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 typesUsing Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology
Joel MZ, Umrao S, Chang E, Choi R, Yang DX, Duncan JS, Omuro A, Herbst R, Krumholz HM, Aneja S. Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology. JCO Clinical Cancer Informatics 2022, 6: e2100170. PMID: 35271304, PMCID: PMC8932490, DOI: 10.1200/cci.21.00170.Peer-Reviewed Original Research
2024
A 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
2023
Selected-Lesion Stereotactic Radiosurgery in Treatment of Patients with Multiple Brain Metastases: A Single Institution Retrospective Study
Mange A, Singh C, Theriault B, Hansen J, An Y, Aneja S, Chiang V. Selected-Lesion Stereotactic Radiosurgery in Treatment of Patients with Multiple Brain Metastases: A Single Institution Retrospective Study. International Journal Of Radiation Oncology • Biology • Physics 2023, 117: e135. DOI: 10.1016/j.ijrobp.2023.06.939.Peer-Reviewed Original ResearchMultiple brain metastasesBrain metastasesStereotactic radiosurgeryMedian KPSCommon indicationTumor characteristicsClinical trialsSRS treatmentSingle-institution retrospective studySubsequent-line treatmentMethods Clinical dataPatient selection criteriaTreatment of patientsSubset of lesionsNumber of lesionsDiagnosis of melanomaCNS progressionCNS radiationPrior WBRTOverall survivalPalliative treatmentPatient characteristicsProgressive diseaseImmunotherapy trialsSurvival groupPACS-Integrated Tools for Peritumoral Edema Volumetrics Provide Additional Information to RANO-BM-Based Assessment of Lung Cancer Brain Metastases after Stereotactic Radiotherapy: A Pilot Study
Kaur M, Petersen G, Jekel L, von Reppert M, Varghese S, de Oliveira Santo I, Avesta A, Aneja S, Omuro A, Chiang V, Aboian M. PACS-Integrated Tools for Peritumoral Edema Volumetrics Provide Additional Information to RANO-BM-Based Assessment of Lung Cancer Brain Metastases after Stereotactic Radiotherapy: A Pilot Study. Cancers 2023, 15: 4822. PMID: 37835516, PMCID: PMC10571649, DOI: 10.3390/cancers15194822.Peer-Reviewed Original ResearchPost-SRTStereotactic radiotherapyLung cancer brain metastasesCancer brain metastasesPost-contrast T1-weighted imagesSignificant clinical symptomsContrast-enhancing tumorT1-weighted imagesCritical additional informationEdema changesBrain metastasesClinical symptomsCare treatmentHyperintense volumeEdema assessmentLesion changesLesion sizeEdemaDifferent timepointsPilot studyRadiotherapyLesionsVolumetric changesAdditional informationMETS
2022
NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET
Jekel L, Bousabarah K, Lin M, Merkaj S, Kaur M, Avesta A, Aneja S, Omuro A, Chiang V, Scheffler B, Aboian M. NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET. Neuro-Oncology 2022, 24: vii162-vii162. PMCID: PMC9661012, DOI: 10.1093/neuonc/noac209.622.Peer-Reviewed Original Research