Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning
European Heart Journal - Cardiovascular Imaging

Abstract
Left ventricular hypertrophy (LVH) in aortic stenosis (AS) varies widely before and after aortic valve replacement (AVR), and deeper phenotyping beyond traditional global measures may improve risk stratification. We hypothesized that machine learning derived 3D LV models may provide a more sensitive assessment of remodelling and sex-related differences in AS than conventional measurements.
One hundred and sixteen patients with severe, symptomatic AS (54% male, 70 ± 10 years) underwent cardiovascular magnetic resonance pre-AVR and 1 year post-AVR. Computational analysis produced co-registered 3D models of wall thickness, which were compared with 40 propensity-matched healthy controls. Preoperative regional wall thickness and post-operative percentage wall thickness regression were analysed, stratified by sex. AS hypertrophy and regression post-AVR was non-uniform—greatest in the septum with more pronounced changes in males than females (wall thickness regression: −13 ± 3.6 vs. −6 ± 1.9%, respectively,
In patients with severe AS, including those without overt LVH, LV remodelling is most plastic in the septum, and greater in males, both pre-AVR and post-AVR. Three-dimensional machine learning is more sensitive than conventional analysis to these changes, potentially enhancing risk stratification.
Regression of myocardial fibrosis after aortic valve replacement (RELIEF-AS); NCT02174471.
Contributors

Anish N Bhuva
Author

Thomas A Treibel
Author

Antonio De Marvao
Author

Carlo Biffi
Author

Timothy J W Dawes
Author

Georgia Doumou
Author

Wenjia Bai
Author

Kush Patel
Author

Redha Boubertakh
Author

Daniel Rueckert
Author

Declan P O’Regan
Author

Alun D Hughes
Author

James C Moon
Author

Charlotte H Manisty
Author

