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Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention

  • Multi-Scale Modeling in the Clinic
  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

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.

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Abbreviations

2PEF:

Two-photon excitation fluorescence

3-D:

Three-dimensional

ABM:

Agent-based model

APD:

Action potential duration

ATP:

Adenosine triphosphate

CARS:

Coherent anti-stokes Raman scattering

CT:

Computerized tomography

CV:

Conduction velocity

CVD:

Cardiovascular disease

DENSE:

Displacement encoding with stimulated echoes

EADs:

Early afterdepolarizations

ECG:

Electrocardiogram

ECM:

Extracellular matrix

HARP:

Harmonic phase

IVUS:

Intravascular ultrasound

MRI:

Magnetic resonance imaging

NO:

Nitric oxide

OCT:

Optical coherence tomography

ODE:

Ordinary differential equation

PDE:

Partial differential equation

PET:

Positron emission tomography

SHG:

Second harmonic generation

SR:

Sarcoplasmic reticulum

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Acknowledgement

The authors acknowledge funding supports from National Science Foundation IUCRC CYBHOR NSF 106022 (Garbey); NSF CMMI 1463390 and CMMI 0954825 (Zhang), National Institute of Health U01EB016638 (Barocas); U01 EB016027 and R01 EB006818 (Eckmann); U01HL119178-01 (Berceli, Garbey, Tran Son Tay); R01HL117990 (Kassab) and U01 HL118738 (Beard and Kassab); P50 GM094503 (Beard), P41 GM103426-19 (Amaro), R01HL105242, and R01HL121754 (McCulloch); and R01HL098028 (Zhang), and FDA Critical Path Initiative (Lochner).

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Zhang, Y., Barocas, V.H., Berceli, S.A. et al. Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention. Ann Biomed Eng 44, 2642–2660 (2016). https://doi.org/10.1007/s10439-016-1628-0

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