AI-Based Prediction of Neoadjuvant Chemotherapy Benefit Using Pre-Treatment DCE-MRI in Hormone Receptor Positive HER2-Negative Breast Cancer A Multicenter Observational Cohort Study

What this Trial Is About

Researchers are conducting a multicenter, prospective observational study to evaluate how well artificial intelligence AI models using pre-treatment dynamic contrast-enhanced MRI DCE-MRI can predict the benefit of neoadjuvant chemotherapy in women with hormone receptor-positive, HER2-negative HRHER2- breast cancer. The study aims to stratify patients into groups with high or low expected benefit from chemotherapy and assess outcomes such as residual cancer burden and long-term survival. Participants receive routine standard neoadjuvant chemotherapy and undergo pre-treatment breast DCE-MRI scans. The AI model analyzes these images to categorize patients into high-benefit or low-benefit subgroups. Data collected include baseline clinical and pathological information, chemotherapy regimens, and post-surgery residual cancer classifications. The study evaluates response rates and survival outcomes up to five years after surgery. During the study, participants provide clinical data and imaging before starting chemotherapy. After treatment and surgery, researchers measure residual cancer burden and objective tumor response. Long-term follow-up tracks disease-free and overall survival for up to 60 months. The main outcome is the rate of minimal residual cancer after chemotherapy, helping to verify the AI models usefulness for individualized treatment selection in this breast cancer population.

Pre-Treatment DCE-MRI AI Models Predict Neoadjuvant Chemotherapy Response in HR+/HER2- Breast Cancer