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A bi-atrial statistical shape model for large-scale in silico studies of human atria: Model development and application to ECG simulations

Nagel, Claudia 1; Schuler, Steffen 1; Dössel, Olaf 1; Loewe, Axel ORCID iD icon 1
1 Institut für Biomedizinische Technik (IBT), Karlsruher Institut für Technologie (KIT)

Abstract:

Large-scale electrophysiological simulations to obtain electrocardiograms (ECG) carry the potential to produce extensive datasets for training of machine learning classifiers to, e.g., discriminate between different cardiac pathologies. The adoption of simulations for these purposes is limited due to a lack of ready-to-use models covering atrial anatomical variability. We built a bi-atrial statistical shape model (SSM) of the endocardial wall based on 47 segmented human CT and MRI datasets using Gaussian process morphable models. Generalization, specificity, and compactness metrics were evaluated. The SSM was applied to simulate atrial ECGs in 100 random volumetric instances. The first eigenmode of our SSM reflects a change of the total volume of both atria, the second the asymmetry between left vs. right atrial volume, the third a change in the prominence of the atrial appendages. The SSM is capable of generalizing well to unseen geometries and 95% of the total shape variance is covered by its first 24 eigenvectors. The P waves in the 12-lead ECG of 100 random instances showed a duration of 109.7±12.2 ms in accordance with large cohort studies. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000137449
Originalveröffentlichung
DOI: 10.1016/j.media.2021.102210
Scopus
Zitationen: 19
Web of Science
Zitationen: 14
Dimensions
Zitationen: 27
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Biomedizinische Technik (IBT)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2021
Sprache Englisch
Identifikator ISSN: 1361-8415, 1361-8423, 1361-8431
KITopen-ID: 1000137449
Erschienen in Medical Image Analysis
Verlag Elsevier
Band 74
Seiten Art.-Nr.: 102210
Vorab online veröffentlicht am 10.08.2021
Nachgewiesen in Dimensions
Scopus
Web of Science
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