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Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.

World neurosurgery - 1 Jul 2021

Kandemirli Sedat Giray, Kocak Burak, Naganawa Shotaro, Ozturk Kerem, Yip Stephen S F, Chopra Saurav, Rivetti Luciano, Aldine Amro Saad, Jones Karra, Cayci Zuzan, Moritani Toshio, Sato Takashi Shawn

Abstract excerpt

OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distinguishing imaging features compared with wild-type gliomas. We aimed to construct an MRI machine learning (ML)-based radiomic model to predict H3K27M mutation in...

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PMID: 33819703
DOI: 10.1016/j.wneu.2021.03.135

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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