Abstract

Introduction: Myocardial strain, a marker of heart muscle deformation, is crucial for assessing cardiac function and prognosis in cardiovascular diseases. Speckle Tracking Echocardiography (STE) is the preferred non-invasive method for strain. However, STE's accuracy can vary due to image quality, vendor-dependence, and operator inconsistency. STE-derived Global Longitudinal Strain (manual GLS) changes are key in early detection of cancer treatment-related cardiotoxicity. Hypothesis: We hypothesized that AI-derived GLS would have a stronger correlation with all-cause mortality (ACM) than STE-derived GLS. Methods: We retrospectively analyzed 1,224 echocardiograms, from 762 patients, with STE GLS values from Harrington Heart and Vascular Institute Cardio-Oncology studies performed between Jan 2021 - Jun 2022. Images were analyzed using EchoGo Core (Ultromics Ltd), a cloud-based, AI-powered software employing convolutional neural networks. Pearson's correlation coefficients and Bland-Altman analysis compared STE and AI-derived GLS (R-Studio). Both methods were evaluated using Receiver Operating Characteristic (ROC) curves. Patients were divided into tertiles based on their GLS values to assess ACM hazard ratios (HR). Results: Out of 762 patients, a moderate correlation (r=0.63, p<0.001) existed between STE and AI-derived GLS. The mean difference between the two was 2.37 and the limits of agreement were -3.65 to 8.39. The Area Under the Curve (AUC) was higher for AI (0.66) than STE GLS (0.59). Over an average follow-up of 215 days (± 169 days), 26 deaths occurred. When Tertile 3 was compared to Tertile 1, AI-derived GLS showed an HR of 4.46 (p=0.023), whereas the STE GLS HR was not statistically significant (HR=2.4). Conclusions: The study showed moderate agreement between AI and manual GLS measurements. The HR for ACM was statistically significant only in AI-derived GLS in patients undergoing cardiotoxic chemotherapy.

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