U.S. patent application number 17/063383 was filed with the patent office on 2021-04-22 for predictive apparatus for assisting a physician during ophthalmic surgery.
The applicant listed for this patent is Alcon Inc.. Invention is credited to Michael J. Papac, Robert Joseph Sanchez, Jr..
Application Number | 20210113281 17/063383 |
Document ID | / |
Family ID | 1000005312741 |
Filed Date | 2021-04-22 |
United States Patent
Application |
20210113281 |
Kind Code |
A1 |
Papac; Michael J. ; et
al. |
April 22, 2021 |
PREDICTIVE APPARATUS FOR ASSISTING A PHYSICIAN DURING OPHTHALMIC
SURGERY
Abstract
A method and system assist a physician in performing an
ophthalmic surgery. The method includes receiving a quasi-real time
image of at least a first portion of the eye. The at least the
first portion of the eye includes an operating field for the
ophthalmic surgery. A recommended next region and a recommended
next procedure are determined based on the quasi-real time image
and a computational model of the eye. An expected next result for
the recommended next procedure is calculated using the quasi-real
time image and the computational model. The recommended next
region, the recommended next procedure and the expected result are
provided to the physician.
Inventors: |
Papac; Michael J.; (North
Tustin, CA) ; Sanchez, Jr.; Robert Joseph;
(Oceanside, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Alcon Inc. |
Fribourg |
|
CH |
|
|
Family ID: |
1000005312741 |
Appl. No.: |
17/063383 |
Filed: |
October 5, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15245328 |
Aug 24, 2016 |
10842573 |
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17063383 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 2034/2065 20160201;
A61B 2034/252 20160201; G16H 30/40 20180101; A61F 9/00736 20130101;
A61B 8/10 20130101; G16H 50/50 20180101; A61B 3/102 20130101; A61F
2009/00851 20130101; A61B 34/25 20160201 |
International
Class: |
A61B 34/00 20060101
A61B034/00; G16H 50/50 20060101 G16H050/50; G16H 30/40 20060101
G16H030/40; A61B 3/10 20060101 A61B003/10; A61B 8/10 20060101
A61B008/10; A61F 9/007 20060101 A61F009/007 |
Claims
1. A method for assisting a physician in performing an ophthalmic
surgery comprising: receiving a quasi-real time image of at least a
first portion of the eye, the at least the first portion of the eye
including an operating field for the ophthalmic surgery;
determining a recommended next region and a recommended next
procedure based on the quasi-real time image and a computational
model of the eye; calculating an expected next result for the
recommended next procedure using the quasi-real time image and the
computational model; and providing the recommended next region, the
recommended next procedure and the expected result to the
physician.
2. The method of claim 1 further comprising: receiving an initial
image of at least a second portion of the eye including the
operating field, the initial image including an initial region for
an initial procedure; calculating an initial expected result for
the initial procedure using the initial image; and providing the
initial expected result to the physician.
3. The method of claim 1 further comprising: iteratively repeating
the receiving, determining, calculating and providing steps after
the physician performs at least one procedure.
4. The method of claim 1 wherein the quasi-real time image includes
at least one of an optical coherence tomograph, an ultrasound
image, a high frequency ultrasound image, a ultrasound
biomicroscopy (UBM) image and a three-dimensional image.
5. The method of claim further comprising: capturing the quasi-real
time image.
6. The method of claim 5 wherein the step of capturing the
quasi-real time image takes not more than thirty minutes.
7. The method of claim 5 wherein the step of capturing the
quasi-real time image takes not more than ten minutes.
8. The method of claim 5 wherein the step of capturing the
quasi-real time image takes not more than one minute.
9. The method of claim 5 wherein the step of capturing the
quasi-real time image further includes: acquiring a plurality of
quasi-real time images at a plurality of intraocular pressures; and
wherein the step of determining the recommended next region and the
recommended next procedure further includes determining a stress
level at a plurality of regions based on the plurality of
quasi-real time images, a first portion of the plurality of regions
having a higher stress than a second portion of the plurality of
regions; and indicating the first portion of the plurality of
regions and the second portion of the plurality of regions.
10. The method of claim 1 wherein the computational model includes
mechanical properties of the eye.
11. The method of claim 1 wherein the ophthalmic surgery includes
epiretinal membrane (ERM) removal and the recommended next
procedure includes a recommended cut of the ERM.
12. A method for assisting a physician in performing an ophthalmic
surgery comprising: receiving an initial image of at least a first
portion of the eye including an operating field for the ophthalmic
surgery; providing an initial recommended procedure for an initial
recommended region; calculating an initial expected result for the
initial procedure using the initial image; providing the initial
expected result to the physician; after a physician has performed a
procedure, providing a quasi-real time image of at least a second
portion of the eye, the at least the second portion of the eye
including the operating field, the quasi-real time image including
at least one of an optical coherence tomograph, an ultrasound
image, a high frequency ultrasound image, a ultrasound
biomicroscopy (UBM) image and a three-dimensional image, the step
of providing the quasi-real time image occurring in-situ and
expending not more than ten minutes; determining a recommended next
region and a recommended next procedure based on the quasi-real
time image and a computational model of the eye; calculating an
expected next result for the recommended next procedure using the
quasi-real time image and the computational model; providing the
recommended next region, the recommended next procedure and the
expected result to the physician; and iteratively repeating the
quasi-real time image providing, recommended next region
determining, the expected next result calculating and the
recommended next region providing steps after the physician
performs at least one procedure.
13. A system for assisting a physician in performing ophthalmic
surgery comprising: a quasi real-time image capture unit for
providing a quasi-real time image of at least a first portion of
the eye including an operating field for the ophthalmic surgery,
the quasi-real time image capture unit capturing images of the eye
in an image capture time not exceeding ten minutes; a predictive
unit for determining a recommended next region and a recommended
next procedure based on the quasi-real time image and a
computational model of the eye, the predictive unit also for
calculating an expected next result for the recommended next
procedure using the quasi-real time image and the computational
model; and a user interface for providing the recommended next
region, the recommended next procedure and the expected result to
the physician.
14. The system of claim 13 wherein the quasi-real time image
capture unit also provides an initial image of at least a second
portion of the eye including the operating field, the initial image
including an initial region for an initial procedure; and the
predictive unit further calculates an initial expected result for
the initial procedure using the initial image and provides the
initial expected result to the physician.
15. The system of claim 13 wherein the quasi-real time image
includes at least one of an optical coherence tomograph, an
ultrasound image, a high frequency ultrasound image, a ultrasound
biomicroscopy (UBM) image and a three-dimensional image.
16. The system of claim 13 wherein the quasi-real time image is
captured in not more than one minute.
17. The system of claim 13 wherein the computational model includes
mechanical properties of the eye.
Description
BACKGROUND
[0001] The human eye sees by transmitting and refracting light
through a clear outer portion of the eye called the cornea,
focusing the light via a lens, transmitting the focused light
through the vitreal cavity and onto the retina. The quality of the
focused image depends on many factors including but not limited to
the size, shape and length of the eye, the quality of the vitreous
humor, and the shape and transparency of the cornea and lens.
Trauma, age, disease and/or another malady may cause an
individual's vision to degrade. The treatment for such conditions
includes ophthalmic surgery.
[0002] For example, changes in the vitreous cavity, either
spontaneous or due to disease, may cause epiretinal membrane (ERM)
growth within the vitreous cavity. The ERM may adversely affect
vision and pull on the retina. The retina may pucker and eventually
tear. In order to address this, ophthalmic surgery may be performed
to remove the ERM.
[0003] In order to perform an ERM removal, a physician may perform
a fundus exam by dilating and examining the eye. The physician may
also photograph or create a drawing of the eye during the exam.
Surgery may then be scheduled. The physician may prepare a surgical
plan based on the photograph and clinical notes from the exam. The
surgical plan indicates where in the vitreal cavity the ERM was
present during the exam and may note likely positions at which cuts
can be made to the ERM for removal. The physician may start the
surgery based in part on the surgical plan, and proceed based on
the current status of the patient.
[0004] Although the ophthalmic surgery may be performed, the status
of the eye may have changed significantly between the time of the
last clinical exam and the surgery. For example, for diabetic
retinopathy, there can be substantial progression of the disease in
the time between the last exam and the surgery. As a result, the
physician may need to make changes to the surgical plan on the fly.
In addition, the situation presented to the physician may be very
complex. Consequently, the starting point for the ERM removal or
other procedure and/or the next step in the procedure may be
difficult to determine.
[0005] Accordingly, what is needed is a mechanism for assisting a
physician in planning and carrying out surgery.
BRIEF SUMMARY OF THE INVENTION
[0006] A method and system assist a physician in performing an
ophthalmic surgery. The method includes receiving a quasi-real time
image of at least a first portion of the eye. The at least the
first portion of the eye includes an operating field for the
ophthalmic surgery. A recommended next region and a recommended
next procedure are determined based on the quasi-real time image
and a computational model of the eye. An expected next result for
the recommended next procedure is calculated using the quasi-real
time image and the computational model. The recommended next
region, the recommended next procedure and the expected result are
provided to the physician.
[0007] According to the method and system disclosed herein, a
physician may not only be provided with recommendations for next
procedures but also the expected results for the next procedures.
Consequently, a physician is better able to prepare for and perform
surgery.
BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS
[0008] FIG. 1 is a flow chart depicting an exemplary embodiment of
a method for assisting a physician during ophthalmic surgery using
quasi-real time image(s).
[0009] FIGS. 2A, 2B, 2C and 2D depict exemplary embodiments of
quasi-real time images of the eye including recommendations and
expected results of procedures.
[0010] FIG. 3 is a flow chart depicting an exemplary embodiment of
a method for assisting a physician during ophthalmic surgery using
quasi-real time image(s).
[0011] FIG. 4 is a block diagram of an exemplary embodiment of an
apparatus for assisting a physician during ophthalmic surgery using
quasi-real time image(s).
[0012] FIG. 5 is a flow chart depicting an embodiment of a method
500 for assisting a physician during ophthalmic surgery using
quasi-real time image(s).
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0013] The exemplary embodiments relate to mechanisms for assisting
physicians during surgeries including ophthalmic surgery. The
following description is presented to enable one of ordinary skill
in the art to make and use the invention and is provided in the
context of a patent application and its requirements. Various
modifications to the exemplary embodiments and the generic
principles and features described herein will be readily apparent.
The exemplary embodiments are mainly described in terms of
particular methods and systems provided in particular
implementations. However, the methods and systems will operate
effectively in other implementations. Phrases such as "exemplary
embodiment", "one embodiment" and "another embodiment" may refer to
the same or different embodiments as well as to multiple
embodiments. The embodiments will be described with respect to
systems and/or devices having certain components. However, the
systems and/or devices may include more or less components than
those shown, and variations in the arrangement and type of the
components may be made without departing from the scope of the
invention. Further, although specific blocks are depicted, various
functions of the blocks may be separated into different blocks or
combined. The exemplary embodiments will also be described in the
context of particular methods having certain steps. However, the
method and system operate effectively for other methods having
different and/or additional steps and steps in different orders
that are not inconsistent with the exemplary embodiments. Thus, the
present invention is not intended to be limited to the embodiments
shown, but is to be accorded the widest scope consistent with the
principles and features described herein.
[0014] The method and system are also described in terms of
singular items rather than plural items. For example, a quasi-real
time image, a recommended next region, a recommended next procedure
and an expected result are discussed. One of ordinary skill in the
art will recognize that these singular terms encompass plural. For
example, a quasi-real time image may include one or more quasi-real
time images, an expected result may include one or more expected
results, a recommended next procedure may include one or more
procedures, a next procedure may include one or more next
procedures and so on.
[0015] In certain embodiments, the system includes one or more
processors and a memory. The one or more processors may be
configured to execute instructions stored in the memory to cause
and control the process set forth in the drawings and described
below. As used herein, a processor may include one or more
microprocessors, field-programmable gate arrays (FPGAs),
controllers, or any other suitable computing devices or resources,
and memory may take the form of volatile or non-volatile memory
including, without limitation, magnetic media, optical media,
random access memory (RAM), read-only memory (ROM), removable
media, or any other suitable memory component. Memory may store
instructions for programs and algorithms that, when executed by a
processor, implement the functionality described herein with
respect to any such processor, memory, or component that includes
processing functionality. Further, aspects of the method and system
may take the form of an entirely hardware embodiment, an entirely
software embodiment (including firmware, resident software,
micro-code, etc.) or an embodiment combining software and hardware
aspects. Furthermore, aspects of the method and system may take the
form of a software component(s) executed on at least one processor
and which may be embodied in one or more computer readable
medium(s) having computer readable program code embodied
thereon.
[0016] A method and system assist a physician in performing an
ophthalmic surgery. The method includes receiving a quasi-real time
image of at least a first portion of the eye. This portion of the
eye includes an operating field for the ophthalmic surgery. A
recommended next region and a recommended next procedure are
determined based on the quasi-real time image and a computational
model of the eye. An expected next result for the recommended next
procedure is calculated using the quasi-real time image and the
computational model. The recommended next region, the recommended
next procedure and the expected result are provided to the
physician.
[0017] FIG. 1 is a flow chart depicting an exemplary embodiment of
a method 100 for assisting a physician during ophthalmic surgery
using quasi-real time image(s). For simplicity, some steps may be
omitted, interleaved, performed in another order and/or combined.
The method 100 may include executing instructions on one or more
processors. Further, the method 100 is described in the context of
ophthalmic surgery. However, the method 100 may be extended to
other types of surgery.
[0018] At least one quasi-real time image of at least a portion of
the eye is received, via step 102. Receipt of the image in step 102
may include receiving data for the image from a separate imaging
system or capturing the image by a portion of the system carrying
out the method 100. Step 102 need not include rendering the image
for the physician. Instead, step 102 includes obtaining data for
the eye. The quasi-real time image(s) are captured in situ. In
other words, the quasi-real time image(s) are captured in the
operating room. Further, quasi-real time images may include the
entire eye or a portion of the eye. However, the operating field in
which the physician desires to perform the next surgical procedure
is shown in the quasi-real time image(s). The quasi-real time
image(s) may include optical coherence tomograph(s) (OCTs),
ultrasound image(s), high frequency ultrasound image(s), ultrasound
biomicroscopy (UBM) image(s) and/or other image(s). Thus, as used
herein, the term image may refer to a quantitative scan. Thus, the
quasi-real time image may include the volume of the eye or simply a
cross-section of the eye. In some embodiments, video or other
mechanism for showing the progression of time may be part of the
quasi-real time image(s) received in step 102. Further, the
resolution of the imaging technique is sufficiently to allow the
physician to view the relevant features of the eye within the
operating field. The quasi-real time image is termed "quasi-real
time" because the procedures used to capture the images are
sufficiently fast to be performed during surgery. For example, in
some embodiments, the image may be provided in not more than thirty
minutes. In some such embodiments, capturing the image may be
completed in not more than ten minutes. In some embodiments,
capturing the quasi-real time image may require not more than one
minute.
[0019] As used herein, capturing an image may include any focusing
and/or other processes performed. For example, if the quasi-real
time image(s) are desired to indicate stress concentrations, then
step 102 may include obtaining multiple quasi-real time images
using optical coherence tomography (OCT) at different intraocular
pressures (IOPs) for the patient's eye. In some cases, an OCT image
of the eye is acquired at each IOP. Different IOPs may result in
different distortions for high stress regions than for low stress
regions. Further, thinning or tearing of particular components of
the eye may be better indicated at different IOPs. A single,
concatenating image or model of the eye indicating the high and low
stress regions may be formed as described below.
[0020] A recommended next region and a recommended next procedure
are determined based on the quasi-real time image(s) and a
computational model of the eye, via step 104. The computational
model of the eye may include data that are specific to the patient
as well as data characteristic of portions of eye. For example, the
quasi-real time image(s) received in step 102 or a pre-operation
image of the patient's eye may be used to determine sizes of
various components of the eye and/or expected locations of features
such as an ERM. Such data may be unique to the patient. The
computational model may also include mechanical properties of the
eye such as the tensile strength of certain tissue within the eye.
Such data may be characteristic to the tissue across different
patients. In some embodiments, a finite element analysis (FEM)
model of the eye may be generated and used as the computational
model of the eye.
[0021] As part of step 104, therefore, data for the quasi-real time
image(s) received in step 102 are processed. For example, the
stresses in particular regions may be determined from the
distortions seen in the quasi-real time image data at various IOPs.
Similarly, striations due to higher stress, fold marks, thinning,
tears and/or other issues in various regions may be determined
based on the data acquired and the computational model, which may
indicate how an eye is expected to behave.
[0022] Determination of the recommended next region and next
procedure in step 104 may include identifying regions of high
stress or other issues within the operating fields. For example,
step 104 may also include generating data for an arrow near tissue
under higher stress and/or near thinned tissue. Step 104 may also
include generating a visual model of the eye. For example, the one
color (e.g. red) may be selected for high stress regions or regions
near retinal tears and another color (e.g. blue) may be selected
for lower stress regions. Thus, regions which are more problematic
and/or are likely candidates for the next procedure are
determined.
[0023] In some embodiments, step 104 may include explicitly
determining a specific recommended procedure. However, in general,
the recommended procedure is known for the particular operation
underway. For example, for ERM removal, the next procedure is
typically cutting a section of the ERM. Thus, highlighting a region
of high stress may inherently indicate the next procedure (a
cut).
[0024] An expected next result for the recommended next procedure
is also calculated using the quasi-real time image and the
computational model, via step 108. For example, for ERM removal,
the next recommended procedure (a cut) at a particular, recommended
region releases stress in that region. The procedure may also
result in a release of the ERM in that location. Thus, step 108
includes using the computational model of the eye to determine the
reaction of surrounding tissue to a release of stress in that
region. For example, the ERM may be expected to move in a
particular direction. Step 108 models this response.
[0025] The recommended next region, the recommended next procedure
and the expected result are provided to the physician, via step
108. Portions of step 108 may be performed at different times. For
example, the recommended next region and recommended next procedure
may be performed by rendering the quasi-real time image or model
that is generated in step 104. For example, an arrow may be placed
near tissue under higher stress and/or near thinned tissue to
indicate the recommended next region and/or procedure.
Alternatively, the quasi-real time image may simply be rendered and
shown to the physician to allow the physician to analyze the image.
Step 108 may also include rendering the visual model of the eye
generated in step 104. For example, the image may render high
stress regions or regions near retinal tears in one color (e.g.
red) and lower stress regions in another color (e.g. blue). Thus,
regions which are more problematic and/or are likely candidates for
the next procedure are indicated. The surgeon may be shown a model
of the eye with particular high stress regions in a different color
or otherwise indicated. Providing the expected result to the
physician may be performed in response to input received. For
example, if a particular recommended region is selected, then the
expected result of performing the recommended procedure at that
region (which was calculated in step 106) is provided in step 108.
Step 108 may thus include rendering the model of the eye calculated
in step 106.
[0026] The output of method 100 may be seen, for example, via FIGS.
2A-2D. FIGS. 2A, 2B, 2C and 2D depict exemplary embodiments of
quasi-real time images and models of the eye 200 including
recommendations and expected results of procedures. FIGS. 2A-2D are
not to scale and for explanatory purposes only. Thus, a particular
patient, condition or response is not intended to be shown in FIGS.
2A-2D. FIG. 2A depicts an image 200 of the eye. The cornea 202,
lens 204, iris 206, pupil 208, vitreal cavity 210 and retina 220
are indicated for the purposes of explanation. Region 230 in the
vitreal cavity 210 may be an ERM, a region of high stress or other
issue. For the purposes of explanation, it is presumed that region
230 is an ERM 230. The image 200 may be or be part of a quasi-real
time image taken just before or at some time during surgery.
Alternatively, the image 200 may be a pre-operation image taken
previously that happens to continue to represent the condition of
the eye.
[0027] FIG. 5 is a flow chart depicting an embodiment of a method
500 for assisting a physician during ophthalmic surgery using
quasi-real time image(s). The method 500 includes acquiring a
plurality of quasi-real time images at a plurality of intraocular
pressures at a plurality of regions of an eye 502. Using a
plurality of intraocular pressures results in a varied degree in
distortions in the plurality of quasi-real time images and an
indication of a varied degree of stress concentrations in an eye
tissue. Next, the method 500 involves determining a stress level
for a plurality of regions based on the plurality of quasi-real
time images 504. In some cases, a first portion of the plurality of
regions has a higher stress than a second portion of the plurality
of regions. Next, the method 500 involves determining a recommended
next region to be the first portion and a recommended next
procedure to be treatment of epiretinal membrane (ERM) based on the
quasi-real time image and a computational model of the eye 506 and
calculating an expected next result for the recommended next
procedure to be a release in stress on a retinal tissue caused by
the ERM using the quasi-real time image and the computational model
508. The method 500 also involves displaying, on a graphical
display, the recommended next region, the recommended next
procedure and the expected result to the physician 510.
[0028] FIG. 2B depicts an image 200 of the eye with recommended
regions 232 and 234 indicated by arrows. The recommended regions
232 and 234 may be high stress regions and/or regions where the ERM
230 is pulling on the retina 220, The image 200 may be purely a
model or may be the image 200 shown in FIG. 2A with recommended
regions 232 and 234 highlighted. Because the ERM 230 is to be
removed, the recommended procedure (cutting the ERM 230) is
inherently known. The image 200' may be rendered on a graphical
display for the physician to view. In other embodiments, the
recommendations may be provided in another manner.
[0029] FIG. 2C depicts an image 200' or an expected result of the
recommended procedure for recommended region 232 being carried out.
Thus, the image 200' may be considered to be a model of the eye in
the event that a cut is made at the region 232. As can be seen, the
ERM 230' is modeled to shrink away from the region 232, change
shape and rotate. Other changes in shape and/or position might be
modeled for different stresses. The image 200' may be rendered on a
graphical display for the physician to view in response to the
physician selecting the region 232. In other embodiments, the
expected result may be provided in another manner.
[0030] FIG. 2C depicts an image 200'' or an expected result of the
recommended procedure for the recommended region 234 being carried
out. Thus, the image 200'' may be considered to be a model of the
eye in the event that a cut is made at the region 234. As can be
seen, the ERM 230'' is modeled to shrink away from the region 234,
change shape and rotate. Other changes in shape and/or position
might be modeled for different stresses. The image 200'' may be
rendered on a graphical display for the physician to view in
response to the physician selecting the region 234. In other
embodiments, the expected result may be provided in another
manner.
[0031] Using the method 100, a surgeon may be better able to
perform surgery on the eye. For example, just prior to surgery, the
method 100 may be used to provide up-to-date information on the eye
and indicate to the physician whether their surgical plan is still
appropriate. If not, the surgeon may opt to proceed in a different
manner. After one or more procedures (e.g. cuts) have been
performed as part of the surgery, the method 100 may be repeated.
Thus, the surgeon may determine whether the eye is responding as
expected and may be able to adjust for deviations made to the
surgical plan. The surgeon may also be able to have a general idea
of how the eye is expected to respond prior to a particular
procedure and be able to better select the appropriate option. The
ability of the physician to carry out surgery is, therefore,
improved. The method 100 may be particularly useful where the
surgeon is presented with a situation that is very complex and/or
has altered significantly since formation of the surgical plan.
Thus, the method 100 may have particular utility for conditions,
such as diabetic retinopathy or proliferative vitreoretinopathy,
that progress relatively quickly and/or which present the surgeon
with a complicated pathology. The ability of the physician to carry
out surgery is, therefore, improved.
[0032] FIG. 3 is a flow chart depicting an exemplary embodiment of
a method 150 for assisting a physician during ophthalmic surgery
using quasi-real time image(s). For simplicity, some steps may be
omitted, interleaved, performed in another order and/or combined.
The method 150 may include executing instructions on one or more
processors. Further, the method 150 is described in the context of
ophthalmic surgery. However, the method 150 may be extended to
other types of surgery.
[0033] At least one initial image of at least a portion of the eye
is received, via step 152. Receipt of the image in step 152 may
include receiving data for the image from a separate imaging system
or capturing the image by a portion of the system carrying out the
method 150. Thus, the image received in step 152 may, but need not
be a quasi-real time image. The image(s) received in step 152 may
include OCTs, ultrasound image(s), high frequency ultrasound
image(s), UBM image(s) and/or another three-dimensional
image(s)
[0034] A recommended initial region and a recommended initial
procedure are determined based on the initial image(s) and a
computational model of the eye, via step 154. The computational
model of the eye may be analogous the computational model discussed
above for the method 100. As part of step 154, therefore, data for
the initial image(s) received in step 152 are processed. For
example, the stresses in particular regions may be determined from
the distortions seen in the initial image data. Similarly,
striations due to higher stress, fold marks, thinning, tears and/or
other issues in various regions may be determined based on the
image data and the computational model. Step 154 may be performed
in a manner analogous to step 104, described above. However, the
initial image, which may or may not be a quasi-real time image, is
used. In some embodiments, step 154 may include explicitly
determining a specific recommended procedure. However, in general,
the recommended procedure is known for the particular operation
underway.
[0035] An initial expected result for the initial procedure is
calculated, via step 156. Step 156 may be analogous to step 106,
described above. However, the initial image, which may or may not
be a quasi-real time image, is used. The initial recommended
region, the initial recommended procedure and the initial expected
result may be provided, to the physician, via step 158. Step 158 is
analogous to step 108. Thus, image(s) of the eye and/or a model of
the eye may be displayed for the physician. In some embodiments,
therefore, this information is provided graphically to the
physician. In other embodiments, another mechanism for providing
the initial recommended region, the initial recommended procedure
and the initial expected result is used.
[0036] The surgeon may then perform one or more procedures, such as
making cut(s). The surgeon may opt to take the recommendation(s)
provided in step 158 or perform another procedure. For example, the
surgeon may desire to make a cut at a different location. The
surgeon may also perform multiple procedures.
[0037] After the surgeon has performed the procedure(s), at least
one in situ, quasi-real time image of at least a portion of the eye
is received, via step 160. Receipt of the image in step 160 may
include receiving data for the image from a separate imaging system
or capturing the image by a portion of the system carrying out the
method 150. Step 160 need not include rendering the image for the
physician. Instead, step 160 includes obtaining data for the eye.
Step 160 is thus analogous to step 102.
[0038] A recommended next region and a recommended next procedure
are determined based on the quasi-real time image(s) and a
computational model of the eye, via step 162. Step 162 is analogous
to step 104.
[0039] An expected next result for the recommended next procedure
is also calculated using the quasi-real time image and the
computational model, via step 164. Thus, step 164 includes using
the computational model of the eye to determine the reaction of
surrounding tissue to a release of stress in that region.
[0040] The recommended next region, the recommended next procedure
and the expected result are provided to the physician, via step
166. Portions of step 166 may be performed at different times. For
example, the recommended next region and recommended next procedure
may be performed by rendering the quasi-real time image or model
that is generated in step 162. Providing the expected result to the
physician may be performed in response to input received. For
example, if a particular recommended region is selected, then the
expected result of performing the recommended procedure at that
region is provided in step 166. Step 166 may thus include rendering
the model of the eye calculated in step 164.
[0041] The surgeon may then be allowed to execute one or more other
procedure(s). For example, one or more other cuts may be made. The
physician can, but need not, follow the recommendations provided in
the method 150. Step 160 may then be returned to and the eye
rescanned. The recommendations for the next step and next region
may be determined with the new scan and expected results of the new
recommendations determined in step 164. These new recommendations
and new expected results may be provided to the physician, via step
166. Thus, steps 160, 162, 164 and 166 may be iteratively repeated
to assist the surgeon. These steps can, but need not, be repeated
every time the surgeon performs a procedure. Alternatively, the
steps 160, 162, 164 and 166 may be repeated at selected time(s)
during the operation. Thus, the physician may opt to repeat these
steps only when s/he deems it helpful or necessary.
[0042] Using the method 150, a surgeon may be better able to
perform surgery on the eye. The method 150 may commence using the
surgeon's previous information (a more dated initial image) and/or
may use a quasi-real time image that is recently captured. Thus,
the physician may determine whether their surgical plan is still
appropriate. After one or more procedures have been performed as
part of the surgery, the steps 160, 162, 164 and 166 may be carried
out or repeated. Thus, the surgeon may determine whether the eye is
responding as expected and may be able to adjust for their actions
throughout surgery. The surgeon may also be able to have a general
idea of how the eye is expected to respond prior to a particular
procedure and be able to better select the appropriate option.
Consequently, the ability of the physician to carry out ophthalmic
surgery may be enhanced.
[0043] FIG. 4 is a block diagram of an exemplary embodiment of an
apparatus 300 for assisting a physician during ophthalmic surgery
using quasi-real time image(s). For simplicity, only some
components are shown. In addition, the components depicted in FIG.
4 may be packaged together in a single apparatus such as an OCT or
other imaging system. Alternatively, certain components, such as
portions of data collection and processing, may be implemented
separately. Further, the components may be implemented in hardware
and, in some cases, software. Also shown in FIG. 4 is the sample
eye 302 to be interrogated.
[0044] The apparatus 300 includes an imaging system 310, a
controller/processor 320, a prediction unit 330 and a user
interface (U/I) 340. The imaging system 310 may be separate from
the remainder of the system 300. Consequently, the imaging system
310 is shown as connected by dashed lines. If part of the apparatus
300, the imaging system 310 may be is controlled by the processor
320. The operator may input instructions and receive output from
the U/I 340. For example, the operator may set the regions of the
eye 302 scanned by the imaging system 310, view results or
otherwise provide instructions and receive output from the system
300. In some embodiments, the controller/processor 320 is linked
with or controls a system that sets the 10P for the eye 302 or
other features. Thus, the controller processor 320 may be used to
control quasi-real time image capture.
[0045] The prediction unit 330 may be implemented at least in part
in software. The prediction unit 330 processes data from the
imaging system 310. Thus, image data 332 and computational model
334 of the eye are shown. Portions of the computational model 334
may be stored in memory and are indicated as such in FIG. 4. For
example, values for the tensile strength or density of various
portions of the eye 302 as well as parameters for the patient may
be stored for the computational model 334. As such, an FEA model or
other model of the eye may be generated and used. The
recommendation/expected result generator 336 processes the image
data 332 and uses the computational model 334 to determine the
recommended region(s), recommended procedure(s) and expected
result(s). Using the optional renderer 338, these may be
graphically displayed to the physician on U/I 340. The optional
renderer 338 may also be used to simply display the quasi-real time
image data on the U/I 340. The apparatus 300 thus allows the eye
302 to be scanned and mapped during surgery, data for the eye to be
processed and recommendations and expected responses of the eye 302
to be determined. Using the apparatus 300, therefore, the method
100 and/or 150 may be implemented. One or more of the benefits of
the methods 100 and/or 150 may thus be achieved.
[0046] A method and system for assisting a surgeon, particularly
for ophthalmic surgery, have been described. The method and systems
have been described in accordance with the exemplary embodiments
shown, and one of ordinary skill in the art will readily recognize
that there could be variations to the embodiments, and any
variations would be within the spirit and scope of the method and
system. Accordingly, many modifications may be made by one of
ordinary skill in the art without departing from the spirit and
scope of the appended claims.
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