Evidence map›Paper›PMID 42371294›Full record

ArticleLa Radiologia medica2026

Diagnostic performance of bpMRI versus mpMRI and AI-assisted bpMRI in prostate cancer detection: a multi-reader study.

Luca Russo, Silvia Bottazzi, Luca D'Erme, Giacomo Avesani, Valerio Di Paola, Salvatore Persiani, Alessandra Iacono, Ina Isufi, Lucy Davies, Zobair Arya and 8 more

Abstract readComparative Study
In one paragraph

Article in La Radiologia medica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

18 authors.

Luca RussoFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy. lucarusso.md@gmail.com.ORCID http://orcid.org/0000-0002-0495-7462
Silvia BottazziFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Luca D'ErmeFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Giacomo AvesaniFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Valerio Di PaolaFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Salvatore PersianiFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Alessandra IaconoUniversità Cattolica del Sacro Cuore, Rome, Italy.
Ina IsufiUniversità Cattolica del Sacro Cuore, Rome, Italy.
Lucy DaviesLucida Medical Ltd, Cambridge, UK.
Zobair AryaLucida Medical Ltd, Cambridge, UK.
Matteo MancinoUniversità Cattolica del Sacro Cuore, Rome, Italy.
Francesca LiaUniversità Cattolica del Sacro Cuore, Rome, Italy.
Giuseppe PallottaFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Maria Chiara SighinolfiUniversità Cattolica del Sacro Cuore, Rome, Italy.
Francesco PiercontiFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Bernardo RoccoFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Evis SalaFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
Benedetta GuiFondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo compare biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for detecting clinically significant prostate cancer (csPCa), and to assess the impact of artificial intelligence (AI)-assisted bpMRI on diagnostic performance and biopsy-related outcomes in readers with different expertise. MATERIAL AND

methodsIn this retrospective multi-reader study, 173 men referred for prostate mpMRI were evaluated by five radiologists (two experts, three basic readers) who scored bpMRI and mpMRI using PI-RADS v2.1. After a 45-day wash-out, the same readers reinterpreted bpMRI with concurrent AI decision support (available for 127 cases). Diagnostic performance for csPCa (ISUP ≥ 2) and benefit-to-harm ratios were compared across protocols and reader groups.

resultsMean area under the receiver operating characteristic curve was 0.820 for bpMRI and 0.819 for mpMRI (difference 0.001), indicating comparable diagnostic performance. In the AI subset, AI increased mean specificity from 59.7% to 67.8% while reducing sensitivity from 90.2% to 84.5%. Biopsy selectivity and efficiency improved (3.9 to 4.6 and 1.7-1.9), particularly in basic readers. The effect was significant in basic readers (McNemar p = 0.012 for sensitivity, p < 0.001 for specificity) but not in experts.

conclusionbpMRI showed comparable performance to mpMRI for csPCa detection in routine practice. AI-assisted bpMRI improved biopsy efficiency in less-experienced readers at the cost of reduced sensitivity, warranting careful consideration of the trade-off between missed cancers and avoided unproductive biopsies.

Indexed as

Artificial IntelligenceMagnetic Resonance ImagingMultiparametric Magnetic Resonance ImagingProstatic NeoplasmsAgedClinical RelevanceHumansMaleMiddle AgedRetrospective StudiesSensitivity and SpecificityArtificial intelligenceDecision supportMagnetic resonance imagingProstatic neoplasms

Identifiers

PMID42371294
PMCPMC13658483

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.