RADT-12. DERIVING IMAGING BIOMARKERS FOR PRIMARY CENTRAL NERVOUS SYSTEM LYMPHOMA USING DEEP LEARNING
Zhu J, Hager T, Chadha S, Sritharan D, Weiss D, Hossain S, Osenberg K, Moore N, Aneja S. RADT-12. DERIVING IMAGING BIOMARKERS FOR PRIMARY CENTRAL NERVOUS SYSTEM LYMPHOMA USING DEEP LEARNING. Neuro-Oncology 2024, 26: viii74-viii74. PMCID: PMC11553274, DOI: 10.1093/neuonc/noae165.0296.Peer-Reviewed Original ResearchPrimary central nervous system lymphomaWhole-brain radiotherapyTreated with chemotherapyOverall survivalHigh-risk groupPatient phenotypesCentral nervous system lymphomaPCNSL treatmentRisk of neurocognitive side effectsImaging biomarkersC-statisticOne-year OSTwo-year OSNervous system lymphomaAssociated with improved outcomesLog-rank testNeurocognitive side effectsTime-dependent AUCBrain radiotherapySystem lymphomaTumor volumeTumor sizeRisk stratificationAnalyses assessed differencesSub-analysisA large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information
Ramakrishnan D, Jekel L, Chadha S, Janas A, Moy H, Maleki N, Sala M, Kaur M, Petersen G, Merkaj S, von Reppert M, Baid U, Bakas S, Kirsch C, Davis M, Bousabarah K, Holler W, Lin M, Westerhoff M, Aneja S, Memon F, Aboian M. A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. Scientific Data 2024, 11: 254. PMID: 38424079, PMCID: PMC10904366, DOI: 10.1038/s41597-024-03021-9.Peer-Reviewed Original ResearchConceptsWhole-brain radiotherapyStereotactic radiosurgeryT1 post-contrastBrain metastasesPost-contrastSide effectsImage informationArtificial intelligenceAssociated with cognitive side effectsContrast-enhancing lesionsQuality of datasetsCognitive side effectsFLAIR MR imagesValidation of AI modelsBrain radiotherapyLimitations of algorithmsStandard treatmentAI modelsMR imagingAI networksContrast enhancementClinical settingSegmentation workflowDatasetClinical adoption