In a cohort of 237 women with breast cancer receiving doxorubicin with or without trastuzumab, 1151 echocardiograms were prospectively acquired over a median (Q1–Q3) of 7 (2–24) months. LV ejection fraction (LVEF) and 36 segmental strain measures were core lab quantified. A supervised machine learning (ML) model was then developed using random forest regression to identify segmental strain measures predictive of nadir LVEF post-doxorubicin completion. Cancer therapy-related cardiac dysfunction (CTRCD) was defined as a ≥10% absolute LVEF decline pre-treatment to a value <50%. Median (Q1–Q3) baseline age was 48 (41–57) years. Thirty-five women developed CTRCD, and eight of these developed symptomatic heart failure. From pre-treatment to doxorubicin completion, longitudinal strain worsened across the basal and mid-LV segments but not in the apical segments; circumferential strain worsened primarily in the septum; radial strain worsened uniformly and transverse strain remained unchanged across all LV segments. In the ML model, anterolateral and inferoseptal circumferential strain were the most predictive features; longitudinal and transverse strain in the basal inferoseptal, anterior, basal anterolateral, and apical lateral segments were also top predictive features. The addition of predictive segmental strain measures to a model including age, cancer therapy regimen, hypertension, and LVEF increased the area under the curve (AUC) from 0.70 (95% confidence interval (CI) 0.60–0.80) to 0.87 (95% CI 0.81–0.92), ΔAUC = 0.18 (95% CI 0.08–0.27) for the prediction of CTRCD.
Our findings suggest that segmental strain measures can enhance cardiotoxicity risk prediction in women with breast cancer receiving doxorubicin.