Cardiac mechanics modeling: recent developments and current challenges

Fuente: arXiv
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Autori principali: Brown, Aaron L., Liu, Ju, Ennis, Daniel B., Marsden, Alison L.
Natura: Preprint
Pubblicazione: 2025
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author Brown, Aaron L.
Liu, Ju
Ennis, Daniel B.
Marsden, Alison L.
author_facet Brown, Aaron L.
Liu, Ju
Ennis, Daniel B.
Marsden, Alison L.
contents Patient-specific computational models of the heart are powerful tools for cardiovascular research and medicine, with demonstrated applications in treatment planning, device evaluation, and surgical decision-making. Yet constructing such models is inherently difficult, reflecting the extraordinary complexity of the heart itself. Numerous considerations are required, including reconstructing the anatomy from medical images, representing myocardial mesostructure, capturing material behavior, defining model geometry and boundary conditions, coupling multiple physics, and selecting numerical methods. Many of these choices involve a tradeoff between physiological fidelity and modeling complexity. In this review, we summarize recent advances and unresolved questions in each of these areas, with particular emphasis on cardiac tissue mechanics. We argue that clarifying which complexities are essential, and which can be safely simplified, will be key to enabling clinical translation of these models.
format Preprint
id arxiv_https___arxiv_org_abs_2509_07971
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cardiac mechanics modeling: recent developments and current challenges
Brown, Aaron L.
Liu, Ju
Ennis, Daniel B.
Marsden, Alison L.
Medical Physics
Patient-specific computational models of the heart are powerful tools for cardiovascular research and medicine, with demonstrated applications in treatment planning, device evaluation, and surgical decision-making. Yet constructing such models is inherently difficult, reflecting the extraordinary complexity of the heart itself. Numerous considerations are required, including reconstructing the anatomy from medical images, representing myocardial mesostructure, capturing material behavior, defining model geometry and boundary conditions, coupling multiple physics, and selecting numerical methods. Many of these choices involve a tradeoff between physiological fidelity and modeling complexity. In this review, we summarize recent advances and unresolved questions in each of these areas, with particular emphasis on cardiac tissue mechanics. We argue that clarifying which complexities are essential, and which can be safely simplified, will be key to enabling clinical translation of these models.
title Cardiac mechanics modeling: recent developments and current challenges
topic Medical Physics
url https://arxiv.org/abs/2509.07971