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Abstract 11383: Automated Measurement of Global Longitudinal Strain by Speckle-Tracking Echocardiography in Cardio-Oncology Patients Using Artificial Intelligence


 Introduction:
 Left ventricular (LV) global longitudinal strain (GLS) is a robust LV systolic function measure used to detect subtle chemotherapy cardiotoxicity. However, inter-reader and inter-vendor variabilities compromise the clinical value of longitudinal follow-up of GLS. Artificial intelligence (AI)-based, fully automated measurement of longitudinal strain may be more reliable compared with human interpretation.
 
 
 Methods:
 We studied 52 transthoracic echocardiographic examinations randomly selected from a Cardio-oncology registry. All subjects received anthracycline-based chemotherapy in 2016-2019. AI-based longitudinal strain was assessed by EchoGo Core using standard 2- and 4-chamber apical views. Two readers verified the myocardium tracing by AI and found no errors. Longitudinal strain results by EchoGo were compared to GLS measured by conventional software (TomTec and Philips QLAB) using standard 3-, 2- and 4-chamber apical views.
 
 
 Results:
 AI-based longitudinal strain analysis was feasible in 51/52 (98%) transthoracic echocardiographic studies. The mean longitudinal strain was -17.3±3.3% for EchoGo, -16.9±2.4% for TomTec and -17.5±3.1% for QLAB. Bland-Altman analysis showed a bias of -0.4 ± 2.7% and 95% limits of -5.7 to 4.9% between EchoGo longitudinal strain and TomTec GLS (Figure 1A). A bias of 0.2 ± 3.3% and 95% limits of -6.2 to 6.6% between EchoGo longitudinal strain and QLAB GLS (Figure 1B) were seen. The bias between TomTec GLS and QLAB GLS was 0.6 ±2.2% (Figure 1C). The inter-reader correlation coefficients of TomTec GLS and QLAB GLS were 0.57 and 0.71, respectively.
 
 
 Conclusions:
 This novel AI-based longitudinal strain analysis was feasible in the majority of echocardiograms without any operator input. The bias between EchoGo longitudinal strain and conventional software appears small. AI-based myocardial strain analysis may reduce variabilities and facilitate longitudinal follow-up of GLS in Cardio-oncology patients.
 
 
 
