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Background: Neoadjuvant systemic therapy (NST), whose primary purposes include response assessment and treatment individualization, is a key strategy in the treatment of HER2-positive breast cancer. This study investigated the predictive value of the magnetic resonance imaging (MRI)-derived tumor volume reduction rate (δV1) for the early identification of pathological complete response (pCR) during NST and established clinically applicable δV1 thresholds for patient stratification. Methods: HER2-positive breast cancer patients who received THP (taxane, trastuzumab, pertuzumab) followed by epirubicin/cyclophosphamide (EC) were enrolled. MRI was performed at baseline, after THP, and after EC. Tumor volumes were manually segmented using 3D Slicer, and δV1/δV2 were calculated via Python (version3.13). Longest diameter reduction rates (δL1/δL2) were recorded. pCR (ypT0/is ypN0) was the primary endpoint. Receiver operating characteristic (ROC) analysis determined predictive accuracy, and logistic regression identified independent predictors. Thresholds for δV1 were explored, and subgroup analyses were conducted by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. Results: Overall, 59.3% of patients achieved pCR. δV1 demonstrated superior predictive accuracy compared with longest diameter reduction (δL1), with an AUC of 0.745 (95% CI: 0.642–0.847) vs. 0.634 (95% CI: 0.512–0.757). A δV1 cutoff of 0.85 discriminated responders (68.4% vs. 41.4%, p = 0.016), while one of 0.91 represented the optimal predictive threshold. In multivariate analysis, δV1 was independently associated with pCR (OR = 1227.1, 95% CI: 6.86–219,562; p = 0.007), along with HER2 3+ expression (OR = 4.24, 95% CI: 1.26–14.31; p = 0.020). Among HR-positive patients, δV1 < 0.93 identified a subgroup with significantly lower pCR rates (19.0% vs. 81.0%, p < 0.001). Conclusions: δV1 is a reliable and early MRI-based imaging biomarker for predicting pCR in HER2-positive breast cancer. Defining thresholds such as 0.85 and 0.91 supports early therapeutic stratification and may help identify patients who could benefit from anthracycline-containing regimens.
Qian et al. (Thu,) studied this question.