Artificial intelligence implementation in automated heart chambers quantification during pharmacological stress echocardiography.

ABSTRACT:

Aims

Stress echocardiography (SE) is widely used for assessing coronary artery disease, but volumetric chamber analysis during SE is limited by time-consuming manual tracings and operator-dependent variability. Automated evaluation may overcome these barriers and enhance efficiency.

Methods and results

This multi-centre study included 240 participants undergoing pharmacological SE for ischaemic heart disease evaluation from five sites in four countries. SE imaging data from apical four-chamber and two-chamber views were acquired during rest and stress phases. Expert cardiologists manually traced endocardial borders for left ventricular (LV), left atrial (LA) and right ventricular (RV), right atrial (RA) areas, which were compared to machine learning (ML) derived measurements

SUBMITTER: Karuzas A 

PROVIDER: S-EPMC12821065 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature