Biparametric magnetic resonance imaging (bpMRI), excluding dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), is a potential replacement for multiparametric MRI (mpMRI) in diagnosing clinically significant prostate cancer (csPCa). An extensive international multireader multicase observer study was conducted to assess the noninferiority of bpMRI to mpMRI in csPCa diagnosis.
An observer study was conducted with 400 mpMRI examinations from four European centers, excluding examinations with prior prostate treatment or csPCa (Gleason grade [GG] ≥2) findings. Readers assessed bpMRI and mpMRI sequentially, assigning lesion-specific Prostate Imaging Reporting and Data System (PI-RADS) scores (3-5) and a patient-level suspicion score (0-100). The noninferiority of patient-level bpMRI versus mpMRI csPCa diagnosis was evaluated using the area under the receiver operating curve (AUROC) alongside the sensitivity and specificity at PI-RADS ≥3 with a 5% margin. The secondary outcomes included insignificant prostate cancer (GG1) diagnosis, diagnostic evaluations at alternative risk thresholds, decision curve analyses (DCAs), and subgroup analyses considering reader expertise. Histopathology and ≥3 yr of follow-up were used for the reference standard.
Sixty-two readers (45 centers and 20 countries) participated. The prevalence of csPCa was 33% (133/400); bpMRI and mpMRI showed similar AUROC values of 0.853 (95% confidence interval [CI], 0.819-0.887) and 0.859 (95% CI, 0.826-0.893), respectively, with a noninferior difference of -0.6% (95% CI, -1.2% to 0.1%, p < 0.001). At PI-RADS ≥3, bpMRI and mpMRI had sensitivities of 88.6% (95% CI, 84.8-92.3%) and 89.4% (95% CI, 85.8-93.1%), respectively, with a noninferior difference of -0.9% (95% CI, -1.7% to 0.0%, p < 0.001), and specificities of 58.6% (95% CI, 52.3-63.1%) and 57.7% (95% CI, 52.3-63.1%), respectively, with a noninferior difference of 0.9% (95% CI, 0.0-1.8%, p < 0.001). At alternative risk thresholds, mpMRI increased sensitivity at the expense of reduced specificity. DCA demonstrated the highest net benefit for an mpMRI pathway in cancer-averse scenarios, whereas a bpMRI pathway showed greater benefit for biopsy-averse scenarios. A subgroup analysis indicated limited additional benefit of DCE MRI for nonexperts. Limitations included that biopsies were conducted based on mpMRI imaging, and reading was performed in a sequential order.
It has been found that bpMRI is noninferior to mpMRI in csPCa diagnosis at AUROC, along with the sensitivity and specificity at PI-RADS ≥3, showing its value in individuals without prior csPCa findings and prostate treatment. Additional randomized prospective studies are required to investigate the generalizability of outcomes.
European urology. 2024 Oct 21 [Epub ahead of print]
Jasper J Twilt, Anindo Saha, Joeran S Bosma, Bram van Ginneken, Anders Bjartell, Anwar R Padhani, David Bonekamp, Geert Villeirs, Georg Salomon, Gianluca Giannarini, Jayashree Kalpathy-Cramer, Jelle Barentsz, Klaus H Maier-Hein, Mirabela Rusu, Olivier Rouvière, Roderick van den Bergh, Valeria Panebianco, Veeru Kasivisvanathan, Nancy A Obuchowski, Derya Yakar, Mattijs Elschot, Jeroen Veltman, Jurgen J Fütterer, Henkjan Huisman, Maarten de Rooij, PI-CAI Consortium
Minimally Invasive Image-Guided Intervention Center, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands. Electronic address: ., Minimally Invasive Image-Guided Intervention Center, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands; Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands., Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands., Department of Urology, Skåne University Hospital, Lund, Sweden; Division of Translational Cancer Research, Lund University Cancer Centre, Lund, Sweden., Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, UK., Division of Radiology, Deutsches Krebsforschungszentrum, Heidelberg, Germany., Department of Diagnostic Sciences, Ghent University Hospital, Ghent, Belgium., Martini Clinic, Prostate Cancer Center, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany., Urology Unit, Santa Maria della Misericordia University Hospital, Udine, Italy., Division of Artificial Medical Intelligence in Ophthalmology, University of Colorado, Boulder, CO, USA., Department of Medical Imaging, Andros Clinics, Amsterdam, The Netherlands., Division of Medical Image Computing, Deutsches Krebsforschungszentrum, Heidelberg, Germany; Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany., Departments of Radiology, Urology and Biomedical Data Science, Stanford University, Stanford, CA, USA., Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France; Faculté de Médecine Lyon-Est, Université Lyon 1, Université de Lyon, Lyon, France., Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands., Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome, Rome, Italy., Division of Surgery and Interventional Sciences, University College London and University College London Hospital, London, UK., Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Diagnostic Radiology, Cleveland Clinic Foundation, Cleveland, OH, USA., Department of Radiology, University Medical Center Groningen, Groningen, The Netherlands; Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands., Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway., Department of Radiology, Ziekenhuisgroep Twente, Almelo, The Netherland; Department of Multi-Modality Medical Imaging, Technical Medical Centre, University of Twente, Enschede, The Netherlands., Minimally Invasive Image-Guided Intervention Center, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands., Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway., Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.