{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T22:08:21Z","timestamp":1779228501929,"version":"3.51.4"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643682648","type":"print"},{"value":"9781643682655","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,6]]},"abstract":"<jats:p>Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue types and prognosis. They could be graded with four levels according to the 2007 WHO classification. The emergence of non-invasive histological and molecular diagnostics for nervous system neoplasms can revolutionize the efficacy and safety of medical care and radically reduce healthcare costs. Our pilot study aimed to evaluate the diagnostic accuracy of deep learning (DL) in subtyping gliomas by WHO grades (I\u2013IV) based on preoperative magnetic resonance imaging (MRI) from Burdenko Neurosurgery Center\u2019s database. A total of 707 MRI studies was included. A \u201c3D classification\u201d approach predicting tumor type for the entire patient\u2019s MRI data showed the best result (accuracy = 83%, ROC AUC = 0.95), consistent with that of other authors who used different methodologies. Our preliminary results proved the separability of MR T1 axial images with contrast enhancement by WHO grade using DL.<\/jats:p>","DOI":"10.3233\/shti220163","type":"book-chapter","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:33:19Z","timestamp":1654594399000},"source":"Crossref","is-referenced-by-count":3,"title":["Noninvasive Glioma Grading with Deep Learning: A Pilot Study"],"prefix":"10.3233","author":[{"given":"Gleb","family":"Danilov","sequence":"first","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vladislav","family":"Korolev","sequence":"additional","affiliation":[{"name":"Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Shifrin","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eugene","family":"Ilyushin","sequence":"additional","affiliation":[{"name":"Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Narek","family":"Maloyan","sequence":"additional","affiliation":[{"name":"Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Saada","sequence":"additional","affiliation":[{"name":"Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timur","family":"Ishankulov","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramin","family":"Afandiev","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Shevchenko","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatyana","family":"Konakova","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatyana","family":"Tsukanova","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Svetlana","family":"Shugay","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Igor","family":"Pronin","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Potapov","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2021: One World, One Health \u2013 Global Partnership for Digital Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220163","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:33:20Z","timestamp":1654594400000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220163"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,6]]},"ISBN":["9781643682648","9781643682655"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220163","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,6]]}}}