TY - JOUR
T1 - Multi-scale Modeling of the Cardiovascular System
T2 - Disease Development, Progression, and Clinical Intervention
AU - Zhang, Yanhang
AU - Barocas, Victor H.
AU - Berceli, Scott A.
AU - Clancy, Colleen E.
AU - Eckmann, David M.
AU - Garbey, Marc
AU - Kassab, Ghassan S.
AU - Lochner, Donna R.
AU - McCulloch, Andrew D.
AU - Tran-Son-Tay, Roger
AU - Trayanova, Natalia A.
N1 - Publisher Copyright:
© 2016, Biomedical Engineering Society.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure–function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.
AB - Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure–function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.
KW - Cardiac mechanics
KW - Cardiovascular fluid mechanics
KW - Constitutive model
KW - Electrophysiological modeling
KW - Extracellular matrix
KW - Mechanical forces
KW - Multi-scale modeling
KW - Pathway network analysis
KW - Vascular mechanics
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U2 - 10.1007/s10439-016-1628-0
DO - 10.1007/s10439-016-1628-0
M3 - Article
C2 - 27138523
AN - SCOPUS:85007386761
SN - 0090-6964
VL - 44
SP - 2642
EP - 2660
JO - Annals of Biomedical Engineering
JF - Annals of Biomedical Engineering
IS - 9
ER -