Residual Convolutional Neural Network for Determination of IDH Status in Low- and High-grade Gliomas from MR Imaging
Chang K, Bai HX, Zhou H, Su C, Bi WL, Agbodza E, Kavouridis VK, Senders JT, Boaro A, Beers A, Zhang B, Capellini A, Liao W, Shen Q, Li X, Xiao B, Cryan J, Ramkissoon S, Ramkissoon L, Ligon K, Wen PY, Bindra RS, Woo J, Arnaout O, Gerstner ER, Zhang PJ, Rosen BR, Yang L, Huang RY, Kalpathy-Cramer J. Residual Convolutional Neural Network for Determination of IDH Status in Low- and High-grade Gliomas from MR Imaging. Clinical Cancer Research 2018, 24: clincanres.2236.2017. PMID: 29167275, PMCID: PMC6051535, DOI: 10.1158/1078-0432.ccr-17-2236.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBrainBrain NeoplasmsDatasets as TopicFemaleGliomaHumansImage Processing, Computer-AssistedIsocitrate DehydrogenaseMagnetic Resonance ImagingMaleMiddle AgedMutationNeoplasm GradingNeural Networks, ComputerPredictive Value of TestsPreoperative PeriodRetrospective StudiesYoung AdultConceptsResidual convolutional neural networkConvolutional neural networkNeural networkDeep learning techniquesTesting setNeural network modelMulti-institutional data setCancer Imaging ArchiveLearning techniquesTesting accuracyNetwork modelTraining setPrediction accuracyPreoperative radiographic dataClin Cancer ResData setsConventional MR imagingHospital of UniversityIsocitrate dehydrogenase (IDH) mutationPreoperative imagingLonger survivalWomen's HospitalGrade IINetworkTreatment decisions