Early Prediction of Volumetric Progression in Sellar–Parasellar Meningiomas Using Delta Radiomics on 6-Month MRI Following Gamma Knife Radiosurgery

Background/Objectives: This study aimed to develop and internally validate multiparametric MRI radiomics models for predicting volumetric progression following Gamma Knife radiosurgery (GKRS) in sellar–parasellar meningiomas and to evaluate the incremental value of diffusion-derived features beyond contrast-enhanced imaging. Methods: Fifty-four patients underwent pretreatment and approximately 6-month post-treatment MRI, including contrast-enhanced T1-weighted imaging (T1C-WI) and apparent diffusion coefficient (ADC) maps. Whole-tumor segmentations were reviewed by two neuroradiologists by consensus. Radiomic features were extracted using PyRadiomics, and delta features were calculated as post-treatment minus pretreatment values. Elastic-net logistic regression models were evaluated using repeated nested cross-validation with five-fold inner and outer loops repeated 10 times. The primary endpoint was volumetric progression, defined as a >20% volume increase at 3 years. Results: At 3 years, 9 tumors (16.7%) progressed, 25 (46.3%) remained stable, and 20 (37.0%) regressed. The ΔT1C-WI model showed the highest repeated nested cross-validation performance, with a mean AUC of 0.861 ± 0.065, an accuracy of 0.846 ± 0.037, and an F1 score of 0.579 ± 0.097. Averaged patient-level out-of-fold predictions yielded an AUC of 0.914 (95% CI, 0.822–0.980), a sensitivity of 77.8%, and a specificity of 88.9%. The ΔADC model showed moderate discrimination, whereas combining ΔT1C-WI and ΔADC features did not improve performance. Conclusions: Delta radiomics derived from 6-month post-treatment T1C-WI may help identify sellar–parasellar meningiomas at risk of 3-year volumetric progression after GKRS. These findings suggest that 6-month ΔT1C-WI radiomics may support early risk stratification, but its clinical value requires external validation and prospective evaluation.