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24 files

A Virtual Cohort of Twenty-four Left-ventricular Models of Ischemic Cardiomyopathy Patients

dataset
posted on 2021-09-13, 18:33 authored by Caroline Mendonca Costa, Aurel Neic, Eric Kerfoot, Karli Gillette, Bradley Porter, Benjamin Sieniewicz, Justin Gould, Baldeep Sidhu, Zhong Chen, Mark Elliott, Vishal Mehta, Gernot Plank, Aldo Rinaldi, Martin Bishop, Steven Niederer
Motivation: 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. Dataset Description: We present the first database of left-ventricular (LV) models suitable for electrophysiology simulations. Our database consists of twenty-four LV models including infarct scar morphology. These were generated from LGE-MRI acquired from ICM patients undergoing CRT. We used 24 image-based patient-specific models of LV anatomy and scar morphology. Briefly, LV endocardium and epicardium contours were manually drawn in each short-axis slice of LGE-MRI. Scar and BZ were segmented and reconstructed in 3D. A finite element tetrahedral mesh (mean edge length of 0.8mm) was generated and 3D reconstructed scar and BZ segmentations were mapped onto it. Rule-based fibres were assigned to the models. The elements of all the twenty-four meshes are labelled as follows: 1) Left ventricular myocardium 3) Scar core 4) Scar border zone We defined a system of universal ventricular coordinates on the meshes: an apico-basal coordinate varying continuously from 0 at the apex to 1 at the base; a transmural coordinate varying continuously from 0 at the endocardium to 1 at the epicardium; a rotational coordinate varying continuously from – π at the left ventricular free wall, 0 at the septum and then back to + π at the left ventricular free wall. We built the first cohort of twenty-four LV meshes from ICM patients LGE-MRI data. These geometries can be used for large cohort computational studies.

Funding

NIHR

Wellcome Trust/EPSRC

Medical Research Council

British Heart Foundation

History

Language

English