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Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 See also the editorial by Badve and Hodges in this issue.
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http://dx.doi.org/10.1148/radiol.233120 | DOI Listing |
Sci Rep
September 2025
Department of Neurosurgery, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, 518035, P.R. China.
Glioblastoma multiforme (GBM) is a lethal brain tumor with limited therapies. NUF2, a kinetochore protein involved in cell cycle regulation, shows oncogenic potential in various cancers; however, its role in GBM pathogenesis remains unclear. In this study, we investigated NUF2's function and mechanisms in GBM and developed an MRI-based machine learning model to predict its expression non-invasively, and evaluated its potential as a therapeutic target and prognostic biomarker.
View Article and Find Full Text PDFFree Radic Biol Med
August 2025
Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China. Electronic address:
Gliomas are highly aggressive and heterogeneous brain tumors with poor clinical outcomes, necessitating an urgent need for novel prognostic biomarkers and therapeutic targets. Redox regulation, which balances reactive oxygen species (ROS) generation with antioxidant defense mechanisms, has emerged as a crucial adaptive mechanism supporting glioma progression. However, the precise roles and clinical implications of redox-associated genes in glioma remain poorly defined.
View Article and Find Full Text PDFActa Neuropathol
August 2025
Divison of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
IDH-mutant gliomas represent a subtype of diffuse gliomas that primarily affect patients in early to mid-adolescence. These tumors are classified into three distinct CNS WHO grades of malignancy. Accurate grading is essential for selecting an appropriate treatment maximizing anti-tumor efficacy while minimizing adverse effects.
View Article and Find Full Text PDFEur Radiol
August 2025
Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia.
Objectives: We aimed to evaluate the diagnostic performance of deep learning (DL)-based radiomics models for the noninvasive prediction of isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status in glioma patients using MRI sequences, and to identify methodological factors influencing accuracy and generalizability.
Materials And Methods: Following PRISMA guidelines, we systematically searched major databases (PubMed, Scopus, Embase, Web of Science, and Google Scholar) up to March 2025, screening studies that utilized DL to predict IDH and 1p/19q co-deletion status from MRI data. We assessed study quality and risk of bias using the Radiomics Quality Score and the QUADAS-2 tool.
IEEE Trans Comput Biol Bioinform
July 2025
Brain cancer has a very high mortality rate. Gliomas are the most common malignant brain tumors, causing this severe fatality. Recent biological investigations revealed that a holistic study of biomarkers, responsible for causing genetic mutations in gliomas, can ensure a comprehensive prognosis and treatment plan for the patients.
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