2024
Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI
Lost J, Ashraf N, Jekel L, von Reppert M, Tillmanns N, Willms K, Merkaj S, Petersen G, Avesta A, Ramakrishnan D, Omuro A, Nabavizadeh A, Bakas S, Bousabarah K, De Lin M, Aneja S, Sabel M, Aboian M. Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI. Neuro-Oncology Advances 2024, vdae157. DOI: 10.1093/noajnl/vdae157.Peer-Reviewed Original ResearchIsocitrate dehydrogenase mutation statusArea under the curveMagnetic resonance imagingMutation statusML modelsMachine learningSemi-automated tumour segmentationsPre-surgical magnetic resonance imagingCare of glioma patientsMachine learning modelsClinical care of glioma patientsIsocitrate dehydrogenase statusAnnotated datasetsFeature extractionPrediction taskMulti-institutional dataModel trainingIDH mutationsPredicting IDH mutationLearning modelsRetrospective studyHeterogeneous datasetsTumor segmentationGlioma patientsBrain tumors
2014
Transcriptional diversity of long-term glioblastoma survivors
Gerber NK, Goenka A, Turcan S, Reyngold M, Makarov V, Kannan K, Beal K, Omuro A, Yamada Y, Gutin P, Brennan CW, Huse JT, Chan TA. Transcriptional diversity of long-term glioblastoma survivors. Neuro-Oncology 2014, 16: 1186-1195. PMID: 24662514, PMCID: PMC4136896, DOI: 10.1093/neuonc/nou043.Peer-Reviewed Original ResearchConceptsMemorial Sloan-Kettering Cancer CenterLong-term survivorsLong-term glioblastoma survivorsIDH mutationsIDH2 mutational statusMedian overall survivalStrong prognostic valueBiology of glioblastomaMGMT promoter methylationMedian survivalOverall survivalBetter prognosisPoor prognosisPrognostic valueCancer CenterAggressive typeIndependent cohortMesenchymal subtypeREMBRANDT cohortMutational statusIDH2 mutationsGBM biologyPatientsMGMT methylationMGMT promoter