
microphone, tablet, cellular phone, any handheld device, or any
haptic device capable of performing motions or functions
representing surgical operations or other non-surgical invasive
procedures that effect anatomic structures. In some embodiments,
the user input is sent via a web browser or any application with
access to the Internet. In some embodiments, processing the user
input includes performing one more actions in a queue, utilizing
the user input to generate or modify a computational anatomic
model, the computational anatomic model being divided into one or
more parts including a geometric mesh, material properties, and
loading conditions. In some embodiments, the method further
includes converting clinical imaging or information, such as blood
pressure, height, weight, and lab results, into data and
representing the data in a computational model including a
geometric mesh, material properties, and loading conditions. In
some embodiments, the user input includes surgical language and
processing the user data includes converting, via a clinical
translation module, the surgical language to changes or discrete
values in a geometric mesh, material properties, or loading
conditions of a computational model. In some embodiments,
determining results of the simulation includes converting output
geometric mesh, material properties, or other data with associated
physical properties into surgical language. In some embodiments,
the method further includes validating the user information
submitted from the user system to the clinical system.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1A is an overview of an example system for implementing
various methods of the present disclosure.
[0009] FIG. 1B is a flow diagram illustrating an overview of an
example process implemented with the example system in FIG. 1A, in
accordance with various embodiments of the present disclosure.
[0010] FIGS. 2A and 2B illustrate various aspects of a real heart,
in accordance with various embodiments of the present
disclosure.
[0011] FIGS. 2C and 2D illustrate examples of geometric mesh models
corresponding to the various aspects of a real heart presented in
FIGS. 2A and 2B, in accordance with various embodiments of the
present disclosure.
[0012] FIGS. 3A-3D depicts an example of a typical surgical
procedure for mitral valve repair, in accordance with various
embodiments of the present disclosure.
[0013] FIGS. 4A-4F are examples of simulating a mitral valve repair
procedure using computational modeling, in accordance with various
embodiments of the present disclosure.
[0014] FIG. 5 illustrates an example of human knee, in accordance
with various embodiments of the present disclosure.
[0015] FIG. 6A illustrates a simulated model of a human knee, in
accordance with various embodiments of the present disclosure.
[0016] FIG. 6B illustrates a simulated model of a human knee that
has undergone a medial meniscectomy, in accordance with various
embodiments of the present disclosure.
[0017] FIG. 7 is a flow chart illustrating an exemplary process for
performing virtual surgery, in accordance with various embodiments
of the present disclosure.
[0018] FIG. 8 is a block diagram illustrating an example of a
computer system capable of implementing various processes described
in the present disclosure.
[0019] Like reference numerals refer to corresponding parts
throughout the drawings.
DESCRIPTION OF EMBODIMENTS
[0020] It will be understood that, although the terms "first,"
"second," etc. may be used herein to describe various elements,
these elements should not be limited by these terms. These terms
are only used to distinguish one element from another. For example,
a first contact could be termed a second contact, and, similarly, a
second contact could be termed a first contact, which changing the
meaning of the description, so long as all occurrences of the
"first contact" are renamed consistently and all occurrences of the
second contact are renamed consistently. The first contact and the
second contact are both contacts, but they are not the same
contact.
[0021] Definitions
[0022] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the claims. As used in the description of the embodiments and the
appended claims, the singular forms "a", "an" and "the" are
intended to include the plural forms as well, unless the context
clearly indicates otherwise. It will also be understood that the
term "and/or" as used herein refers to and encompasses any and all
possible combinations of one or more of the associated listed
items. It will be further understood that the terms "comprises"
and/or "comprising," when used in this specification, specify the
presence of stated features, integers, steps, operations, elements,
and/or components, but do not preclude the presence or addition of
one or more other features, integers, steps, operations, elements,
components, and/or groups thereof.
[0023] As used herein, the term "if" may be construed to mean
"when" or "upon" or "in response to determining" or "in accordance
with a determination" or "in response to detecting," that a stated
condition precedent is true, depending on the context. Similarly,
the phrase "if it is determined [that a stated condition precedent
is true]" or "if [a stated condition precedent is true]" or "when
[a stated condition precedent is true]" may be construed to mean
"upon determining" or "in response to determining" or "in
accordance with a determination" or "upon detecting" or "in
response to detecting" that the stated condition precedent is true,
depending on the context.
[0024] As used herein, the term "user" is used interchangeably with
"surgeon." In addition, as used herein, the term "user" is also
used interchangeably with "trainee," "clinician," "engineer," and
"scientist."
[0025] As used herein, the term "surgical language" is used
interchangeably with "medical language." As used herein, the term
"surgical language" is intended to mean the system by which
physicians or surgeons or those in practice or development of
medicine use to communicate or acquire thought or information. This
includes letters, acronyms, words, symbols, signs, images,
photographs, graphs, numbers, statistics and diagrams and other
visual representations of information. It also includes sounds,
tactile sensations, smell, and taste.
[0026] As used herein, the term "computational model" is intended
to describe any set of mathematical equations, numerical methods,
algorithms, symbolic computation, or manipulation of mathematical
expressions or mathematical objects that can be used to describe or
represent the physical mechanics or biology of the surgery to be
studied. These models can be stochastic, deterministic,
steady-state, dynamic, continuous or discrete.
[0027] As used herein, the term "medical imaging" is used
interchangeably with "clinical imaging." As used herein, "medical
imaging" is intended to describe any tool and the images generated
by those tools that describe or quantify anatomic features, e.g.
x-rays, computed tomography (CT) scans, magnetic resonance imaging
(MM), and ultrasound.
[0028] As used herein, the term "surgery" is used interchangeably
with "surgical operation."
[0029] As used herein, the term "non-surgical invasive procedure"
is used interchangeably with "medical intervention." As used
herein, the term "non-surgical invasive procedure" is used
interchangeably with "interventional procedures." In addition, as
used herein, the term "non-surgical invasive procedure" is used
interchangeably with "minimally invasive procedure."
[0030] As used herein, the terms "surgery" and "non-surgical
invasive procedure" are intended to describe any set of actions
that alters anatomy directly or indirectly. In addition, as used
herein, the terms "surgery" and "non-surgical invasive procedure"
include actions involved in the development of an implant, device,
or product that alters anatomy directly or indirectly. An example
of direct alteration of anatomy includes the use of a surgical
instrument to cut or modify tissue. An example of indirect
alteration of anatomy includes the use of medications that increase
the strength of heart muscle contraction or increases the bone
mineral density of the skeleton.
[0031] As used herein, the terms "surgery" and "non-surgical
invasive procedure" are intended to describe any set of actions
performed by a user that would require or be expected to require
informed consent from a patient if performed or used clinically,
regardless of whether or not the present use of the present
disclosure is in a clinical setting.
[0032] As used herein, the distinction between a surgery and a
non-surgical invasive procedure reflects the difference in
visibility of the anatomy that is expected to be available to the
user. In a surgery, direct visualization is used more than indirect
visualization. In a nonsurgical invasive procedure, indirect
visualization is used more than direct visualization. In a scenario
where direct visualization and indirect visualization are used
equally, the user's activity is considered both a surgery and a
non-surgical invasive procedure. Direct visualization reflects a
direct optical pathway between the anatomy and the user and in some
cases will include optics to assist with magnification or
visualization. Indirect visualization reflects the use of an
intermediate tool such as camera, fluoroscopy, CT, Mill or
ultrasound where the user does not have a direct optical pathway to
the anatomy.
[0033] As used herein, the term "solver" is used interchangeably
with "solver module" and is intended to describe any set of
numerical methods that are used to represent true physical
phenomena such as Newton's Laws of Motion that provides sufficient
accuracy to reflect clinical reality. The "finite element" approach
is one such example that can be used in one embodiment of the
present disclosure. The present disclosure is not restricted to the
use a "finite element" based solver. In some embodiments, the
solver module uses numerical methods of simulation such as finite
difference, finite volume, finite element, Arbitrary
Lagrangian-Eulerian, Navier-Stokes, or Conservation Element &
Solution Element methodsfor fluid modeling.
[0034] As used herein, the action of "alteration of anatomy" refers
to any action that can be represented as a change to a description
of a geometric mesh, a material property, or any loading
conditions.
[0035] As used herein, the term "geometric mesh" refers to any
generated description that describes or defines the physical shape,
micro- and macro-structure, or form of one or more anatomic
structures.
[0036] As used herein, the term "material property" refers to any
description of the physical characteristics of the anatomy
described by the geometric mesh in response to physical loads. In
addition, as used herein, "material property" also refers to the
response to pharmacologic, electrical, magnetic, or heating or
cooling interventions. In addition, as used herein, "material
property" also refers to any characteristic of anatomy that can be
represented as physical changes, whether directly or indirectly
through biological changes.
[0037] As used herein, the term "loading condition" refers to any
description of the physical loads applied to or experienced by the
anatomy. In addition, as used herein, the "loading condition"
includes any description of pharmacologic, electrical, magnetic, or
heating or cooling interventions.
[0038] As used herein, the term "clinical information" refers to
medical imaging, laboratory results such as serum potassium or
calcium levels, physical examination results such as blood
pressure, height, patient history such as occupation, use of
tobacco products, and any additional clinical data describing a
patient that can be represented as a change to the anatomy through
a description of a geometric mesh, a material property, or a
loading condition.
[0039] As used herein, the term "patient" refers to both an entire
individual as an organism as a whole as well as any subset of the
patient's anatomy such as a patient's organ system (e.g.,
cardiopulmonary system reflecting the heart and lungs and the
associated connective tissue), an individual organ (e.g., a heart),
a substructure of an organ (e.g. a heart valve), a substructure of
a substructure (e.g. a leaflet of a heart valve), or a substructure
of a substructure of the substructure (e.g. collagen bundle of a
leaflet of a heart valve). There is no limit to the restriction to
minimum size of the subset of the anatomy as the size is defined by
the user's request and anatomy of interest.
[0040] Reference will now be made in detail to various embodiments,
examples of which are illustrated in the accompanying drawings. In
the following detailed description, numerous specific details are
set forth in order to provide a thorough understanding of the
present disclosure and the described embodiments. However, the
present disclosure may be practiced without these specific details.
In other instances, well-known methods, procedures, components, and
circuits have not been described in detail so as not to
unnecessarily obscure aspects of the embodiments.
[0041] For example, the techniques of the present disclosure will
be described in the context of fragments, particular servers and
encoding mechanisms. However, it should be noted that the
techniques of the present disclosure apply to a wide variety of
different fragments, segments, servers and encoding mechanisms. In
the following description, numerous specific details are set forth
in order to provide a thorough understanding of the present
disclosure. Particular example embodiments of the present
disclosure may be implemented without some or all of these specific
details. In other instances, well known process operations have not
been described in detail in order not to unnecessarily obscure the
present disclosure.
[0042] Various techniques and mechanisms of the present disclosure
will sometimes be described in singular form for clarity. However,
it should be noted that some embodiments include multiple
iterations of a technique or multiple instantiations of a mechanism
unless noted otherwise. For example, a system uses a processor in a
variety of contexts. However, it will be appreciated that a system
can use multiple processors while remaining within the scope of the
present disclosure unless otherwise noted. Furthermore, the
techniques and mechanisms of the present disclosure will sometimes
describe a connection between two entities. It should be noted that
a connection between two entities does not necessarily mean a
direct, unimpeded connection, as a variety of other entities may
reside between the two entities. For example, a processor may be
connected to memory, but it will be appreciated that a variety of
bridges and controllers may reside between the processor and
memory. Consequently, a connection does not necessarily mean a
direct, unimpeded connection unless otherwise noted.
Example Embodiments
[0043] FIG. 1 illustrates a general overview of an example system
(100) for implementing various methods of the present disclosure.
In particular, FIG. 1A describes a user accessing the Internet or
Web (104) using a computer (102) configured with a web browser to
interact with another computer configured as a server (106)
containing modules required for fulfilling the user's simulation
request.
[0044] FIG. 1B is a flow diagram illustrating an overview of an
example process (120) implemented with the example system in FIG.
1A. In this example, the user provides patient information
including cardiac pressures and imaging data such as MM (122) to
the server. Once the data is received by the server, a
computational model is created (124). In some embodiments, the
computational model is a finite element model. The server provides
information back to the user that will allow the user to perform
virtual surgery (126). This is done using a graphical user
interface (GUI). Once the user has completed the virtual surgery,
the data is sent back to server where pre- and post-operative
assessment is obtained through finite element analysis (128). The
server then provides data back to the user to detail the mechanical
effect of virtual surgery and the change in key mechanical
pressures is presented (130).
[0045] According to various embodiments, virtual surgery
simulations are based upon the use of a prototypical source model,
e.g., a three-dimensional (3-D) computational model representing a
physical object, such as an individual patient or a hypothetical
patient made from averages. In some embodiments, the 3-D model
contains one or more geometric meshes, material properties, and
loading conditions. In some embodiments, parametric analysis is
performed by changing the mesh geometry (altering the shape of the
patient) or adding or removing the mesh geometry. In some
embodiments, changing the assigned material properties (altering
the stiffness/softness of the tissue) is performed. In some
embodiments, changing the loading conditions (e.g. blood pressure)
is performed. In some embodiments, small, directional increments in
the geometric mesh, material properties, or loading conditions are
performed followed by observations. Parametric analysis in this way
allows for understanding, in general terms, of the consequences or
benefits of an action. For instance, if a heart is to be resized,
the starting point would be a normal heart. Then, incrementally,
the heart is adjusted to be smaller and smaller or bigger and
bigger. Another example is a spine fusion. With parametric
analysis, differences between a one or two-level fusion can be
readily observed. Another example is a meniscectomy of the knee.
With parametric analysis, the optimal amount of meniscus to be
removed can be readily observed. Various surgical operations and
other non-surgical invasive procedures and devices can be simulated
in this way.
[0046] The following example illustrates an exemplary embodiment of
the present disclosure. In this embodiment, the user is a
practicing surgeon interested in determining the effects of
performing a mitral valve repair on a specific patient. The surgeon
begins by taking a Mill of the patient's heart in the pre-operative
state and then sends it to the server along with relevant patient
information such as age, blood pressure, and current medications
(122). This is performed using a web browser (102). This data is
received by the server (106) via the Internet (104) and processed
by a clinical translation module. The module recognizes that the
mitral valve repair requires a computational model of the left
ventricle and mitral valve. Mill data is sent from the "clinical
translation module" to an "information integration module" where a
geometric mesh representing the left ventricle and mitral valve is
created. The geometric mesh is then assigned material properties
based upon both values in the Mill and a known database of
materials in clinical translation module. The age, blood pressure
and current medications are used to further refine the material
properties and establish the loading conditions for the
computational model. This process generates a finite element model
(124) which is then shown to the surgeon via a user interface.
Through this interface, the surgeon performs the mitral valve
repair, selecting the portion of the posterior mitral valve leaflet
to be excised, the manner in which the remain free ends of the
leaflet are sutured, and then the manner in which an annuloplasty
ring is implanted and sutured (126). In this example, the surgeon
uses the graphical interface to replicate the surgery illustrated
in FIG. 3. The surgeon will identify the mitral valve (300)
including the anterior (306) and posterior (308, 312, and 310)
leaflets. In this example patient, the middle section of the
posterior leaflet is prolapsing and causing the valve to leak
(mitral regurgitation). The surgeon uses a scalpel (305) and
forceps (302) to excise out the triangular section of the mitral
valve prolapse (312) along the dotted lines. The resulting
triangular defect between the left (308) and right (310) scallops
of the posterior mitral leaflet caused by the excision of the
prolapsing segment are identified. The surgeon places sutures (322)
to bring the cut edges of the leaflet together. The repaired
leaflet (308, 310) after the sutures (322) have been tied. The
surgeon then applies a supporting or buttressing "annuloplasty"
ring (360, 362). In this example, the surgery is expected to result
in a repaired valve that is competent and functional.
[0047] The surgeon's actions are stored in a queue and sent back to
the server (106) for further processing. The clinical translation
module translates the queue of actions into a series of
modifications to a geometric mesh, material property, and/or
loading condition. The translation is performed by a database
within the clinical translation module, and actions by the surgeon
that are outside of the database are submitted to the information
integration module for further processing. The information
integration module will either combine imaging data or other
clinical information to determine how the action in the queue will
be represented as changes to a geometric mesh, material property,
and/or loading condition. If the information integration module is
unable to determine the optional representation needed for the
solver module, the surgeon's action is flagged for human evaluation
and modification. After the surgeon's input has fully been
processed, it is provided to the solver module. The solver module
uses realistic mathematical simulation to perform the surgery as
described by the surgeon. This entire sequence of steps (128)
results in a mathematical representation of the surgical outcome.
The clinical translation module then converts the output from the
solver module into surgical language. This is then presented to the
surgeon (130). In this example, the outcome will be presented as a
visual animation of the beating left ventricle and motion of the
mitral valve before and after surgery along with changes in key
mechanical parameters for this surgery (130). In this example, the
clinical translation module will report cardiac outcome parameters
based upon the location of the surgery such as the force across the
sutures, the stress to the fibers of the muscle at the different
regions of the left ventricle, as well as the pressure and stress
to the mitral valve leaflets.
[0048] In some embodiments, parametric analysis is requested by the
clinical translation module to be performed by the solver module.
After the user performs virtual surgery (126), the clinical
translation module will evaluate the outcome of small perturbations
in the surgeon's technique. For example, in some embodiments
different annuloplasty rings (362) from different device
manufacturers made from different materials or shapes can be
simulated with the change in outcome, if any, reported to the
surgeon (130). In some embodiments, the number of sutures (322)
used is increased or decreased. In some embodiments the amount of
the leaflet to be removed (312, dashed lines) is increased or
decreased. In some embodiments, the clinical translation module
will continue to test additional perturbations and report the
outcome of the surgeon's plan in comparison to the optimal approach
as determined through this iterative parametric analysis.
[0049] In another embodiment, a similar set of steps can be used to
evaluate a trainee and determine if the steps made by the trainee
in surgery (126) result in a clinically successful outcome. In some
embodiments, surgical complications will be introduced such as a
failure of a suture (322) to determine if the trainee will
recognize the problem and make the appropriate surgical maneuvers
to correct the failure.
[0050] In some embodiments, the user is a device engineer or
scientist and a similar set of steps can be used to evaluate the
optimal conditions for implanting a device or the optimal
characteristics of a device.
[0051] In some embodiments, the user is interested in understanding
the effects of a surgery generally for an improved understanding of
the actions of specific alteration of anatomy. In some embodiments,
there is no specific patient of interest, no specific device or
instrumentation of interest, and no assessment of skills to be
performed.
[0052] In some embodiments, the user can alter the anatomy in
real-life through a surgical operation or a non-surgical invasive
procedure. In some embodiments, the user will use the present
disclosure to evaluate the technical difficulty of the approach to
anatomic alteration. In some embodiments, the user will use the
present disclosure to determine the portions of the procedure which
are best achieved through a surgery and a non-surgical invasive
procedure.
[0053] In some embodiments, the data submitted by the user (122)
contains additional types of clinical imaging such as CT scan or
additional information or data in surgical language. In some
embodiments, the data submitted by the user excludes cardiac
pressures and MM. The present disclosure is not restricted to a
requirement for input of cardiac pressures and MM. In some
embodiments, the user will submit a complete existing computational
model and bypass the need for the server (106) to create a model
(124). In some embodiments, the user will submit an incomplete
computational model containing one or more geometric meshes,
material properties, or loading conditions.
[0054] In some embodiments, the user input is performed using a
keyboard or mouse. In some embodiments, other input may be used
including point and click with a mouse, voice activated input,
typing input via a keyboard, scanned input via cameras or motion
sensors, or input from handheld devices such as a smart phone or
tablet PC. Input can also be made via any haptic device capable of
performing motions or functions representing surgical operations or
other interventions or procedures that affect anatomic structures.
The motions or functions are captured and stored for processing or
transmission. In some embodiments, there is a direct translation of
the input actions to the computational model.
[0055] According to various embodiments, the system providing the
clinical translation module, through a combination of automated
tools and/or human labor, translates the user input representing
virtual surgical operations into input for the solver module. In
some embodiments, this includes describing in surgical language,
via a text or graphical interface, the planned procedure.
[0056] According to various embodiments, the system providing the
clinical translation module, through a combination of automated
tools and/or human labor, translates the output of the solver
module representing the outcome or result of virtual surgical
operations into surgical language. In some embodiments, this
reporting of information in surgical language, occurs via a text or
graphical interface.
[0057] According to various embodiments, data available to the
clinical translation module is made available to the information
integration module for additional pre- and post-processing before
input is provided to the solver module or output is provided to the
user.
[0058] According to various embodiments, the system providing the
information integration module, through a combination of automated
tools and/or human labor, translates the user input representing
"clinical information" into alterations of a geometric mesh, a
material property, or a loading condition.
[0059] In some embodiments, clinical imaging data available to the
information integration module lacks sufficient visual fidelity to
identify anatomic structures of importance. One such example would
be the intermeniscal ligaments that connect the medial meniscus and
lateral meniscus of the knee. In some embodiments, the information
integration module will generate a geometric mesh, material
property, or a loading condition representing structures that are
known to exist despite the absence of the structure on imaging
based upon landmarks that are visible. One such example would be
generating a computational model of the intermeniscal ligaments
based upon the location of the anterior horn of the medial meniscus
and lateral meniscus. In some embodiments, the addition of
computational models of anatomic structures not visible in the
imaging data occurs without additional user input. In other
embodiments, the addition of computational models of anatomic
structures not visible in the imaging data occurs with user
input.
[0060] In some embodiments, clinical information necessary for a
computational model used by the solver module is not available to
the information integration module. One such example would be a
user that has not specified the blood pressure, or a height, or a
weight as input. In some embodiments, the information integration
module will provide the missing clinical information necessary for
a computational module used by the solver module. In some
embodiments, the substituted information reflects a 50th percentile
value. In some embodiments, the substituted information reflects a
5th percentile value. In some embodiments, the substituted
information reflects a 95th percentile value. In some embodiments,
the substitution of clinical information is performed without
additional user input. In other embodiments, the substitution of
clinical information occurs with user input.
[0061] According to various embodiments, the system providing the
information integration module exchanges data to translate the user
input into alterations of a geometric mesh, a material property, or
a loading condition or into a surgical language that can be
processed by the clinical translation module.
[0062] The following example illustrates another exemplary
embodiment of the present disclosure. In this embodiment, the user
is a trainee interested in understanding the effects of performing
a medial meniscectomy in the knee without a specific patient in
mind or surgical goal. In this embodiment, the trainee uses a
pre-existing template representing a computational model of the
knee and does not need to upload any new information to the server
nor does the server need to create a new computational model. Using
the standardized template computational model of the knee, the
trainee identifies the geometric mesh representing the medial
meniscus and uses the user interface to remove this structure. The
trainee then selects the loading condition of a standing patient
for analysis. The system mathematically identifies the resulting
varus moment and presents the output to the user in surgical
language via the user interface.
[0063] In some embodiments a template computational model
represents an average patient. In other embodiments, the template
computational model represents a patient with anatomy that does not
have an average geometric mesh, material property, or loading
condition. One such example would be a patient with a disease.
[0064] In some embodiments, the user will alter a geometric mesh
directly to determine the effects of that action. In some
embodiments, the alteration is done using surgical language. In
some embodiments, the alteration is done through manipulation of a
geometric mesh directly through the user interface.
[0065] In some embodiments, the user will alter a material property
directly to determine the effects of that action. In some
embodiments, the alteration is done using surgical language. In
some embodiments, the alteration is done through manipulation of a
material property directly through the user interface.
[0066] In some embodiments, the user will alter a loading condition
directly to determine the effects of that action. In some
embodiments, the alteration is done using surgical language. In
some embodiments, the alteration is done through manipulation of a
loading condition directly through the user interface.
[0067] FIGS. 2A and 2B are exemplary drawings of the various
aspects of a real heart, in accordance with various embodiments of
the present disclosure. FIG. 2A shows the outside of the left
ventricle (200) and in this case also shows an area of heart attack
(myocardial infarction (MI) where the MI (206) is surrounded by a
border of poorly contractile heart muscle (204) and the normal
undamaged heart muscle (202). FIG. 2B shows the inside of the left
ventricle (220). The mitral valve is the inflow valve to the left
ventricle and FIG. 2B further shows the muscular connections or
papillary muscles (208) by which the valve is connected to the left
ventricular wall.
[0068] FIGS. 2C and 2D illustrate examples of geometric mesh models
similar to models that would be created by exemplary systems such
as system 100 in FIG. 1. In this exemplary case, FIGS. 2C and 2D
correspond to the various aspects of a real heart presented in
FIGS. 2A and 2B, in accordance with various embodiments of the
present disclosure. Specifically, as in FIG. 2A, the mesh model in
FIG. 2C shows the area of myocardial infarction (206), surrounded
by a border of poorly contractile heart muscle (204) and beyond
that the normal undamaged heart muscle (202). As in FIG. 2B, FIG.
2D shows the inside of the left ventricle (220) where in this case
the muscular connections to the mitral valve or papillary muscles
are seen (208) with their connections (chordae) to the mitral valve
at the top of the left ventricle.
[0069] FIGS. 3A-3D illustrate an example of the steps involved in a
typical cardiac surgical procedure, in accordance with various
embodiments of the present disclosure. In this exemplary case, a
mitral valve repair procedure is illustrated. The illustrations
show the mitral valve (300) including the anterior (306) and
posterior (308 and 310) leaflets. In this case, the middle section
of the posterior leaflet is prolapsing and causing the valve to
leak (mitral regurgitation). In FIG. 3A, the surgeon is performing
a mitral valve repair procedure to repair the mitral valve prolapse
(312). Specifically, FIG. 3A shows the surgeon grasping the
prolapsing segment (312) of the posterior leaflet of the valve
(308, 310) with forceps (302). A scalpel (304) is being used to
excise a triangular section (dotted lines) of the prolapsing
segment (312). FIG. 3B shows the triangular defect between the left
(308) and right (310) scallops of the posterior mitral leaflet
caused by the excision of the prolapsing segment. In this case,
sutures (322) are now in place to bring the cut edges of the
leaflet together. FIG. 3C shows the repaired leaflet (308, 310)
after the sutures (322) have been tied. Finally, FIG. 3D shows the
application of a supporting or buttressing "annuloplasty" ring
(362). The valve should now be competent.
[0070] FIGS. 4A-4F are examples of simulating a mitral valve repair
procedure using computational modeling in accordance with various
embodiments of the present disclosure. In this case, the
computational model corresponds roughly to the steps of the
operation illustrated in FIGS. 3A-3D. FIG. 4A shows the mitral
valve and left ventricle prior to the virtual surgical procedure
(480). FIGS. 4B-4E show a close-up view of the mitral valve repair
as shown through a series of actions. FIG. 4F shows a zoomed out
view summarizing the post-operative state of the mitral valve
repair (490). Specifically, FIG. 4B shows the mitral valve after
excision of the triangular section of the prolapsing segment. This
reflects the condition after FIG. 3A and before FIG. 3B. In FIG.
4B, the anterior (406) and posterior (408, 410) leaflets of the
mitral valve are shown. The prolapsing segment has already been
excised leaving a triangular defect (412). The edge of the
remaining leaflet is labeled with the arrow (404). FIG. 4C
corresponds to FIG. 3B. In FIG. 4C, virtual sutures (422) are seen
in place and now bridge the defect in the posterior leaflet.
Similar to FIG. 3C, FIG. 4D shows the repair after the leaflet
sutures have been virtually tied (422) bringing the edges of the
posterior leaflet together. Similar to FIG. 3D, FIG. 4E shows
virtual sutures in place between a supporting annuloplasty ring and
the edge of the mitral valve orifice (462). The aorta is seen
(482). In FIG. 4F, the ring (462) has been virtually secured in
place.
[0071] FIG. 5 illustrates an example of human knee (500), in
accordance with various embodiments of the present disclosure.
Right knee (500) is presented in surgical language and reflects a
description of anatomy that may be encountered in a textbook. The
undersurface of the patella, or knee cap, is shown dissected and
reflected off (502). The anterior cruciate ligament (504),
patellofemoral groove (506), posterior cruciate ligament (508),
lateral distal femoral condyle (510), tibial or medial collateral
ligament (512), medial meniscus (514), tibial plateau (516), tibia
(518), lateral meniscus (520), lateral or fibular collateral
ligament (522), and fibula (524) have been labeled. These are
anatomic structures of clinical importance as it generally relates
to knee function as well as anatomy relevant to surgical operations
as well as non-surgical invasive procedures. This figure also
illustrates an example of information that a user may provide,
using surgical language, in certain embodiments of the present
disclosure.
[0072] FIG. 6A illustrates a computational model of a human knee,
in accordance with various embodiments of the present disclosure.
This drawing is representative of a three dimensional mesh of a
right knee (600) as used for computational simulation of knee
mechanics. The mesh includes all of the anatomic structures of
importance to the simulation task at hand. In this example, the
patella and fibula are not required although these anatomic
structures may be described in a textbook or provided by the user
using surgical language. In some embodiments of the present
disclosure, the patella and fibula may be included. The portions of
computational mesh representing the anterior cruciate ligament
(604), patellofemoral groove (606), posterior cruciate ligament
(608), lateral distal femoral condyle (610), tibial or medial
collateral ligament (612), medial meniscus (614), tibial plateau
(616), tibia (618), lateral meniscus (620), lateral or fibular
collateral ligament (622), and fibula (624) have been labeled.
These are anatomic structures of clinical importance as it
generally relates to knee function as well as anatomy relevant to
surgical procedures as well as non-invasive interventions. For the
purpose of computational simulation, anatomic structures that are
present and required for realistic and accurate results computed by
the solver module but not commonly discussed in medical textbooks
may be included. In this example, the three dimensional mesh
includes representation of the transverse meniscomeniscal or
anterior intermeniscal ligament (624) even if it has not been
provided by the user.
[0073] FIG. 6B illustrates a simulated model of a human knee (660)
that has undergone a medial meniscectomy, in accordance with
various embodiments of the present disclosure. This drawing is
representative of a three dimensional mesh of a right knee that has
undergone a total medial meniscectomy as used for computational
simulation of knee mechanics. The mesh includes all of the anatomic
structures of importance to the simulation task at hand. In this
example, the patella and fibula are not required although these
anatomic structures may be described in a textbook or provided by
the user using surgical language. In some embodiments of the
present disclosure, the patella and fibula may be included. The
portions of computational mesh representing the anterior cruciate
ligament (604), patellofemoral groove (606), posterior cruciate
ligament (608), lateral distal femoral condyle (610), tibial or
medial collateral ligament (612), medial meniscus (614), tibial
plateau (616), tibia (618), lateral meniscus (620), lateral or
fibular collateral ligament (622), and fibula (624) have been
labeled. These are anatomic structures of clinical importance as it
generally relates to knee function as well as anatomy relevant to
surgical procedures as well as non-invasive interventions. For the
purpose of computational simulation, anatomic structures that are
present and required for realistic and accurate results computed by
the solver module but not commonly discussed in medical textbooks
may be included. The output of the solver module, indicates that
the removal of the medial meniscus results in a directional force
represented by the arrows (662). There is an increase in the gap or
distance between the lateral meniscus (620) and lateral distal
femoral condyle (610). In this embodiment, the output of the solver
module could be processed by the clinical translation module and
described in surgical language as a "varus moment."
[0074] FIG. 7 is a flow chart illustrating an exemplary process
(700) for performing virtual surgery, in accordance with various
embodiments of the present disclosure. First, a virtual surgery
system, e.g. system 100, receives (702) user input from the user
interface. The user input includes input representing surgical
operations or surgical procedures. Next, the system processes (704)
the user input and utilizes the input to generate or modify a
computational model. Subsequently, the system runs (706)
simulations using the computational model in accordance with the
user input. Then, the system determines (708) results from the
simulations. In some embodiments, the results correspond to
probable effects or outcomes of performing real life surgical
operations or surgical procedures corresponding to the user input.
Last, the system presents (710) the results to the user via the
user interface.
[0075] In the present disclosure, the clinical translation module
determines the relevant output from the solver module to be
provided in surgical language. In some embodiments, for example in
orthopedic surgery, solver output can be translated into surgical
language to determine if an intended surgical implant fits well or
does not fit well. Criteria for a "good" fit may additionally be
provided. In some embodiments, as in for cardiac surgery, the
solver output will be translated into surgical language to describe
the cardiac output, myocardial wall stress, or stroke volume as a
result of a surgical operation or non-surgical invasive procedure.
In other embodiments, the user may specify the relevant output to
be reported by the solver module and the preferred translation into
surgical language.
[0076] In some implementations, further processing of the clinical
information is performed by an information integration module which
converts the clinical information into a format usable by the
solver module or a format appropriate for further processing by the
clinical translation module. In some implementations, the
conversion is performed in an automated fashion by a computer. In
some implementations, the conversion is performed in a
semi-automated fashion where approval and confirmation is required.
In some implementations, the confirmation is performed by the user
performing the simulation. In other implementations, the
confirmation is performed by a different user from the user
performing the simulation.
[0077] In some implementations, once the data which has been fully
analyzed and processed by the information integration module, the
clinical translation module translates the steps of the surgery or
procedure in the queue into a format usable by the solver module.
As an example, an example of one surgical step in a virtual surgery
is presented below. For instance, a "simple, interrupted stitch"
which is the equivalent of sticking a needle through one piece and
then another and then tying the free ends of the suture together,
can be implemented by identifying the portion of the geometric mesh
describing the location of the sutures, the material properties of
the suture to be used, and the loading conditions which reflect the
manner in which the surgical knot is performed. According to
various embodiments, the system can simulate multiple different
types of stiches as well as different types of cutting of tissue or
altering the shape of different organs or tissues. According to
various embodiments, the system can simulate multiple surgical
steps that represent one virtual surgery or many virtual
surgeries.
[0078] According to various embodiments, the virtual instructions
are converted into an "input file" for use with the solver module.
In some embodiments, the input file has coordinates for elements
representing a geometric mesh, descriptions of the material
properties for each element, and the loading conditions reflecting
one or more steps of a surgery. The input file is then passed onto
the solver module that computes the result of the surgeon's action
or actions.
[0079] According to various embodiments, the solver module outputs
data in the format of numbers describing how the coordinates of
each element of the mesh have changed after surgery as well as the
forces, stress and strain that affect each part of the portion of
the human body to be analyzed. In some embodiments, other
information relevant to the computational outcome of the surgery is
included by the solver module. This data may include information
that is not in surgical language such as a large database of
numbers that can be very difficult for a user to interpret and
understand.
[0080] According to various embodiments, the clinical translation
module then modifies the output to reflect the next step or steps
of the user queue to produce a new input for the solver module,
determines that the surgery is complete, or awaits further user
input.
[0081] According to various embodiments, the clinical translation
module then converts the numerical information and other
non-surgical language from the solver into a clinically useful
presentation of the outcome of the surgery using surgical language.
In some embodiments, this can be a graph of pressure on the surface
of a portion of the joint, a color-coded picture or video, a
description of the change in a parameter such as stroke volume, or
even a simple pass/fail statement. In some embodiments, the
information is delivered to the surgeon so that he/she can
determine the best surgical plan for the patient.
[0082] In some embodiments, the system translates the output from
the solver into surgical language using touch, e.g. the tactile
resistance of a surgical screwdriver traveling through bone of
different density, a vibration on a surgical instrument, or heat of
surgical saw.
[0083] In some embodiments, the system translates the output from
the solver into surgical language using sound, e.g. an audible
tone, the change in pitch of a surgical drill going from a low to
high density portion of bone, the change in rate and rhythm of a
beating heart.
[0084] In some embodiments, the system can be used to train
surgeons on surgical procedures. In some embodiments, the system
can be designed such multiple simulations with different outcomes
can be accessed by a user. The system can also be designed to only
allow a limited selection of surgical procedures or operations.
[0085] In some embodiments, the system is used prior to the actual
surgery or procedure to provide the outcome of the virtual surgery
in surgical language before the actual surgery or procedure is
performed.
[0086] In some embodiments, the system is used during the actual
surgery or procedure to provide an on-going predictive outcome of
the surgery as the surgery or procedure is being performed.
[0087] In some embodiments, the system is used after the actual
surgery or procedure is complete to provide a retrospective
comparison between the true results and the predicted results.
[0088] In some embodiments, the system is used in a combination of
time periods before, during, and after surgery.
[0089] In some embodiments, the system is used to develop,
optimize, or otherwise evaluate a device or instrument intended for
use as a part of the surgery.
[0090] In some embodiments, the software used for computational
modeling can be LS-DYNA. LS-DYNA, is a finite element software,
originally designed by military scientists. It allows computers to
solve a very large set of partial differential mathematical
equations on supercomputers. LS-DYNA only accepts input files in
its own proprietary format and outputs numbers and data, which may
be difficult to interpret by surgeons. The following represents an
exemplary input file representing a cube of aluminum containing a
geometric mesh of one element and eight nodes, one material
property consistent with aluminum, and one loading condition in
LS-DYNA:
TABLE-US-00001 *KEYWORD *TITLE Example of aluminum cube deformation
$ output parameters *CONTROL TERMINATION 1. *DATABASE BINARY D3PLOT
.1 $ geometric mesh *PART aluminum cube 1 1 1 *SECTION_SOLID 1
*NODE 1 0 0 0 7 7 2 1 0 0 5 0 3 1 1 0 3 0 4 0 1 0 6 0 5 0 0 1 4 0 6
1 0 1 2 0 7 1 1 1 0 0 8 0 1 1 1 0 *ELEMENT SOLID 1 1 1 2 3 4 5 6 7
8 $ material properties *MAT ELASTIC 1 2700. 70.e+09 .3 $ loading
conditions *LOAD SEGMENT 1 1 0 5 6 7 8 *DEFINE CURVE 1 0 0 1
70.e+05
[0091] In some embodiments, the input required for realistic
surgical simulation requires more than one element or node to be
described. In one example, a computational model of a right knee
may have over 88,000 nodes and over 74,000 elements. The amount of
input is dependent on the complexity of the anatomy being simulated
and the virtual surgery to be performed and therefore does not have
an upper or lower limit.
[0092] In some embodiments, the solver module can be LS-DYNA. The
output from the solver module describing the coordinates of each
element of the mesh that have changed after simulation as well as
the forces, stress and strain is a large database of numbers which
requires effort to interpret. The database of numbers can be
thousands to pages to hundreds of thousands of pages. The amount of
output is dependent on the complexity of the anatomy being
simulated and therefore does not have an upper or lower limit The
following represents an exemplary output of the numerical data
produced by LS-DYNA for a representing a cube of aluminum
containing a geometric mesh of one element and eight nodes, one
material property consistent with aluminum, and one loading
condition:
TABLE-US-00002 *KEYWORD $TIME VALUE = 9.9999309e-001 $STATE NO = 11
*ELEMENT SOLID 1 1 1 2 3 4 5 6 7 *NODE 8 1 0.0000000e+000
0.0000000e+000 0.0000000e+000 2 1.0000300e+000 0.0000000e+000
0.0000000e+000 3 1.0000300e+000 1.0000300e+000 0.0000000e+000 4
0.0000000e+000 1.0000300e+000 0.0000000e+000 5 0.0000000e+000
0.0000000e+000 9.9990004e-001 6 1.0000300e+000 0.0000000e+000
9.9990004e-001 7 1.0000300e+000 1.0000300e+000 9.9990004e-001 8
0.0000000e+000 1.0000300e+000 9.9990004e-001 *INITIAL VELOCITY NODE
2 -9.620E-6 0.0 0.0 3 -9.620E-6 -9.620E-6 0.0 4 0.0 -9.620E-6 0.0 5
0.0 0.0 -2.095E-5 6 -9.620E-6 0.0 -2.095E-5 7 -9.620E-6 -9.620E-6
-2.095E-5 8 0.0 -9.620E-6 -2.095E-5 *END $NODAL DISPLACEMENT 1
0.0000000e+000 0.0000000e+000 0.0000000e+000 2 3.0040741e-005
0.0000000e+000 0.0000000e+000 3 3.0040741e-005 3.0040741e-005
0.0000000e+000 4 0.0000000e+000 3.0040741e-005 0.0000000e+000 5
0.0000000e+000 0.0000000e+000 -9.9956989e-005 6 3.0040741e-005
0.0000000e+000 -9.9956989e-005 7 3.0040741e-005 3.0040741e-005
-9.9956989e-005 8 0.0000000e+000 3.0040741e-005 -9.9956989e-005
$NODAL RESULTS $RESULT OF 1 2.1125E-36 2 0.0 3 7.9903E-36 4 0.0 5
3.6434E-44 6 4.2039E-44 7 4.6243E-44 8 5.1848E-44
[0093] In some embodiments, the output required for realistic
surgical simulation requires more than one element or node to be
described. In one such example, a computational model of a right
knee may have over 88,000 nodes and over 74,000 elements. The
amount of output is dependent on the complexity of the anatomy
being simulated and the virtual surgery to be performed and
therefore does not have an upper or lower limit.
[0094] FIG. 8 is a block diagram illustrating an example of a
computer system capable of implementing various processes described
in the present disclosure. The system 800 typically includes a
power source 824; one or more processing units (CPU's) 802 for
executing modules, programs and/or instructions stored in memory
812 and thereby performing processing operations; one or more
network or other communications circuitry or interfaces 820 for
communicating with a network 822; controller 812; and one or more
communication buses 814 for interconnecting these components. In
some embodiments, network 822 can be the another communication bus,
the Internet, an Ethernet, an Intranet, other wide area networks,
local area networks, and metropolitan area networks. Communication
buses 814 optionally include circuitry (sometimes called a chipset)
that interconnects and controls communications between system
components. System 800 optionally includes a user interface 804
comprising a display device 806, a keyboard 808, and a mouse 810.
Memory 812 includes high-speed random access memory, such as DRAM,
SRAM, DDR RAM or other random access solid state memory devices;
and may include non-volatile memory, such as one or more magnetic
disk storage devices, optical disk storage devices, flash memory
devices, or other non-volatile solid state storage devices. Memory
812 may optionally include one or more storage devices 816 remotely
located from the CPU(s) 802. Memory 812, or alternately the
non-volatile memory device(s) within memory 812, comprises a
non-transitory computer readable storage medium. In some
embodiments, memory 812, or the computer readable storage medium of
memory 812 stores the following programs, modules and data
structures, or a subset thereof: [0095] an operating system 840
that includes procedures for handling various basic system services
and for performing hardware dependent tasks; [0096] a file system
844 for storing various program files; [0097] a virtual surgery
application module 846 for a user to provide clinical imaging and
other clinical information to the clinical translation module, to
make modifications to virtual anatomy, to review the output from
the solver module. [0098] a solver module 856 for receiving input
from a clinical translation module 860 and computes the outcome of
a surgery defined by one or more geometric meshes, material
properties, and loading conditions and provides that output to the
clinical translation module using methods that represent true
physical phenomena with sufficient accuracy to reflect clinical
reality. [0099] an information integration module 858 that
processes clinical imaging and other clinical information to
generate or modify a geometric mesh, a material property or a
loading condition for use with solver module 856 or for use with a
clinical translation module 860. [0100] a clinical translation
module 860 that receives input from and provides output to the
virtual surgery application module 846, that provides input to and
receives output from the solver module 856, that provides and/or
receives input and/or output to the information integration module
and performs translation to and from surgical language. [0101] and
a user database 862 for storing user information, for example first
and last name, passwords, contact information, and billing or
subscription information.
[0102] Virtual surgery application module 846 may include the
following submodules, or a subset thereof: [0103] a digital
anatomic model module 850 containing the following fields and
subfields, or a subset thereof: geometric mesh (mesh ID, mesh
elements, nodes, parts, sections), material property (material
property ID, constitutive equation, constant [1-N]), loading
conditions (loading condition ID, loading condition type,
direction, magnitude, constant [1-N]). Multiple geometric meshes
exist. In some embodiments, these can be divided into parts and
sections. Multiple parts can be assigned to a single mesh ID and
can represent a portion of anatomy. Multiple sections can be
assigned to a single part ID. Multiple elements can be assigned to
a single section ID. Multiple nodes can be assigned to a single
element ID. In various embodiments, these subsets describe the
appearance of anatomy and allows each relevant component of the
anatomy to be uniquely assigned material properties and loading
conditions as appropriate. [0104] a user action queue module 852
containing the following fields and subfields, or a subset thereof:
action ID, queue position, action, time of action. Each action
performed by the user is assigned an action ID. Multiple actions
can share a single queue position. The action can be modification
of anatomy through surgical language or direct interaction with a
geometric mesh, material property or loading condition. The action
can also be a request for output from the system through surgical
language or in terms of a geometric mesh, material property and
other data associated physical properties. The time of action is
combined with queue position to precisely determine when an action
is simulated. [0105] an additional clinical information module 854
containing the following fields and subfields, or a subset thereof:
clinical info ID, clinical data [1-N], datatype. Each item of
clinical information is assigned a unique ID. The clinical data can
be in arbitrary text or binary format with the datatype defining
the type of data.
[0106] Each of the above identified elements may be stored in one
or more of the previously mentioned memory devices, and corresponds
to a set of instructions for performing a function described above.
The above identified modules or programs (i.e., sets of
instructions) need not be implemented as separate software
programs, procedures or modules, and thus various subsets of these
modules may be combined or otherwise re-arranged in various
embodiments. In some embodiments, memory 812 may store a subset of
the modules and data structures identified above. Furthermore,
memory 812 may store additional modules and data structures not
described above.
[0107] Although FIG. 8 shows a "virtual surgery simulation system,"
FIG. 8 is intended more as functional description of the various
features which may be present in a set of servers than as a
structural schematic of the embodiments described herein. In
practice, and as recognized by those of ordinary skill in the art,
items shown separately could be combined and some items could be
separated. For example, some items shown separately in FIG. 8 could
be implemented on single servers and single items could be
implemented by one or more servers. The actual number of servers
used to implement a virtual surgery simulation system and how
features are allocated among them will vary from one implementation
to another, and may depend in part on the amount of data traffic
that the system must handle during peak usage periods as well as
during average usage periods.
[0108] According to various embodiments, the system includes
software that implements a graphical user interface that allows
surgeons to describe their surgical plan on a patient, whether it
is a cardiac surgery or orthopedic surgery patient, using surgical
language they are familiar with. Similarly the system will
incorporate software that presents the solution or outcome of the
surgery in a format using surgical language.
[0109] The foregoing description, for purpose of explanation, has
been described with reference to specific embodiments. However, the
illustrative discussions above are not intended to be exhaustive or
to limit the present disclosure to the precise forms disclosed.
Many modifications and variations are possible in view of the above
teachings. The embodiments were chosen and described in order to
best explain the principles of the present disclosure and its
practical applications, to thereby enable others skilled in the art
to best utilize the present disclosure and various embodiments with
various modifications as are suited to the particular use
contemplated.
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