Enhanced Extraction of Activation Time and Contractility From Myocardial Strain Data Using Parameter Space Features and Computational Simulations.


Journal

TheScientificWorldJournal
ISSN: 1537-744X
Titre abrégé: ScientificWorldJournal
Pays: United States
ID NLM: 101131163

Informations de publication

Date de publication:
2024
Historique:
received: 09 01 2024
revised: 14 08 2024
accepted: 25 09 2024
medline: 21 10 2024
pubmed: 21 10 2024
entrez: 21 10 2024
Statut: epublish

Résumé

A computational model enables the extraction of two critical myocardial tissue properties: activation time (AT) and contractility (Con) from recorded cardiac strains. However, interference between these parameters reduces the precision and accuracy of the extraction process. This study investigates whether leveraging features in the parameter space can enhance parameter extraction. We utilized a computational model to simulate sarcomere mechanics, creating a parameter space grid of 41 × 41 AT and Con pairs. Each pair generated a simulated strain pattern, and by scanning the grid, we identified cohorts of similar strain patterns for each simulation. These cohorts were represented as binary images-synthetic fingerprints-where the position and shape of each blob indicated extraction uniqueness. We also generated a measurement fingerprint for a strain pattern from a patient with left bundle branch block and compared it to the synthetic fingerprints to calculate a proximity map based on their similarity. This approach allowed us to extract AT and Con using both the measurement fingerprint and the proximity map, corresponding to simple optimization and enhanced parameter extraction methods, respectively. Each synthetic fingerprint consisted of a single connected blob whose size and shape varied characteristically within the parameter space. The AT values extracted from the measurement fingerprint and the proximity map ranged from -59 to 19 ms and from -16 to 14 ms, respectively, while Con values ranged from 48% to 110% and from 85% to 110%, respectively. This study demonstrates that similarity in simulations leads to an asymmetric distribution of parameter values in the parameter space. By using a proximity map, this distortion is considered, significantly improving the accuracy of parameter extraction.

Identifiants

pubmed: 39431043
doi: 10.1155/2024/1059164
pmc: PMC11490350
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1059164

Informations de copyright

Copyright © 2024 Borut Kirn.

Déclaration de conflit d'intérêts

The author declares no conflicts of interest.

Auteurs

Borut Kirn (B)

Medical Faculty, University of Ljubljana, Ljubljana, Slovenia.

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Classifications MeSH