Journal of Biomechanical Science and Engineering
Online ISSN : 1880-9863
ISSN-L : 1880-9863
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Prediction of hemodynamics and cardiac function in aortic stenosis patients with heart failure using a patient-specific hemodynamic model
Kenshu MAEDAKoichi SUGHIMOTODaiki KODAToru MIKIHao LIU
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ジャーナル オープンアクセス
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2026 年 21 巻 1 号 p. 25-00309

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The aortic valve plays a crucial role in cardiac function by opening synchronously with left ventricular contraction to pump blood into the aorta and closing during left ventricular relaxation to prevent blood regurgitation. Aortic valve stenosis (AS), resulting from congenital bicuspid valves or age-related calcification, can cause symptoms of heart failure (HF) or angina. In severe cases, angina may develop even in the absence of coronary artery stenosis, potentially leading to impaired cardiac function or worsening HF. In this study, we developed a patient-specific hemodynamic computational fluid dynamics model by adjusting internal parameters such as vessel length, cardiac resistance, and cardiac elastance, based on previously established 0D-1D multiscale cardiovascular hemodynamic models developed by our research team. Seven patients with both diastolic and systolic HF were included, and their hemodynamic parameters were used to construct patient-specific models. This study aims to predict coronary hemodynamics and cardiac function under conditions of AS using patient-specific models of individuals with HF. Hemodynamics and coronary circulation were evaluated under various conditions by imposing AS on the HF models. As a result, coronary blood flow was decreased by approximately 20% in HF patients under AS, compared to a 7% reduction observed in healthy individuals. These simulation results suggest that AS in HF patients leads to a reduction in coronary blood flow and may contribute to myocardial ischemia, even in the absence of coronary artery stenosis. Furthermore, patient-specific hemodynamic models may offer a valuable non-invasive approach for evaluating cardiovascular risk and guiding individualized treatment strategies.

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© 2026 by The Japan Society of Mechanical Engineers

This article is licensed under a Creative Commons [Attribution 4.0 International] license.
https://creativecommons.org/licenses/by/4.0/
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