ArticlePLoS computational biology2021
Linking statistical shape models and simulated function in the healthy adult human heart.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing.Computer methods in applied mechanics and engineering · 2026Article
- Predictive simulation of coil mechanics uncovers shape-driven determinants of endovascular coiling efficacy in intracranial aneurysms.APL bioengineering · 2026Article
- Unveiling sex dimorphism in the healthy cardiac anatomy: Fundamental differences between male and female heart shapes.The Journal of physiology · 2026Article
- Assessing the importance of sex and disease-specific anatomy in electrophysiology and mechanical simulations with a newly developed public virtual cohort of four-chamber heart models.PLoS computational biology · 2026Article
- T-World Virtual Human Cardiomyocyte. II. Organ-Scale Simulations and Applications.Circulation research · 2026Article
- Uncertainty quantification of conduction velocity in models of cardiac spread of activation.Medical & biological engineering & computing · 2026Article
- Feasibility of whole heart 3D shape reconstruction from sparse echocardiographic views using CT-derived simulations.Scientific reports · 2026Article
- Weaving the Digital Tapestry: Methods for Emulating Cohorts of Cardiac Digital Twins Using Gaussian Processes.Annals of biomedical engineering · 2026Article
- An efficient end-to-end computational framework for the generation of ECG calibrated volumetric models of human atrial electrophysiology.Medical image analysis · 2026Article
- Full-field surrogate modeling of cardiac electrophysiology encoding geometric variability.Computer methods in applied mechanics and engineering · 2026Article
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- Sex-specific human electromechanical multiscale in-silico models for virtual therapy evaluation.Journal of molecular and cellular cardiology plus · 2025Article
- 3D cardiac shape analysis with variational point cloud autoencoders for myocardial infarction prediction and virtual heart synthesis.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2025Article
- AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.Cardiovascular diabetology · 2025Article
- Cardiac digital twins: a tool to investigate the function and treatment of the diabetic heart.Cardiovascular diabetology · 2025Review
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- Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs.IEEE transactions on medical imaging · 2025Article
- A computational study on the influence of antegrade accessory pathway location on the 12-lead electrocardiogram in Wolff-Parkinson-White syndrome.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Article
- Comparing the effects of left bundle branch pacing and leadless right ventricular pacing on intraventricular and interventricular dyssynchrony usingFrontiers in physiology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors.
Funding
Abstract
Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.
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