ArticleEuropean radiology2021
Reproducible imaging-based prediction of molecular subtype and risk stratification of gliomas across different experience levels using a structured reporting system.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Review
- Phenotype augmentation using generative AI for isocitrate dehydrogenase mutation prediction in glioma.Scientific reports · 2025Article
- Preoperative prediction of diffuse glioma type and grade in adults: a gadolinium-free MRI-based decision tree.European radiology · 2025Article
- Contrast-enhanced ultrasound can differentiate the level of glioma infiltration and correlate it with biological behavior: a study based on local pathology.Journal of ultrasound · 2025Article
- Unraveling the heterogeneity of WHO grade 4 gliomas: insights from clinical, imaging, and molecular characterization.Discover oncology · 2025Article
- IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations.iScience · 2025Article
- Association between dichotomized VASARI feature and overall survival in glioblastoma patients: a single-institution propensity score matching analysis.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- The T2-FLAIR mismatch sign in oncologic neuroradiology: History, current use, emerging data, and future directions.The neuroradiology journal · 2024Review
- Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction.Neuro-oncology · 2024Article
- Intratumoral calcification: not only a diagnostic but also a prognostic indicator in oligodendrogliomas.European radiology · 2024Article
- Beyond invasive biopsies: using VASARI MRI features to predict grade and molecular parameters in gliomas.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- VASARI 2.0: a new updated MRI VASARI lexicon to predict grading andFrontiers in oncology · 2024Article
- Advances in diffuse glial tumors diagnosis.Arquivos de neuro-psiquiatria · 2023Review
- Radiogenomics: a key component of precision cancer medicine.British journal of cancer · 2023Review
- Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System.Korean journal of radiology · 2023Article
- The sinuous, wave-like intratumoral-wall sign is a sensitive and specific radiological biomarker for oligodendrogliomas.European radiology · 2023Article
- Structured reporting in neuro-oncological imaging: achieving reliable prediction of molecular subtypes in glioma based on pre-treatment multi-sequence MRI.European radiology · 2021Article
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7 authors.
Funding
Abstract
objectivesTo determine reproducible MRI parameters predictive of molecular subtype and risk stratification in glioma and develop a structured reporting system.
methodsAll study patients were initially diagnosed with glioma, 141 from the Cancer Genome Atlas and 131 from our tertiary institution, as training and validation sets, respectively. Images were analyzed by three neuroradiologists with 1-7 years of experience. MRI features including contrast enhancement pattern, necrosis, margin, edema, T2/FLAIR mismatch, internal cyst, and cerebral blood volume higher than normal cortex were reported using a structured reporting system. The pathology was stratified into five risk types: (1) oligodendroglioma, isocitrate dehydrogenase [IDH]-mutant, 1p19q co-deleted; (2) diffuse astrocytoma, IDH-mutant, grade II-III; (3) glioblastoma, IDH-mutant, grade IV; (4) diffuse astrocytoma, IDH-wild, grade II-III; and (5) glioblastoma, IDH-wild, grade IV. Significant predictors were selected using multivariate logistic regression, and diagnostic performance was tested using a validation set.
resultsReproducible imaging parameters exhibiting > 50% agreement across readers included the presence of necrosis, T2/FLAIR mismatch, internal cyst, and predominant contrast enhancement. In the validation set, prediction of risk type 5 exhibited the highest diagnostic performance with AUCs of 0.92 (reader 1) and 0.93 (reader 2) with predominant enhancement, followed by risk type 2 with AUCs of 0.95 and 0.95 with T2/FLAIR mismatch sign and no necrosis, and risk type 1 with AUCs of 0.84 and 0.83 with internal cyst or necrosis. Risk types 3 and 4 were difficult to visually predict.
conclusionsImaging parameters with high reproducibility enabling prediction of IDH-wild-type glioblastoma, IDH-mutant/1p19q co-deletion oligodendroglioma, and IDH-mutant diffuse astrocytoma were identified. KEY POINTS: • Reproducible MRI parameters for determining molecular subtypes of glioma included the presence of necrosis, T2/FLAIR mismatch, internal cyst, and predominant contrast enhancement. • IDH-wild type glioblastoma, IDH-mutant/1p19q co-deletion oligodendroglioma, and IDH-mutant low-grade astrocytoma were identified using MRI parameters with high inter-reader reproducibility. • Identification of IDH-wild type low-grade glioma and IDH-mutant glioblastoma was difficult by visual analysis.
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