Abstract

In recent years, transcatheter edge-to-edge repair (TEER) has been widely adopted as an effective treatment for mitral regurgitation (MR). The aim of this study is to develop a personalized in silico model to predict the effect of edge-to-edge repair in advance to the procedure for each individual patient. For this purpose, we propose a combination of a valve deformation model for computing the mitral valve (MV) orifice area (MVOA) and a lumped parameter model for the hemodynamics, specifically mitral regurgitation volume (RVol). Although we cannot obtain detailed information on the three-dimensional flow field near the mitral valve, we can rapidly simulate the important medical parameters for the clinical decision support. In the present method, we construct the patient-specific pre-operative models by using the parameter optimization and then simulate the postoperative state by applying the additional clipping condition. The computed preclip MVOAs show good agreement with the clinical measurements, and the correlation coefficient takes 0.998. In addition, the MR grade in terms of RVol also has good correlation with the grade by ground truth MVOA. Finally, we try to investigate the applicability for the predicting the postclip state. The simulated valve shapes clearly show the well-known double orifice and the improvement of the MVOA, compared with the preclip state. Similarly, we confirmed the improved reverse flow and MR grade in terms of RVol. A total computational time is approximately 8 h by using general-purpose PC. These results obviously indicate that the present in silico model has good capability for the assessment of edge-to-edge repair.

Issue Section:
Research Papers
Keywords:
in silico, patient-specific model, mitral regurgitation, edge-to-edge repair, MitraClip
Topics:
Deformation, Hemodynamics, Simulation, Valves, Maintenance, Optimization, Pressure

References

1.
Yadgir
,
S.
,
Johnson
,
C. O.
,
Aboyans
,
V.
,
Adebayo
,
O. M.
,
Adedoyin
,
R. A.
,
Afarideh
,
M.
,
Alahdab
,
F.
, et al.,
2020
, “
Global, Regional, and National Burden of Calcific Aortic Valve and Degenerative Mitral Valve Diseases, 1990–2017
,”
Circulation
,
141
(
21
), pp.
1670
–
1680
.10.1161/CIRCULATIONAHA.119.043391
2.
Deuschl
,
F.
,
Schofer
,
N.
,
Lubos
,
E.
,
Blankenberg
,
S.
, and Schäfer, U.,
2016
, “
Critical Evaluation of the MitraClip System in the Management of Mitral Regurgitation
,”
Vasc. Health Risk Manage.
, 12, p.
1
.10.2147/VHRM.S65185
3.
Corpataux
,
N.
,
Winkel
,
M.
,
Kassar
,
M.
,
Brugger
,
N.
,
Windecker
,
S.
, and
Praz
,
F.
,
2020
, “
The PASCAL Device-Early Experience With a Leaflet Approximation Device: What Are the Benefits/Limitations Compared With the MitraClip?
,”
Curr. Cardiol. Rep.
,
22
(
8
), pp.
1
–
7
.10.1007/s11886-020-01305-1
4.
Feldman
,
T.
,
Foster
,
E.
,
Glower
,
D. D.
,
Kar
,
S.
,
Rinaldi
,
M. J.
,
Fail
,
P. S.
,
Smalling
,
R. W.
, et al.,
2011
, “
Percutaneous Repair or Surgery for Mitral Regurgitation
,”
N. Engl. J. Med.
,
364
(
15
), pp.
1395
–
1406
.10.1056/NEJMoa1009355
5.
Chakravarty
,
T.
,
Makar
,
M.
,
Patel
,
D.
,
Oakley
,
L.
,
Yoon
,
S. H.
,
Stegic
,
J.
,
Singh
,
S.
,
Skaf
,
S.
,
Nakamura
,
M.
, and
Makkar
,
R. R.
,
2020
, “
Transcatheter Edge-to-Edge Mitral Valve Repair With the MitraClip G4 System
,”
JACC: Cardiovasc. Interventions
,
13
(
20
), pp.
2402
–
2414
.10.1016/j.jcin.2020.06.053
6.
McQueen
,
D. M.
, and
Peskin
,
C. S.
,
2002
, “
Heart Simulation by an Immersed Boundary Method With Formal Second-Order Accuracy and Reduced Numerical Viscosity
,”
Mechanics for a New Mellennium
,
H.
Aref
 and
J. W.
Phillips
, eds.,
Springer
,
Dordrecht
, The Netherlands, pp.
429
–
444
.
7.
Mao
,
W.
,
Caballero
,
A.
,
McKay
,
R.
,
Primiano
,
C.
, and
Sun
,
W.
,
2017
, “
Fully-Coupled Fluid-Structure Interaction Simulation of the Aortic and Mitral Valves in a Realistic 3D Left Ventricle Model
,”
Plos One
,
12
(
9
), p.
e0184729
.10.1371/journal.pone.0184729
8.
Kamakoti
,
R.
,
Dabiri
,
Y.
,
Wang
,
D. D.
,
Guccione
,
J.
, and
Kassab
,
G. S.
,
2019
, “
Numerical Simulations of MitraClip Placement: Clinical Implications
,”
Sci. Rep.
,
9
(
1
), p.
15823
.10.1038/s41598-019-52342-y
9.
Caballero
,
A.
,
Mao
,
W.
,
McKay
,
R.
,
Primiano
,
C.
,
Hashim
,
S.
, and
Sun
,
W.
,
2018
, “
New Insights Into Mitral Heart Valve Prolapse After Chordae Rupture Through Fluid–Structure Interaction Computational Modeling
,”
Sci. Rep.
,
8
(
1
), p.
17306
.10.1038/s41598-018-35555-5
10.
Mansi
,
T.
,
Voigt
,
I.
,
Georgescu
,
B.
,
Zheng
,
X.
,
Mengue
,
E. A.
,
Hackl
,
M.
,
Ionasec
,
R. I.
,
Noack
,
T.
,
Seeburger
,
J.
, and
Comaniciu
,
D.
,
2012
, “
An Integrated Framework for Finite-Element Modeling of Mitral Valve Biomechanics From Medical Images: Application to MitralClip Intervention Planning
,”
Med. Image Anal.
,
16
(
7
), pp.
1330
–
1346
.10.1016/j.media.2012.05.009
11.
Pham
,
T.
,
Kong
,
F.
,
Martin
,
C.
,
Wang
,
Q.
,
Primiano
,
C.
,
McKay
,
R.
,
Elefteriades
,
J.
, and
Sun
,
W.
,
2017
, “
Finite Element Analysis of Patient-Specific Mitral Valve With Mitral Regurgitation
,”
Cardiovasc. Eng. Technol.
,
8
(
1
), pp.
3
–
16
.10.1007/s13239-016-0291-9
12.
Hammer
,
P. E.
,
del Nido
,
P. J.
, and
Howe
,
R. D.
,
2011
, “
Anisotropic Mass-Spring Method Accurately Simulates Mitral Valve Closure From Image-Based Models
,”
Functional Imaging and Modeling of the Heart
,
D. N.
Metaxas
 and
L.
Axel
, eds.,
Springer
,
Berlin Heidelberg, Berlin, Heidelberg
, pp.
233
–
240
.
13.
Pappalardo
,
O.
,
Sturla
,
F.
,
Onorati
,
F.
,
Puppini
,
G.
,
Selmi
,
M.
,
Luciani
,
G.
,
Faggian
,
G.
,
Redaelli
,
A.
, and
Votta
,
E.
,
2017
, “
Mass-Spring Models for the Simulation of Mitral Valve Function: Looking for a Trade-Off Between Reliability and Time-Efficiency
,”
Med. Eng. Phys.
,
47
, pp.
93
–
104
.10.1016/j.medengphy.2017.07.001
14.
Frank
,
O.
,
1899
, “
Die Grundform Des Arteriellen Pulses
,”
Z. Für Biol.
,
37
, pp.
483
–
526
.https://www.semanticscholar.org/paper/Diegrundform-des-arteriellen-pulses-Frank/3835cd54f2147da36db7b44d9db51a05dc5aa51e
15.
Ursino
,
M.
,
1998
, “
Interaction Between Carotid Baroregulation and the Pulsating Heart: A Mathematical Model
,”
Am. J. Physiol.-Heart Circ. Physiol.
,
275
(
5
), pp.
H1733
–
H1747
.10.1152/ajpheart.1998.275.5.H1733
16.
Pant
,
S.
,
Corsini
,
C.
,
Baker
,
C.
,
Hsia
,
T.-Y.
,
Pennati
,
G.
, and
Vignon-Clementel
,
I. E.
,
2016
, “
Data Assimilation and Modelling of Patient-Specific Single-Ventricle Physiology With and Without Valve Regurgitation
,”
J. Biomech.
,
49
(
11
), pp.
2162
–
2173
.10.1016/j.jbiomech.2015.11.030
17.
Zhang
,
X.
,
Noda
,
S.
,
Himeno
,
R.
, and
Liu
,
H.
,
2016
, “
Cardiovascular Disease-Induced Thermal Responses During Passive Heat Stress: An Integrated Computational Study
,”
Int. J. Numer. Methods Biomed. Eng.
,
32
(
11
), p.
e02768
.10.1002/cnm.2768
18.
Pant
,
S.
,
Corsini
,
C.
,
Baker
,
C.
,
Hsia
,
T.-Y.
,
Pennati
,
G.
, and
Vignon-Clementel
,
I. E.
,
2018
, “
A Lumped Parameter Model to Study Atrioventricular Valve Regurgitation in Stage 1 and Changes Across Stage 2 Surgery in Single Ventricle Patients
,”
IEEE Trans. Biomed. Eng.
,
65
(
11
), pp.
2450
–
2458
.10.1109/TBME.2018.2797999
19.
Aoyama
,
G.
,
Zhao
,
L.
,
Zhao
,
S.
,
Xue
,
X.
,
Zhong
,
Y.
,
Yamauchi
,
H.
,
Tsukihara
,
H.
, et al.,
2022
, “
Automatic Aortic Valve Cusps Segmentation From CT Images Based on the Cascading Multiple Deep Neural Networks
,”
J. Imaging
,
8
(
1
). p.
11
.10.3390/jimaging8010011
20.
Masuda
,
Y.
,
Ishikawa
,
R.
,
Tanaka
,
T.
,
Aoyama
,
G.
,
Kawashima
,
K.
,
Chapman
,
J.
,
Asami
,
M.
, et al.,
2023
, “
CNN-Based Fully Automatic Mitral Valve Extraction Using CT Images and Existence Probability Maps
,”
arXiv:2305.00627
.10.48550/arXiv.2305.00627
21.
Votta
,
E.
,
Caiani
,
E.
,
Veronesi
,
F.
,
Soncini
,
M.
,
Montevecchi
,
F. M.
, and
Redaelli
,
A.
,
2008
, “
Mitral Valve Finite-Element Modelling From Ultrasound Data: A Pilot Study for a New Approach to Understand Mitral Function and Clinical Scenarios
,”
Philos. Trans. R. Soc., A
,
366
(
1879
), pp.
3411
–
3434
.10.1098/rsta.2008.0095
22.
Lim
,
K. H.
,
Yeo
,
J. H.
, and
Duran
,
C. M. G.
,
2005
, “
Three-Dimensional Asymmetrical Modeling of the Mitral Valve: A Finite Element Study With Dynamic Boundaries
,”
J. Heart Valve Dis.
,
14
(
3
), pp.
386
–
392
.https://pubmed.ncbi.nlm.nih.gov/15974534/
23.
Lau
,
K.
,
Díaz-Zuccarini
,
V.
,
Scambler
,
P.
, and
Burriesci
,
G.
,
2011
, “
Fluid-Structure Interaction Study of the Edge-to-Edge Repair Technique on the Mitral Valve
,”
J. Biomech.
,
44
(
13
), pp.
2409
–
2417
.10.1016/j.jbiomech.2011.06.030
24.
Toma
,
M.
,
Jensen
,
M.
,
Einstein
,
D.
,
Yoganathan
,
A.
,
Cøchran
,
R.
, and
Kunzelman
,
K.
,
2016
, “
Fluid-Structure Interaction Analysis of Papillary Muscle Forces Using a Comprehensive Mitral Valve Model With 3D Chordal Structure
,”
Ann. Biomed. Eng.
,
44
(
4
), pp.
942
–
953
.10.1007/s10439-015-1385-5
25.
Sturla
,
F.
,
Redaelli
,
A.
,
Puppini
,
G.
,
Onorati
,
F.
,
Faggian
,
G.
, and
Votta
,
E.
,
2015
, “
Functional and Biomechanical Effects of the Edge-to-Edge Repair in the Setting of Mitral Regurgitation: Consolidated Knowledge and Novel Tools to Gain Insight Into Its Percutaneous Implementation
,”
Cardiovasc. Eng. Technol.
,
6
(
2
), pp.
117
–
140
.10.1007/s13239-014-0208-4
26.
Rego
,
B.
,
Khalighi
,
A.
,
Lai
,
E.
,
Gorman
,
R.
,
Gorman
,
J. R.
, and
Sacks
,
M.
,
2022
, “
In Vivo Assessment of Mitral Valve Leaflet Remodelling Following Myocardial Infarction
,”
Sci. Rep.
,
12
(
1
), p.
18012
.10.1038/s41598-022-22790-0
27.
Stevanella
,
M.
,
Votta
,
E.
, and
Redaelli
,
A.
,
2009
, “
Mitral Valve Finite Element Modeling: Implications of Tissues' Nonlinear Response and Annular Motion
,”
ASME J. Biomech. Eng.
,
131
(
12
), p.
121010
.10.1115/1.4000107
28.
Mynard
,
J. P.
,
Davidson
,
M. R.
,
Penny
,
D. J.
, and
Smolich
,
J. J.
,
2012
, “
A Simple, Versatile Valve Model for Use in Lumped Parameter and One-Dimensional Cardiovascular Models
,”
Int. J. Numer. Methods Biomed. Eng.
,
28
(
6–7
), pp.
626
–
641
.10.1002/cnm.1466
29.
Hansen
,
N.
, and
Ostermeier
,
A.
,
1996
, “
Adapting Arbitrary Normal Mutation Distributions in Evolution Strategies: The Covariance Matrix Adaptation
,”
Proceedings of IEEE International Conference on Evolutionary Computation
, Nagoya, Japan, May 20–22, pp.
312
–
317
.10.1109/ICEC.1996.542381
30.
Hansen
,
N.
, and
Kern
,
S.
,
2004
, “
Evaluating the CMA Evolution Strategy on Multimodal Test Functions
,”
Parallel Problem Solving From Nature - PPSN VIII
,
X.
Yao
,
E. K.
Burke
,
J. A.
Lozano
,
J.
Smith
,
J. J.
Merelo-Guervós
,
J. A.
Bullinaria
,
J. E.
Rowe
,
P.
Tiňo
,
A.
Kabán
, and
H.-P.
Schwefel
, eds.,
Springer
,
Berlin, Heidelberg
, pp.
282
–
291
.
31.
Kelly
,
R. P.
,
Ting
,
C. T.
,
Yang
,
T. M.
,
Liu
,
C. P.
,
Maughan
,
W. L.
,
Chang
,
M. S.
, and
Kass
,
D. A.
,
1992
, “
Effective Arterial Elastance as Index of Arterial Vascular Load in Humans
,”
Circulation
,
86
(
2
), pp.
513
–
521
.10.1161/01.CIR.86.2.513
32.
Chen
,
C.
,
Fetics
,
B.
,
Nevo
,
E.
,
Rochitte
,
C.
,
Chiou
,
K.
,
Ding
,
P.
,
Kawaguchi
,
M.
, and
Kass
,
D.
,
2001
, “
Noninvasive Single-Beat Determination of Left Ventricular End-Systolic Elastance in Humans
,”
J. Am. Coll. Cardiol.
,
38
(
7
), pp.
2028
–
2034
.10.1016/S0735-1097(01)01651-5
33.
Nelder
,
J. A.
, and
Mead
,
R.
,
1965
, “
A Simplex Method for Function Minimization
,”
Comput. J.
,
7
(
4
), pp.
308
–
313
.10.1093/comjnl/7.4.308
34.
Gao
,
F.
, and
Han
,
L.
,
2012
, “
Implementing the Nelder-Mead Simplex Algorithm With Adaptive Parameters
,”
Comput. Optim. Appl.
,
51
(
1
), pp.
259
–
277
.10.1007/s10589-010-9329-3
35.
Caballero
,
A.
,
Mao
,
W.
,
McKay
,
R.
,
Hahn
,
R.
, and
Sun
,
W.
,
2020
, “
A Comprehensive Engineering Analysis of Left Heart Dynamics After MitraClip in a Functional Mitral Regurgitation Patient
,”
Front. Physiol.
,
11
, p.
432
.10.3389/fphys.2020.00432
36.
Caballero
,
A.
,
Qin
,
T.
,
Hahn
,
R.
,
McKay
,
R.
, and
Sun
,
W.
,
2022
, “
Quantification of Mitral Regurgitation After Transcatheter Edge-to-Edge Repair: Comparison of Echocardiography and Patient-Specific in Silico Models
,”
Comput. Biol. Med.
,
148
, p.
105855
.10.1016/j.compbiomed.2022.105855
37.
Zoghbi
,
W. A.
,
Adams
,
D.
,
Bonow
,
R. O.
,
Enriquez-Sarano
,
M.
,
Foster
,
E.
,
Grayburn
,
P. A.
,
Hahn
,
R. T.
, et al.,
2017
, “
Recommendations for Noninvasive Evaluation of Native Valvular Regurgitation: A Report From the American Society of Echocardiography Developed in Collaboration With the Society for Cardiovascular Magnetic Resonance
,”
J. Am. Soc. Echocardiography
,
30
(
4
), pp.
303
–
371
.10.1016/j.echo.2017.01.007
38.
Braunwald
,
E.
,
1969
, “
Mitral Regurgitation
,”
N. Engl. J. Med.
,
281
(
8
), pp.
425
–
433
.10.1056/NEJM196908212810807
39.
Chiampan
,
A.
,
Nahum
,
J.
,
Leye
,
M.
,
Oziel
,
J.
,
Cueff
,
C.
,
Brochet
,
E.
,
Iung
,
B.
,
Rossi
,
A.
,
Vahanian
,
A.
, and
Messika-Zeitoun
,
D.
,
2012
, “
Determinants of Regurgitant Volume in Mitral Regurgitation: Contrasting Effect of Similar Effective Regurgitant Orifice Area in Functional and Organic Mitral Regurgitation
,”
Eur. Heart J. - Cardiovasc. Imaging
,
13
(
4
), pp.
324
–
329
.10.1093/ejechocard/jer244
Copyright © 2024 by ASME
You do not currently have access to this content.