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MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas
- MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas
- Park, Chae Jung; Han, Kyunghwa; Shin, Haesol; Ahn, Sung Soo; Choi, Yoon Seong; Park, Yae Won; Chang, Jong Hee; Kim, Se Hoon; Jain, Rajan; Lee, Seung-Koo
- Ewha Authors
- Issue Date
- Journal Title
- EUROPEAN RADIOLOGY
- EUROPEAN RADIOLOGY vol. 30, no. 6, pp. 3035 - 3045
- Glioma; Isocitrate dehydrogenase; Magnetic resonance imaging; Prognosis; Survival
- SCIE; SCOPUS
- Document Type
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- Purpose To identify significant prognostic magnetic resonance imaging (MRI) features and their prognostic value when added to clinical features in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas. Materials and methods Preoperative MR images of 158 patients (discovery set = 112, external validation set = 46) with IDHwt lower-grade gliomas (WHO grade II or III) were retrospectively analyzed using the Visually Accessible Rembrandt Images feature set. Radiologic risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator and elastic net. Multivariable Cox regression analysis, including age, Karnofsky Performance score, extent of resection, WHO grade, and RRS, was performed. The added prognostic value of RRS was calculated by comparing the integrated area under the receiver operating characteristic curve (iAUC) between models with and without RRS. Results The presence of cysts, pial invasion, and cortical involvement were favorable prognostic factors, while ependymal extension, multifocal or multicentric distribution, nonlobar location, proportion of necrosis > 33%, satellites, and eloquent cortex involvement were significantly associated with worse prognosis. RRS independently predicted survival and significantly enhanced model performance for survival prediction when integrated to clinical features (iAUC increased to 0.773-0.777 from 0.737), which was successfully validated on the validation set (iAUC increased to 0.805-0.830 from 0.735). Conclusion MRI features associated with prognosis in patients with IDHwt lower-grade gliomas were identified. RRSs derived from MRI features independently predicted survival and significantly improved performance of survival prediction models when integrated into clinical features.
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