Structural Magnetic Resonance Imaging (MRI) in Differentiating Radionecrosis from Metastatic Recurrence in Post-Surgical Patients: A Tertiary Center Experience

Purpose: Distinguishing radionecrosis (RN) from recurrent brain metastasis (rM1) remains a major challenge in the follow-up of patients treated with surgery and radiotherapy. Although advanced imaging techniques have been proposed to improve diagnostic accuracy, they are not always available in routine clinical practice and may be limited by postoperative changes and artifacts. Histopathologically validated studies in this setting remain scarce. Methods: We retrospectively evaluated 16 patients with 17 histologically confirmed lesions who underwent repeat surgery for suspected progression after the resection of brain metastases and adjuvant radiotherapy. Preoperative MRI examinations were reviewed by two neuroradiologists using a standard MRI protocol. Qualitative features included signal characteristics, T1/T2 mismatch, enhancement patterns, and the presence of the “inflammatory cloud” and “incomplete ring enhancement” signs. Quantitative analysis included lesion, edema and necrosis volumes, apparent diffusion coefficient (ADC), intratumoral susceptibility signal (ITSS) grading, and volumetric lesion quotient (vLQ). A LASSO logistic regression model with leave-one-out cross-validation and bootstrap stability analysis was used to identify the most relevant predictors. Results: Histopathology demonstrated 11 RN lesions and six recurrent metastases. The LASSO model achieved an area under the curve of 0.71 and an overall accuracy of 76% (13/17 lesions) with a sensitivity of 82% for RN and a specificity of 67% for rM1. RN lesions were characterized by significantly higher ADC values and ITSS grades and by the exclusive presence of the inflammatory cloud and incomplete ring enhancement signs. Stability analysis identified incomplete ring enhancement (49%), ITSS grade (45%), ADC values (45%), and inflammatory cloud (44%) as the most robust predictors of RN, whereas volumetric measurements showed limited independent predictive value. Conclusions: In patients with histologically confirmed post-treatment lesions, conventional MRI provided several reproducible features that aided differentiation between radionecrosis and recurrent brain metastasis. The inflammatory cloud, incomplete ring enhancement, elevated ADC values, and higher ITSS grades emerged as the most robust imaging markers of RN. While predictive multivariable models remain exploratory, these readily available MRI features may improve diagnostic confidence in routine clinical practice and warrant validation in larger multicenter cohorts.