Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

doi:10.1038/s41598-019-56767-3

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Article

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Scientific reports - 30 Dec 2019

Fukuma Ryohei, Yanagisawa Takufumi, Kinoshita Manabu, Shinozaki Takashi, Arita Hideyuki, Kawaguchi Atsushi, Takahashi Masamichi, Narita Yoshitaka, Terakawa Yuzo, Tsuyuguchi Naohiro, Okita Yoshiko, Nonaka Masahiro, Moriuchi Shusuke, Takagaki Masatoshi, Fujimoto Yasunori, Fukai Junya, Izumoto Shuichi, Ishibashi Kenichi, Nakajima Yoshikazu, Shofuda Tomoko, Kanematsu Daisuke, Yoshioka Ema, Kodama Yoshinori, Mano Masayuki, Mori Kanji, Ichimura Koichi, Kanemura Yonehiro, Kishima Haruhiko

Abstract excerpt

Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutional neural network (CNN) from magnetic resonance (MR) images and compared the accuracy to that of a diagnosis based on conventional radiomic features and patient age. Multisite preoperative MR images of 164 patients with grade II/III glioma were grouped by IDH and...

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Identifiers

PMID: 31889117
DOI: 10.1038/s41598-019-56767-3
PMCID: PMC6937237

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

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