Preoperative Cardiac Risk Stratification in Dogs with Mammary Tumors Using Two-Dimensional Speckle Tracking...

Although breast cancer has been associated with subclinical left ventricular dysfunction in humans, the cardiac effects of CMTs remain poorly defined. This pilot, exploratory (communication) study compared clinical and echocardiographic parameters between dogs with CMTs and healthy controls and assessed the feasibility of combining myocardial deformation imaging with exploratory data-driven analysis for preoperative cardiac assessment. All dogs underwent a standardized clinical and echocardiographic assessment, including two-dimensional speckle-tracking echocardiography (2D-STE). Given the limited sample size, analyses were designed to generate hypotheses rather than to provide definitive predictive conclusions. Exploratory machine learning modeling (XGBoost), receiver operating characteristic (ROC) analysis, calibration, and decision curve analysis were performed as proof-of-concept approaches without external validation. Despite normal conventional systolic indices, dogs with CMTs exhibited reduced global longitudinal strain (GLS) and mitral annular plane systolic excursion (MAPSE) (p < 0.01), suggesting subclinical systolic dysfunction. Deformation-derived parameters appeared more sensitive for detecting subtle myocardial alterations within this cohort. The exploratory machine learning model demonstrated moderate discrimination (AUC-ROC = 0.75); however, these findings are preliminary and should not be interpreted as evidence of clinical predictive performance. Overall, these results suggest that conventional systolic indices may underestimate early myocardial changes in dogs with CMTs. This communication highlights the feasibility of integrating deformation imaging with exploratory analytical approaches and provides a basis for future large-scale, validated studies in veterinary cardio-oncology.