2024
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-gammaNeuroradiologists
2022
NIMG-07. APPLYING A GLIOMA-TRAINED DEEP LEARNING AUTO-SEGMENTATION TOOL ON BM PRE- AND POST-RADIOSURGERY
Kaur M, Varghese S, Jekel L, Tillmanns N, Merkaj S, Bousabarah K, Lin M, Bhawnani J, Chiang V, Aboian M. NIMG-07. APPLYING A GLIOMA-TRAINED DEEP LEARNING AUTO-SEGMENTATION TOOL ON BM PRE- AND POST-RADIOSURGERY. Neuro-Oncology 2022, 24: vii162-vii163. PMCID: PMC9660643, DOI: 10.1093/neuonc/noac209.626.Peer-Reviewed Original ResearchStereotactic radiosurgeryPosttreatment lesionsBoard-certified neuroradiologistsRoutine clinical useWhole tumorTumor coreMulticentric lesionsTreatment responsePeritumoral edemaBM preLesionsClinical useVolumetric segmentationEdemaPatientsT2w FLAIRTherapy planningTumorsDedicated trainingLesion detectionBM dataVolumetric measurementsBMMRIPre