Association of Post-Neoadjuvant Chemotherapy MRI and 18F-FDG PET/CT Findings with Tumor Response and Prognosis in Breast Cancer

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Accurate non-invasive prediction of pathological complete response (pCR) following neoadjuvant chemotherapy (NACT) in breast cancer (BC) remains challenging despite its established prognostic significance. Objective: We aimed to evaluate the prognostic utility of baseline and post-NACT magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for predicting pCR and survival outcomes, focusing on molecular subtype-specific performance and post-NACT imaging discordance. Methods: In this multicenter study, we retrospectively analyzed 335 patients with BC who received NACT between 2015 and 2025. Baseline (pre-NACT) and post-NACT imaging assessments were performed using MRI and 18F-FDG PET/CT. Pathological response was graded using the Miller–Payne classification system. Multivariable logistic regression was applied to identify independent predictors of pCR, whereas survival outcomes were examined using Kaplan–Meier analysis and Cox regression. Results: The overall pCR rate was 41.2%. Post-NACT imaging demonstrated complete response in 58.7% of patients by 18F-FDG PET/CT and 43.6% by MRI, both significantly correlating with pCR (p < 0.001). Pre-NACT MRI tumor size showed predictive value exclusively in Luminal A/B HER2-negative disease (area under curve = 0.681; p = 0.013). Importantly, post-NACT discordance between MRI and 18F-FDG PET/CT-based tumor size assessments was an independent predictor of both mortality (hazard ratio, 1.03) and disease progression (hazard ratio, 1.01). Conclusions: Post-NACT MRI and 18F-FDG PET/CT findings correlate strongly with pCR achievement, whereas pre-NACT MRI tumor size predicts pCR only in hormone receptor-positive HER2-negative subtypes. Importantly, post-NACT imaging discordance independently predicted mortality and disease progression, suggesting that dual-modality imaging assessment may identify high-risk patients requiring intensified surveillance.

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