Investigating Strain as a Biomarker for Atrial Fibrosis Quantified by Patient Cine MRI Data

Ahmed Qureshi*, Aditi Roy, Henry Chubb, Adelaide De Vecchi, Oleg Aslanidi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

3 Citations (Scopus)


Atrial fibrillation (AF) is responsible for deterioration of left atrial (LA) mechanical function. Sinus rhythm (SR) can be restored by terminating AF using catheter ablation (CA) therapy. CA often targets fibrotic tissue by creating scar tissue which is similar to fibrosis. We propose the use of myocardial strain to identify regions of fibrosis and understand its role in atrial mechanics. Patient-specific LA models were reconstructed from Cine and Late Gadolinium Enhanced (LGE) MRI data for two groups of patients: AF and SR pre-CA. LGE intensities represented atrial fibrosis and feature-tracking was applied on the Cine images to produce a series of 3D deforming LA meshes. The myocardial area strain (MAS) was calculated as a measure of regional contractile ability. 24 regions of clinical interest were assigned for inter- and intra-patient comparisons on the effects of CA and fibrosis on LA mechanical function. Correlation was found between low strain and dense fibrosis in the LA posterior wall for both patient groups (rs = -0.74). MAS increased (8.9%) after CA in the AF group but decreased (10%) in the SR group. This study suggests that myocardial strain can be used as a biomarker for atrial fibrosis and also identifies the detrimental effect of intentional CA-induced damage to the LA on its mechanical function.

Original languageEnglish
Title of host publication2020 Computing in Cardiology, CinC 2020
PublisherIEEE Computer Society
ISBN (Electronic)9781728173825
Publication statusPublished - 13 Sept 2020
Event2020 Computing in Cardiology, CinC 2020 - Rimini, Italy
Duration: 13 Sept 202016 Sept 2020

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X


Conference2020 Computing in Cardiology, CinC 2020


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