U.S. patent application number 17/663427 was filed with the patent office on 2022-09-01 for method and system for determining a risk of hemodynamic compromise after cardiac intervention.
This patent application is currently assigned to FEops NV. The applicant listed for this patent is FEops NV. Invention is credited to Matthieu Robert Anna Firmin DE BEULE, Gianluca DE SANTIS, Nic DEBUSSCHERE, Tim DeZUTTER, Peter Eddy J. MORTIER.
Application Number | 20220273369 17/663427 |
Document ID | / |
Family ID | 1000006333006 |
Filed Date | 2022-09-01 |
United States Patent
Application |
20220273369 |
Kind Code |
A1 |
MORTIER; Peter Eddy J. ; et
al. |
September 1, 2022 |
METHOD AND SYSTEM FOR DETERMINING A RISK OF HEMODYNAMIC COMPROMISE
AFTER CARDIAC INTERVENTION
Abstract
A method and system for predicting a measure of hemodynamic
compromise as a result of transcatheter cardiac treatment. The
method includes providing a patient-specific anatomical model
representing cardiac region and an implant model representing a
three-dimensional representation of a cardiac implant. The method
includes virtually deploying said implant model into said
patient-specific anatomical model. A deformation of the
patient-specific anatomical model is calculated as a result of
implant model deployment A measure of hemodynamic compromise is
determined from the virtually deployed implant model and the
deformed patient-specific anatomical model.
Inventors: |
MORTIER; Peter Eddy J.;
(Ingooigem, BE) ; DEBUSSCHERE; Nic; (Gent, BE)
; DE SANTIS; Gianluca; (Gent, BE) ; DeZUTTER;
Tim; (Aalter, BE) ; DE BEULE; Matthieu Robert Anna
Firmin; (Gent, BE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
FEops NV |
Gent |
|
BE |
|
|
Assignee: |
FEops NV
Gent
BE
|
Family ID: |
1000006333006 |
Appl. No.: |
17/663427 |
Filed: |
May 14, 2022 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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17361156 |
Jun 28, 2021 |
11331149 |
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17663427 |
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17003653 |
Aug 26, 2020 |
11051885 |
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17361156 |
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16482509 |
Jul 31, 2019 |
11045256 |
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PCT/EP2018/052701 |
Feb 2, 2018 |
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17003653 |
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14399781 |
Nov 7, 2014 |
10789772 |
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PCT/EP2013/058392 |
Apr 23, 2013 |
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17003653 |
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15570976 |
Oct 31, 2017 |
11141220 |
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PCT/EP2016/059688 |
Apr 29, 2016 |
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17361156 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 2034/105 20160201;
G16H 50/50 20180101; G16H 30/20 20180101; G16H 20/40 20180101; A61B
2034/102 20160201; A61B 5/026 20130101; A61B 5/021 20130101; A61B
34/10 20160201 |
International
Class: |
A61B 34/10 20060101
A61B034/10; G16H 20/40 20060101 G16H020/40; G16H 50/50 20060101
G16H050/50; G16H 30/20 20060101 G16H030/20; A61B 5/021 20060101
A61B005/021; A61B 5/026 20060101 A61B005/026 |
Foreign Application Data
Date |
Code |
Application Number |
May 16, 2012 |
EP |
PCT/EP2012/059207 |
Mar 4, 2013 |
EP |
PCT/EP2013/054276 |
May 1, 2015 |
EP |
15166130.3 |
Feb 3, 2017 |
EP |
17154648.4 |
Claims
1. A computer-implemented method for pre-operative planning for
delivery of a prosthetic cardiac implant to a patient's heart, the
method comprising: obtaining a plurality of digital images of a
patient's heart; obtaining a digital three-dimensional model of a
prosthetic cardiac implant; generating, from the plurality of
digital images, a digital patient-specific anatomical model
representing a patient-specific cardiac region including a
deployment site for the prosthetic cardiac implant; virtually
deploying the digital three-dimensional model of the prosthetic
cardiac implant at the deployment site; calculating deformation of
the digital three-dimensional model of the prosthetic cardiac
implant, in the deployed state, within the deployment site of the
patient-specific cardiac region; and determining a measure of
interaction between the digital three-dimensional model of the
prosthetic cardiac implant and the patient-specific cardiac region
of the digital patient-specific anatomical model.
2. The computer-based method of claim 1, wherein determining a
measure of interaction comprises determining a blood flow path
associated with the digital three-dimensional model of the
prosthetic cardiac implant and the patient-specific cardiac region
of the digital patient-specific anatomical model.
3. The computer-based method of claim 1, wherein determining a
measure of interaction comprises determining a measure of leakage
in or around a perimeter of the digital three-dimensional model of
the prosthetic cardiac implant.
4. The computer-based method of claim 1, further comprising
providing the patient-specific digital anatomical model of the
patient-specific cardiac region at a plurality of moments during a
cardiac cycle, and wherein the measure of interaction is determined
at the plurality of moments.
5. The computer-based method of claim 1, further comprising
determining the measure of interaction after simulating remodeling
of the patient-specific digital anatomical model of the
patient-specific cardiac region caused by prolonged presence of the
digital three-dimensional model of the prosthetic cardiac
implant.
6. The computer-based method of claim 1, wherein determining the
measure of interaction comprises determining a degree of incomplete
deployment of the digital three-dimensional model of the prosthetic
cardiac implant.
7. The computer-based method of claim 1, wherein the digital
three-dimensional model of the prosthetic cardiac implant is a
digital three-dimensional model of a prosthetic heart valve.
8. The computer-based method of claim 1, wherein the digital
three-dimensional model of the prosthetic cardiac implant is a
digital three-dimensional model of a left atrial appendage closure
device.
9. The computer-based method of claim 1, wherein determining the
measure of interaction comprises determining a measure of
hemodynamic compromise associated with deploying the digital
three-dimensional model of the prosthetic cardiac implant at the
deployment site.
10. The computer-based method of claim 1, wherein the digital
three-dimensional model of the prosthetic cardiac implant is
selected to block clots from going into a bloodstream.
11. The computer-based method of claim 1, further comprising
virtually deploying the digital three-dimensional model of the
prosthetic cardiac implant into the patient-specific digital
anatomical model of the cardiac region at a plurality of different
locations and determining the measure of interaction for each of
the plurality of different locations.
12. The computer-based method of claim 1, wherein virtually
deploying the digital three-dimensional model of the prosthetic
cardiac implant further comprises: providing a plurality of digital
three-dimensional models of prosthetic cardiac implants having
different geometrical or material properties; and virtually
deploying each of the plurality of digital three-dimensional models
of prosthetic cardiac implants into the patient specific digital
anatomical model of the patient's cardiac region, and determining
the measure of interaction for each of the plurality of digital
three-dimensional models of prosthetic cardiac implants.
13. The computer-based method of claim 12, further comprising
determining a corresponding one of the plurality of digital
three-dimensional models of prosthetic cardiac implants that causes
a preferred degree of interaction as compared to others of the
plurality of digital three-dimensional models of prosthetic cardiac
implants.
14. The computer-based method of claim 1, further comprising
displaying the measure of interaction on a computer system display
and the digital three-dimensional model of the prosthetic cardiac
implant deployed at the deployment site.
15. A system for pre-operative planning for delivery of a
prosthetic cardiac implant to a patient's heart, the system
comprising at least one processor configured to: obtain a plurality
of digital images of a patient's heart; obtain a digital
three-dimensional model of a prosthetic cardiac implant; generate,
from the plurality of digital images, a digital patient-specific
anatomical model representing a patient-specific cardiac region
including a deployment site for the prosthetic cardiac implant;
virtually deploy the digital three-dimensional model of the
prosthetic cardiac implant at the deployment site; calculate
deformation of the digital three-dimensional model of the
prosthetic cardiac implant, in the deployed state, within the
deployment site of the patient-specific cardiac region; and
determine a measure of interaction between the digital
three-dimensional model of the prosthetic cardiac implant and the
patient-specific cardiac region of the digital patient-specific
anatomical model.
16. The system of claim 15, wherein the digital three-dimensional
model of the prosthetic cardiac implant is a digital
three-dimensional model of a prosthetic heart valve.
17. The system of claim 15, wherein the digital three-dimensional
model of the prosthetic cardiac implant is a digital
three-dimensional model of a left atrial appendage closure
device.
18. The system of claim 15, wherein the system is further
configured to virtually deploy the digital three-dimensional model
of the prosthetic cardiac implant into the patient-specific digital
anatomical model of the cardiac region at a plurality of different
locations and determine the measure of interaction for each of the
plurality of different locations.
19. The system of claim 15, wherein the virtually deployment of the
digital three-dimensional model of the prosthetic cardiac implant
further comprises: provide a plurality of digital three-dimensional
models of prosthetic cardiac implants having different geometrical
or material properties; and virtually deploy each of the plurality
of digital three-dimensional models of prosthetic cardiac implants
into the patient specific digital anatomical model of the patient's
cardiac region, and determine the measure of interaction for each
of the plurality of digital three-dimensional models of prosthetic
cardiac implants.
20. The system of claim 19, wherein the system is further
configured to determine a corresponding one of the plurality of
digital three-dimensional models of prosthetic cardiac implants
that causes a preferred degree of interaction as compared to others
of the plurality of digital three-dimensional models of prosthetic
cardiac implants.
21. A non-transitory computer-readable medium storing computer
implementable instructions that when executed by a programmable
computer cause the computer to: obtain a plurality of digital
images of a patient's heart; obtain a digital three-dimensional
model of a prosthetic cardiac implant; generate, from the plurality
of digital images, a digital patient-specific anatomical model
representing a patient-specific cardiac region including a
deployment site for the prosthetic cardiac implant; virtually
deploy the digital three-dimensional model of the prosthetic
cardiac implant at the deployment site; calculate deformation of
the digital three-dimensional model of the prosthetic cardiac
implant, in the deployed state, within the deployment site of the
patient-specific cardiac region; and determine a measure of
interaction between the digital three-dimensional model of the
prosthetic cardiac implant and the patient-specific cardiac region
of the digital patient-specific anatomical model.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 17/361,156, filed Jun. 28, 2021, now U.S. Pat.
No. 11,331,149, which is a continuation of U.S. patent application
Ser. No. 17/003,653, filed Aug. 26, 2020, now U.S. Pat. No.
11,051,885, which is a continuation of U.S. patent application Ser.
No. 16/482,509, filed Jul. 31, 2019, now U.S. Pat. No. 11,045,256,
which is a national phase application under 35 U.S.C. .sctn. 371 of
PCT/EP2018/052701, filed Feb. 2, 2018, which claims priority to
European Patent Application Serial No. 17154648.4, filed Feb. 3,
2017, and is also a continuation-in-part of U.S. patent application
Ser. No. 14/399,781, filed Nov. 7, 2014, now U.S. Pat. No.
10,789,772, which is a national phase application under 35 U.S.C.
.sctn. 371 of PCT/EP2013/058392, filed Apr. 23, 2013, which claims
priority to PCT/EP2013/054276, filed Mar. 4, 2013, and
PCT/EP2012/059207, filed May 16, 2012, the entire contents of each
of which are incorporated herein by reference. U.S. patent
application Ser. No. 17/361,156, filed Jun. 28, 2021, now U.S. Pat.
No. 11,331,149, is also a continuation-in-part of U.S. patent
application Ser. No. 15/570,976, filed Oct. 31, 2017, now U.S. Pat.
No. 11,141,220, which is a national phase application under 35
U.S.C. .sctn. 371 of PCT/EP2016/059688, filed Apr. 29, 2016, which
claims priority to European Patent Application Serial No.
15166130.3, filed May 1, 2015, the entire contents of each of which
are incorporated herein by reference.
FIELD OF THE INVENTION
[0002] The present invention relates to the field of pre-operative
planning of transcatheter structural heart interventions, e.g.
valve treatment, such as valve implantation and/or repair. More in
particular, the invention relates to pre-operative prediction of
the risk a patient developing hemodynamic compromise as a result of
transcatheter valve treatment.
BACKGROUND TO THE INVENTION
[0003] The left ventricle of the heart pumps the blood to the aorta
through the aortic valve. Aortic (valve) stenosis is a pathology
occurring when the aortic valve does not open fully because the
leaflets calcify, thicken and stiffen and, as a result, the blood
flow going from the heart to the systemic circulation decreases.
Aortic stenosis manifests itself in elderly people, with a
prevalence going from 1.3% in over 65 and 4% in over 85 year old
people. Currently it is one of the most common valvular heart
diseases in the Western world and its prevalence is increasing with
the aging population. The traditional treatment for an aortic
stenosis is the Surgical Aortic Valve Replacement (SAVR) aiming at
reproducing the correct function of the native valve with an
implanted valve. This invasive procedure requires total anesthesia,
sternotomy (open-heart surgery) and cardiopulmonary bypass (the
blood is pumped and oxygenated using an external machine), and is
associated with about 6% in-hospital mortality for over 65 year old
patients. Moreover, at least one-third of the patients with severe
aortic stenosis are denied valve surgery as the risks associated
with surgery are too high.
[0004] Trans-catheter aortic valve implantation (TAVI) or
trans-catheter aortic valve replacement (TAVR) is a
minimally-invasive procedure for treating aortic stenosis: (1) the
valve (e.g. a bioprosthetic valve made of porcine pericardium
sutured on a metal stent) is crimped inside a catheter, (2) the
catheter is inserted, for example, in the femoral artery, (3)
pushed upstream along the aorta up to the aortic annulus and (4)
the new valve is deployed within the diseased native valve. TAVI
has the potential of treating high-risk patients and replacing the
SAVR with a minimally-invasive intervention (no need for open-heart
surgery or cardiopulmonary bypass) which can be performed in e.g.
about 80 minutes. Main TAVI complications are vascular injury,
stroke, cardiac injury (heart block, coronary obstruction, cardiac
perforation), aortic regurgitation, cardiac conduction
abnormalities and valve misplacement. Accurate pre operative
planning is crucial to select the optimal device size and to
anticipate potential difficulties.
[0005] Undersizing of a valve implant may lead to paravalvular
aortic regurgitation, while oversizing may result in a rupture of
the aortic annulus or in a suboptimal functional behavior of the
implant (e.g. central regurgitation) or in conduction disturbances
or in coronary obstruction. Currently available planning tools
(Philips, Siemens, Pie Medical, Paeion) provide insights into the
patient anatomy and can, for example, be used to determine the size
of the aortic annulus, or to measure the distance between the valve
plane and the coronary ostia. A problem with these tools is that
they do not provide preoperative insights into the interaction
between a certain implant device and the specific patient anatomy,
and can thus not be used to predict complications such as
regurgitation. Such insights are extremely valuable for
interventional cardiologists.
[0006] Document US 2011/0153286 A1 discloses a method and system
for virtual percutaneous valve implantation. In one embodiment of
the application a patient-specific anatomical model of a heart
valve is estimated based on 3D cardiac medical image data. An
implant model representing a valve implant is virtually deployed
into the patient-specific anatomical model of the heart valve. A
library of implant models, each modeling geometrical properties of
a corresponding valve implant, can be maintained. The implant
models maintained in the library can be virtually deployed into the
patient specific anatomical model of the heart valve to select one
of the implant models for use in a percutaneous valve implantation
procedure.
[0007] US 2011/0153286 A1 does not provide a prediction of the
mechanical behavior and interaction of the patient-specific aortic
root, ascending aorta and aortic valve leaflets with the deployment
of a valve implant. Said document also does not account for
calcification of aortic valve leaflets. Neither does it provide a
means to study the hemodynamic performance of an implant deployed
in the aortic valve. Balloon-expandable devices whose deployment is
based on permanent plastic deformations of the metal cannot be
modeled. There is a need for more precise valve sizing and
positioning. Problem is that the aortic annulus is not circular,
that the aortic annulus may deform and that calcium deposits may
deform a valve frame. Another problem is that the aortic root
visualized with Computed Tomography (CT) imaging changes in shape
and size after TAVI. Also the geometry of the stent frame of the
transcatheter aortic valve (TAV) is affected by the stiffness of
the aortic root, by the presence of stiff calcified regions and by
the exact device position.
[0008] Sub-optimal treatment planning can have two socio-economic
effects. On the one hand this gives higher costs for the health
system. If the incorrect device/size of the TAV is chosen, the
first TAVI procedure may fail and additional treatments, including
a second TAVI procedure (valve-in-valve), SAVR, or
rehospitalization may be necessary, with a considerable increase of
the costs per patient. As a reference, one single TAVI procedure
costs about 40 k Euro and the stented valve itself costs about 20 k
Euro. On the other hand this leads to a lower prognosis.
Sub-optimal treatment planning may result in peri-procedural
complications, which affect both the life quality and the life
expectancy of the patient. An oversized valve may rupture the
annulus or dissect the aorta whereas an undersized valve may
dislodge and migrate or can induce paravalvular regurgitation.
[0009] In WO2013/171039 A1 the present inventors described a
solution to overcome at least part of the above-mentioned
disadvantages. WO2013/171039 A1 provides an improved method for
preoperative insights into the interaction of an implant device and
specific patient anatomy, for better prediction of complications,
such as regurgitation, for better prediction of the hemodynamic
performance of an implant deployed in an aortic valve, and for
better patient selection and stratification. Also WO2013/171039 A1
provides a web-based pre-operative planning service for TAVI using
computer simulations that predict stent frame deformation and
incomplete frame apposition, allowing to assess the risk of
regurgitation and other complications such as coronary obstruction
and conduction abnormalities prior to the intervention.
[0010] In WO2016/177647 A1 the present inventors described method
for determining a measure of a risk of a patient developing cardiac
conduction abnormalities and/or disorders, such as left
bundle-branch block (LBBB), as a result of transcatheter structural
heart intervention, such a transcatheter cardiac valve
implantation/replacement or repair.
SUMMARY OF THE INVENTION
[0011] Transcatheter mitral valve replacement, TMVR, may lead to an
obstruction of the left ventricular outflow tract, LVOT, so blood
flow towards the aorta may be significantly reduced. TMVR may also
lead to a compression/obstruction of the left circumflex coronary
artery, LCX, and/or the coronary sinus. It has been found that LVOT
obstruction after TMVR in patients with mitral annular
calcification occurs in approximately 10% of the patients. TAVI may
lead to an obstruction of the coronary arteries, due to the
movement of the calcified native leaflets towards the coronary
ostia, or due to the presence of the TAV itself. Coronary
obstruction after TAVI occurs in 0.5-1% of cases.
[0012] Thus, transcatheter cardiac valve implantation/replacement
or repair can lead to hemodynamic compromise. The hemodynamic
compromise can be obstruction of a primary blood flow path in which
the valve is implanted. Such obstruction can cause a drop
(gradient) in blood pressure over the implanted device. The
hemodynamic compromise can be obstruction of a secondary blood flow
path in communication with the primary blood flow path, e.g. at the
location of the implanted device. The hemodynamic compromise can be
leakage (or regurgitation) with occurs in the primary blood flow
path.
[0013] Hence, there is a need to predict hemodynamic compromise,
such as obstruction and/or leakage, as a result of valve treatment.
Hence, a physician can preoperatively predict whether, and to what
extent, a procedure such as valve replacement will result in
complications such as obstruction of an adjacent blood flow path,
such as the LVOT, LCX, coronary sinus, or coronary artery.
[0014] According to an aspect is provided a method for predicting a
measure of hemodynamic compromise as a result of transcatheter
structural heart intervention, such a transcatheter cardiac valve
treatment. The treatment may be trans-catheter valve
implantation/replacement or trans-catheter valve repair. The
transcatheter cardiac valve may e.g. be a transcatheter aortic or
mitral valve or tricuspid valve. The method includes providing an
implant model representing a three-dimensional representation of a
cardiac implant, such as a cardiac valve implant, e.g. an aortic
valve implant or mitral valve implant. The implant model can
represent a three-dimensional representation of a transcatheter
mitral valve, TMV, or transcatheter aortic valve, TAV, or
transcatheter tricuspid valve. The implant model can be a finite
element representation of the cardiac implant. The method includes
providing a patient-specific anatomical model representing a
patient-specific cardiac region including a deployment site for the
cardiac implant in a first blood flow path, such as a
patient-specific cardiac valve region, and a second blood flow
path, such as a LVOT or aorta. The patient-specific anatomical
model may represent a patient-specific left ventricle and/or atrium
and/or aorta or a part thereof. The patient-specific anatomical
model can comprise a finite element mesh. The implant model is
virtually, e.g. in silico, placed, e.g. deployed, into the
patient-specific anatomical model at the deployment site. A
deformation of the patient-specific anatomical model as a result of
implant model deployment is calculated. From the virtually deployed
implant model and the deformed patient-specific anatomical model, a
measure of hemodynamic compromise in the deformed patient-specific
anatomical model is determined. On the basis of the determined
measure of hemodynamic compromise, a measure may be determined of
the risk of the patient developing complications if an actual
implant corresponding to the implant model were actually implanted
in the anatomical region of the patient corresponding to the
patient-specific anatomical model.
[0015] The method can be used for predicting obstruction of the
second blood flow path. Then, from the virtually deployed implant
model and the deformed patient-specific anatomical model, a measure
of obstruction of the second blood flow path in the deformed
patient-specific anatomical model is determined. On the basis of
the determined measure of obstruction, a measure may be determined
of the risk of the patient developing complications if an actual
implant corresponding to the implant model were actually implanted
in the anatomical region of the patient corresponding to the
patient-specific anatomical model.
[0016] The method can be used for predicting obstruction of the
first blood flow path. For example, it is possible that with the
valve leaflets open an open area of the valve is reduced, e.g. due
to a not well expanded or deployed valve. This can cause a pressure
drop (or gradient) in the blood flow through the valve. Then, from
the virtually deployed implant model and the deformed
patient-specific anatomical model, a measure of obstruction of the
first blood flow path in the deformed patient-specific anatomical
model is determined. On the basis of the determined measure of
obstruction, a measure may be determined of the risk of the patient
developing complications if an actual implant corresponding to the
implant model were actually implanted in the anatomical region of
the patient corresponding to the patient-specific anatomical
model.
[0017] The method can be used for predicting leakage in the first
blood flow path. For example, it is possible that with the valve
leaflets closed blood leaks around the outside of the implanted
valve, between the valve and the surrounding tissue. Alternatively,
or additionally, in the closed position the valve leaflets may not
fully close, allowing blood to leak through the implanted valve.
Then, from the virtually deployed implant model and the deformed
patient-specific anatomical model, a measure of leakage in the
first blood flow path in the deformed patient-specific anatomical
model is determined. On the basis of the determined measure of
leakage, a measure may be determined of the risk of the patient
developing complications if an actual implant corresponding to the
implant model were actually implanted in the anatomical region of
the patient corresponding to the patient-specific anatomical
model.
[0018] It will be appreciated that the method includes computer
implemented steps. It will be appreciated that all above mentioned
steps can be computer implemented steps.
[0019] A cardiac valve implant and a cardiac valve region of the
patient is an important example of the present invention.
Nevertheless, the invention can also be applied to other implants,
such as stents. Although below is referred in particular to a
cardiac valve implant and a cardiac valve region of the patient, it
will be appreciated that the features and advantages also apply to
other implants for the heart. Therefore, for the purpose of
understanding the invention where herein is referred to a cardiac
valve implant and cardiac valve region this similarly holds for
other cardiac implants and/or other cardiac regions, including LAA,
atrial or ventricular septal defect closure.
[0020] Optionally, the method includes providing the
patient-specific anatomical model at a plurality of moments during
the cardiac cycle, and determining the measure of hemodynamic
compromise, at the plurality of moments. It will be appreciated
that the geometry of the heart changes significantly during the
cardiac cycle. Therefore, the measure of hemodynamic compromise may
vary significantly during the cardiac cycle as well. Hence,
determining the measure of hemodynamic compromise at a plurality of
moments during the cardiac cycle allows to determine minimum and
maximum values of the hemodynamic compromise.
[0021] Optionally, the measure of obstruction of the second blood
flow path is a cross sectional area of the second blood flow path.
The cross sectional area, for instance, e.g. substantially,
orthogonal to the direction of blood flow has proven to be a
reliable measure of obstruction. The cross sectional area of the
second blood flow path after deployment of the implant model can be
compared with a cross sectional area of the second blood flow path
in the patient-specific anatomical model in which no implant model
is deployed. This provides insight into the predicted change of
cross sectional area available for blood flow after deployment of
the implant. Also a volume reduction of a segment of the second
blood flow path can be a good measure to quantify obstruction.
[0022] Optionally, the measure of obstruction of the second blood
flow path is a ratio of a cross sectional area of the second blood
flow path when the implant model is deployed divided by a cross
sectional area of the second blood flow path in the
patient-specific anatomical model in which no implant model is
deployed. This takes into account deformation of the anatomy, e.g.
a TMVR device pushing against the LVOT reducing LVOT area, and
presence of the device, e.g. the remaining area is the deformed
area minus area occupied by the device. The ratio provides insight
into the predicted change of the cross sectional area due to
implant deployment.
[0023] Optionally, the measure of obstruction of the first blood
flow path is a cross sectional area of the first blood flow path,
e.g. in view of valve leaflet positions. The cross sectional area,
for instance, e.g. substantially, orthogonal to the direction of
blood flow has proven to be a reliable measure of obstruction. The
cross sectional area of the first blood flow path after deployment
of the implant model can be compared with a cross sectional area of
the first blood flow path in the patient-specific anatomical model
in which no implant model is deployed. This provides insight into
the predicted change of cross sectional area available for blood
flow after deployment of the implant. Also a volume reduction of a
segment of the first blood flow path can be a good measure to
quantify obstruction.
[0024] Optionally, the measure of obstruction of the first blood
flow path is a ratio of a cross sectional area of the first blood
flow path when the implant model is deployed divided by a cross
sectional area of the first blood flow path in the patient-specific
anatomical model in which no implant model is deployed. The ratio
provides insight into the predicted change of the cross sectional
area due to implant deployment.
[0025] Optionally, the patient-specific anatomical model further
includes fluid pressures in the cardiac region. Hence, deformation
of the patient-specific anatomical model can be calculated taking
into account the fluid pressure. It is also possible to use
computational fluid dynamics, CFD. Hence, obstruction and/or
leakage can be determined.
[0026] Optionally, the method includes the step of simulating a
displacement of at least one valve leaflet of the cardiac valve
implant. The measure of hemodynamic compromise, e.g. the measure of
obstruction of the second blood flow path, can then be determined
also on the basis of the leaflet displacement.
[0027] Optionally, the method includes the step of simulating a
displacement of at least one valve native leaflet due to
device-anatomy interaction and optionally hydrodynamic forces. The
measure of hemodynamic compromise, e.g. the measure of obstruction
of the second blood flow path, can then be determined also on the
basis of the leaflet displacement.
[0028] Optionally, the displacement of the valve leaflet (of the
implant and/or native valve) can be calculated using CFD, or fluid
structure interactions, FSI. For example, the anterior mitral valve
leaflet is displaced towards the LVOT by TMVR, but may further move
during systole due to blood flow. This may be modelled as
suggested.
[0029] Optionally, the measure of obstruction of the second blood
flow path is a pressure gradient at the second blood flow path.
Optionally, the measure of obstruction of the first blood flow path
is a pressure gradient at the first blood flow path. Optionally,
the measure of obstruction of the first blood flow path is a
pressure gradient across the implant, e.g. the valve (i.e. non-zero
pressure difference across the valve when valve is open).
[0030] Optionally, the measure of obstruction of the second blood
flow path is a flow measure at the second blood flow path.
Optionally, the flow measure is the maximum velocity at the second
blood flow path or the extension of the cross sectional portion of
the second blood flow path with velocity magnitude above a
threshold. Optionally, the measure of obstruction of the first
blood flow path is a flow measure at the first blood flow path.
Optionally, the flow measure is the maximum velocity at the first
blood flow path or the extension of the cross sectional portion of
the first blood flow path with velocity magnitude above a
threshold.
[0031] It will be appreciated that this method provides the
advantage that the measure of the risk of the patient developing
hemodynamic compromise, such as obstruction and/or leakage, as a
result of transcatheter treatment of the cardiac valve can be
predicted pre-operatively. Hence, it is possible to predict how
likely e.g. a planned TAVI or TMVR procedure will result in
hemodynamic problems.
[0032] Optionally, determining the measure of hemodynamic
compromise includes determining an evolution of the hemodynamic
compromise over time during the process of deployment. It is
possible to determine the measure of hemodynamic compromise at a
first moment and at a second moment. The first moment may be prior
to the implant model being fully deployed into the patient-specific
anatomical model. The second moment may be after the implant model
has been fully deployed into the patient-specific anatomical model.
It is also possible to determine the measure of the hemodynamic
compromise at a plurality of first moments. Hence a time evolution
of the hemodynamic compromise during deployment of the implant
model can be determined. Optionally, time evolution of hemodynamic
compromise after deployment is also determined. Hence, remodeling
of the heart, due to the heart anatomy changing due to the
prolonged presence of the implant, can be taken into account. For
instance, hemodynamic compromise at one week, at one month, and at
one year after treatment can be determined.
[0033] Optionally, determining the measure of hemodynamic
compromise may include determining a series of situations of
progressing deployment of the implant model into the
patient-specific anatomical model. The situations may progressively
differ by a predetermined amount or ratio of deployment. The
deployment can include insertion of the implant model into the
patient-specific anatomical model. The insertion can include travel
of a model of a, collapsed, implant along a vessel. The series of
situations can include situations of progressively differing
positions of insertion up to an intended deployment position. The
deployment can include expansion of the implant model in the
patient-specific anatomical model. The series of situations can
include situations of progressively differing stages of expansion
of the implant model. For each of the situations of the series of
situations the measure of hemodynamic compromise can be determined
as described above. Hence, all stages of deployment can be modeled.
The processing unit can be arranged to determine the situation of
the series of situations in which the determined hemodynamic
compromise is most significant, e.g. highest obstruction. The
processing unit may be arranged to determine the measure of
hemodynamic compromise in the situation of the series of situations
in which the determined mechanical interaction is most significant
for predicting hemodynamic problems, e.g. highest. The series of
situations may be generated for a plurality of different deployment
sites. The processing unit may be arranged to select the optimum
deployment site.
[0034] It will be appreciated that the risk of the patient
developing hemodynamic problems can be quantified by taking a
combination of the determinations mentioned above.
[0035] Optionally, the method includes estimating the
patient-specific anatomical model on the basis of a, preferably
preoperative, cardiovascular 2D or 3D or 4D medical image data,
such as a X-rays, CT-scan, an MRI image, echocardiography images or
the like, and combinations thereof.
[0036] Optionally, the method includes estimating the
patient-specific anatomical model on the basis of anatomical
measurements, using for example, a parametric heart model.
[0037] Optionally, the implant model comprises a finite element
mesh. Each element of said mesh can be featured by a set of nodes.
Adjacent elements of said element can comprise mutually shared
nodes with said element. Said element can be featured by material
dependent parameters. Each element of said mesh can differ in
material dependent parameters from an adjacent element of said
element of said mesh.
[0038] Optionally, stiffness elements are provided to a plurality
of nodes of a mesh of the anatomical model. A stiffness element
induces a reacting force on the corresponding node of said mesh,
wherein said force is dependent on the displacement of said node or
on the distance between said node and a fixed position equal or
very close to the initial position of said node.
[0039] Optionally, the step of virtually deploying the implant
model into the patient-specific anatomical model includes a
three-dimensional finite element analysis. Hence, deployment of the
implant in the patient-specific anatomical model can be simulated
in silico in three dimensions.
[0040] Optionally, the method includes virtually deploying the
implant model into the patient-specific anatomical model at a
plurality of different locations at and/or near the deployment site
and determining the measure of obstruction of the second blood flow
path for each of the different locations. Hence, it is possible to
assess the risk of hemodynamic problems for the plurality of
different locations of the implant. Hence, it is also possible to
select the location for the implant associated with the lowest risk
of developing hemodynamic obstruction problems. Such selected
location can be used in pre-operative planning of a TAVI or TMVR
procedure.
[0041] Optionally, the step of virtually deploying the implant
model includes providing a plurality of implant models, each
modeling geometrical and/or material properties of a corresponding
implant; and virtually deploying each of the implant models into
the patient specific anatomical model, and determining the measure
of hemodynamic compromise for each of the implant models. Hence, it
is possible to assess the risk of hemodynamic problems for each the
plurality of different implant models. Hence, it is also possible
to select the implant model associated with the lowest risk of
developing hemodynamic obstruction problems. Such selected implant
model can be used in pre-operative planning of a TAVI or TMVR or
TTVR procedure. The method can include selecting a cardiac valve
implant corresponding to one of the plurality of the implant models
for a percutaneous implantation procedure. A cardiac valve implant
associated with the selected implant model can be used in a
percutaneous implantation procedure to minimize risk of the patient
developing hemodynamic problems. It will be appreciated that it is
also possible to virtually deploy each implant model of the
plurality of implant models into the patient specific anatomical
model at a plurality of different locations at and/or near the
deployment site. Thus the implant models can be compared each at
its optimal location.
[0042] Optionally, the method includes reporting the measure of
hemodynamic compromise to a user. The measure of hemodynamic
compromise, e.g. the measure of obstruction and/or leakage, may
e.g. be displayed on a display, printed in hardcopy or the like. It
is also possible to report an indication of the risk of the patient
developing hemodynamic problems to the user.
[0043] According to an aspect is provided a system for determining,
e.g. predicting, a measure of hemodynamic compromise as a result of
transcatheter cardiac valve treatment. The system includes a
processor. The processor is arranged for receiving an implant model
representing a three-dimensional representation of a cardiac valve
implant. The processor is arranged for receiving a patient-specific
anatomical model representing a patient-specific cardiac region
including a deployment site for the cardiac implant in a first
blood flow path and a second blood flow path. The patient-specific
anatomical model can comprise a finite element mesh. The processor
is arranged for virtually deploying said implant model into said
patient-specific anatomical model at the deployment site. The
processor is arranged for calculating deformation of the
patient-specific anatomical model as a result of implant model
deployment. The processor is arranged for determining, from the
virtually deployed implant model and the deformed patient-specific
anatomical model, a measure of hemodynamic compromise in the
deformed patient-specific anatomical model. The processor can be
arranged for determining a measure of risk of the patient
developing hemodynamic problems on the basis of the determined
measure of hemodynamic compromise. Thus, the system can be used to
perform the method as described above.
[0044] According to an aspect is provided a computer program
product including computer implementable instructions. The computer
program product can be stored on a non-transient data carrier. When
implemented by a programmable computer the instructions cause the
computer to retrieve an implant model representing a
three-dimensional representation of a cardiac valve implant. When
implemented by a programmable computer the instructions cause the
computer to retrieve a patient-specific anatomical model
representing a patient-specific cardiac region including a
deployment site for the cardiac implant in a first blood flow path
and a second blood flow path. The patient-specific anatomical model
can comprise a finite element mesh. When implemented by a
programmable computer the instructions cause the computer to
virtually deploy said implant model into said patient-specific
anatomical model at the deployment site. When implemented by a
programmable computer the instructions cause the computer to
calculate deformation of the patient-specific anatomical model as a
result of implant model deployment. When implemented by a
programmable computer the instructions cause the computer to
determine, from the virtually deployed implant model and the
deformed patient-specific anatomical model, a measure of
hemodynamic compromise in the deformed patient-specific anatomical
model. When implemented by a programmable computer the instructions
can cause the computer to determine a measure of risk of the
patient developing hemodynamic problems on the basis of the
determined measure of hemodynamic compromise. Thus, the computer
program product can be used to perform the method as described
above.
[0045] It will be appreciated that all features and options
mentioned in view of the method apply equally to the system and the
computer program product. It will also be clear that any one or
more of the above aspects, features and options can be
combined.
BRIEF DESCRIPTION OF THE DRAWINGS
[0046] Embodiments of the present invention will now be described
in detail with reference to the accompanying drawings in which:
[0047] FIG. 1 is schematic representation of a system;
[0048] FIG. 2 is a schematic example in which an implant model and
a patient-specific anatomical model are represented; and
[0049] FIGS. 3a, 3b, 3c are an example wherein the implant model is
deployed into the patient-specific anatomical model at a plurality
of different locations.
DETAILED DESCRIPTION
[0050] Left ventricular outflow tract (LVOT) obstruction after a
transcatheter mitral valve replacement (TMVR) procedure is a
frequent complication. LVOT obstruction after TMVR in patients with
mitral annular calcification may occur in approximately 10% of the
patients. This can result in increased mortality after one year.
Using the present technology, however, a predictor for the
occurrence of LVOT obstruction or other hemodynamic compromise can
be given.
[0051] FIG. 1 shows a schematic example of a system 1 for
predicting a measure of hemodynamic compromise, such as obstruction
of a blood flow path, as a result of transcatheter cardiac valve
treatment. The system includes a processing unit 2. The processing
unit 2 includes a first receiving unit 4 for receiving a
patient-specific anatomical model. Here the patient-specific
anatomical model represents a patient-specific cardiac valve
region.
[0052] In this example, the patient-specific anatomical model is
provided as a three dimensional (3D) finite element model
comprising a finite element mesh. In this example the
patient-specific anatomical model is received from a conversion
unit 6. The conversion unit 6 is arranged for receiving medical
imaging data from a medical imaging device 8. The medical imaging
data may be 2D, 2.5D (stacked 2D), 3D or 4D imaging data. The
medical imaging data may be preoperative imaging data. The medical
imaging device 8 may e.g. be a X-ray scanner, computer tomography
(CT) device, an echocardiography device or a magnetic resonance
imaging (MRI) device. In this example, the conversion unit 6 is
arranged for creating the patient-specific 3D finite element model
on the basis of the medical imaging data. Alternatively, or
additionally, the patient-specific anatomical model can be received
from a database 10.
[0053] The processing unit 2 further includes a second receiving
unit 14 arranged for receiving an implant model representing a 3D
representation of a cardiac valve implant, here a finite element
representation. The 3D representation of the cardiac valve implant
may e.g. be received from a 3D modelling system 16. Alternatively,
or additionally, the 3D representation of the cardiac valve implant
can be received from a database 18.
[0054] FIG. 2 shows a schematic example of a patient-specific
anatomical model 40 of a cardiac valve region. FIG. 2 also shows a
schematic example of an implant model 42. In this example the
implant model 42 represents a mitral valve implant. The
patient-specific anatomical model 40 includes a deployment site 44
for the cardiac implant 42 in a first blood flow path 46. The
patient-specific anatomical model 40 also includes a second blood
flow path 48. The first blood flow path 46 can e.g. be a blood flow
path extending through the mitral valve, while the second blood
flow path 48 is the LVOT. In another example, the first blood flow
path can e.g. be a blood flow path extending through the aortic
valve, while the second blood flow path is a coronary artery.
[0055] Returning to FIG. 1, the processing unit 2 includes a
placing unit 20 arranged for virtually deploying said implant model
into said patient-specific anatomical model. The placing unit can
place the implant model 42 into the patient-specific anatomical
model 40. The placing unit 20 can be arranged for bringing the
implant model and the patient-specific anatomical model in a common
model space. The processing unit 2 can be arranged for defining a
deployment site 44 for the implant model in the first blood flow
path 46 in the patient-specific anatomical model 40. The processing
unit can include an input unit 19 arranged for receiving
information relating to the deployment site 44. The input unit 19
can be associated with a graphical user interface arranged for
allowing a user, such as a surgeon, to input a desired deployment
site 44 for the implant model 42 in the patient-specific anatomical
model 40. It is also possible that the processing unit 2 is
arranged for autonomously determining, or proposing, the deployment
site 44. The determined or proposed deployment site 44 can be based
on a rule. The rule can be associated with a predefined location of
an anatomical structure in the patient-specific anatomical model
40. The placing unit 20 can apply three dimensional finite element
analysis.
[0056] The placing by the placing unit 20 also includes virtually
expanding the implant model 42 into the patient-specific anatomical
model 40. The expanded implant model 42 will abut against the
patient-specific anatomical model 40. It will be appreciated that
the patient-specific model 40 may deform, e.g. locally, due to the
presence of the, e.g. expanded, implant model 42.
[0057] The processing unit 2 here includes a calculation unit 21
arranged for calculating a deformation of the patient-specific
anatomical model 40 as a result of implant model 42 deployment. It
will be appreciated that physical properties, such as stiffness,
associated with both the implant model and the patient-specific
anatomical model will determine the shape of the expanded implant
model 42, the corresponding shape of the deformed patient-specific
anatomical model 40, and a mechanical interaction between the
implant model and the patient-specific anatomical model. The
mechanical interaction can include one or more of force, pressure,
stress, and strain between the implant model and the
patient-specific anatomical model.
[0058] The processing unit 2 further includes a determination unit
22 arranged for determining, from the virtually deployed implant
model 42 and the deformed patient-specific anatomical model 40, a
predicted value of a measure of hemodynamic compromise. In this
example, the determination unit 22 determines a predicted value of
a measure of obstruction of the second blood flow path 48 in the
deformed patient-specific anatomical model 40. In this example the
determination unit 22 is arranged for determining a cross sectional
area of the second blood flow path 48 after deployment of the
implant model 42. Thereto the determination unit 22 can determine
the deformation of the implant model 42 and the patient-specific
anatomical model 40 due to deployment, and possible post-dilation.
The deformations of both models 40, 42, in conjunction with modeled
elasticities of the models 40, 42, allow to determine the force
exerted by the one model onto the other. The elasticities of the
models can be modeled as stiffnesses between nodes of the
respective models.
[0059] Additionally, the determination unit 22 can be operated for
determining a cross sectional area of the second blood flow path 48
before deployment of the implant model 42. Hence a difference in
cross sectional area before and after deployment of the implant
model 42 can be determined. The difference can be a measure for
obstruction of the second blood flow path 48 due to presence of the
implant model 42 and deformation of the patient-specific anatomical
model 40. Alternatively, or additionally, the measure of
obstruction of the second blood flow path 48 can be determined as a
ratio of the cross sectional area of the second blood flow path 48
when the implant model 42 is deployed divided by the cross
sectional area of the second blood flow path 48 in the
patient-specific anatomical model 40 in which no implant model 42
is deployed.
[0060] In the above example, the determined hemodynamic compromise
includes obstruction of the second blood flow path 48.
Alternatively, or additionally, the determined hemodynamic
compromise includes obstruction of the first blood flow path 46. It
will be appreciated that the first blood flow path 46 may be
somewhat obstructed by the presence of the implant. Thus, the
calculation unit 21 can calculate a deformation of the
patient-specific anatomical model 40 as a result of implant model
42 deployment. The determination unit 22 can be operated for
determining a cross sectional area of the first blood flow path 46.
This may e.g. be compared to a cross sectional area of the first
blood flow path 46 before deployment of the implant model 42.
Hence, the determination unit 22 can determine a measure of
obstruction of the first blood flow path. It will be appreciated
that possibly the way in which the implant is deployed in the first
blood flow path 46 affects positioning of leaflets 43 of the
implant model 42. Possibly the leaflets 43 do not fully open.
Thereto, the determination unit 22 can calculate leaflet 43
position in the opened position. Thus, the determination unit 22
can take leaflet 43 positioning into account for determining an
open area of the first blood flow path 46 for determining the
measure of obstruction.
[0061] Alternatively, or additionally, the determination unit 22
can determine a pressure drop in the first blood flow path 46 along
the implant model 42. The pressure drop is also representative for
obstruction of the first blood flow path 46 due to the implant
model 42.
[0062] Alternatively, or additionally, the determined hemodynamic
compromise includes leakage of blood in the first blood flow path.
For example, it is possible that with the implant valve leaflets 43
closed blood leaks around the outside of the implanted valve,
between the valve and the surrounding tissue. Then, from the
virtually deployed implant model 42 and the deformed
patient-specific anatomical model 40, the determination unit 22 can
determine a measure of leakage in the first blood flow path in the
deformed patient-specific anatomical model. Thereto, the
determination unit 22 can use calculated fluid pressures in the
cardiac region. It is also possible to use computational fluid
dynamics, CFD.
[0063] It is also possible that the implant valve leaflets 43 do
not fully close due to the way in which the implant is deployed in
the first blood flow path 46. This too may result in leakage of
blood, in the closed position of the leaflets 43. Thereto, the
determination unit 22 can calculate leaflet 43 position in the
closed position. Thus, the determination unit 22 can calculate
leakage.
[0064] The processing unit 2 can further include an assessment unit
24 arranged for determining a measure of risk of the patient
developing hemodynamic problems, such as second blood flow path
obstruction on the basis of the determined deformed models 40, 42.
The determined risk can e.g. be expressed as a percentage, a
number, a level or the like. The processing unit 2 is
communicatively connectable to a presentation unit 26. The
presentation unit 26 in this example is a display to display the
measure of risk of the patient developing hemodynamic compromise to
a user. It will be appreciated that the presentation unit can also
present a representation, such as a numerical and/or graphical
representation, of the obstruction to the user. Alternative, or
additional, presentation units could be used, such as a hardcopy
printer, an email server, a message service, a speaker device,
etc.
[0065] It will be appreciated that the processing unit 2 may be
arranged for applying a calibration. Thereto the processing unit 2
can include a calibration unit 28. Optionally, the predicted
measure of hemodynamic compromise is determined for a plurality of
patients. For each of these patients the predicted measure of
hemodynamic compromise and the occurring or not-occurring of
hemodynamic problems in reality are stored in a calibration
database. From this calibration database a correlation between the
predicted measure of hemodynamic compromise and the occurrence of
hemodynamic problems in real life can be determined. From the
correlation a measure of risk of the patient developing hemodynamic
problems on the basis of the determined hemodynamic compromise can
be determined. It will be appreciated that the calibration database
can be updated over time.
[0066] FIGS. 3a, 3b, 3c show an example wherein the implant model
42 is placed into the patient-specific anatomical model 40 at a
plurality of different locations. In this example the
patient-specific anatomical model 40 includes the region around the
mitral valve 50. Here the first blood flow path 44 extends through
the mitral valve 50. The second blood flow path 46 is formed by the
LVOT and prolongs into the aorta. The native valve leaflets 52 can
be identified in the FIGS. 3a-3c. In this example going from FIGS.
3a to 3b to 3c the implant model 42 is placed at three positions
which are successively shifted by a few millimeters along the
mitral valve. Thereto the processing unit 2 includes a position
variation unit 30. As can be seen in the example of FIG. 3a, the
tips 53 of the native valve leaflets 52 are freely overhanging the
implant model 42. In 3c the native valve leaflets 52, including
their tips 53, are pressed against the LVOT. Therefore, going from
FIG. 3a to FIG. 3c the obstruction gradually increases.
[0067] The assessment unit 24 determines the measure of obstruction
for each of the different locations. From this analysis a user can
learn which position of the implant provides the lowest risk of the
patient developing hemodynamic problems. This information can be
used in planning of the TMVR procedure. It is also possible that
the processing unit 2 selects the position of the implant providing
the lowest risk measure of hemodynamic problems. The processing
unit can present the selected position as preferred the deployment
site 44.
[0068] It will be appreciated that it is also possible that a
plurality of different implant models 42 is provided. Each implant
model 42 can represent geometrical and/or material properties of a
corresponding real-life implant. The implant models 42 may e.g.
differ in size, brand, construction, material or the like. Each of
the implant models can then be placed into the patient specific
anatomical model 40. The measure of hemodynamic compromise, and/or
the risk of the patient developing hemodynamic problems, is then
determined for each of the implant models 42. From this analysis it
can be determined which one of the plurality of implant models has
associated therewith the lowest measure of hemodynamic compromise
and/or the lowest risk of the patient developing hemodynamic
problems. A cardiac valve implant corresponding to the implant
model 42 having the lowest associated measure of hemodynamic
compromise and/or risk of the patient developing hemodynamic
problems can then be selected for a real-life percutaneous
implantation procedure. It will be appreciated that it is also
possible that each of the implant models 42 is placed into the
patient-specific anatomical model 40 at a plurality of different
locations. Thus for each implant model a position of lowest
hemodynamic compromise and/or risk can be determined. The lowest
compromise and/or risk per implant model 42 can then be compared to
select the cardiac valve implant for real-life percutaneous
implantation.
[0069] It is also possible that the patient-specific model 40
includes time information. The patient-specific model may include a
plurality of views, each corresponding to a different moment during
the cardiac cycle. The measure of hemodynamic compromise for the
implant model can be determined for each of the views. Hence, the
measure of hemodynamic compromise can be determined at different
moments during the cardiac cycle.
[0070] It will be appreciated that it is also possible that each of
the implant models 42 is placed into the patient-specific
anatomical model 40 at a plurality of different locations and
analyzed for each of the views. Thus for each implant model a
lowest measure of hemodynamic compromise and/or risk can be
determined among the different locations and during the cardiac
cycle. Also for each implant model a highest measure of hemodynamic
compromise and/or risk can be determined among the different
locations and during the cardiac cycle. The lowest and highest
hemodynamic compromise and/or risk per implant model 42 can then be
compared to select the cardiac valve implant for real-life
percutaneous implantation. As can be seen in FIGS. 2 and 3a-3d,
parts of the anatomy of the cardiac region may also contribute to
the obstruction. For example the pressure of blood flowing through
the first and/or second blood flow path can affect a position of
parts of the anatomy, such as (calcified) native valve leaflets.
According to an aspect, the calculation unit 21 calculates the
deformation of the patient-specific anatomical model 40 as a result
of implant model 42 deployment and fluid pressure. The interaction
of the fluid and the structures of the patient-specific anatomical
model can be included (fluid structure interaction, FSI) in the
calculation of the deformed patient-specific anatomical model. Also
computational fluid dynamics, CFD, can be used for determining the
deformation of the patient-specific anatomical model 40 as a result
of implant model 42 deployment and fluid mechanics inside the blood
flow paths.
[0071] Herein, the invention is described with reference to
specific examples of embodiments of the invention. It will,
however, be evident that various modifications and changes may be
made therein, without departing from the essence of the invention.
For the purpose of clarity and a concise description features are
described herein as part of the same or separate embodiments,
however, alternative embodiments having combinations of all or some
of the features described in these separate embodiments are also
envisaged.
[0072] It will be appreciated that in each of the examples, and in
general, determining the measure of hemodynamic compromise may
include determining a plurality of situations of progressing
deployment of the implant model into the patient-specific
anatomical model. The situations may progressively differ by a
predetermined amount or ratio of deployment. The deployment can
include insertion of the implant model into the patient-specific
anatomical model. The insertion can include travel of a model of a,
collapsed, implant along a vessel. The situations can include
progressively differing positions of insertion up to the intended
deployment position. The deployment can include expansion of the
implant model in the patient-specific anatomical model. The
situations can include progressively differing stages of expansion
of the implant model. For each of the situations the measure of
hemodynamic compromise can be determined as described above. Hence,
all stages of deployment can be modeled. The processing unit may be
arranged to determine the situation of the plurality of situations
in which the determined hemodynamic compromise is least
significant, e.g. lowest, or most significant, e.g. highest. The
processing unit may be arranged to determine the measure of
hemodynamic compromise in the situation of the plurality of
situations in which the determined hemodynamic compromise is least
or most significant for predicting hemodynamic problems.
[0073] It will be appreciated that such determining of a plurality
of situations simulates determining an evolution of the measure of
hemodynamic compromise between the implant model and the
patient-specific anatomical model over time during the process of
deployment.
[0074] It will be appreciated that simulating an evolution of the
measure of hemodynamic compromise over time, may also be performed
for a period of time after deployment, such as days, weeks, months,
or even years after deployment. As such, remodeling of the heart,
due to the heart anatomy changing due to the prolonged presence of
the implant, can be taken into account.
[0075] In the examples, the implant model comprises a finite
element model. It will be appreciated that it is also possible that
the implant model comprises a mesh-free model. In the examples, the
patient-specific anatomical model comprises a finite element model.
It will be appreciated that it is also possible that the
patient-specific anatomical model comprises a mesh-free model. It
will be appreciated that the processing unit, first receiving unit,
conversion unit, second receiving unit, input unit, modelling
system, placing unit, calculation unit, determination unit,
assessment unit, presentation unit, and/or position variation unit
can be embodied as dedicated electronic circuits, possibly
including software code portions. The processing unit, first
receiving unit, conversion unit, second receiving unit, input unit,
modelling system, placing unit, calculation unit, determination
unit, assessment unit, presentation unit, and/or position variation
unit can also be embodied as software code portions executed on,
and e.g. stored in, a memory of, a programmable apparatus such as a
computer, tablet or smartphone.
[0076] Although the embodiments of the invention described with
reference to the drawings comprise computer apparatus and processes
performed in computer apparatus, the invention also extends to
computer programs, particularly computer programs on or in a
carrier, adapted for putting the invention into practice. The
program may be in the form of source or object code or in any other
form suitable for use in the implementation of the processes
according to the invention. The carrier may be any entity or device
capable of carrying the program.
[0077] For example, the carrier may comprise a storage medium, such
as a ROM, for example a CD ROM or a semiconductor ROM, or a
magnetic recording medium, for example a floppy disc or hard disk.
Further, the carrier may be a transmissible carrier such as an
electrical or optical signal which may be conveyed via electrical
or optical cable or by radio or other means, e.g. via the internet
or cloud.
[0078] When a program is embodied in a signal which may be conveyed
directly by a cable or other device or means, the carrier may be
constituted by such cable or other device or means. Alternatively,
the carrier may be an integrated circuit in which the program is
embedded, the integrated circuit being adapted for performing, or
for use in the performance of, the relevant processes.
[0079] However, other modifications, variations, and alternatives
are also possible. The specifications, drawings and examples are,
accordingly, to be regarded in an illustrative sense rather than in
a restrictive sense.
[0080] For the purpose of clarity and a concise description
features are described herein as part of the same or separate
embodiments, however, it will be appreciated that the scope of the
invention may include embodiments having combinations of all or
some of the features described.
[0081] In the claims, any reference sign placed between parentheses
shall not be construed as limiting the claim. The word `comprising`
does not exclude the presence of other features or steps than those
listed in a claim. Furthermore, the words `a` and `an` shall not be
construed as limited to `only one`, but instead are used to mean
`at least one`, and do not exclude a plurality. The mere fact that
certain measures are recited in mutually different claims does not
indicate that a combination of these measures cannot be used to an
advantage.
* * * * *