Volume 14, Issue 6
A Parallel Numerical Method for Risk Assessment of Myocardial Infarction During Liver Transplantation: A Case Study

Adv. Appl. Math. Mech., 14 (2022), pp. 1225-1245.

Published online: 2022-08

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• Abstract

Coronary artery disease is a devastating complication of some patients undergoing liver transplantation. Anesthesia, anhepatic blood flow occlusion, and reperfusion of the liver can cause severe fluctuations in hemodynamics. However, the vast majority of liver transplant patients cannot undergo invasive coronary examinations due to their critical illness and abnormal coagulation function. In this paper, we present a retrospective case of acute myocardial infarction during surgery in order to demonstrate a noninvasive method to obtain coronary hemodynamic functional information based on scalable computational fluid dynamics technology. A $P_1−P_1$ stabilized finite element method and second-order backward differentiation formula are applied to discretize the time-dependent Navier-Stokes equations in the spatial and temporal directions, respectively. A Windkessel model constructed based on the measured clinic data is used to characterize the outlet blood flow. We then apply a parallel Newton-Krylov method with a restricted additive Schwarz preconditioner to accelerate the timeliness of the simulation. The simulated functional indicator successfully verifies the myocardial ischemia in the anhepatic phase of liver transplantation. We also present the parallel performance of the algorithm on a supercomputer, and the results show that the proposed solver achieves over 55% parallel efficiency with 3840 processor cores.

• Keywords

Numerical simulation, coronary artery disease, computational fluid dynamics, liver transplant, Newton-Krylov-Schwarz algorithm.

76D05, 76F65, 65M55, 65Y05

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@Article{AAMM-14-1225, author = {Zhengzheng and Yan and and 24212 and and Zhengzheng Yan and Dandan and Shang and and 24213 and and Dandan Shang and Jingzhi and Li and and 24214 and and Jingzhi Li and Rongliang and Chen and and 24215 and and Rongliang Chen}, title = {A Parallel Numerical Method for Risk Assessment of Myocardial Infarction During Liver Transplantation: A Case Study}, journal = {Advances in Applied Mathematics and Mechanics}, year = {2022}, volume = {14}, number = {6}, pages = {1225--1245}, abstract = {

Coronary artery disease is a devastating complication of some patients undergoing liver transplantation. Anesthesia, anhepatic blood flow occlusion, and reperfusion of the liver can cause severe fluctuations in hemodynamics. However, the vast majority of liver transplant patients cannot undergo invasive coronary examinations due to their critical illness and abnormal coagulation function. In this paper, we present a retrospective case of acute myocardial infarction during surgery in order to demonstrate a noninvasive method to obtain coronary hemodynamic functional information based on scalable computational fluid dynamics technology. A $P_1−P_1$ stabilized finite element method and second-order backward differentiation formula are applied to discretize the time-dependent Navier-Stokes equations in the spatial and temporal directions, respectively. A Windkessel model constructed based on the measured clinic data is used to characterize the outlet blood flow. We then apply a parallel Newton-Krylov method with a restricted additive Schwarz preconditioner to accelerate the timeliness of the simulation. The simulated functional indicator successfully verifies the myocardial ischemia in the anhepatic phase of liver transplantation. We also present the parallel performance of the algorithm on a supercomputer, and the results show that the proposed solver achieves over 55% parallel efficiency with 3840 processor cores.

}, issn = {2075-1354}, doi = {https://doi.org/10.4208/aamm.OA-2021-0214}, url = {http://global-sci.org/intro/article_detail/aamm/20846.html} }
TY - JOUR T1 - A Parallel Numerical Method for Risk Assessment of Myocardial Infarction During Liver Transplantation: A Case Study AU - Yan , Zhengzheng AU - Shang , Dandan AU - Li , Jingzhi AU - Chen , Rongliang JO - Advances in Applied Mathematics and Mechanics VL - 6 SP - 1225 EP - 1245 PY - 2022 DA - 2022/08 SN - 14 DO - http://doi.org/10.4208/aamm.OA-2021-0214 UR - https://global-sci.org/intro/article_detail/aamm/20846.html KW - Numerical simulation, coronary artery disease, computational fluid dynamics, liver transplant, Newton-Krylov-Schwarz algorithm. AB -

Coronary artery disease is a devastating complication of some patients undergoing liver transplantation. Anesthesia, anhepatic blood flow occlusion, and reperfusion of the liver can cause severe fluctuations in hemodynamics. However, the vast majority of liver transplant patients cannot undergo invasive coronary examinations due to their critical illness and abnormal coagulation function. In this paper, we present a retrospective case of acute myocardial infarction during surgery in order to demonstrate a noninvasive method to obtain coronary hemodynamic functional information based on scalable computational fluid dynamics technology. A $P_1−P_1$ stabilized finite element method and second-order backward differentiation formula are applied to discretize the time-dependent Navier-Stokes equations in the spatial and temporal directions, respectively. A Windkessel model constructed based on the measured clinic data is used to characterize the outlet blood flow. We then apply a parallel Newton-Krylov method with a restricted additive Schwarz preconditioner to accelerate the timeliness of the simulation. The simulated functional indicator successfully verifies the myocardial ischemia in the anhepatic phase of liver transplantation. We also present the parallel performance of the algorithm on a supercomputer, and the results show that the proposed solver achieves over 55% parallel efficiency with 3840 processor cores.

Zhengzheng Yan, Dandan Shang, Jingzhi Li & Rongliang Chen. (2022). A Parallel Numerical Method for Risk Assessment of Myocardial Infarction During Liver Transplantation: A Case Study. Advances in Applied Mathematics and Mechanics. 14 (6). 1225-1245. doi:10.4208/aamm.OA-2021-0214
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