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Precision medicine in human heart modeling
Authors:Peirlinck  M  Costabal  F Sahli  Yao  J  Guccione  J M  Tripathy  S  Wang  Y  Ozturk  D  Segars  P  Morrison  T M  Levine  S  Kuhl  E
Institution:1.Department of Mechanical Engineering, Stanford University, Stanford, California, USA
;2.Department of Mechanical Engineering, Pontificia Universidad Catholica de Chile, Santiago, Chile
;3.Dassault Systèmes Simulia Corporation, Johnston, Rhode Island, USA
;4.University of California, San Francisco, California, USA
;5.Edwards Lifesciences, Irvine, California, USA
;6.Thornton Tomasetti Inc., Santa Clara, California, USA
;7.Capvidia, Leuven, Belgium
;8.Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, Durham, North Carolina, USA
;9.Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
;10.Departments of Mechanical Engineering and Bioengineering, Stanford University, Stanford, California, USA
;
Abstract:

Precision medicine is a new frontier in healthcare that uses scientific methods to customize medical treatment to the individual genes, anatomy, physiology, and lifestyle of each person. In cardiovascular health, precision medicine has emerged as a promising paradigm to enable cost-effective solutions that improve quality of life and reduce mortality rates. However, the exact role in precision medicine for human heart modeling has not yet been fully explored. Here, we discuss the challenges and opportunities for personalized human heart simulations, from diagnosis to device design, treatment planning, and prognosis. With a view toward personalization, we map out the history of anatomic, physical, and constitutive human heart models throughout the past three decades. We illustrate recent human heart modeling in electrophysiology, cardiac mechanics, and fluid dynamics and highlight clinically relevant applications of these models for drug development, pacing lead failure, heart failure, ventricular assist devices, edge-to-edge repair, and annuloplasty. With a view toward translational medicine, we provide a clinical perspective on virtual imaging trials and a regulatory perspective on medical device innovation. We show that precision medicine in human heart modeling does not necessarily require a fully personalized, high-resolution whole heart model with an entire personalized medical history. Instead, we advocate for creating personalized models out of population-based libraries with geometric, biological, physical, and clinical information by morphing between clinical data and medical histories from cohorts of patients using machine learning. We anticipate that this perspective will shape the path toward introducing human heart simulations into precision medicine with the ultimate goals to facilitate clinical decision making, guide treatment planning, and accelerate device design.

Keywords:
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