Keywords: Tumors (Post-Treatment), Radiomics, Glioma, Habitat Imaging, Heterogeneity
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.
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