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.
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).
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.
• Comprehensive analysis of MRI features conveys prognostic information in patients with isocitrate dehydrogenase wild-type lower-grade gliomas.
• Presence of cysts, pial invasion, and cortical involvement of the tumor were favorable prognostic factors.
• Radiological phenotypes derived from MRI independently predict survival and have the potential to improve survival prediction when added to clinical features.
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Akaike information criterion
Fluid-attenuated inversion recovery
Field of view
Integrated area under the receiver operating characteristic curve
Karnofsky Performance Status
Least absolute shrinkage and selection operator
Radiologic risk score
Contrast-enhanced T1-weighted imaging
The Cancer Genome Atlas
The Cancer Imaging Archive
Visually Accessible Rembrandt Images
World Health Organization
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This study has received funding from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies & Future Planning (2017R1D1A1B03030440).
The scientific guarantor of this publication is Sung Soo Ahn.
Conflict of interest
The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Statistics and biometry
One of the authors has significant statistical expertise.
Kyunghwa Han, Ph.D., from the Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, has significant statistical expertise and is one of the authors.
Written informed consent was waived by the Institutional Review Board.
Institutional Review Board approval was obtained.
• Diagnostic or prognostic study
• Performed at one institution
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Park, C.J., Han, K., Shin, H. et al. MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas. Eur Radiol (2020). https://doi.org/10.1007/s00330-020-06683-2
- Isocitrate dehydrogenase
- Magnetic resonance imaging