MRI Features May Predict Molecular Features of Glioblastoma in Isocitrate Dehydrogenase Wild-Type Lower-Grade Gliomas
نویسندگان
چکیده
منابع مشابه
MRI features predict p53 status in lower-grade gliomas via a machine-learning approach
Background P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images. Methods Preoperative MR images were retrospectively obtained from 272 patients with primary grade II/III gliomas. The patients were randomly allocated i...
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Diffuse gliomas and secondary glioblastomas (GBMs) that develop from low-grade gliomas are a common and incurable class of brain tumor. Mutations in the metabolic enzyme glioblastomas (IDH1) represent a distinguishing feature of low-grade gliomas and secondary GBMs. IDH1 mutations are one of the most common and earliest detectable genetic alterations in low-grade diffuse gliomas, and evidence s...
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ژورنال
عنوان ژورنال: American Journal of Neuroradiology
سال: 2021
ISSN: 0195-6108,1936-959X
DOI: 10.3174/ajnr.a6983