P10.25.A STANDARDIZATION AND AUTOMATIZATION OF MEASURING AND REPORTING BRAIN METASTASIS OVER TIME BY LEVERAGING ARTIFICIAL INTELLIGENCE
Weiss D, Bousabarah K, Deuschl C, Chadha S, Ashraf N, Ramakrishnan D, Moawad A, Osenberg K, Schoenherr S, Lautenschlager J, Holler W, Westerhoff M, Schrickel E, Memon F, Moily N, Malhotra A, Lin M, Aboian M. P10.25.A STANDARDIZATION AND AUTOMATIZATION OF MEASURING AND REPORTING BRAIN METASTASIS OVER TIME BY LEVERAGING ARTIFICIAL INTELLIGENCE. Neuro-Oncology 2024, 26: v61-v61. PMCID: PMC11485790, DOI: 10.1093/neuonc/noae144.201.Peer-Reviewed Original ResearchReports of brain metastasesBrain metastasesInter-observer variabilityFollow-up imaging of patientsPost-Gamma knife radiosurgeryBrain tumorsRANO-BM criteriaFollow-up imagingBoard-certified neuroradiologistsTreatment response monitoringMean Dice coefficientImages of patientsNnU-Net segmentationManual diameter measurementsBM evaluationRANO-BMRetrospective studyTreatment regimenSpearman correlation coefficientInter-rater variabilityMRI reportsIdentified lesionsPercentual changePost-gammaNeuroradiologistsEnhancing clinical decision-making: An externally validated machine learning model for predicting isocitrate dehydrogenase mutation in gliomas using radiomics from presurgical magnetic resonance imaging
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, Lin M, Aneja S, Sabel M, Aboian M. Enhancing clinical decision-making: An externally validated machine learning model for predicting isocitrate dehydrogenase mutation in gliomas using radiomics from presurgical magnetic resonance imaging. Neuro-Oncology Advances 2024, 6: vdae157. PMID: 39659829, PMCID: PMC11630777, 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