Using Artificial Intelligence to Detect and Measure Aortic Regurgitation in Adults A Multicenter Randomized Trial

What this Trial Is About

Researchers are evaluating an artificial intelligence AI tool designed to automatically detect and measure aortic regurgitation AR. This tool aims to improve diagnosis by reducing variability and the need for specialized expertise in interpreting echocardiograms. The study compares the AI system with manual diagnostic methods across multiple centers in a randomized controlled trial, seeking to enhance accuracy, consistency, and accessibility of AR diagnosis, especially in resource-limited settings. Participants will be divided into two groups one group will have AR severity assessed using the AI tool that analyzes key echocardiographic parameters such as Effective Regurgitant Orifice Area EROA, Vena Contracta VC, Proximal Isovelocity Surface Area PISA, jet width, and Regurgitant Volume RegVol, along with timing of assessments. The other group will have AR severity measured manually by trained sonographers following standard protocols. Cardiologists blinded to patient details will review both AI-generated and manual results to make final diagnoses and treatment decisions. During the study, participant data will be collected from baseline through 20 months, including accuracy of AR severity differentiation, deviations in key echocardiographic measurements, and the time taken to complete assessments. Participants will be followed up at 6 and 12 months to monitor outcomes such as all-cause mortality and heart failure hospitalizations. This design allows researchers to evaluate the clinical utility of the AI tool compared to traditional methods over time.

Artificial Intelligence in Aortic Regurgitation