Ahdoot M, Wilbur AR, Reese SE, Lebastchi AH, Mehralivand S, Gomella PT, Bloom J, Gurram S, Siddiqui M, Pinsky P, Parnes H, Linehan WM, Merino M, Choyke PL, Shih JH, Turkbey B, Wood BJ, Pinto PA. MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer Diagnosis. N Engl J Med 2020;382(10):917–928. doi: https://doi.org/10.1056/NEJMoa1910038

Article  PubMed  PubMed Central  Google Scholar 

Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, Collaco-Moraes Y, Ward K, Hindley RG, Freeman A, Kirkham AP, Oldroyd R, Parker C, Emberton M, group Ps. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 2017;389(10071):815–822. doi: https://doi.org/10.1016/S0140-6736(16)32401-1

Article  PubMed  Google Scholar 

Kasivisvanathan V, Rannikko AS, Borghi M, Panebianco V, Mynderse LA, Vaarala MH, Briganti A, Budäus L, Hellawell G, Hindley RG, Roobol MJ, Eggener S, Ghei M, Villers A, Bladou F, Villeirs GM, Virdi J, Boxler S, Robert G, Singh PB, Venderink W, Hadaschik BA, Ruffion A, Hu JC, Margolis D, Crouzet S, Klotz L, Taneja SS, Pinto P, Gill I, Allen C, Giganti F, Freeman A, Morris S, Punwani S, Williams NR, Brew-Graves C, Deeks J, Takwoingi Y, Emberton M, Moore CM, Collaborators PSG. MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis. N Engl J Med 2018;378(19):1767–1777. doi: https://doi.org/10.1056/NEJMoa1801993

Article  PubMed  PubMed Central  Google Scholar 

Rosenkrantz AB, Ginocchio LA, Cornfeld D, Froemming AT, Gupta RT, Turkbey B, Westphalen AC, Babb JS, Margolis DJ. Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists. Radiology 2016;280(3):793–804. doi: https://doi.org/10.1148/radiol.2016152542

Article  PubMed  Google Scholar 

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(1):76–84. doi: https://doi.org/10.1148/radiol.2020190646

Article  PubMed  Google Scholar 

Yilmaz EC, Belue MJ, Turkbey B, Reinhold C, Choyke PL. A Brief Review of Artificial Intelligence in Genitourinary Oncological Imaging. Can Assoc Radiol J 2023;74(3):534–547. doi: https://doi.org/10.1177/08465371221135782

Article  PubMed  Google Scholar 

Ramacciotti LS, Hershenhouse JS, Mokhtar D, Paralkar D, Kaneko M, Eppler M, Gill K, Mogoulianitis V, Duddalwar V, Abreu AL, Gill I, Cacciamani GE. Comprehensive Assessment of MRI-based Artificial Intelligence Frameworks Performance in the Detection, Segmentation, and Classification of Prostate Lesions Using Open-Source Databases. Urol Clin North Am 2024;51(1):131–161. doi: https://doi.org/10.1016/j.ucl.2023.08.003

Article  PubMed  Google Scholar 

Yan G, Wang Y, Chen L. Diagnostic Performance of Artificial Intelligence Based on Biparametric MRI for Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis. Acad Radiol 2025. doi: https://doi.org/10.1016/j.acra.2025.02.044

Article  PubMed  Google Scholar 

Giganti F, Moreira da Silva N, Yeung M, Davies L, Frary A, Ferrer Rodriguez M, Sushentsev N, Ashley N, Andreou A, Bradley A, Wilson C, Maskell G, Brembilla G, Caglic I, Suchánek J, Budd J, Arya Z, Aning J, Hayes J, De Bono M, Vasdev N, Sanmugalingam N, Burn P, Persad R, Woitek R, Hindley R, Liyanage S, Squire S, Barrett T, Barwick S, Hinton M, Padhani AR, Rix A, Shah A, Sala E. AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study. Eur Radiol 2025. doi: https://doi.org/10.1007/s00330-024-11323-0

Article  PubMed  PubMed Central  Google Scholar 

Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med 2019;17(1):195. doi: https://doi.org/10.1186/s12916-019-1426-2

Article  PubMed  PubMed Central  CAS  Google Scholar 

Recht MP, Dewey M, Dreyer K, Langlotz C, Niessen W, Prainsack B, Smith JJ. Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations. Eur Radiol 2020;30(6):3576–3584. doi: https://doi.org/10.1007/s00330-020-06672-5

Article  PubMed  Google Scholar 

Erdal BS, Gupta V, Demirer M, Fair KH, White RD, Blair J, Deichert B, Lafleur L, Qin MM, Bericat D. Integration and Implementation Strategies for AI Algorithm Deployment with Smart Routing Rules and Workflow Management. arXiv preprint arXiv:231110840 2023.

Gupta V, Erdal BS, Ramirez C, Floca R, Jackson L, Genereaux B, Bryson S, Bridge CP, Kleesiek J, Nensa F. Current state of community-driven radiological ai deployment in medical imaging. arXiv preprint arXiv:221214177 2022.

Mehralivand S, Yang D, Harmon SA, Xu D, Xu Z, Roth H, Masoudi S, Sanford TH, Kesani D, Lay NS, Merino MJ, Wood BJ, Pinto PA, Choyke PL, Turkbey B. A Cascaded Deep Learning-Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging. Acad Radiol 2022;29(8):1159–1168. doi: https://doi.org/10.1016/j.acra.2021.08.019

Article  PubMed  Google Scholar 

Sanford T, Zhang L, Harmon S, Sackett J, Yang D, Roth H, Xu Z, Kesani D, Mehralivand S, Baroni R, Girometti R, Oto A, Purysko A, Xu S, Pinto P, Xu D, Wood B, Choyke P, Turkbey B. Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model. AJR 2020(215):1–8. doi: https://doi.org/10.2214/AJR.19.22347

Lin Y, Yilmaz EC, Belue MJ, Harmon SA, Tetreault J, Phelps TE, Merriman KM, Hazen L, Garcia C, Yang D, Xu Z, Lay NS, Toubaji A, Merino MJ, Xu D, Law YM, Gurram S, Wood BJ, Choyke PL, Pinto PA, Turkbey B. Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI. Radiology 2024;311(2):e230750. doi: https://doi.org/10.1148/radiol.230750

Article  PubMed  Google Scholar 

Belue MJ, Mukhtar V, Ram R, Gokden N, Jose J, Massey JL, Biben E, Buddha S, Langford T, Shah S, Harmon SA, Turkbey B, Aydin AM. External Validation of an Artificial Intelligence Algorithm Using Biparametric MRI and Its Simulated Integration with Conventional PI-RADS for Prostate Cancer Detection. Acad Radiol 2025. doi: https://doi.org/10.1016/j.acra.2025.03.039

Article  PubMed  Google Scholar 

Yilmaz EC, Harmon SA, Law YM, Huang EP, Belue MJ, Lin Y, Gelikman DG, Ozyoruk KB, Yang D, Xu Z, Tetreault J, Xu D, Hazen LA, Garcia C, Lay NS, Eclarinal P, Toubaji A, Merino MJ, Wood BJ, Gurram S, Choyke PL, Pinto PA, Turkbey B. External Validation of a Previously Developed Deep Learning-based Prostate Lesion Detection Algorithm on Paired External and In-House Biparametric MRI Scans. Radiol Imaging Cancer 2024;6(6):e240050. doi: https://doi.org/10.1148/rycan.240050

Article  PubMed  PubMed Central  Google Scholar 

Yilmaz EC, Harmon SA, Lis RT, Esengur OT, Gelikman DG, Garmendia-Cedillos M, Merino MJ, Wood BJ, Patel K, Citrin DE, Gurram S, Choyke PL, Pinto PA, Turkbey B. Evaluating deep learning and radiologist performance in volumetric prostate cancer analysis with biparametric MRI and histopathologically mapped slides. Abdom Radiol (NY) 2025;50(6):2732–2744. doi: https://doi.org/10.1007/s00261-024-04734-6

Article  PubMed  Google Scholar 

Gelikman DG, Harmon SA, Kenigsberg AP, Law YM, Yilmaz EC, Merino MJ, Wood BJ, Choyke PL, Pinto PA, Turkbey B. Evaluating a deep learning AI algorithm for detecting residual prostate cancer on MRI after focal therapy. BJUI Compass 2024;5(7):665–667. doi: https://doi.org/10.1002/bco2.373

Article  PubMed  PubMed Central  Google Scholar 

Yilmaz EC, Harmon SA, Belue MJ, Merriman KM, Phelps TE, Lin Y, Garcia C, Hazen L, Patel KR, Merino MJ, Wood BJ, Choyke PL, Pinto PA, Citrin DE, Turkbey B. Evaluation of a Deep Learning-based Algorithm for Post-Radiotherapy Prostate Cancer Local Recurrence Detection Using Biparametric MRI. Eur J Radiol 2023;168:111095. doi: https://doi.org/10.1016/j.ejrad.2023.111095

Article  PubMed  PubMed Central  Google Scholar 

NVIDIA Clara Train SDK v3. https://docs.nvidia.com/clara/tlt-mi/clara-train-sdk-v3.0/index.html#. https://docs.nvidia.com/clara/tlt-mi/clara-train-sdk-v3.0/index.html#. Published 2020.

Cardoso MJ, Li W, Brown R, Ma N, Kerfoot E, Wang Y, Murrey B, Myronenko A, Zhao C, Yang D. Monai: An open-source framework for deep learning in healthcare. arXiv preprint arXiv:221102701 2022.

Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA, Committee G. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System. Am J Surg Pathol 2016;40(2):244–252. doi: https://doi.org/10.1097/PAS.0000000000000530

Park KJ, Choi SH, Lee JS, Kim JK, Kim MH. Interreader Agreement with Prostate Imaging Reporting and Data System Version 2 for Prostate Cancer Detection: A Systematic Review and Meta-Analysis. J Urol 2020;204(4):661–670. doi: https://doi.org/10.1097/JU.0000000000001200

Article  PubMed  Google Scholar 

Saha A, Bosma JS, Twilt JJ, van Ginneken B, Bjartell A, Padhani AR, Bonekamp D, Villeirs G, Salomon G, Giannarini G, Kalpathy-Cramer J, Barentsz J, Maier-Hein KH, Rusu M, Rouvière O, van den Bergh R, Panebianco V, Kasivisvanathan V, Obuchowski NA, Yakar D, Elschot M, Veltman J, Fütterer JJ, de Rooij M, Huisman H, consortium P-C. Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study. Lancet Oncol 2024;25(7):879–887. doi: https://doi.org/10.1016/S1470-2045(24)00220-1

Article  PubMed  PubMed Central  CAS  Google Scholar 

Turkbey B, Haider MA. Artificial Intelligence for Automated Cancer Detection on Prostate MRI: Opportunities and Ongoing Challenges, From the. AJR Am J Roentgenol 2022;219(2):188–194. doi: https://doi.org/10.2214/AJR.21.26917

Article  PubMed  Google Scholar 

Sohn JH, Chillakuru YR, Lee S, Lee AY, Kelil T, Hess CP, Seo Y, Vu T, Joe BN. An Open-Source, Vender Agnostic Hardware and Software Pipeline for Integration of Artificial Intelligence in Radiology Workflow. J Digit Imaging 2020;33(4):1041–1046. doi: https://doi.org/10.1007/s10278-020-00348-8

Article  PubMed  PubMed Central  Google Scholar 

Le AH, Liu B, Huang HK. Integration of computer-aided diagnosis/detection (CAD) results in a PACS environment using CAD-PACS toolkit and DICOM SR. Int J Comput Assist Radiol Surg 2009;4(4):317–329. doi: https://doi.org/10.1007/s11548-009-0297-y

Article  PubMed  Google Scholar