Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images

Abstract

BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to ECG images as a surrogate for imaging risk biomarkers and its association with early CTRCD. METHODS: Across a US-based health system (2013-2023), we identified 1550 patients (aged, 60 [interquartile range, 51-69] years, 1223 [78.9%] women) without cardiomyopathy who received anthracyclines or trastuzumab for breast cancer or non-Hodgkin lymphoma and had ECG performed ≤12 months before treatment. We deployed a validated AI model of left ventricular systolic dysfunction to baseline ECG images and defined low-, intermediate-, and high-risk groups based on AI-ECG left ventricular systolic dysfunction probabilities of <0.01, 0.01 to 0.1, and ≥0.1 (positive screen), respectively. We explored the association with early CTRCD (new cardiomyopathy, heart failure, or left ventricular ejection fraction <50%), or left ventricular ejection fraction <40%, up to 12 months after treatment. In a mechanistic analysis, we assessed the association between global longitudinal strain and AI-ECG left ventricular systolic dysfunction probabilities in studies performed within 15 days of each other. RESULTS: Among 1550 patients without known cardiomyopathy (median follow-up, 14.1 [interquartile range, 13.4-17.1] months), 83 (5.4%), 562 (36.3%), and 905 (58.4%) were classified as high, intermediate, and low risk, respectively, by baseline AI-ECG. A high-risk versus low-risk AI-ECG screen (≥0.1 versus <0.01) was associated with a 3.4-fold and 13.5-fold higher incidence of CTRCD (adjusted hazard ratio, 3.35 [95% CI, 2.25-4.99]) and left ventricular ejection fraction <40% (adjusted hazard ratio, 13.52 [95% CI, 5.06-36.10]), respectively. Post hoc analyses supported longitudinal increases in AI-ECG probabilities within 6 to 12 months of a CTRCD event. Among 1428 temporally linked echocardiograms and ECGs, AI-ECG left ventricular systolic dysfunction probabilities were associated with worse global longitudinal strain (global longitudinal strain, -19% [interquartile range, -21% to -17%] for probabilities <0.1, to -15% [interquartile range, -15% to -9%] for ≥0.5 [P<0.001]). CONCLUSIONS: AI applied to baseline ECG images can stratify the risk of early CTRCD associated with anthracycline or trastuzumab exposure in the setting of breast cancer and non-Hodgkin lymphoma therapy.