Motivation: Accurate prediction of pathological completed response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer. Goal(s): Evaluate the value of potential MRI biomarkers for predicting pCR and establish a new nomogram to improve predictive performance. Approach: We conducted an analysis of 692 patients, utilizing univariable and multivariable logistic regression analyses, and training/validation cohorts for model development and validation. Results: Our newly developed model, combining the selected MRI parameters, hormone receptor (HR) and Ki67 index, exhibited strong predictive power, and also identified the rimed enhancement pre-NAC, and tumor size, wash-in slope, and ADC after NAC as significant imaging biomarkers of pCR. Impact: The impact of this study is significant, as it enhances breast cancer treatment by providing a reliable predictive model for neoadjuvant chemotherapy response, potentially improving patient outcomes and treatment strategies.
Li et al. (Tue,) studied this question.