2023
Development and Validation of MRI Imaging Biomarkers for Prostate Cancer Using Deep Learning
Hossain S, Hossain S, Avesta A, Nene A, Maresca R, Aneja S. Development and Validation of MRI Imaging Biomarkers for Prostate Cancer Using Deep Learning. International Journal Of Radiation Oncology • Biology • Physics 2023, 117: e393. DOI: 10.1016/j.ijrobp.2023.06.1517.Peer-Reviewed Original ResearchBiochemical-free survivalSeminal vesicle invasionHigh-risk phenotypeExtraprostatic extensionProstate cancerHigh riskRadical prostatectomyProstate MRILower riskImaging biomarkersNon-invasive imaging biomarkersPost-treatment PSAUnderwent radical prostatectomyIntermediate-risk patientsDiscriminatory abilityLog-rank testAggressive prostate cancerProstate cancer patientsProstate cancer phenotypePersonalization of treatmentMATERIAL/METHODSGood discriminatory abilityMedian followTreatment escalationFree survival
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