Fully automated analysis of cardiotoxicity surveillance echocardiograms: A direct test-retest precision comparison with experts

Abstract Aims Serial imaging demands measurement precision – particularly for cardiotoxicity screening where small changes gatekeeper major management decisions. Automated measurement using artificial intelligence (AI)-based techniques should reduce variability and increase confidence for detection of true interval change. We directly compared the precision of fully-automated AI versus expert manual analysis of left ventricular function by echocardiography. Methods and Results Consecutive cancer patients referred for cardiotoxicity monitoring underwent same day repeat 2D echocardiography (n=60, 83% female, mean age 52±12years, mean LVEF 57±7%), with 3D acquisition where feasible (n=45). All 2D images underwent blinded manual analysis by fully automated analysis software and four individual experts. Quantitative 2D LVEF measurement was feasible in 97% scans by both methods. Mean absolute difference (MAD) between repeat scans was significantly lower for AI than experts for both 2D LVEF (3.6% [CI 2.8–4.4] vs 6.6% [CI 5.3–7.9], p=0.011) and global longitudinal strain (1.5% [CI 1.1–1.9] vs 2.5% [CI 2.0–3.0], p=0.006). In participants with 3DE datasets, 3D LVEF MAD was lower than manual 2D LVEF (3.6% [CI 2.8-4.6] vs 6.4% [CI 5.0-8.0], p=0.006) but comparable to AI-derived 2D LVEF (3.5% [CI 2.9-4.2], p=0.4). In a subset (n=48) also with same day cardiovascular magnetic resonance studies (CMR), AI 2DE analysis demonstrated stronger agreement with CMR than expert 2DE analysis (LVEF MAD 5.0% [CI 4.1-5.9] vs 7.8% ([CI 6.6-9.0] p=0.006). Conclusions In cancer patients at risk of cardiotoxicity, the precision of 2D echocardiographic AI analysis exceeds that of experts, matching that of 3D LVEF assessment.