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Radiomics from edema zone predicts progression-free survival in postoperative glioma patients

Radiomics from edema zone predicts progression-free survival in postoperative glioma patients
Photo by Navy Medicine / Unsplash
Key Takeaway
Consider radiomics from edema zone for PFS prediction in glioma, but await prospective validation.

This retrospective cohort study included 89 postoperative glioma patients and evaluated a radiomics model derived from the 2-cm edema zone surrounding the postoperative residual cavity using habitat analysis based on multimodal MRI, integrated with clinical data. The model was compared to clinical and traditional radiomic models, with progression-free survival (PFS) as the primary outcome. Main results showed the model predicted 1-year PFS with a time-dependent AUC of 0.813, 2-year PFS with an AUC of 0.933, and 3-year PFS with an AUC of 0.930, while a high-risk habitat nomogram had a C-index of 0.916. Safety and tolerability data were not reported. Key limitations include the retrospective design, small sample size of 89 patients, and lack of reported follow-up duration, which may affect generalizability. The study suggests this approach could aid in targeting postoperative radiotherapy, but clinicians should interpret findings cautiously due to the observational nature and need for prospective validation.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
ObjectiveTo assess the predictive value of radiomics from the 2-cm edema zone surrounding the postoperative residual cavity for progression-free survival (PFS), using habitat analysis based on multimodal magnetic resonance imaging (MRI) and integrating clinical data to construct a nomogram model.MethodsThis retrospective study analyzed MRI and clinical data from 89 postoperative glioma patients. The 2-cm edema zone surrounding the postoperative residual cavity was defined as the region of interest (ROI), and habitat subregions were created using K-means clustering based on contrast-enhanced T1-weighted imaging (CE-T1WI) and apparent diffusion coefficient (ADC) sequences. Radiomic features were extracted from the ROI and each habitat subregion, followed by Least Absolute Shrinkage and Selection Operator (LASSO)-Cox selection to generate radiomic scores. Clinical, traditional radiomic, and high-risk habitat models were constructed, and the high-risk habitat nomogram was further developed and evaluated.ResultsFour habitat subregions were identified. A total of 944 radiomic features were extracted from each subregion and the ROI; the most relevant features were used to generate radiomic scores. The high-risk habitat nomogram was constructed by combining clinical factors. The nomogram showed good calibration, with observed values closely matching predictions. In the validation cohort, the time-dependent AUCs for predicting 1-, 2-, and 3-year PFS were 0.813, 0.933, and 0.930, respectively. Compared with the clinical and traditional radiomic models, the high-risk habitat nomogram achieved a C-index of 0.916.ConclusionThe nomogram based on high-risk habitats in the 2-cm edema zone surrounding the postoperative residual cavity provides significant predictive value for PFS and aids in targeting postoperative radiotherapy.
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