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Record W4414084547 · doi:10.1001/jama.2025.13722

Biparametric vs Multiparametric MRI for Prostate Cancer Diagnosis

2025· article· en· W4414084547 on OpenAlexaff
Alexander Ng, Aqua Asif, Ridhi Agarwal, Valeria Panebianco, Rossano Girometti, Sangeet Ghai, Enrique Gómez‐Gómez, Lars Budäus, Tristan Barrett, Jan Philipp Radtke, Claudia Kesch, Francesco De Cobelli, Samir S. Taneja, Jim C. Hu, Ash Tewari, M.A. Rodríguez Cabello, Adriano Basso Dias, Lance A. Mynderse, Marcelo Borghi, Lars Boesen, Paras B. Singh, Raphaële Renard‐Penna, Jeffrey J. Leow, Fabian Falkenbach, Martina Pecoraro, Gianluca Giannarini, Nathan Perlis, Daniel López-Ruiz, Christof Kastner, Lars Schimmöller, Marimo Rossiter, Arjun Nathan, Pramit Khetrapal, Vinson Wai‐Shun Chan, Aiman Haider, Caroline S. Clarke, Shonit Punwani, Chris Brew‐Graves, Louise Dickinson, Anita Mitra, Giorgio Brembilla, Daniel J. A. Margolis, Yemisi Takwoingi, Mark Emberton, Clare Allen, Francesco Giganti, Caroline M. Moore, Veeru Kasivisvanathan, Alberto Briganti, Alessandro Crestani, Alessandro Sciarra, Alex Freeman, Alex Kirkham, Alexandre R. Zlotta, Ana Blanca, Anders Bjartell, Andrew Ryan, Angela Tong, Anne Y. Warren, Antonella Borrelli, Antonette Andrews, Antonio Finelli, Antonio Ciardi, Antti Rannikko, Armando Stabile, Arnauld Villers, Arturo Platas Sancho, Ashley Baring, Ashoke Roy, Bas Israël, Boris Hadaschik, Carolina Aulló González, Caroline English, Chau Hung Lee, Chiara Zuiani, Christien Caris, Conrad von Stempel, Cristina Amate, Daniel Yong, Davide Rozze, Derek J. Lomas, Donato Cannoletta, Eileen Wang Chang, Emanuele Messina, Gaia Zussino, Gerald Antoch, Giorgio Gandaglia, G. Robert, Guido Sauter, Harini Thevarajah, Harriet Sorrell, Hazel McBain, Henning Reis, Hernando Ríos Pita, Ingrid Potyka, Iztok Caglič, Jeanlou Collavino, Jens Theysohn, Jeremy Grummet, Jing Yi Weng, John Wilkinson, Jon Piper, Jonathan J Deeks, Jonathan O’Brien, José Valero Rosa, Juan Luis Sanz, Juan Mesa Quesada, Kai Jannusch, Kateri Corr, Kenneth Haines, Lale Umutlu, Leonardo Quarta, Letizia Casarotto, Linda Gimeno, Luca Orecchia, Ludovica Laschena, Lukas Drewes, Maarten de Rooij, Manuel Sanchez Ostos, Marco Bicchetti, Marco Gatti, M. Peris, Mariano Volpacchio, Mark Prentice, Markus Graefen, Matteo Soligo, Matthias Boschheidgen, Matthias Roethke, Maurizio Del Monte, M. Singhera, Monali Fatterpekar, Mulham Al‐Nader, Mykyta Kachanov, Nadeem Shaida, Naoki Takahashi, Neil Fleshner, Nicola Muirhead, Nikhil Vasdev, Nimalan Sanmugalingam, Nis Nørgaard, Pete Vicente, Peter Albers, Peter Incze, Philip Ryan, Philippe Rouvier, Pierre Mozer, Pieter De Visschere, Públio César Cavalcante Viana, Rafael E. Jiménez, Réka Novotta, Richard O’Sullivan, Rikke Karlin Jepsen, Robert Frese, Rosemary Clow, Rouvier Al‐Monajjed, Sara Lewis, Sophia Cashman, Stefano Pizzolitto, S. Lelie, Sydney Lindner, Syed Ahmar Shah, Tarek Al‐Hammouri, Teresa González Sánchez, Tharakeswara Bathala, Theodorus van der Kwast, Thomas Reid, Timothy McClure, Tobias Maurer, Valeria Peruzzi, Vibeke Løgager, Vinay Prabhu, Vinayak Wagaskar, Wim P.J. Witjes

Bibliographic record

VenueJAMA · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsUniversity Health NetworkWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsProstate cancerMultiparametric MRIMagnetic resonance imagingCancerMEDLINE

Abstract

fetched live from OpenAlex

Importance: Multiparametric magnetic resonance imaging (MRI), with or without prostate biopsy, has become the standard of care for diagnosing clinically significant prostate cancer. Resource capacity limits widespread adoption. Biparametric MRI, which omits the gadolinium contrast sequence, is a shorter and cheaper alternative offering time-saving capacity gains for health systems globally. Objective: To assess whether biparametric MRI is noninferior to multiparametric MRI for diagnosis of clinically significant prostate cancer. Design, Setting, and Participants: A prospective, multicenter, within-patient, noninferiority trial of biopsy-naive men from 22 centers (12 countries) with clinical suspicion of prostate cancer (elevated prostate-specific antigen [PSA] level and/or abnormal digital rectal examination findings) from April 2022 to September 2023, with the last follow-up conducted on December 3, 2024. Interventions: Participants underwent multiparametric MRI, comprising T2-weighted, diffusion-weighted, and dynamic contrast-enhanced (DCE) sequences. Radiologists reported abbreviated biparametric MRI first (T2-weighted and diffusion-weighted), blinded to the DCE sequence. After unblinding, radiologists reported the full multiparametric MRI. Patients underwent a targeted biopsy with or without systematic biopsy if either biparametric MRI or multiparametric MRI was suggestive of clinically significant prostate cancer. Main outcomes and measures: The primary outcome was the proportion of men with clinically significant prostate cancer. Secondary outcomes included the proportion of men with clinically insignificant cancer. The noninferiority margin was 5%. Results: Of 555 men recruited, 490 were included for primary outcome analysis. Median age was 65 (IQR, 59-70) years and median PSA level was 5.6 (IQR, 4.4-8.0) ng/mL. The proportion of patients with abnormal digital rectal examination findings was 12.7%. Biparametric MRI was noninferior to multiparametric MRI, detecting clinically significant prostate cancer in 143 of 490 men (29.2%), compared with 145 of 490 men (29.6%) (difference, -0.4 [95% CI, -1.2 to 0.4] percentage points; P = .50). Biparametric MRI detected clinically insignificant cancer in 45 of 490 men (9.2%), compared with 47 of 490 men (9.6%) with the use of multiparametric MRI (difference, -0.4 [95% CI, -1.2 to 0.4] percentage points). Central quality control demonstrated that 99% of scans were of adequate diagnostic quality. Conclusion and relevance: In men with suspected prostate cancer, provided image quality is adequate, an abbreviated biparametric MRI scan, with or without targeted biopsy, could become the new standard of care for prostate cancer diagnosis. With approximately 4 million prostate MRIs performed globally annually, adopting biparametric MRI could substantially increase scanner throughput and reduce costs worldwide. Trial registration: ClinicalTrials.gov Identifier: NCT04571840.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.325
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2025
Admission routes1
Has abstractyes

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