An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation
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An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation. / Ooida, Junichi; Kiyohara, Naoki; Noguchi, Hironaga; Oguchi, Yuichiro; Nagane, Kohei; Sakaguchi, Takuya; Aoyama, Gakuto; Shige, Fumimasa; Chapman, James V.; Asami, Masahiko; Kofoed, Klaus Fuglsang; Pham, Michael Huy Cuong; Suzuki, Koshiro.
In: Journal of Biomechanical Engineering, Vol. 146, No. 2, 021004, 2024.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation
AU - Ooida, Junichi
AU - Kiyohara, Naoki
AU - Noguchi, Hironaga
AU - Oguchi, Yuichiro
AU - Nagane, Kohei
AU - Sakaguchi, Takuya
AU - Aoyama, Gakuto
AU - Shige, Fumimasa
AU - Chapman, James V.
AU - Asami, Masahiko
AU - Kofoed, Klaus Fuglsang
AU - Pham, Michael Huy Cuong
AU - Suzuki, Koshiro
N1 - Publisher Copyright: © 2024 American Society of Mechanical Engineers (ASME). All rights reserved.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - edge-to-edge repair
KW - in silico
KW - MitraClip
KW - mitral regurgitation
KW - patient-specific model
U2 - 10.1115/1.4064055
DO - 10.1115/1.4064055
M3 - Journal article
C2 - 37978048
AN - SCOPUS:85180005318
VL - 146
JO - Journal of Biomechanical Engineering
JF - Journal of Biomechanical Engineering
SN - 0148-0731
IS - 2
M1 - 021004
ER -
ID: 389897917