Fekete B, Werlenius K, Örndal C, Rydenhag B. Prognostic factors for glioblastoma patients – a clinical population-based study. Acta Neurol Scand. 2016;133(6):434–41.

Article  CAS  PubMed  Google Scholar 

Brown NF, Ottaviani D, Tazare J, Gregson J, Kitchen N, Brandner S, Fersht N, Mulholland P. Survival outcomes and prognostic factors in Glioblastoma. Cancers. 2022;14(13):3161.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Stark AM, van de Bergh J, Hedderich J, Mehdorn HM, Nabavi A. Glioblastoma: clinical characteristics, prognostic factors and survival in 492 patients. Clin Neurol Neurosurg. 2012;114(7):840–5.

Article  PubMed  Google Scholar 

Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, Hawkins C, Ng HK, Pfister SM, Reifenberger G, et al. The 2021 WHO classification of tumors of the Central Nervous System: a summary. Neurooncology. 2021;23(8):1231–51.

CAS  Google Scholar 

Ding C, Peng H. Minimum redundancy feature selection from microarray gene expression data. J Bioinform Comput Biol. 2005;3(2):185–205.

Article  CAS  PubMed  Google Scholar 

Calabrese E, Rudie JD, Rauschecker AM, Villanueva-Meyer JE, Clarke JL, Solomon DA, Cha S. Combining radiomics and deep convolutional neural network features from preoperative MRI for predicting clinically relevant genetic biomarkers in glioblastoma. Neuro-Oncology Adv. 2022;4(1):vdac060.

Article  Google Scholar 

Chen H, Lin F, Zhang J, Lv X, Zhou J, Li ZC, Chen Y. Deep learning Radiomics to predict PTEN Mutation Status from magnetic resonance imaging in patients with glioma. Front Oncol. 2021;11:734433.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hosseini SA, Hosseini E, Hajianfar G, Shiri I, Servaes S, Rosa-Neto P, Godoy L, Nasrallah MP, O’Rourke DM, Mohan S et al. MRI-Based Radiomics combined with deep learning for distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas. Cancers (Basel) 2023, 15(3).

Choi YS, Bae S, Chang JH, Kang SG, Kim SH, Kim J, Rim TH, Choi SH, Jain R, Lee SK. Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics. Neuro Oncol. 2021;23(2):304–13.

Article  CAS  PubMed  Google Scholar 

Bralten LBC, Kloosterhof NK, Balvers R, Sacchetti A, Lapre L, Lamfers M, Leenstra S, De Jonge H, Kros JM, Jansen EEW, et al. IDH1 R132H decreases proliferation of glioma cell lines in vitro and in vivo. Ann Neurol. 2011;69(3):455–63.

Article  CAS  PubMed  Google Scholar 

Jain R, Johnson DR, Patel SH, Castillo M, Smits M, Van Den Bent MJ, Chi AS, Cahill DP. Real world use of a highly reliable imaging sign: T2-FLAIR mismatch for identification of IDH mutant astrocytomas. Neurooncology. 2020;22(7):936–43.

CAS  Google Scholar 

Patel SH, Poisson LM, Brat DJ, Zhou Y, Cooper L, Snuderl M, Thomas C, Franceschi AM, Griffith B, Flanders AE, et al. T2–FLAIR mismatch, an imaging biomarker for IDH and 1p/19q status in Lower-grade gliomas: a TCGA/TCIA project. Clin Cancer Res. 2017;23(20):6078–85.

Article  CAS  PubMed  Google Scholar 

Batchala PP, Muttikkal TJE, Donahue JH, Patrie JT, Schiff D, Fadul CE, Mrachek EK, Lopes M-B, Jain R, Patel SH. Neuroimaging-based classification algorithm for Predicting 1p/19q-Codeletion status in IDH -Mutant Lower Grade Gliomas. Am J Neuroradiol 2019:ajnr;ajnr.A5957v5951.

Iwahashi H, Nagashima H, Tanaka K, Uno T, Hashiguchi M, Maeyama M, Somiya Y, Komatsu M, Hirose T, Itoh T, et al. 2-Hydroxyglutarate magnetic resonance spectroscopy in adult brainstem glioma. J Neurosurg. 2023;139(2):355–62.

Article  CAS  PubMed  Google Scholar 

Kasap DNG, Mora NGN, Blömer DA, Akkurt BH, Heindel WL, Mannil M, Musigmann M. Comparison of MRI sequences to Predict IDH Mutation Status in Gliomas using Radiomics-based machine learning. Biomedicines. 2024;12(4):725.

Article  CAS  PubMed  PubMed Central  Google Scholar 

He A, Wang P, Zhu A, Liu Y, Chen J, Liu L. Predicting IDH Mutation Status in Low-Grade Gliomas based on optimal Radiomic features combined with Multi-sequence magnetic resonance imaging. Diagnostics. 2022;12(12):2995.

Article  PubMed  PubMed Central  Google Scholar 

Hasanau T, Pisarev E, Kisil O, Nonoguchi N, Le Calvez-Kelm F, Zvereva M. Detection of TERT Promoter Mutations as a Prognostic Biomarker in Gliomas: Methodology, Prospects, and Advances. Biomedicines 2022, 10(3).

Fang S, Fan Z, Sun Z, Li Y, Liu X, Liang Y, Liu Y, Zhou C, Zhu Q, Zhang H, et al. Radiomics features predict telomerase reverse transcriptase promoter mutations in World Health Organization Grade II gliomas via a machine-learning Approach. Front Oncol. 2021;10:606741.

Article  PubMed  PubMed Central  Google Scholar 

Zhang H, Zhang H, Zhang Y, Zhou B, Wu L, Lei Y, Huang B. Deep learning Radiomics for the Assessment of Telomerase Reverse transcriptase promoter mutation status in patients with Glioblastoma using Multiparametric MRI. J Magn Reson Imaging. 2023;58(5):1441–51.

Article  PubMed  Google Scholar 

Gupta A, Young RJ, Shah AD, Schweitzer AD, Graber JJ, Shi W, Zhang Z, Huse J, Omuro AMP. Pretreatment dynamic susceptibility contrast MRI perfusion in Glioblastoma: prediction of EGFR Gene amplification. Clin Neuroradiol. 2015;25(2):143–50.

Article  CAS  PubMed  Google Scholar 

Pasquini L, Napolitano A, Lucignani M, Tagliente E, Dellepiane F, Rossi-Espagnet MC, Ritrovato M, Vidiri A, Villani V, Ranazzi G, et al. AI and high-Grade Glioma for diagnosis and outcome prediction: do all machine learning models perform equally well? Front Oncol. 2021;11:601425.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sohn B, An C, Kim D, Ahn SS, Han K, Kim SH, Kang S-G, Chang JH, Lee S-K. Radiomics-based prediction of multiple gene alteration incorporating mutual genetic information in glioblastoma and grade 4 astrocytoma, IDH-mutant. J Neurooncol. 2021;155(3):267–76.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shinojima N, Tada K, Shiraishi S, Kamiryo T, Kochi M, Nakamura H, Makino K, Saya H, Hirano H, Kuratsu J-, et al. Prognostic Value of Epidermal Growth Factor Receptor in patients with Glioblastoma Multiforme1. Cancer Res. 2003;63(20):6962–70.

CAS  PubMed  Google Scholar 

Saadeh FS, Mahfouz R, Assi HI. EGFR as a clinical marker in glioblastomas and other gliomas. Int J Biol Mark. 2018;33(1):22–32.

Article  CAS  Google Scholar 

Brandner S, McAleenan A, Jones HE, Kernohan A, Robinson T, Schmidt L, Dawson S, Kelly C, Leal ES, Faulkner CL, et al. Diagnostic accuracy of 1p/19q codeletion tests in oligodendroglioma: a comprehensive meta-analysis based on a Cochrane systematic review. Neuropathol Appl Neurobiol. 2022;48(4):e12790.

Article  CAS  PubMed  PubMed Central  Google Scholar 

McAleenan A, Jones HE, Kernohan A, Robinson T, Schmidt L, Dawson S, Kelly C, Spencer Leal E, Faulkner CL, Palmer A, et al. Diagnostic test accuracy and cost-effectiveness of tests for codeletion of chromosomal arms 1p and 19q in people with glioma. Cochrane Database Syst Rev. 2022;3(3):CD013387.

PubMed  Google Scholar 

Lv L, Zhang Y, Zhao Y, Wei Q, Zhao Y, Yi Q. Effects of 1p/19q codeletion on Immune phenotype in Low Grade Glioma. Front Cell Neurosci 2021, 15.

Kihira S, Derakhshani A, Leung M, Mahmoudi K, Bauer A, Zhang H, Polson J, Arnold C, Tsankova NM, Hormigo A, et al. Multi-parametric Radiomic Model to predict 1p/19q Co-deletion in patients with IDH-1 mutant glioma: added value to the T2-FLAIR mismatch sign. Cancers. 2023;15(4):1037.

Article  PubMed  PubMed Central  Google Scholar 

Peng Y, Ren Y, Huang B, Tang J, Jv Y, Mao Q, Liu Y, Lei Y, Zhang Y. A validated prognostic nomogram for patients with H3 K27M-mutant diffuse midline glioma. Sci Rep. 2023;13(1):9970.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kandemirli SG, Kocak B, Naganawa S, Ozturk K, Yip SSF, Chopra S, Rivetti L, Aldine AS, Jones K, Cayci Z, et al. Machine learning-based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas. World Neurosurg. 2021;151:e78–85.

Article  PubMed  Google Scholar 

Shao H, Gong J, Su X, Chen N, Li S, Yang X, Zhang S, Huang Z, Hu W, Gong Q, et al. MRI characteristics of H3 G34-mutant diffuse hemispheric gliomas and possible differentiation from IDH-wild-type glioblastomas in adolescents and young adults. J Neurosurg Pediatr. 2024;33(3):236–44.

PubMed  Google Scholar 

Lasocki A, Abdalla G, Chow G, Thust SC. Imaging features associated with H3 K27-altered and H3 G34-mutant gliomas: a narrative systematic review. Cancer Imaging. 2022;22(1):63.

Article  PubMed  PubMed Central  Google Scholar 

Vettermann FJ, Felsberg J, Reifenberger G, Hasselblatt M, Forbrig R, Berding G, La Fougère C, Galldiks N, Schittenhelm J, Weis J, et al. Characterization of diffuse gliomas with histone H3-G34 mutation by MRI and dynamic 18F-FET PET. Clin Nucl Med. 2018;43(12):895–8.

Article  PubMed  Google Scholar 

Kurokawa R, Baba A, Kurokawa M, Pinarbasi ES, Makise N, Ota Y, Kim J, Srinivasan A, Moritani T. Neuroimaging features