Motivation: Accurate prognosis prediction for postoperative glioma patients is challenging due to tumor heterogeneity in the pericavitary edema zone. Goal(s): To develop model integrating habitat imaging and radiomic features of the 2cm pericavitary edema zone to predict prognosis in glioma patients. Approach: Multimodal MRI was used to perform habitat imaging analysis on the pericavitary edema zone. K-means clustering divided the region into habitat subregions. Radiomic features from these subregions were extracted and combined with clinical factors to build predictive models. Results: The high-risk habitat model showed superior predictive performance over traditional radiomic and clinical models, with higher efficiency in both training and validation groups. Impact: This study introduces a novel method to visualize and quantify tumor heterogeneity in the pericavitary edema zone, improving prognosis prediction for postoperative glioma patients and aiding clinicians in precisely delineating radiotherapy target volumes.
Cheng et al. (Tue,) studied this question.
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