ArticleMathematics (Basel, Switzerland)2022
An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics.
Article in Mathematics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Technologies, Clinical Applications, and Implementation Barriers of Digital Twins in Precision Cardiology: Systematic Review.JMIR cardio · 2026Pooled it
- Enhancing randomized clinical trials with digital twins.NPJ systems biology and applications · 2025Review
- A scoping review of human digital twins in healthcare applications and usage patterns.NPJ digital medicine · 2025Article
- Article
- Computational modelling for improved translation of cardiac inotropic and lusitropic drug effects from rats to humans.Journal of pharmacological and toxicological methods · 2025Article
- Cardiovascular care with digital twin technology in the era of generative artificial intelligence.European heart journal · 2024Review
- Immune digital twins for complex human pathologies: applications, limitations, and challenges.NPJ systems biology and applications · 2024Review
- Definitions and Characteristics of Patient Digital Twins Being Developed for Clinical Use: Scoping Review.Journal of medical Internet research · 2024Article
- A computational model reveals an early transient decrease in fiber cross-linking that unlocks adult regeneration.NPJ Regenerative medicine · 2024Article
- Bridging the gap between human beings and digital twins in radiology.European radiology · 2024Article
- Evolution of digital twins in precision health applications: a scoping review study.Research square · 2024Article
- Navigating the Landscape of Digital Twins in Medicine: A Relational Bioethical Inquiry.Asian bioethics review · 2024Article
- Digital twinning of cardiac electrophysiology for congenital heart disease.Journal of the Royal Society, Interface · 2024Article
- Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations.NPJ digital medicine · 2024Article
- Digital Twins of Biological Systems: A Narrative Review.IEEE open journal of engineering in medicine and biology · 2024Article
- Digital twinning of cardiac electrophysiology for congenital heart disease.bioRxiv : the preprint server for biology · 2023Article
- Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems.Biomimetics (Basel, Switzerland) · 2023Review
- A coupling strategy for a first 3D-1D model of the cardiovascular system to study the effects of pulse wave propagation on cardiac function.Computational mechanics · 2022Article
- The Digital Twin in Medicine: A Key to the Future of Healthcare?Frontiers in medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
Personalised computer models of cardiac function, referred to as cardiac digital twins, are envisioned to play an important role in clinical precision therapies of cardiovascular diseases. A major obstacle hampering clinical translation involves the significant computational costs involved in the personalisation of biophysically detailed mechanistic models that require the identification of high-dimensional parameter vectors. An important aspect to identify in electromechanics (EM) models are active mechanics parameters that govern cardiac contraction and relaxation. In this study, we present a novel, fully automated, and efficient approach for personalising biophysically detailed active mechanics models using a two-step multi-fidelity solution. In the first step, active mechanical behaviour in a given 3D EM model is represented by a purely phenomenological, low-fidelity model, which is personalised at the organ scale by calibration to clinical cavity pressure data. Then, in the second step, median traces of nodal cellular active stress, intracellular calcium concentration, and fibre stretch are generated and utilised to personalise the desired high-fidelity model at the cellular scale using a 0D model of cardiac EM. Our novel approach was tested on a cohort of seven human left ventricular (LV) EM models, created from patients treated for aortic coarctation (CoA). Goodness of fit, computational cost, and robustness of the algorithm against uncertainty in the clinical data and variations of initial guesses were evaluated. We demonstrate that our multi-fidelity approach facilitates the personalisation of a biophysically detailed active stress model within only a few (2 to 4) expensive 3D organ-scale simulations-a computational effort compatible with clinical model applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.