In a new study published in Circulation: Cardiovascular Quality and Outcomes , researchers at Yale School of Medicine say an artificial intelligence (AI) tool can use electrocardiographic (ECG) images to define the risk of cardiac dysfunction for patients undergoing cancer treatments. "There are certain treatments for breast cancer and lymphomas, such as anthracyclines and trastuzumab, that have cardiotoxic effects," said Rohan Khera, MD, Assistant Professor of Medicine, Director of the Cardiovascular Data Science (CarDS) Lab, and senior author of the study. "1 in 10 individuals receiving these drugs individually, and nearly 1 in 3 using the drugs in combination, have adverse cardiac reactions.
" After identifying 1,550 patients who had received anthracyclines or trastuzumab to treat breast cancer or non-Hodgkin lymphoma, researchers applied an AI model of left ventricular systolic dysfunction (LVSD) to ECG images of patients to sort them into low-, intermediate-, and high-risk groups . The team says compared with low-risk patients, patients in the high-risk group had 3.4 times the risk of cardiac dysfunction after cancer treatment , and 13.
5 times the risk of a left ventricular ejection fraction (LVEF) below 40%. The new AI-driven method could help quickly make safe clinical decisions for patients with breast cancer or non-Hodgkin lymphoma at risk of heart dysfunction, especially for providers in under-resourced communities. "Identifying those at heightened risk on a simple t.