Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability

Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability

Abstract Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold standard for viability evaluation, it has limitations, including contraindications in patients with renal dysfunction an...

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Bibliographic Details
Main Authors: Amir GhaffariJolfayi, Alireza Salmanipour, Kiyan Heshmat-Ghahdarijani, MohammadHossein MozafaryBazargany, Amir Azimi, Pirouz Pirouzi, Ali Mohammadzadeh
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Cardiovascular magnetic resonance
Feature tracking strain analysis
T1/T2 mapping
Myocardial viability
Online Access:https://doi.org/10.1038/s41598-024-85029-0
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