Predictive Value of Dimensional and Functional MRI Parameters on Mid-Treatment MRI for Pathologic Complete Response in Breast Cancer.

Objective: To evaluate the predictive performance of dimensional and functional magnetic resonance imaging (MRI) parameters obtained from mid-treatment breast MRI for forecasting pathologic complete response (pCR) in patients with locally advanced breast cancer (LABC) undergoing neoadjuvant chemotherapy (NAC). Materials and Methods: Sixty-five women with LABC who underwent NAC followed by surgery were retrospectively included. Quantitative MRI parameters-including % change (Δ%) in longest diameter, bidimensional size, tumor volume, apparent diffusion coefficient (ADC), and enhancement percentage (Epeak) -were calculated between pre- and mid-NAC MRI. Receiver operating characteristic (ROC) analysis and logistic regression were used to identify predictors of pCR. Logistic regression and ROC analysis (with DeLong's test) were used to assess associations with pCR and compare area under the curves (AUCs). Results: pCR was achieved in 19 of 65 patients (29%). Compared to non-pCR cases, patients with pCR showed significantly greater reductions in tumor size and Epeak, and larger increases in ADC value (all Conclusion: Mid-treatment MRI biomarkers, particularly Δ% longest diameter and Δ% ADC value, are effective early predictors of pCR and may support individualized treatment strategies during NAC.