Featured Publications
Comparison of radiomic feature aggregation methods for patients with multiple tumors
Chang E, Joel MZ, Chang HY, Du J, Khanna O, Omuro A, Chiang V, Aneja S. Comparison of radiomic feature aggregation methods for patients with multiple tumors. Scientific Reports 2021, 11: 9758. PMID: 33963236, PMCID: PMC8105371, DOI: 10.1038/s41598-021-89114-6.Peer-Reviewed Original ResearchConceptsCox proportional hazards modelCox proportional hazardsProportional hazards modelBrain metastasesRadiomic featuresHazards modelProportional hazardsStandard Cox proportional hazards modelMultifocal brain metastasesMultiple brain metastasesNumber of patientsPatient-level outcomesHigher concordance indexRadiomic feature analysisRandom survival forest modelSurvival modelsDifferent tumor volumesMultifocal tumorsCancer outcomesMultiple tumorsMetastatic cancerConcordance indexTumor volumePatientsTumor types
2024
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-analysis