Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort.
Author(s)
Type
Journal Article
Abstract
This paper presents a morphological analysis of fibrotic scarring in non-ischemic dilated cardiomyopathy, and its relationship to electrical instabilities which underlie reentrant arrhythmias. Two dimensional electrophysiological simulation models were constructed from a set of 699 late gadolinium enhanced cardiac magnetic resonance images originating from 157 patients. Areas of late gadolinium enhancement (LGE) in each image were assigned one of 10 possible microstructures, which modelled the details of fibrotic scarring an order of magnitude below the MRI scan resolution. A simulated programmed electrical stimulation protocol tested each model for the possibility of generating either a transmural block or a transmural reentry. The outcomes of the simulations were compared against morphological LGE features extracted from the images. Models which blocked or reentered, grouped by microstructure, were significantly different from one another in myocardial-LGE interface length, number of components and entropy, but not in relative area and transmurality. With an unknown microstructure, transmurality alone was the best predictor of block, whereas a combination of interface length, transmurality and number of components was the best predictor of reentry in linear discriminant analysis.
Date Issued
2019-10
Date Acceptance
2019-09-18
Citation
PLoS Computational Biology, 2019, 15 (10), pp.1-18
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Start Page
1
End Page
18
Journal / Book Title
PLoS Computational Biology
Volume
15
Issue
10
Copyright Statement
© 2019 Balaban et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/31658247
PII: PCOMPBIOL-D-19-00760
Subjects
Bioinformatics
06 Biological Sciences
08 Information and Computing Sciences
01 Mathematical Sciences
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2019-10-28