Evidence map›Paper›PMID 42094201›Full record

ArticleFrontiers in oncology2026

Clinical value of habitat radiomics within the 2-cm edema zone surrounding the postoperative residual cavity in predicting glioma recurrence.

MengYu Cheng, Dong Bai, Wenjuan Liu, Jiawei Fan, Yuanzi Liang, Wenfei Li, Zhiqun Wang

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

MengYu ChengDepartment of Radiology, Aerospace Center Hospital, Beijing, China.
Dong BaiDepartment of Radiology, Aerospace Center Hospital, Beijing, China.
Wenjuan LiuDepartment of Radiology, Aerospace Center Hospital, Beijing, China.
Jiawei FanDepartment of Radiology, Aerospace Center Hospital, Beijing, China.
Yuanzi LiangDepartment of Radiology, Aerospace Center Hospital, Beijing, China.
Wenfei LiDepartment of Radiology, The First Hospital of Qinhuangdao, Qinhuangdao, China.
Zhiqun WangDepartment of Radiology, Aerospace Center Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To 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. Methods: This 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. Results: Four 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. Conclusion: The 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.

Indexed as

gliomahabitat radiomicsheterogeneitynomogramPFS prediction

Identifiers

PMID42094201
PMCPMC13138962

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