Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning.

ABSTRACT:

Aims

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.

Methods and results

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

SUBMITTER: Bhuva AN 

PROVIDER: S-EPMC7100908 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature