Ahmet Bozer, Levent Altın, Hamza Eren Güzel
European Journal of Breast Health - 2026;22(1):44-53
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 (Delta%) 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 p<0.05). In multiple logistic regression, Delta% longest diameter >60% [odds ratio (OR)=7.1, p = 0.008] and Delta% ADC value >=32% (OR=4.7, p = 0.016) remained statistically significant independent predictors of pCR. Delta% tumor volume >92% had the highest univariable AUC (0.754), while Epeak <=21% showed perfect specificity but was excluded due to wide confidence intervals. Pairwise AUC comparisons showed no significant differences among Delta% longest diameter, bidimensional size, and tumor volume (all p>0.05). Conclusion: Mid-treatment MRI biomarkers, particularly Delta% longest diameter and Delta% ADC value, are effective early predictors of pCR and may support individualized treatment strategies during NAC.
