U.S. patent application number 13/835479 was filed with the patent office on 2014-03-13 for system and method for image guided medical procedures.
This patent application is currently assigned to CONVERGENT LIFE SCIENCES, INC.. The applicant listed for this patent is CONVERGENT LIFE SCIENCES, INC.. Invention is credited to Dinesh Kumar, Daniel S. Sperling, Amit Vohra.
Application Number | 20140073907 13/835479 |
Document ID | / |
Family ID | 50233964 |
Filed Date | 2014-03-13 |
United States Patent
Application |
20140073907 |
Kind Code |
A1 |
Kumar; Dinesh ; et
al. |
March 13, 2014 |
SYSTEM AND METHOD FOR IMAGE GUIDED MEDICAL PROCEDURES
Abstract
A system and method combines information from a plurality of
medical imaging modalities, such as PET, CT, MRI, MRSI, Ultrasound,
Echo Cardiograms, Photoacoustic Imaging and Elastography for a
medical image guided procedure, such that a pre-procedure image
using one of these imaging modalities, is fused with an
intra-procedure imaging modality used for real time image guidance
for a medical procedure for any soft tissue organ or gland such as
prostate, skin, heart, lung, kidney, liver, bladder, ovaries, and
thyroid, wherein the soft tissue deformation and changes between
the two imaging instances are modeled and accounted for
automatically.
Inventors: |
Kumar; Dinesh; (Roseville,
CA) ; Vohra; Amit; (Roseville, CA) ; Sperling;
Daniel S.; (West Orange, NJ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
CONVERGENT LIFE SCIENCES, INC. |
Los Angeles |
CA |
US |
|
|
Assignee: |
CONVERGENT LIFE SCIENCES,
INC.
Los Angeles
CA
|
Family ID: |
50233964 |
Appl. No.: |
13/835479 |
Filed: |
March 15, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61700273 |
Sep 12, 2012 |
|
|
|
Current U.S.
Class: |
600/414 ;
600/407; 600/426; 600/437 |
Current CPC
Class: |
A61B 34/10 20160201;
A61B 2090/365 20160201; A61B 2017/00274 20130101; A61B 10/00
20130101; A61B 34/20 20160201; A61B 2090/378 20160201; A61B 90/39
20160201; A61B 2090/364 20160201; A61B 2034/107 20160201; A61B
10/0241 20130101; A61B 90/361 20160201; A61B 10/02 20130101; A61B
18/20 20130101 |
Class at
Publication: |
600/414 ;
600/407; 600/426; 600/437 |
International
Class: |
A61B 19/00 20060101
A61B019/00 |
Claims
1. A method for combining information from plurality of medical
imaging modalities, comprising: acquiring a first volumetric image
using a first volumetric imaging modality of an anatomical region;
defining an elastic soft tissue model for at least a portion of the
anatomical region encompassed by the first volumetric image;
labeling features of the anatomical region based on at least the
first volumetric image and the soft tissue model, comprising at
least features of the anatomical region which are visualized by
both the first imaging modality and a second imaging modality, and
features of the anatomical region which are poorly visualized in
the second imaging modality; acquiring a second volumetric image of
the anatomical region using the second imaging modality comprising
a real time image; registering the features of the anatomical
region which are visualized by both the first imaging modality and
a second imaging modality, and the features of the anatomical
region which are poorly visualized in the second imaging modality,
with respect to the soft tissue model, such that the features of
the anatomical region which are visualized by both the first
imaging modality and a second imaging modality are linked,
compensating for at least one distortion of the portion of the
anatomical region between a first time of the first volumetric
image and a second time of the second volumetric image; and
presenting an output based on at least the features of the
anatomical region which are poorly visualized in the second imaging
modality in the real time image, compensated based on at least the
registered features and the soft tissue model.
2. The method according to claim 1, wherein the first imaging
modality comprises at least one selected from the group consisting
of positron emission tomography, computed tomography, magnetic
resonance imaging, magnetic resonance spectrography imaging,
photoacoustic imaging, high frequency ultrasound, and
elastography.
3. The method according to claim 1, wherein the anatomical region
comprises at least one organ selected from the group consisting of
prostate, skin, heart, lung, kidney, liver, bladder, ovaries, and
thyroid.
4. The method according to claim 1, wherein further comprising
acquiring a tissue sample from a location determined based on at
least the first imaging modality and the second imaging
modality.
5. The method according to claim 1, wherein further comprising
delivering a therapeutic intervention at a location determined
based on at least the first imaging modality and the second imaging
modality.
6. The method according to claim 5, wherein the therapeutic
intervention includes one or more selected from the group
consisting of laser ablation, radiofrequency ablation, high
intensity focused ultrasound, brachytherapy, stem cell injection
for ischemia of the heart, cryotherapy, direct injection of a
photothermal or photodynamic agent, and radiotherapy.
7. The method according to claim 1, further comprising performing
at least one image-guided at least partially automated procedure
selected from the group consisting of high intensity focused
ultrasound, IMRT, and robotic surgery.
8. The method according to claim 1, wherein the differentially
visualized anatomical region comprises at least one selected from
the group consisting of a suspicious lesion for targeted biopsy, a
suspicious lesion for targeted therapy, and a lesion for targeted
dose delivery.
9. The method according to claim 1, wherein the differentially
visualized anatomical region is at least one anatomical structure
to be spared in an invasive procedure, selected from the group
consisting of a nerve bundle, a urethra, a rectum and a
bladder.
10. The method according to claim 1, wherein the registered
features comprise at least one anatomical landmark selected from
the group consisting of a urethra, a urethra at a prostate base, a
urethra at an apex, a verumontanum, a calcification and a cyst, a
seminal vesicle, an ejaculatory duct, a bladder and a rectum.
11. The method according to claim 1, further comprising
automatically defining a plan comprising a target and an invasive
path to reach the target.
12. The method according to claim 11, wherein the plan is defined
based on the first imaging modality, and is adapted in real time
based on at least the second imaging modality.
13. The method according to claim 11, wherein the plan comprises a
plurality of targets.
14. The method according to claim 1, wherein a plurality of
anatomical features are consistently labeled in the first
volumetric image and the second volumetric image.
15. The method according to claim 1, wherein the soft tissue model
comprises an elastic triangular mesh approximating a surface of an
organ.
16. The method according to claim 1, wherein the anatomical
landmark registration is performed rigidly using a simultaneous
landmark and surface registration algorithm.
17. The method according to claim 16, further comprising performing
an affine registration.
18. The method according to claim 1, wherein the registering
comprises an elastic registration based on at least one parameter
selected from the group consisting of an intensity, a binary mask,
and surfaces and landmarks.
19. The method according to claim 1, wherein the model is derived
from a plurality of training datasets representing different states
of deformation of an organ of a respective human using the first
imaging modality and the second imaging modality.
20. The method according to claim 1, further comprising identifying
a mismatch of corresponding anatomical features of the first
volumetric image and the second volumetric image, and updating the
registration to converge the corresponding anatomical features to
reduce the mismatch based on corrections of an elastic deformation
model constrained by object boundaries.
21. A method for combining information from plurality of medical
imaging modalities, comprising: acquiring volumetric images using a
first volumetric imaging modality of an anatomical region of a
person under a plurality of states of deformation; acquiring
volumetric images using a second volumetric imaging modality of the
anatomical region of the person under a plurality of states of
deformation; defining an elastic soft tissue model for the
anatomical region comprising model parameters representing tissue
compliance and surface properties; labeling features of the
anatomical region based on at least the volumetric images of the
first imaging modality, the volumetric images of the second imaging
modality, and the soft tissue model, wherein the labeling aligns
corresponding features and compensates for rigid, elastic and
affine transform of the anatomical region between times for
acquiring the volumetric images of the first imaging modality and
the volumetric images of the second imaging modality; and
presenting an output based on at least the labeled features of the
anatomical region.
22. A system for combining information from plurality of medical
imaging modalities, comprising: an input port configured to receive
at least two first volumetric images using a first volumetric
imaging modality of an anatomical region representing respectively
different states of elastic deformation, and at least two second
volumetric images using a second volumetric imaging modality, of
the anatomical region representing respectively different states of
elastic deformation; at least one processor configured to define an
elastic soft tissue model for at least a portion of the anatomical
region encompassed by the first volumetric image, and to label
features of the anatomical region based on at least the first
volumetric image and the soft tissue model; and a memory configured
to store the defined elastic soft tissue model.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] The present application is a non-provisional of U.S.
Provisional Patent Application 61/691,758, filed Aug. 12, 2012, the
entirety of which is expressly incorporated herein by
reference.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] The present disclosure relates to systems and methods for
image guided medical and surgical procedures.
[0004] 2. Description of the Art
[0005] U.S. Pat Pub. 2009/0054772 (EP20050781862), expressly
incorporated herein by reference, entitled "Focused ultrasound
therapy system", provides a method for performing a High Intensity
Focused Ultrasound (HIFU) procedure for specific clinical
application. Basic image registration is performed for fusion from
a diagnostic modality such as Computed Tomography (CT) or Magnetic
Resonance Imaging (MRI) to ultrasound, only through body
positioning, referred to as "immobilization", resulting in only
image registration via horizontal movement and zoom factor. See
also U.S. Pat. No. 8,224,420, expressly incorporated herein by
reference, which provides a mechanical positioning means for moving
said ultrasound energy applicator to position the applicator so
that the energy application zone intersects said magnetic resonance
volume within said region of the subject.
[0006] U.S. Pub. Pat. 2007/0167762, expressly incorporated herein
by reference, entitled "Ultrasound System for interventional
treatment", provides an ultrasound system that can load a
"wide-area" image signal such as CT or MRI that can be loaded and
fused with the ultrasound image, using a manual definition of
position of lesions and needle insertion position at the time of
procedure.
[0007] U.S. Pub. App. 2010/02906853, expressly incorporated herein
by reference, entitled "Fusion of 3D volumes with CT
reconstruction" discloses a method for registration of ultrasound
device in three dimensions to a C-arm scan, the method including
acquiring a baseline volume, acquiring images in which ultrasound
device is disposed, locating the device within the images,
registering the location of the device to the baseline volume,
acquiring an ultrasound volume from the ultrasound device,
registering the ultrasound volume to the baseline volume, and
performing fusion imaging to display a view of the ultrasound
device in the baseline volume. Thus, a mutual information based
method is provided to register and display a 3D ultrasound image
fused with a CT image.
[0008] U.S. Pub. App. 2011/0178389, expressly incorporated herein
by reference, entitled "Fused image modalities guidance" discloses
a system and method for registration of medical images, which
registers a previously obtained volume(s) onto an ultrasound volume
during an ultrasound procedure, to produce a multimodal image,
which may be used to guide a medical procedure. In one arrangement,
the multimodal image includes MRI information presented in the
framework of a Trans Rectal Ultrasound (TRUS) image during a TRUS
procedure.
[0009] Prostate cancer is one of the most common types of cancer
affecting men. It is a slow growing cancer, which is easily
treatable if identified at an early stage. A prostate cancer
diagnosis often leads to surgery or radiation therapy. Such
treatments are costly and can cause serious side effects, including
incontinence and erectile dysfunction. Unlike many other types of
cancer, prostate cancer is not always lethal and often is unlikely
to spread or cause harm. Many patients who are diagnosed with
prostate cancer receive radical treatment even though it would not
prolong the patient's life, ease pain, or significantly increase
the patient's health.
[0010] Prostate cancer may be diagnosed by taking a biopsy of the
prostate, which is conventionally conducted under the guidance of
ultrasound imaging. Ultrasound imaging has high spatial resolution,
and is relatively inexpensive and portable. However, ultrasound
imaging has relatively low tissue discrimination ability.
Accordingly, ultrasound imaging provides adequate imaging of the
prostate organ, but it does not provide adequate imaging of tumors
within the organ due to the similarity of cancer tissue and benign
tissues, as well as the lack of tissue uniformity. Due to the
inability to visualize the cancerous portions within the organ with
ultrasound, the entire prostate must be considered during the
biopsy. Thus, in the conventional prostate biopsy procedure, a
urologist relies on the guidance of two-dimensional ultrasound to
systematically remove tissue samples from various areas throughout
the entire prostate, including areas that are free from cancer.
[0011] Magnetic Resonance Imaging (MRI) has long been used to
evaluate the prostate and surrounding structures. MRI is in some
ways superior to ultrasound imaging because it has very good soft
tissue contrast. There are several types of MRI techniques,
including T2 weighted imaging, diffusion weighted imaging, and
dynamic contrast imaging. Standard T2-weighted imaging does not
discriminate cancer from other processes with acceptable accuracy.
Diffusion-weighted imaging and dynamic contrast imaging may be
integrated with traditional T2-weighted imaging to produce
multi-parametric MRI. The use of multi-parametric MRI has been
shown to improve sensitivity over any single parameter and may
enhance overall accuracy in cancer diagnosis.
[0012] As with ultrasound imaging, MRI also has limitations. For
instance, it has a relatively long imaging time, requires
specialized and costly facilities, and is not well-suited for
performance by a urologist at a urology center. Furthermore,
performing direct prostate biopsy within MRI machines is not
practical for a urologist at a urology center.
[0013] To overcome these shortcomings and maximize the usefulness
of the MRI and ultrasound imaging modalities, methods and devices
have been developed for digitizing medical images generated by
multiple imaging modalities (e.g., ultrasound and MRI) and fusing
or integrating multiple images to form a single composite image.
This composite image includes information from each of the original
images that were fused together. A fusion or integration of
Magnetic Resonance (MR) images with ultrasound-generated images has
been useful in the analysis of prostate cancer within a patient.
Image-guided biopsy systems, such as the Artemis produced by Eigen
(See, e.g., U.S. Pub. App. Nos. 2012/0087557, 2011/0184684,
2011/0178389, 2011/0081057, 2010/0207942, 2010/0172559,
2010/0004530, 2010/0004526, 2010/0001996, 2009/0326555,
2009/0326554, 2009/0326363, 2009/0324041, 2009/0227874, and U.S.
Pat. Nos. 8,278,913, 8,175,350, 8,064,664, 7,942,829, 7,942,060,
7,875,039, 7,856,130, 7,832,114, and 7,804,989, expressly
incorporated herein by reference), and UroStation developed by
Koelis (see, e.g., U.S. Pub. App. Nos. 2012/0245455, 2011/0081063,
and U.S. Pat. No. 8,369,592, expressly incorporated herein by
reference), have been invented to aid in fusing MRI and ultrasonic
modalities. These systems are three-dimensional (3D) image-guided
prostate biopsy systems that provide tracking of biopsy sites
within the prostate.
[0014] Until now, however, such systems have not been adequate for
enabling MRI-ultrasound fusion to be performed by a urologist at a
urology center. The use of such systems for MRI-ultrasound fusion
necessarily requires specific MRI data, including MRI scans, data
related to the assessment of those scans, and data produced by the
manipulation of such data. Such MRI data, however, is not readily
available to urologists and it would be commercially impractical
for such MRI data to be generated at a urology center. This is due
to many reasons, including urologists' lack of training or
expertise, as well as the lack of time, to do so. Also, it is
uncertain whether a urologist can profitably implement an
image-guided biopsy system in his or her practice while
contemporaneously attempting to learn to perform MRI scans.
Furthermore, even if a urologist invested the time and money in
purchasing MRI equipment and learning to perform MRI scans, the
urologist would still be unable to perform the MRI-ultrasound
fusion because a radiologist is needed for the performance of
advanced MRI assessment and manipulation techniques which are
outside the scope of a urologist's expertise.
[0015] MRI is generally considered to offer the best soft tissue
contrast of all imaging modalities. Both anatomical (e.g., T.sub.1,
T.sub.2) and functional MRI, e.g. dynamic contrast-enhanced (DCE),
magnetic resonance spectroscopic imaging (MRSI) and
diffusion-weighted imaging (DWI) can help visualize and quantify
regions of the prostate based on specific attributes. Zonal
structures within the gland cannot be visualized clearly on T.sub.1
images. However a hemorrhage can appear as high-signal intensity
after a biopsy to distinguish normal and pathologic tissue. In
T.sub.2 images, zone boundaries can be easily observed. Peripheral
zone appears higher in intensity relative to the central and
transition zone. Cancers in the peripheral zone are characterized
by their lower signal intensity compared to neighboring regions.
DCE improves specificity over T.sub.2 imaging in detecting cancer.
It measures the vascularity of tissue based on the flow of blood
and permeability of vessels. Tumors can be detected based on their
early enhancement and early washout of the contrast agent. DWI
measures the water diffusion in tissues. Increased cellular density
in tumors reduces the signal intensity on apparent diffusion
maps.
[0016] The use of imaging modalities other than trans-rectal
ultrasound (TRUS) for biopsy and/or therapy typically provides a
number of logistic problems. For instance, directly using MRI to
navigate during biopsy or therapy can be complicated (e.g.
requiring use of nonmagnetic materials) and expensive (e.g., MRI
operating costs). This need for specially designed tracking
equipment, access to an MRI machine, and limited availability of
machine time has resulted in very limited use of direct MRI-guided
biopsy or therapy. CT imaging is likewise expensive and has limited
access, and poses a radiation risk for operators and patient.
[0017] Accordingly, one known solution is to register a
pre-acquired image (e.g., an MRI or CT image), with a 3D TRUS image
acquired during a procedure. Regions of interest identifiable in
the pre-acquired image volume may be tied to corresponding
locations within the TRUS image such that they may be visualized
during/prior to biopsy target planning or therapeutic application.
This solution allows a radiologist to acquire, analyze and annotate
MRI/CT scan at the image acquisition facility while a urologist can
still perform the procedure using live ultrasound in his/her
clinic.
[0018] Consequently, there exists a need for improved systems and
methods for performing image fusion for image-guided medical
procedures.
SUMMARY
[0019] The present technology provides a method for combining
information from plurality of medical imaging modalities, such as
positron Emission Tomography (PET), Computed Tomography (CT),
Magnetic Resonance Imaging (MRI), Magnetic Resonance Spectroscopic
Imaging (MRSI), Ultrasound, Echo Cardiograms and Elastography,
supplemented by information obtained in advance by at least one
other modality, which is properly registered to the real time image
despite soft tissue movement, deformation, or change in size.
Advantageously, the real time image is of a soft tissue organ or
gland such as prostate, skin, heart, lung, kidney, liver, bladder,
ovaries, and thyroid, and the supplemented real time image is used
for a medical image guided procedure. The real time image may also
be used for orthopedic or musculoskeletal procedures, or exercise
physiology. A further real-time imaging type is endoscopy, or more
generally, videography, which is in growing use, especially for
minimally invasive procedures.
[0020] The medical procedure may be a needle based procedure, such
as but not limited to biopsy, laser ablation, brachytherapy, stem
cell injection for ischemia of the heart, cryotherapy, and/or
direct injection of a photothermal or photodynamic agent. In these
cases, for example, the medical professional seeks to treat a
highly localized portion of an organ, while either avoiding a toxic
or damaging therapy to adjacent structures, or to avoid waste of a
valuable agent. However, the available real-time medical imaging
modalities for guiding the localized treatment visualize the organ,
but do not clearly delineate the portion of the organ to be
treated. On the other hand, non-real time imaging modalities are
available for defining locations sought to be treated with the
localized treatment. In the case of soft tissues, in the time
between the non-real time imaging and the real time procedure, the
organ can shift, deform (especially as a result of the procedure
itself), or change in size, thus substantially distorting the
relationship between the real time image used to guide the
procedure and the non-real time diagnostic or tissue localization
image. A further complication is that the non-real time image may
have a different intrinsic coordinate system from the real time
imaging, leading to artifacts. Therefore, the present technology
seeks to address these issues by compensating for differences in
the patient's anatomy between acquisition of the non-real time
image and the real time procedure, using, for example, general
anatomical information, landmarks common to both images, and tissue
and procedure models.
[0021] Typical medical procedures comprise image-guided non-needle
based procedures such as but not limited to HIFU, IMRT, and robotic
surgery.
[0022] The pre-operative imaging modality may thus be used to a
identify target object or gland, and suspicious lesions of the
object or gland, for targeted biopsy, targeted therapy, targeted
dose delivery or a combination of the above.
[0023] The pre-operative imaging modality may be used to identify
and annotate surrounding structures that need to be spared in order
to minimize the impact of procedure on quality of life. In a
specific embodiment, in a prostate related procedure, such
structures may be nerve bundles, the urethra, rectum and bladder
identified in a magnetic resonance (MR) image.
[0024] The pre-operative imaging modality may be used to identify
and uniquely label anatomical landmarks for manual, semi-automated
or automated registration. In a specific embodiment, in a prostate
related procedure, such anatomical landmarks may be urethra at
prostate base, urethra at apex, verumontanum, calcifications and
cysts.
[0025] The pre-operative imaging modality may be used to identify
and uniquely label anatomical structures for manual, semi-automated
or automated registration. In a specific embodiment of the
invention, in a prostate related procedure, such structures may be
urethra, seminal vesicles, ejaculatory ducts, bladder and
rectum.
[0026] A targeted biopsy may be performed for a malignancy to
determine the extent of malignancy and best treatment option.
[0027] Needle guidance procedures may be provided where the
pre-operative imaging modality is analyzed to plan the complete
procedure or part of the procedure, such that anatomical locations
of targets for needle placement is planned in advance, and the
anatomical locations are guided by the real time imaging
modality.
[0028] The needle locations and trajectories may be identified in
advance based on the non-real time, pre-operative imaging modality,
such that the target region is adequately sampled for biopsy to
maximize the accuracy while minimizing number of samples for each
target region.
[0029] The needle locations and trajectories may be identified in
advance, such that a target region is effectively treated in a
therapeutic procedure within the target area, while minimizing the
damage to the surrounding tissue and structures. The trajectory may
be optimized in a prostate procedure such that the needle insertion
minimizes damage to important structures such as rectum and nerve
bundles.
[0030] The duration of needle placement at each location in a
therapeutic procedure may be optimized using a pre-operative
imaging modality, to effectively design a treatment for the target
region locally while sparing the surrounding tissues and
structures.
[0031] Anatomical landmarks and/or structures identified in
pre-operative image may also identified in the intra-operative
(live) image and labeled consistently. The pre-operative image may
also identify surfaces and boundaries, which can be defied or
modeled as, for example, triangulated meshes. The surfaces may
represent the entire anatomical structure/object or a part thereof.
In some cases, a boundary may have no real anatomical correlate,
and be defined virtually; however, an advantage arises if the
virtual boundary can be consistently and accurately identified in
both the pre-operative imaging and the real-time inter-operative
imaging, since the facilitates registration and alignment of the
images. The virtual features of the images may be based on generic
anatomy, e.g., of humans or animals, or patient-specific. Labeled
surfaces and landmarks in pre-operative and intra-operative images
may be used for rigid registration. In a specific embodiment, if
the bladder is labeled as "1" in pre-operative image, it is
registered with object labeled "1" in intra-operative image. More
generally, regions on an image are classified or segmented, and
that classification or segment definition from the pre-operative
imaging is applied to the inter-operative real time imaging.
[0032] There may be a plurality of landmarks and objects that are
registered concurrently. In a specific embodiment for prostate
procedures, if the bladder, prostate, rectum, urethra and seminal
vesicles are labeled "1", "2", "3", "4" and "5", respectively, they
intra-operative image employs the same labels to concurrently
register the corresponding objects. The correspondence may be
"hard-correspondence" or "soft-correspondence", i.e., the landmarks
may have absolute correspondence or a "fuzzy" correspondence. The
availability of "soft-correspondence" permits or facilitates
automated or semi-automated labeling of objects, since the
real-time imaging is typically not used by a fully automated system
to perform a procedure, and the skilled medical professional can
employ judgment, especially if the labeling indicates a possible
degree of unreliability, in relying on the automated labeling.
Thus, a urologist in a prostate procedure can review the fused
image in real time to determine whether there is sufficient
consistency to proceed and rely on the pre-operative imaging
information, or whether only the inter-operative real-time imaging
is to be employed. Likewise, in some cases the pre-operative
imaging labeling boundaries are imprecise, and therefore that the
medical professional might wish to treat such boundaries as being
advisory and not absolute.
[0033] The landmark and object registration may be performed
rigidly using a simultaneous landmark and surface registration
algorithm. A rigid registration may be optionally followed by an
affine registration. An elastic registration method may follow the
rigid or affine registration. An elastic registration method may be
at least one of intensity based, binary mask based, surfaces- and
landmarks-based method or a combination of these methods. A
deformation model may be computed from a number of training
datasets is used for image registration. The deformation model
models the deformation of the object of interest, for example, a
prostate goes through deformation upon application of an external
tool such as ultrasound transducer or endo-rectal coil. The
training datasets may include sets of corresponding planning images
and live modality images for same patient. Thus, one aspect of the
technology provides that pre-operative imaging is obtained under
conditions that model a soft tissue deformation that might occur
during the real-time imaging. The correspondence may be further
refined by identifying and defining mismatching corresponding
features between the pre-procedure and intra-procedure images. In a
specific embodiment, in a prostate, a calcification may be seen in
both MRI (pre-procedure) and ultrasound (inter-procedure) images,
and if these anatomical landmarks mismatch slightly, a user may
identify these landmarks visually and select them by click of a
mouse; alternately, an automated indication of mismatch may be
generated. An algorithm can then refine the correspondence such
that the boundaries of the object of interest do not move while the
deformation inside the object gets updated. The deformation inside
the object of interest may thus follow an elastic deformation model
based on the new landmarks constrained by object boundaries.
[0034] An image registration method may therefore be provided that
maps a region of interest from a pre-procedural (planning) image to
an intra-procedural (live) image, along with a complete plan such
that the plan and the region of interest are mapped and deformed to
conform to the shape of the object during the procedure.
[0035] The technology provides a method of image, fusion where the
mapped plan may be displayed as one or more overlays on a live
imaging modality display during an image guided procedure. In some
cases, the fusion need not be an overlay, and may be supplemental
information through a different modality, such as voice or sonic
feedback, force-feedback or proprioceptive feedback, a distinct
display (without overlay), or the like. In the case of an overlay,
different types of information may be distinguished by color,
intensity, depth (on a stereoscopic display), icons, or other known
means. The plan may be indicated by static images or graphics,
animated graphics, and/or acoustic information (e.g., voice
synthesis feedback).
[0036] A planning image can also be overlaid on the live imaging
modality during an image guided procedure such that the images can
be toggled back and forth, or displayed together in a real-time
"fused" display.
[0037] The mapped plan may be further adjusted to account for a new
shape of object revealed during real-time imaging. This may be done
using an automated method, semi-automatic method, or manual method
or a combination thereof.
[0038] A pre-procedure planning image may be used to plan the
procedure such that the plan is embedded in an electronic, printed,
or interactive web-based report.
[0039] The present technology identifies imaging modalities clearly
including landmarks, objects and intensity information, to perform
registration using a combination of rigid, affine and non-rigid
elastic registration.
[0040] The modeling of the objects within an image may thus
comprise a segmentation of anatomical features.
[0041] The method may further comprise transforming coordinate
systems of various imaging modalities. The system may further
comprise at least one modeling processor configured to perform
real-time model updates of a patient soft-tissue to ensure that a
pre-operative image remains accurately registered with an
intra-operative image.
[0042] The annotated regions of the medical imaging scan or the
plan may be generated by a computer-aided diagnosis or therapeutic
planning system. At least apportion of the pre-operative imaging
may be conducted at a remote location from the therapeutic or
diagnostic procedure, and the information conveyed between the two
through the Internet, preferably over a virtual private network. A
true private network may also be used, or simply encrypted files
communicate over otherwise public channels. The physical separation
of the imaging modalities facilitates professional specialization,
since experts at different aspects of the process need not be
collocated.
[0043] The present technology permits porting information from a
planning image frame of reference to a live imaging modality for
guiding a medical procedure. The plan may be defined as a region of
interest and needle placement or a method to plan a treatment or
biopsy, for example.
[0044] The present technology may employ not only object
boundaries, but also surrounding or internal information for
registration, and thus is may be employed in applications where
there is significant internal deformation that cannot be modeled
using boundaries alone.
[0045] The phrase "image fusion" is sometimes used to define the
process of registering two images that are acquired via different
imaging modalities or at different time instances. The
registration/fusion of images obtained from different modalities
creates a number of complications. The shape of soft tissues in two
images may change between acquisitions of each image. Likewise, a
diagnostic or therapeutic procedure can alter the shape of the
object that was previously imaged. Further, in the case of prostate
imaging the frame of reference (FOR) of the acquired images is
typically different. That is, multiple MRI volumes are obtained in
high resolution transverse, coronal or sagittal planes
respectively, with lower resolution representing the slice
distance. These planes are usually in rough alignment with the
patient's head-toe, anterior-posterior or left-right orientations.
In contrast, TRUS images are often acquired while a patient lies on
his side in a fetal position by reconstructing multiple rotated
samples 2D frames to a 3D volume. The 2D image frames are obtained
at various instances of rotation of the TRUS probe after insertion
in to the rectal canal. The probe is inserted at an angle
(approximately 30-45 degrees) to the patient's head-toe
orientation. As a result the gland in MRI and TRUS will need to be
rigidly aligned because their relative orientations are unknown at
scan time. Typically, well-defined and invariant anatomical
landmarks may be used to register the images, though since the
margins of landmarks themselves vary with imaging modality, the
registration may be imperfect or require discretion in
interpretation. A further difficulty with these different
modalities is that the intensity of objects in the images do not
necessarily correspond. For instance, structures that appear bright
in one modality (e.g., MRI) may appear dark in another modality
(e.g., ultrasound). Thus, the logistical process of overlaying or
merging the images requires perceptual optimization. In addition,
structures identified in one image (soft tissue in MRI) may be
entirely absent in another image. TRUS imaging causes further
deformation of gland due to pressure exerted by the TRUS transducer
on prostate. As a result, rigid registration is not sufficient to
account for difference between MRI and TRUS images. Finally, the
resolution of the images may also impact registration quality.
[0046] Due to the FOR differences, image intensity differences
between MRI and TRUS images, and/or the potential for the prostate
to change shape between imaging by the MRI and TRUS scans, one of
the few known correspondences between the prostate images acquired
by MRI and TRUS is the boundary/surface model of the prostate. That
is, the prostate is an elastic object that has a gland boundary or
surface model that defines the volume of the prostate. By defining
the gland surface boundary in the dataset for each modality, the
boundary can then be used as a reference for aligning both images.
Thus, each point of the volume defined within the gland boundary of
the prostate in one image should correspond to a point within a
volume defined by a gland boundary of the prostate in the other
image, and vice versa.
[0047] In seeking to register the surfaces, the data in each data
set may be transformed, assuming elastic deformation of the
prostate gland. Thus, the characteristics of soft tissue under
shear and strain, compression, heating and/or inflammation,
bleeding, coagulation, biopsy sampling, tissue resection, etc., as
well as normal physiological changes for healthy and pathological
tissue, over time, are modeled, and therefore these various effects
accounted for during the pre-operative imaging and real-time
intraprocedural imaging.
[0048] According to a first aspect, a system and method is provided
for use in medical imaging of a prostate of a patient. The utility
includes obtaining a first 3D image volume from an MRI imaging
device. Typically, this first 3D image volume is acquired from data
storage. That is, the first 3D image volume is acquired at a time
prior to a current procedure. A first shape or surface model may be
obtained from the MRI image (e.g., a triangulated mesh describing
the gland). The surface model can be manually or automatically
extracted from all co-registered MRI image modalities. That is,
multiple MRI images may themselves be registered with each other as
a first step. The 3D image processing may be automated, so that a
technician need not be solely occupied by the image processing,
which may take seconds or minutes. The MRI images may be T.sub.1,
T.sub.2, DCE (dynamic contrast-enhanced), DWI (diffusion weighted
imaging), ADC (apparent diffusion coefficient) or other.
[0049] Similarly, data from other imaging modalities, e.g.,
computer aided (or axial) tomography (CAT) scans can also be
registered. In the case of a CAT scan, the surface of the prostate
may not represent a high contrast feature, and therefore other
aspects of the image may be used; typically, the CAT scan is used
to identify radiodense features, such as calcifications, or
brachytherapy seeds, and therefore the goal of the image
registration process would be to ensure that these features are
accurately located in the fused image model. A co-registered CT
image with PET scan can also provide diagnostic information that
can be mapped to TRUS frame of reference for image guidance.
[0050] In one embodiment, the pre-operative imaging comprises use
of the same imaging modality as used intra-operatively, generally
along with an additional imaging technology. Thus, an ultrasound
volume of the patient's prostate may be obtained, for example,
through rotation of a TRUS probe, and the gland boundary is
segmented in an ultrasound image. The ultrasound images acquired at
various angular positions of the TRUS probe during rotation can be
reconstructed to a rectangular grid uniformly through intensity
interpolation to generate a 3D TRUS volume. Of course, other
ultrasound methods may be employed without departing from the scope
of the technology. The MRI or CAT scan volume is registered to the
3D TRUS volume (or vice versa), and a registered image of the 3D
TRUS volume is generated in the same frame of reference (FOR) as
the MRI or CAT scan image. According to a preferred aspect, this
registration occurs prior to a diagnostic or therapeutic
intervention. The advantage here is that both data sets may be
fully processed, with the registration of the 3D TRUS volume
information completed. Thus, during a later real-time TRUS guided
diagnostic or therapeutic procedure, a fully fused volume model is
available. In general, the deviation of a prior 3D TRUS scan from a
subsequent one will be small, so features from the real-time scan
can be aligned with those of the prior imaging procedure. The fused
image from the MRI (or CAT) scan provides better localization of
the suspect pathological tissue, and therefore guidance of the
diagnostic biopsy or therapeutic intervention. Therefore, the
suspect voxels from the MRI are highlighted in the TRUS image,
which during a procedure would be presented in 2D on a display
screen to guide the urologist. The process therefore seeks to
register 3 sets of data; the MRI (or other scan) information, the
pre-operative 3D TRUS information, and the real time TRUS used
during the procedure. Ideally, the preoperative 3D TRUS and the
inter-operative TRUS are identical apparatus, and therefore would
provide maximum similarity and either minimization of artifacts or
present the same artifacts. Indeed, the 3D TRUS preoperative scan
can be obtained using the same TRUS scanner and immediately
pre-operative, though it is preferred that the registration of the
images proceed under the expertise of a radiologist or medical
scanning technician, who may not be immediately available during
that period.
[0051] A plan may be defined manually, semi-automatically, or in
certain cases, automatically. The plan, for example in a prostate
biopsy procedure, defines both the location of the samples to be
acquired, as well as the path to be taken by the biopsy instrument
in order to avoid undue damage to tissues. In some cases, the plan
may be updated in real-time. For example, if the goal of the plan
is to sample a volume of tissue on 1.5 mm spatial distances, but
the accuracy of sampling is .+-.0.5 mm, then subsequent sampling
targets may be defined adaptively based on the actual sampling
location during the procedure. Likewise, in laser therapy, the
course of treatment, including both the location of the laser and
its excitation parameters, may be determined based on both the
actual location of a fiber optic tip, as well as a measured
temperature, and perhaps an inter-operatively determined
physiological response to the therapy, such as changes in
circulation pattern, swelling, and the like.
[0052] The registered image and the geometric transformation that
relates, for example, a MRI scan volume with an ultrasound volume
can be used to guide a medical procedure such as, for example,
biopsy or brachytherapy.
[0053] These regions of interest identified on the MRI scan are
usually defined by a radiologist based on information available in
MRI prior to biopsy, and may be a few points, point clouds
representing regions, or triangulated meshes. Likewise, the 3D TRUS
may also reveal features of interest for biopsy, which may also be
marled as regions of interest. Because of the importance of
registration of the regions of interest in the MRI scan with the
TRUS used intra-operatively, in a manual or semiautomated
pre-operative image processing method, the radiologist can override
or control the image fusion process according to his or her
discretion.
[0054] In a preferred embodiment, a segmented MRI and 3D TRUS is
obtained from a patient for the prostate grand. The MRI and TRUS
data is registered and transformations applied to form a fused
image in which voxels of the MRI and TRUS images physically
correspond to one another. Regions of interest are then identified
either from the source images or from the fused image. The regions
of interest are then communicated to the real-time ultrasound
system, which tracks the earlier TRUS image. Because the ultrasound
image is used for real time guidance, typically the
transformation/alignment takes place on the MRI data, which can
then be superposed or integrated with the ultrasound data.
[0055] During the procedure, the real-time TRUS display is
supplemented with the MRI (or CAT or other scan) data, and an
integrated display presented to the operating urologist. In some
cases, haptic feedback may be provided so that the urologist can
"feel" features when using a tracker.
[0056] It is noted that as an alternate, the MRI or CAT scan data
may be used to provide a coordinate frame of reference for the
procedure, and the TRUS image modified in real-time to reflect an
inverse of the ultrasound distortion. That is, the MRI or CAT data
typically has a precise and undistorted geometry. On the other hand
the ultrasound image may be geometrically distorted by phase
velocity variations in the propagation of the ultrasound waves
through the tissues, and to a lesser extent, by reflections and
resonances. Since the biopsy instrument itself is rigid, it will
correspond more closely to the MRI or CAT model than the TRUS
model, and therefore a urologist seeking to acquire a biopsy sample
may have to make corrections in course if guided by the TRUS image.
If the TRUS image, on the other hand, is normalized to the MRI
coordinate system, then such corrections may be minimized. This
requires that the TRUS data be modified according to the fused
image volume model in real time. However, modern graphics
processors (GPU or APU, multicore CPU, FPGA) and other computing
technologies make this feasible.
[0057] According to another aspect, the urologist is presented with
a 3D display of the patient's anatomy, supplemented by and
registered to the real-time TRUS data. Such 3D displays may be
effectively used with haptic feedback.
[0058] It is noted that two different image transformations are at
play; the first is a frame of reference transformation, due to the
fact that the MRI image is created as a set of slices in parallel
planes (rectangular coordinate system) which will generally differ
from the image plane of the TRUS, defined by the probe angle
(cylindrical coordinate system, with none of the cylindrical axes
aligned with a coordinate axis of the MRI). The second
transformation represents the elastic deformation of the objects
within the image to properly aligned surfaces, landmarks, etc.
[0059] The segmentation and/or digitizing may be carried out
semi-automatically (manual control over automated image processing
tasks) or automatically using computer software. One example of
computer software which may be suitable includes 3D Slicer
(www.slicer.org), an open source software package capable of
automatic image segmentation, manual editing of images, fusion and
co-registering of data using rigid and non-rigid algorithms, and
tracking of devices for image-guided procedures.
[0060] See, e.g. (each of which is expressly incorporated herein by
reference):
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[0062] See also U.S. Pat. Nos. 5,227,969; 5,299,253; 5,389,101;
5,411,026; 5,447,154; 5,531,227; 5,810,007; 6,200,255; 6,256,529;
6,325,758; 6,327,490; 6,360,116; 6,405,072; 6,512,942; 6,539,247;
6,561,980; 6,662,036; 6,694,170; 6,996,430; 7,079,132; 7,085,400;
7,171,255; 7,187,800; 7,201,715; 7,251,352; 7,266,176; 7,313,430;
7,379,769; 7,438,685; 7,520,856; 7,582,461; 7,619,059; 7,634,304;
7,658,714; 7,662,097; 7,672,705; 7,727,752; 7,729,744; 7,804,989;
7,831,082; 7,831,293; 7,850,456; 7,850,626; 7,856,130; 7,925,328;
7,942,829; 8,000,442; 8,016,757; 8,027,712; 8,050,736; 8,052,604;
8,057,391; 8,064,664; 8,067,536; 8,068,650; 8,077,936; 8,090,429;
8,111,892; 8,180,020; 8,135,198; 8,137,274; 8,137,279; 8,167,805;
8,175,350; 8,187,270; 8,189,738; 8,197,409; 8,206,299; 8,211,017;
8,216,161; 8,249,317; 8,275,182; 8,277,379; 8,277,398; 8,295,912;
8,298,147; 8,320,653; 8,337,434; and US Patent Application No.
2011/0178389, each of which is expressly incorporated herein by
reference.
[0063] It is therefore an object to provide a method for combining
information from plurality of medical imaging modalities,
comprising: acquiring a first volumetric image using a first
volumetric imaging modality of an anatomical region; defining an
elastic soft tissue model for at least a portion of the anatomical
region encompassed by the first volumetric image; labeling features
of the anatomical region based on at least the first volumetric
image and the soft tissue model, comprising at least features of
the anatomical region which are visualized by both the first
imaging modality and a second imaging modality, and features of the
anatomical region which are poorly visualized in the second imaging
modality; acquiring a second volumetric image of the anatomical
region using the second imaging modality comprising a real time
image; registering the features of the anatomical region which are
visualized by both the first imaging modality and a second imaging
modality, and the features of the anatomical region which are
poorly visualized in the second imaging modality, with respect to
the soft tissue model, such that the features of the anatomical
region which are visualized by both the first imaging modality and
a second imaging modality are linked, compensating for at least one
distortion of the portion of the anatomical region between a first
time of the first volumetric image and a second time of the second
volumetric image; and presenting an output based on at least the
features of the anatomical region which are poorly visualized in
the second imaging modality in the real time image, compensated
based on at least the registered features and the soft tissue
model.
[0064] It is also an object to provide a method for combining
information from plurality of medical imaging modalities,
comprising: acquiring volumetric images using a first volumetric
imaging modality of an anatomical region of a person under a
plurality of states of deformation; acquiring volumetric images
using a second volumetric imaging modality of the anatomical region
of the person under a plurality of states of deformation; defining
an elastic soft tissue model for the anatomical region comprising
model parameters representing tissue compliance and surface
properties; labeling features of the anatomical region based on at
least the volumetric images of the first imaging modality, the
volumetric images of the second imaging modality, and the soft
tissue model, wherein the labeling aligns corresponding features
and compensates for rigid, elastic and affine transform of the
anatomical region between times for acquiring the volumetric images
of the first imaging modality and the volumetric images of the
second imaging modality; and presenting an output based on at least
the labeled features of the anatomical region.
[0065] A further object provides a system for combining information
from plurality of medical imaging modalities, comprising: an input
port configured to receive at least two first volumetric images
using a first volumetric imaging modality of an anatomical region
representing respectively different states of elastic deformation,
and at least two second volumetric images using a second volumetric
imaging modality, of the anatomical region representing
respectively different states of elastic deformation; at least one
processor configured to define an elastic soft tissue model for at
least a portion of the anatomical region encompassed by the first
volumetric image, and to label features of the anatomical region
based on at least the first volumetric image and the soft tissue
model; and a memory configured to store the defined elastic soft
tissue model
[0066] The first imaging modality may comprise at least one of
positron emission tomography, computed tomography, magnetic
resonance imaging, magnetic resonance spectrography imaging, and
elastography. The anatomical region may comprise an organ selected
from the group consisting of prostate, heart, lung, kidney, liver,
bladder, ovaries, and thyroid. The therapeutic intervention may be
selected from one or more selected from the group consisting of
laser ablation, brachytherapy, stem cell injection for ischemia of
the heart, cryotherapy, direct injection of a photothermal or
photodynamic agent, and radiotherapy. The differentially visualized
anatomical region may be at least one anatomical structure to be
spared in an invasive procedure, selected from the group consisting
of a nerve bundle, a urethra, a rectum and a bladder. The
registered features may comprise anatomical landmarks selected from
the group consisting of a urethra, a urethra at a prostate base, a
urethra at an apex, a verumontanum, a calcification and a cyst, a
seminal vesicle, an ejaculatory duct, a bladder and a rectum.
[0067] The method may further comprise acquiring a tissue sample
from a location determined based on at least the first imaging
modality and the second imaging modality.
[0068] The method may further comprise delivering a therapeutic
intervention at a location determined based on at least the first
imaging modality and the second imaging modality.
[0069] The method may further comprise performing an image-guided
at least partially automated procedure selected from the group
consisting of laser ablation, high intensity focused ultrasound,
cryotherapy, radio frequency, brachytherapy, IMRT, and robotic
surgery.
[0070] The differentially visualized anatomical region may comprise
at least one of a suspicious lesion for targeted biopsy, a
suspicious lesion for targeted therapy, and a lesion for targeted
dose delivery.
[0071] The method may further comprise automatically defining a
plan comprising an target and an invasive path to reach the
target.
[0072] The plan may be defined based on the first imaging modality,
and is adapted in real time based on at least the second imaging
modality. The plan may comprise a plurality of targets.
[0073] A plurality of anatomical features may be consistently
labeled in the first volumetric image and the second volumetric
image. The soft tissue model may comprise an elastic triangular
mesh approximating a surface of an organ. The anatomical landmark
registration may be performed rigidly using a simultaneous landmark
and surface registration algorithm. An affine registration may be
performed. The registering may comprise an elastic registration
based on at least one of an intensity, a binary mask, and surfaces
and landmarks.
[0074] The model may be derived from a plurality of training
datasets representing different states of deformation of an organ
of a respective human using the first imaging modality and the
second imaging modality.
[0075] The method may further comprise identifying a mismatch of
corresponding anatomical features of the first volumetric image and
the second volumetric image, and updating the registration to
converge the corresponding anatomical features to reduce the
mismatch based on corrections of an elastic deformation model
constrained by object boundaries.
BRIEF DESCRIPTION OF THE DRAWINGS
[0076] FIG. 1 shows a typical workflow for a surgeon in using a
fusion platform for mapping plan from a pre-procedural planning
image to the intra-procedural live image;
[0077] FIG. 2 shows a method for rigid registration, in which
I.sub.1(x) and I.sub.2(x) represent the planning and live images,
respectively with x being the coordinate system, .OMEGA..sub.1,i
and .OMEGA..sub.2,i represent domains of the objects labeled in
images I.sub.1 and I.sub.2, respectively such that i=1, 2, 3, . . .
represent object labels 1, 2, 3, etc., and w.sub.i's are relative
weights for different costs and Sim(A,B) represents the similarity
cost between two objects A and B, and R represents the rigid
transformation matrix that includes rotation and translation in 3D
frame of reference;
[0078] FIG. 3 shows a method for affine registration, in which
I.sub.1(x) and I.sub.2(x) represent the planning and live images,
respectively with x being the coordinate system, .OMEGA..sub.1,i
and .OMEGA..sub.2,i represent domains of the objects labeled in
images I.sub.1 and I.sub.2, respectively such that i=1, 2, 3, . . .
represent object labels 1, 2, 3, etc., and w.sub.i's are relative
weights for different costs and Sim(A,B) represents the similarity
cost between two objects A and B;
[0079] FIG. 4 shows an object process diagram for non-rigid elastic
image registration, using rigid and/or affine registration as an
initialization, wherein multiple labeled objects are used to
compute the correspondence while satisfying the regularization
constraints;
[0080] FIG. 5 shows an object process diagram for planning a laser
ablation of the prostate gland, in which a radiologist/radiation
oncologist analyzes multiparametric MRI (mpMRI) images of a
prostate and plans the location of needle tip, trajectory and
duration of needle application; and
[0081] FIGS. 6A and 6B show a conceptual diagram for planning a
laser ablation of the prostate gland, in which FIG. 6A shows the
target lesion identified by an expert in sagittal and transverse
images, and FIG. 6B shows the plan for laser ablation in the two
orthogonal directions.
DESCRIPTION OF THE EMBODIMENTS
[0082] The present invention will be described with respect to a
process, which may be carried out through interaction with a user
or automatically. One skilled in the art will appreciate that
various types of imaging systems, including but not limited to MRI,
ultrasound, PET, CT, SPECT, X-ray, and the like may be used for
either pre-operative or intra-operative imaging, but that a
preferred scheme employs a fusion of MRI and/or CT and/or PET and
ultrasound imaging for the pre-operative imaging, and
trans-urethral ultrasound for intra-operative real time imaging in
a prostate diagnosis or therapeutic procedure.
[0083] According to an embodiment of the present technology, one or
more pre-procedure "planning" images are used to plan a procedure
and one or more intra-procedure "live" images used to guide the
procedure. For example, prostate biopsy and ablation is typically
done under ultrasound guidance. While speed of imaging and cost
make ultrasound an ideal imaging modality for guiding biopsy,
ultrasound images are insufficient and ineffective at identifying
prostate cancer. Multi-parametric MRI (mpMRI) has been shown to be
very sensitive and specific for identifying, localizing and grading
of prostate cancer. mpMRI consists of various protocols for MR
imaging including T2-weighted imaging, Diffusion-weighted imaging
(DWI), Dynamic contrast-enhanced (DCE) and MR Spectroscopic imaging
(MRSI). Radiologists are best placed at analyzing the MRI images
for detection and grading the prostate cancer. However, it remains
challenging to take the information from radiologists and present
to urologists or surgeons who use ultrasound as imaging method for
performing a biopsy. Likewise, MRI is ideal for identifying the
sensitive surrounding structures that must be spared in order to
preserve quality of life after the procedure.
[0084] Recent advances in clinical research and accurate ablation
have increased interest in focal ablation of the prostate, where
the location of malignancy is known and the malignancy is treated
locally with the surroundings remaining intact. For example,
high-intensity focused ultrasound ablation of the prostate is
performed under ultrasound guidance. However, due to limitations of
ultrasound, it is hard to correlate the findings in pre-procedure
MRI with the intra-procedure ultrasound. As a result, a much larger
area is treated to ensure that the malignancy was treated properly.
In other words, most such users perform a "cognitive" registration,
i.e., use their own knowledge and interpretation of prostate
anatomy to guide such a procedure while using an ineffective
imaging method. The same challenge applies in robotic surgery where
the nerve bundles are not seen very clearly under live optical
imaging. As a result, nerve sparing remains a challenge in robotic
surgery. Again, MR imaging provides the necessary information but
there are no insufficient tools available to apply that information
to a surgical method.
[0085] Although methods exist for performing MRI-TRUS image fusion,
the methods suffer from significant drawbacks. For example, Kumar
et al.'s method (see, U.S. Pub. App. 2010/02906853) uses a prostate
surface-based non-rigid image registration method. The method uses
only triangulated prostate boundaries as input to registration and
performs a point-wise image registration only at the surface
boundaries and then interpolates the information from boundaries to
inside the object. Significant drawbacks include lack of
information from surrounding structures, requiring significant
skills, knowledge and effort to provide a good manual image
registration between MRI and ultrasound, which is very challenging,
especially when surgeons are not very skilled at reading and
interpreting MR images. As a result, the results can be variable
since there can be significant difference in orientation and shape
of gland between MRI and transrectal ultrasound. In addition to
outside structures for orienting or rigidly registering the
prostate, the prostate internal structures and details are also
completely ignored. Therefore, any internal twisting, rotation or
non-rigid distortion is not accounted for, which may lead to poor
results especially when an endo-rectal coil is used in MRI. In
addition, the plan is mapped as a region of interest, leaving it up
to the surgeon to interpret how to properly sample a certain
region. Also, in case of misregistration, there is no way disclosed
to edit or refine the registration.
[0086] In a specific embodiment of the invention, for a fusion
guided biopsy procedure (see FIG. 2), the method plans location,
trajectory and depth of needle insertion optimized such that there
is maximum likelihood of sampling the malignancy while minimizing
number of biopsy cores.
[0087] FIG. 2 shows a method according to the present technology
for rigid registration. In FIG. 2, I.sub.1(x) and I.sub.2(x)
represent the planning and live images, respectively with x being
the coordinate system. .OMEGA..sub.1,i and .OMEGA..sub.2,i
represent domains of the objects labeled in images I.sub.1 and
I.sub.2, respectively such that i=1, 2, 3, . . . represent object
labels 1, 2, 3, etc. For example, i=1, 2 and 3 may correspond to
prostate, bladder and rectum, respectively. w.sub.i's are relative
weights for different costs and Sim(A,B) represents the similarity
cost between two objects A and B. For example, for intensity based
metrics, the cost could be sum of the squared intensity differences
or a mutual information based metric, in case of binary objects,
the cost may be relative overlap. In case of surfaces, the cost
could be a symmetric distance between corresponding points. R
represents the rigid transformation matrix that includes rotation
and translation in 3D frame of reference.
[0088] Likewise, in another embodiment for a fusion guided focal
ablation (see FIG. 3), the needle placement is computed in advance
such that the computed location, depth and trajectory maximize
dosage/energy delivery at the malignancy while minimizing exposure
to surrounding region.
[0089] FIG. 3 shows a method for affine registration. In FIG. 3,
I.sub.1(x) and I.sub.2(x) represent the planning and live images,
respectively with x being the coordinate system. .OMEGA..sub.1,i
and .OMEGA..sub.2,i represent domains of the objects labeled in
images I.sub.1 and I.sub.2, respectively such that i=1, 2, 3, . . .
represent object labels 1, 2, 3, etc. For example, i=1, 2 and 3 may
correspond to prostate, bladder and rectum, respectively. w.sub.i's
are relative weights for different costs and Sim(A,B) represents
the similarity cost between two objects A and B. For example, for
intensity based metrics, the cost could be sum of squared intensity
differences or a mutual information based metric, in case of binary
objects, the cost may be relative overlap. In case of surfaces, the
cost could be symmetric distance between corresponding points. A
represents the affine transformation matrix that registers image
I.sub.1 to frame of reference of image I.sub.2.
[0090] The procedure is preferably performed under intra-procedural
image guidance, with the information from pre-procedure mapped to
an intra-procedure image using a combination of rigid, affine and
elastic registration, as shown in FIG. 4, which shows an object
process diagram for non-rigid elastic image registration using
rigid and/or affine registration as an initialization. The method
uses multiple labeled objects to compute the correspondence while
satisfying the regularization constraints. During the procedure,
the surgeon identifies the same landmarks, features and structures
as the pre-procedure image and labels them consistently. This may
be done automatically or manually after acquiring an initial
intra-procedural scan. The registration method then uses the labels
in pre-procedure and intra-procedure images to identify the
structural correspondence and registers the images using a
combination of rigid, affine and elastic registration.
[0091] According to the algorithm detailed in FIG. 4, two inputs
are provided: Rigid or rigid+ affine registered planning image
I.sub.1', having labeled objects .OMEGA..sub.1,i' for i.gtoreq.1,
and landmarks X.sub.j's for j.gtoreq.1; and Intra-operative
planning image I.sub.2, labeled objects .OMEGA..sub.2,i, and
landmarks, Y.sub.j's for ij.gtoreq.1.
The algorithm initializes T=I; perform an identity transformation;
Minimize with respect to T.sup.iter:
i w 1 , i x T iter ( .OMEGA. 1 , i ' ) .OMEGA. 2 , i .intg. sim ( T
iter ( I 1 ) ' , I 2 ) x + i w 3 , i x T iter ( .OMEGA. 1 , i ' )
.OMEGA. 2 , i .intg. Reg ( T iter ) x ; ##EQU00001##
Updated T based on intensity cost;
Minimize:
[0092] j w 2 , i sim ( T iter ( X j ' ) , Y j ) + i w 2 , j Reg ( T
iter ) ; ##EQU00002##
Update T.sup.iter based on landmarks; If convergence,
[0093] Transform T=T.sup.iter
[0094] Registered image T(I.sub.1'),
[0095] Output mapped plan and labeled objects
If no convergence, iterate minimizations.
[0096] There are two different methods to perform the
registrations: use the landmarks and features as
"soft-correspondence" or "hard-correspondence" points and the
structures as binary images, as shown in FIG. 5, which shows an
object process diagram for planning a laser ablation of the
prostate gland. A radiologist/radiation oncologist performs
analysis of mpMRI images of prostate and plans the location of
needle tip, trajectory and duration of needle application. The
landmarks and features are used as "soft-landmarks" or
"hard-landmarks" points and the structures as surface meshes (FIG.
6). "Soft-landmarks" represent the landmarks that may not
correspond exactly with each other and there may be some tolerance
or level of confidence that will be refined during registration.
"Hard-landmarks" refer to landmarks that are assumed to match
exactly and their correspondence is not allowed to change during
registration.
[0097] FIGS. 6A and 6B show a conceptual diagram for planning a
laser ablation of the prostate gland. FIG. 6A shows the target
lesion identified by an expert in sagittal and transverse images.
FIG. 6B shows the plan for laser ablation in the two orthogonal
directions. A and B represent the planned needles, which ablate the
area shown in hatched lines. The ablated area covers the planned
target.
[0098] The registration provides a surgeon with image fusion such
that the information from pre-procedure or planning images is
mapped to the frame of reference of the intra-procedure or live
images. The mapped information contains at least one structural
image, target area to be treated and a plan for the procedure. The
plan may be in the form of needle location and trajectory along
with the duration of needle application, if needed.
[0099] FIG. 1 shows the overall workflow of a surgeon, where the
images planned by an expert (radiologist/radiation oncologist) are
fused with a live imaging modality such as ultrasound for real-time
guidance while taking advantage of diagnostic capabilities of the
pre-procedural planning image. The pre-procedure image is
registered with the live image using a combination of rigid, affine
and non-rigid elastic registration. The registration provides a
correspondence or a deformation map, which is used to map planning
information from the frame of reference of the planning image to
the live image. The method permits a radiologist, radiation
oncologist or an oncological image specialist to analyze
pre-operative images, identify and label various structures
including the objects of interest, say the prostate from the above
detailed examples. The structures identified and labeled by the
imaging specialist could include external and internal structures
and landmarks such as bladder, urethra, rectum, seminal vesicles,
nerve bundles, fibromuscular stroma and prostate zones. These
structures are identified and stored as either points, binary masks
or surface meshes. Each such structure is labeled uniquely. In
addition, the method includes an automatically (or
semi-automatically) generated plan for the entire procedure.
[0100] FIGS. 2, 3 and 4 represent the rigid, affine and non-rigid
elastic registration methods. An expert or a computer algorithm
identifies and labels various anatomical structures and landmarks
in the planning image. Let image I.sub.1(x) represent the
structural planning image. In one embodiment, the structural image
could be a T2-weighted transversally acquired MRI image. The
subscript 1 corresponds to the planning or pre-procedural image.
Let .OMEGA..sub.1,i represent the object labeled i, where i=1, 2,
3, . . . represent a unique label for an anatomical object. For
example, if bladder is labeled as 1 in planning image,
.OMEGA..sub.1,1 consists of all the voxels corresponding to bladder
in the image I.sub.1. Alternatively, objects may also be
represented by surfaces, in which case, the objects will consist of
the vertices and triangles joining the vertices. Let X.sub.i
represent the point landmarks in the planning image, where i=1, 2,
3, . . . represents the index of the point landmarks identified in
the planning image either manually or using an automated method. In
addition, the expert provides the plan for a procedure on the
structural image.
[0101] During the procedure, a surgeon loads the planning image
I.sub.1 along with the object labels or surface meshes, landmarks
and the plan. The planning image I.sub.1 is projected to the
intra-procedure image I.sub.2 acquired during the procedure. The
labels and landmarks may be defined in the image I.sub.2 either
manually or automatically. In one embodiment, the labels in the
target image I.sub.2 are automatically computed by letting the
planning image I.sub.1 deform to the shape of the target image
I.sub.2. The object maps defined in planning image also participate
in the registration such that segmentation (object labeling) and
registration (computation of correspondence) happens at the same
time in the target image.
[0102] FIG. 4 shows one way of performing the registration between
the pre-procedure planning image and the intra-operative image. The
method uses the object maps along with the intensity information
and the landmark correspondences to compute the correspondence
between the images. The resulting deformation map is used to map
the plan from frame of reference of the planning image to the
intra-procedural image.
[0103] FIGS. 5, 6A and 6B represent an embodiment where the plan is
a needle-based laser ablation plan. In this embodiment, the
radiologist or radiation oncologist analyses the MRI image and
automatically or manually computes a target region along with
labeling the surrounding sensitive tissue, i.e., the safety zone.
The automated method embedded in the current method computes the
trajectory, location, energy settings and the duration of
application of laser such that the target region is completely
ablated while the safety zone is spared.
[0104] MRI data, which may include post-segmented MR image data,
pre-segmented interpreted MRI data, the original MRI scans,
suspicion index data, and/or instructions or a plan, may be
communicated to a urologist, The MRI data may be stored in a DICOM
format, in another industry-standard format, or in a proprietary
format unique to the imaging modality or processing platform
generating the medical images.
[0105] The urology center where the MRI data is received may
contain an image-guided biopsy or therapy system such as the
Artemis, UroStation (Koelis, La Tronche, France), or BiopSee
(MedCom GmbH, Darmstadt, Germany). Alternatively, the image-guided
biopsy system may comprise hardware and/or software configured to
work in conjunction with a urology center's preexisting hardware
and/or software. For example, a mechanical tracking arm may be
connected to a preexisting ultrasound machine, and a computer
programmed with suitable software may be connected to the
ultrasound machine or the arm. In this way, the equipment already
found in a urology center can be adapted to serve as an
image-guided biopsy system of the type described in this
disclosure. A tracking arm on the system may be attached to an
ultrasound probe and an ultra sound scan is performed.
[0106] A two-dimensional (2-D) or 3D model of the prostate may be
generated using the ultrasonic images produced by the scan, and
segmentation of the model may be performed. Pre-processed
ultrasound image data and post-processed ultrasound image data may
be transmitted to the urology center. Volumetry may also be
performed, including geometric or planimetric volumetry.
Segmentation and/or volumetry may be performed manually or
automatically by the image guided biopsy system. Preselected biopsy
sites (e.g., selected by the radiologist during the analysis) may
be incorporated into and displayed on the model. All of this
ultrasound data generated from these processes may be
electronically stored on the urology center's server via a
communications link.
[0107] As described above, processing of the MRI data or ultrasound
data, including segmentation and volumetry, may be carried out
manually, automatically, or semi-automatically. This may be
accomplished through the use of segmentation software, such as
Segasist Prostate Auto-Contouring, which may be included in the
image-guided biopsy system. Such software may also be used to
perform various types of contour modification, including manual
delineation, smoothing, rotation, translation, and edge snapping.
Further, the software is capable of being trained or calibrated, in
which it observes, captures, and saves the user's contouring and
editing preferences over time and applies this knowledge to contour
new images. This software need not be hosted locally, but rather,
may be hosted on a remote server or in a cloud computing
environment. At the urology center, MRI data may be integrated with
the image-guided biopsy system.
[0108] The fusion process may be aided by the use of the
instructions included with the MRI data. The fusion process may
include registration of the MR and ultrasonic images, which may
include manual or automatic selection of fixed anatomical landmarks
in each image modality. Such landmarks may include the base and
apex of the prostatic urethra. The two images may be substantially
aligned and then one image superimposed onto the other.
Registration may also be performed with models of the regions of
interest. These models of the regions of interest, or target areas,
may also be superimposed on the digital prostate model.
[0109] The fusion process thus seeks to anatomically align the 3D
models obtained by the radiological imaging, e.g., MRI, with the 3D
models obtained by the ultrasound imaging, using anatomical
landmarks as anchors and performing a warping of at least one of
the models to confirm with the other. The radiological analysis is
preserved, such that information from the analysis relevant to
suspicious regions or areas of interest are conveyed to the
urologist. The fused models are then provided for use with the
real-time ultrasound system, to guide the urologist in obtaining
biopsy samples or performing a therapeutic procedure.
[0110] Through the use of the described methods and systems, the 3D
MR image is integrated or fused with real-time ultrasonic images,
based on a 3D ultrasound model obtained prior to the procedure
(perhaps immediately prior). This allows the regions of interest to
be viewed under real-time ultrasonic imaging so that they can be
targeted during biopsy or therapy.
[0111] In this way, biopsy tracking and targeting using image
fusion may be performed by the urologist for diagnosis and
management of prostate cancer. Targeted biopsies may be more
effective and efficient for revealing cancer than non-targeted,
systematic biopsies. Such methods are particularly useful in
diagnosing the ventral prostate gland, where malignancy may not
always be detected with biopsy. The ventral prostate gland, as well
as other areas of the prostate, often harbor malignancy in spite of
negative biopsy. Targeted biopsy addresses this problem by
providing a more accurate diagnosis method. This may be
particularly true when the procedure involves the use of multimodal
MRI. Additionally, targeting of the suspicious areas may reduce the
need for taking multiple biopsy samples or performing saturation
biopsy.
[0112] The described methods and systems may also be used to
perform saturation biopsy. Saturation biopsy is a multicore biopsy
procedure in which a greater number of samples are obtained from
throughout the prostate than with a standard biopsy. Twenty or more
samples may be obtained during saturation biopsy, and sometimes
more than one hundred. This procedure may increase tumor detection
in high-risk cases. However, the benefits of such a procedure are
often outweighed by its drawbacks, such as the Inherent trauma to
the prostate, the higher incidence of side effects, the additional
use of analgesia or anesthesia, and the high cost of processing the
large amount of samples. Through use of the methods and systems of
the current invention, focused saturation biopsy may be performed
to exploit the benefits of a saturation biopsy while minimizing the
drawbacks. After target areas suspicious of tumor are identified, a
physician may sample four or more cores, all from the suspected
area. This procedure avoids the need for high-concentration
sampling in healthy areas of the prostate. Further, this procedure
will not only improve detection, but will enable one to determine
the extent of the disease.
[0113] These methods and systems of the current invention also
enable physicians to later revisit the suspected areas for
resampling over time in order to monitor the cancer's progression.
Through active surveillance, physicians can assess the seriousness
of the cancer and whether further treatment would be of benefit to
the patient. Since many prostate cancers do not pose serious health
threats, a surveillance program may often provide a preferable
alternative to radical treatment, helping patients to avoid the
risk of side effects associated with treatment.
[0114] In addition to MRI-ultrasound fusion, image-guided biopsy
systems such as the Artemis may also be used in accordance with the
current technology for performing an improved non-targeted,
systematic biopsy under 3D ultrasonic guidance. When using
conventional, unguided, systematic biopsy, the biopsy locations are
not always symmetrically distributed and may be clustered. However,
by attaching the image-guided biopsy system to an ultrasound probe,
non-targeted systematic biopsy may be performed under the guidance
of 3D ultrasonic imaging. This may allow for more even distribution
of biopsy sites and wider sampling over conventional techniques.
During biopsies performed using either MRI-ultrasound fusion or 3D
ultrasonic guidance, the image data may be used as a map to assist
the image-guided biopsy system in navigation of the biopsy needle,
as well as tracking and recording the navigation.
[0115] The process described above may further include making
treatment decisions and carrying out the treatment of prostate
cancer using the image-guided biopsy system. The current invention
provides physicians with information that can help them and
patients make decisions about the course of care, whether it be
watchful waiting, hormone therapy, targeted thermal ablation, nerve
sparing robotic surgery, or radiation therapy. While computed
tomography (CT) may be used, it can overestimate prostate volume by
35%. However, CT scans may be fused with MRI data to provide more
accurate prediction of the correct staging, more precise target
volume identification, and improved target delineation. For
example, MRI, in combination with biopsy, will enhance patient
selection for focal ablation by helping to localize clinically
significant tumor foci.
[0116] White ultrasound at low intensities is commonly used for
diagnostic and imaging applications, it can be used at higher
intensities for therapeutic applications due to its ability to
interact with biological tissues both thermally and mechanically.
Thus, a further embodiment of the current invention contemplates
the use of HIFU for treatment of prostate cancer in conjunction
with the methods and apparatus previously described. An example of
a commercially available HIFU system is the Sonablate 500 by Focus
Surgery, Inc. (Indianapolis, Ind.), which is a HIFU therapy device
that operates under the guidance of 3D ultrasound imaging. Such
treatment systems can be improved by being configured to operate
under the guidance of a fused MRI-ultrasound image.
[0117] During ablative therapy, temperatures in the tissue being
ablated may be closely monitored and the subsequent zone of
necrosis (thermal lesion) visualized, and used to update a
real-time tissue model. Temperature monitoring for the
visualization of a treated region may reduce recurrence rates of
local tumor after therapy. Techniques for the foregoing may include
microwave radiometry, ultrasound, impedance tomography, MRI,
monitoring shifts in diagnostic pulse-echo ultrasound, and the
real-time and in vivo monitoring of the spatial distribution of
heating and temperature elevation, by measuring the local
propagation velocity of sound through an elemental volume of such
tissue structure, or through analysis of changes in backscattered
energy. Other traditional methods of monitoring tissue temperature
include thermometry, such as ultrasound thermometry and the use of
a thermocouple.
[0118] MRI may also be used to monitor treatment, ensure tissue
destruction, and avoid overheating surrounding structures. Further,
because ultrasonic imaging is not always adequate for accurately
defining areas that have been treated, MRI may be used to evaluate
the success of the procedure. For instance, MRI may be used for
assessment of extent of necrosis shortly after therapy and for
long-term surveillance for residual or recurrent tumor that may
then undergo targeted biopsy. Thus, another aspect of the
technology provides post-operative image fusion, that is,
performing an imaging procedure after completion of an
interventional procedure, and fusing or integrating pre-operative
and/or intra-operative imaging data to help understand the
post-operative anatomy. For example, after aggressive therapy, a
standard anatomical model of soft tissue may no longer be accurate,
but by integrating the therapeutic intervention data, a more
accurate understanding, imaging, and image analysis may be
provided.
[0119] According to another aspect of the invention, a diagnostic
and treatment image generation system includes at least one
database containing image data from two different modalities, such
as MRI and ultrasound data, and an image-guided biopsy and/or
therapy system. The diagnostic and treatment image generation
system may also include a computer programmed to aid in the
transmission of the image data and/or the fusion of the data using
the image-guided biopsy system.
[0120] In accordance with yet another aspect of the present
invention, a computer readable storage medium has a non-transitory
computer program stored thereon, to control an automated system to
carry out various methods disclosed herein.
[0121] The present invention has been described in terms of the
preferred embodiment, and it is recognized that equivalents,
alternatives, and modifications, aside from those expressly stated,
are possible and within the scope of the invention.
* * * * *
References