2020
Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel
Westphalen AC, McCulloch CE, Anaokar JM, Arora S, Barashi NS, Barentsz JO, Bathala TK, Bittencourt LK, Booker MT, Braxton VG, Carroll PR, Casalino DD, Chang SD, Coakley FV, Dhatt R, Eberhardt SC, Foster BR, Froemming AT, Fütterer JJ, Ganeshan DM, Gertner MR, Mankowski Gettle L, Ghai S, Gupta RT, Hahn ME, Houshyar R, Kim C, Kim CK, Lall C, Margolis DJA, McRae SE, Oto A, Parsons RB, Patel NU, Pinto PA, Polascik TJ, Spilseth B, Starcevich JB, Tammisetti VS, Taneja SS, Turkbey B, Verma S, Ward JF, Warlick CA, Weinberger AR, Yu J, Zagoria RJ, Rosenkrantz AB. Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel. Radiology 2020, 296: 76-84. PMID: 32315265, PMCID: PMC7373346, DOI: 10.1148/radiol.2020190646.Peer-Reviewed Original ResearchConceptsPositive predictive valuePI-RADS scoreProstate cancerPI-RADSGleason scorePredictive valueRetrospective cross-sectional studyHigh-grade prostate cancerObserved positive predictive valueOverall positive predictive valueUntreated prostate cancerProstate MRIInterquartile rangeSignificant prostate cancerProstate Imaging ReportingCross-sectional studyMixed-model logistic regressionProstate cancer diseaseReporting Data SystemMRI lesionsBiopsy resultsActive surveillanceClinical careMRI scansImaging Reporting
2016
Multisite, multivendor validation of the accuracy and reproducibility of proton‐density fat‐fraction quantification at 1.5T and 3T using a fat–water phantom
Hernando D, Sharma SD, Ghasabeh M, Alvis BD, Arora SS, Hamilton G, Pan L, Shaffer JM, Sofue K, Szeverenyi NM, Welch EB, Yuan Q, Bashir MR, Kamel IR, Rice MJ, Sirlin CB, Yokoo T, Reeder SB. Multisite, multivendor validation of the accuracy and reproducibility of proton‐density fat‐fraction quantification at 1.5T and 3T using a fat–water phantom. Magnetic Resonance In Medicine 2016, 77: 1516-1524. PMID: 27080068, PMCID: PMC4835219, DOI: 10.1002/mrm.26228.Peer-Reviewed Original ResearchMagnetic resonance-ultrasound fusion prostate biopsy in the diagnosis of prostate cancer
Tyson MD, Arora SS, Scarpato KR, Barocas D. Magnetic resonance-ultrasound fusion prostate biopsy in the diagnosis of prostate cancer. Urologic Oncology Seminars And Original Investigations 2016, 34: 326-332. PMID: 27083114, PMCID: PMC4912896, DOI: 10.1016/j.urolonc.2016.03.005.Peer-Reviewed Original ResearchMeSH KeywordsHumansImage-Guided BiopsyMagnetic Resonance ImagingMaleProstatic NeoplasmsReproducibility of ResultsConceptsMultiparametric magnetic resonance imagingMR-US fusionProstate cancerMR-US fusion biopsyLow-risk cancersFusion prostate biopsyProstate needle biopsyBore MRI-guided biopsyMRI-guided biopsyMagnetic resonance imagingInsignificant diseaseFusion biopsyProstate biopsyNeedle biopsySuspicious lesionsTransrectal ultrasoundBiopsyBiopsy techniqueResonance imagingCancerDirect targetingRelevant diseasesProstateDiseaseDiagnosis
2009
Atherosclerotic Plaque Progression in Carotid Arteries: Monitoring with High-Spatial-Resolution MR Imaging—Multicenter Trial
Boussel L, Arora S, Rapp J, Rutt B, Huston J, Parker D, Yuan C, Bassiouny H, Saloner D, Investigators F. Atherosclerotic Plaque Progression in Carotid Arteries: Monitoring with High-Spatial-Resolution MR Imaging—Multicenter Trial. Radiology 2009, 252: 789-96. PMID: 19508991, PMCID: PMC2734890, DOI: 10.1148/radiol.2523081798.Peer-Reviewed Original ResearchConceptsStatin therapyCarotid arteryVessel wall volumeInstitutional review boardMR imagingRate of progressionAtherosclerotic plaque progressionUnenhanced T1-weighted imagesSite's institutional review boardMagnetic resonance imagingT1-weighted imagesU.S. study sitesMean annual changeAtheroma volumeClinical factorsMulticenter trialCarotid diseaseFraction of studiesMulticenter studyPlaque progressionMultiple linear regression analysisLow bifurcationPatientsArteryLinear regression analysis