Multi-modality artificial intelligence-based transthyretin amyloid cardiomyopathy detection in patients with severe aortic stenosis.

ABSTRACT:

Purpose

Transthyretin amyloid cardiomyopathy (ATTR-CM) is a frequent concomitant condition in patients with severe aortic stenosis (AS), yet it often remains undetected. This study aims to comprehensively evaluate artificial intelligence-based models developed based on preprocedural and routinely collected data to detect ATTR-CM in patients with severe AS planned for transcatheter aortic valve implantation (TAVI).

Methods

In this prospective, single-center study, consecutive patients with AS were screened with [^99mTc]-3,3-diphosphono-1,2-propanodicarboxylic acid ([^99mTc]-DPD) for the presence of ATTR-CM. Clinical, laboratory, electrocardiogram, echocardiography, invasive measurements, 4-dimensional cardiac CT (4D-CCT) strain data, and CT-radiomic featur

SUBMITTER: Shiri I 

PROVIDER: S-EPMC11732884 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature