A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations

Marina Strocchi, Christoph M Augustin, Matthias A F Gsell, Elias Karabelas, Aurel Neic, Karli Gillette, Orod Razeghi, Anton J Prassl, Edward J Vigmond, Jonathan M Behar, Justin Gould, Baldeep Sidhu, Christopher A Rinaldi, Martin J Bishop, Gernot Plank and Steven A Niederer

PLOS ONE, 2020, vol. 15, issue 6, 1-26

Abstract: Computational models of the heart are increasingly being used in the development of devices, patient diagnosis and therapy guidance. While software techniques have been developed for simulating single hearts, there remain significant challenges in simulating cohorts of virtual hearts from multiple patients. To facilitate the development of new simulation and model analysis techniques by groups without direct access to medical data, image analysis techniques and meshing tools, we have created the first publicly available virtual cohort of twenty-four four-chamber hearts. Our cohort was built from heart failure patients, age 67±14 years. We segmented four-chamber heart geometries from end-diastolic (ED) CT images and generated linear tetrahedral meshes with an average edge length of 1.1±0.2mm. Ventricular fibres were added in the ventricles with a rule-based method with an orientation of -60° and 80° at the epicardium and endocardium, respectively. We additionally refined the meshes to an average edge length of 0.39±0.10mm to show that all given meshes can be resampled to achieve an arbitrary desired resolution. We ran simulations for ventricular electrical activation and free mechanical contraction on all 1.1mm-resolution meshes to ensure that our meshes are suitable for electro-mechanical simulations. Simulations for electrical activation resulted in a total activation time of 149±16ms. Free mechanical contractions gave an average left ventricular (LV) and right ventricular (RV) ejection fraction (EF) of 35±1% and 30±2%, respectively, and a LV and RV stroke volume (SV) of 95±28mL and 65±11mL, respectively. By making the cohort publicly available, we hope to facilitate large cohort computational studies and to promote the development of cardiac computational electro-mechanics for clinical applications.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0235145

DOI: 10.1371/journal.pone.0235145

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