Annals of Biomedical Engineering

, Volume 44, Issue 9, pp 2642–2660 | Cite as

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

  • Yanhang Zhang
  • Victor H. Barocas
  • Scott A. Berceli
  • Colleen E. Clancy
  • David M. Eckmann
  • Marc Garbey
  • Ghassan S. Kassab
  • Donna R. Lochner
  • Andrew D. McCulloch
  • Roger Tran-Son-Tay
  • Natalia A. Trayanova
Multi-Scale Modeling in the Clinic


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.


Cardiac mechanics Electrophysiological modeling Cardiovascular fluid mechanics Vascular mechanics Extracellular matrix Mechanical forces Pathway network analysis Constitutive model Multi-scale modeling 



Two-photon excitation fluorescence




Agent-based model


Action potential duration


Adenosine triphosphate


Coherent anti-stokes Raman scattering


Computerized tomography


Conduction velocity


Cardiovascular disease


Displacement encoding with stimulated echoes


Early afterdepolarizations




Extracellular matrix


Harmonic phase


Intravascular ultrasound


Magnetic resonance imaging


Nitric oxide


Optical coherence tomography


Ordinary differential equation


Partial differential equation


Positron emission tomography


Second harmonic generation


Sarcoplasmic reticulum



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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Copyright information

© Biomedical Engineering Society 2016

Authors and Affiliations

  • Yanhang Zhang
    • 1
  • Victor H. Barocas
    • 2
  • Scott A. Berceli
    • 3
  • Colleen E. Clancy
    • 4
  • David M. Eckmann
    • 5
  • Marc Garbey
    • 6
  • Ghassan S. Kassab
    • 7
  • Donna R. Lochner
    • 8
  • Andrew D. McCulloch
    • 9
  • Roger Tran-Son-Tay
    • 10
  • Natalia A. Trayanova
    • 11
  1. 1.Departments of Mechanical Engineering and Biomedical EngineeringBoston UniversityBostonUSA
  2. 2.Department of Biomedical EngineeringUniversity of MinnesotaMinneapolisUSA
  3. 3.Department of SurgeryUniversity of FloridaGainesvilleUSA
  4. 4.Department of PharmacologyUniversity of CaliforniaDavisUSA
  5. 5.Department of Anesthesiology and Critical CareUniversity of PennsylvaniaPhiladelphiaUSA
  6. 6.Center for Computational SurgeryMethodist Hospital Research InstituteHoustonUSA
  7. 7.California Medical Innovations InstituteSan DiegoUSA
  8. 8.Office of Science and Engineering Laboratories, Center for Devices and Radiological HealthU.S. Food and Drug AdministrationSilver SpringUSA
  9. 9.Departments of Bioengineering and MedicineUniversity of CaliforniaSan DiegoUSA
  10. 10.Departments of Mechanical & Aerospace Engineering and Biomedical EngineeringUniversity of FloridaGainesvilleUSA
  11. 11.Department of Biomedical Engineering and Institute for Computational MedicineJohns Hopkins UniversityBaltimoreUSA

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