Artificial Intelligence-Enabled Echocardiography as a Surrogate for Multimodality Aortic Stenosis Imaging: Post Hoc Analysis of a Clinical Trial.

ABSTRACT:

Background

Accurate aortic stenosis (AS) phenotyping requires multimodality imaging which has limited availability. The digital aortic stenosis severity index (DASSi), an artificial intelligence biomarker of AS-related remodeling on single-view 2-dimensional echocardiography, predicts AS progression independent of Doppler measurements. We sought to evaluate the ability of DASSi to define personalized AS progression profiles and to validate its performance as a scalable alternative to multimodality imaging features of functional, structural, and biological AS severity.

Methods

In the SALTIRE-2 trial (Study Investigating the Effect of Drugs Used to Treat Osteoporosis on the Progression of Calcific Aortic Stenosis 2) of participants with mild or moderate AS, we performed blinde

SUBMITTER: Oikonomou EK 

PROVIDER: S-EPMC12778975 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature