Featured Publications
Artificial Intelligence in Breast Cancer Screening
Potnis K, Ross J, Aneja S, Gross C, Richman I. Artificial Intelligence in Breast Cancer Screening. JAMA Internal Medicine 2022, 182: 1306-1312. PMID: 36342705, PMCID: PMC10623674, DOI: 10.1001/jamainternmed.2022.4969.Peer-Reviewed Original ResearchPrevalence of Missing Data in the National Cancer Database and Association With Overall Survival
Yang DX, Khera R, Miccio JA, Jairam V, Chang E, Yu JB, Park HS, Krumholz HM, Aneja S. Prevalence of Missing Data in the National Cancer Database and Association With Overall Survival. JAMA Network Open 2021, 4: e211793. PMID: 33755165, PMCID: PMC7988369, DOI: 10.1001/jamanetworkopen.2021.1793.Peer-Reviewed Original ResearchMeSH KeywordsAgedData ManagementDatabases, FactualFemaleFollow-Up StudiesHumansMaleMiddle AgedNeoplasmsPrevalenceRegistriesRetrospective StudiesSurvival RateUnited StatesConceptsNational Cancer DatabaseNon-small cell lung cancerOverall survivalCell lung cancerCancer DatabaseMedical recordsLung cancerProstate cancerBreast cancerPatient recordsComplete dataRetrospective cohort studyCohort studyCancer RegistryCommon cancerVariables of interestHigh prevalenceMAIN OUTCOMEPatientsClinical advancementReal-world data sourcesCancerPrevalenceSurvivalHeterogeneous differencesComparison 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
2023
Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial
Kann B, Likitlersuang J, Bontempi D, Ye Z, Aneja S, Bakst R, Kelly H, Juliano A, Payabvash S, Guenette J, Uppaluri R, Margalit D, Schoenfeld J, Tishler R, Haddad R, Aerts H, Garcia J, Flamand Y, Subramaniam R, Burtness B, Ferris R. Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial. The Lancet Digital Health 2023, 5: e360-e369. PMID: 37087370, PMCID: PMC10245380, DOI: 10.1016/s2589-7500(23)00046-8.Peer-Reviewed Original ResearchConceptsExtranodal extensionOropharyngeal carcinomaShort-axis diameterChallenging cohortPathology reportsECOG-ACRIN Cancer Research GroupDe-escalation trialsCancer Research GroupDe-escalation strategiesSurgical pathology reportsNational Cancer InstituteInter-reader agreementLargest short-axis diameterPostoperative chemoradiationProtocol exclusionsConcurrent chemoradiationPrimary endpointMulticentre trialPretreatment CTAdjuvant strategiesHuman papillomavirusTreatment selection toolUS National InstitutesPretreatment identificationStudy protocol
2018
MRI-Ultrasound Fusion Targeted Biopsy of Prostate Imaging Reporting and Data System Version 2 Category 5 Lesions Found False-Positive at Multiparametric Prostate MRI.
Sheridan AD, Nath SK, Aneja S, Syed JS, Pahade J, Mathur M, Sprenkle P, Weinreb JC, Spektor M. MRI-Ultrasound Fusion Targeted Biopsy of Prostate Imaging Reporting and Data System Version 2 Category 5 Lesions Found False-Positive at Multiparametric Prostate MRI. American Journal Of Roentgenology 2018, 210: w218-w225. PMID: 29489409, DOI: 10.2214/ajr.17.18680.Peer-Reviewed Original ResearchConceptsPI-RADS 5 lesionsBenign pathologic resultsLower prostate-specific antigen densitySignificant prostate cancerProstate-specific antigen densityBenign prostatic hyperplasia nodulesMRI-ultrasound fusionProstate Imaging ReportingCategory 5 lesionsPathologic resultsProstate cancerClinical featuresBenign diseaseAntigen densityImaging ReportingGleason 6 diseasePI-RADS version 2High-risk lesionsMultivariate logistic regressionRoutine clinical interpretationMultiparametric prostate MRIInflammatory changesNormal anatomic structuresBiopsy resultsTargeted biopsies
2017
Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI.
Sheridan AD, Nath SK, Syed JS, Aneja S, Sprenkle PC, Weinreb JC, Spektor M. Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI. American Journal Of Roentgenology 2017, 210: 347-357. PMID: 29112469, DOI: 10.2214/ajr.17.18516.Peer-Reviewed Original ResearchConceptsCategory 3 lesionsData System (BI-RADS) category 3 lesionsPI-RADS category 3 lesionsMultiparametric prostate MRIRisk factorsProstate Imaging ReportingProstate MRIAbnormal digital rectal examination findingsPredictive valueImaging ReportingDigital rectal examination findingsClinically Significant Prostate CancerMultivariate logistic regression modelPI-RADS category 3Smaller prostate volumePI-RADS version 2Older patient ageRectal examination findingsMore risk factorsRisk stratification algorithmMRI-ultrasound fusionSignificant prostate cancerNegative predictive valuePositive predictive valueLogistic regression models