Evidence map›Paper›PMID 37543656›Full record

SynthesisProstate cancer and prostatic diseases2024

Novel non-MRI imaging techniques for primary diagnosis of prostate cancer: micro-ultrasound, contrast-enhanced ultrasound, elastography, multiparametric ultrasound, and PSMA PET/CT.

Francesco Ditonno, Antonio Franco, Celeste Manfredi, Alessandro Veccia, Massimo Valerio, Laura Bukavina, Lucas B Zukowski, Srinivas Vourganti, Arnuf Stenzl, Gerald L Andriole and 3 more

Abstract readMeta-AnalysisReview
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In one paragraph

Synthesis in Prostate cancer and prostatic diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  10. Prostate cancer detection: achieving an optimal balance.Prostate cancer and prostatic diseases · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Francesco DitonnoDepartment of Urology, Rush University Medical Center, Chicago, IL, USA.ORCID 0009-0005-0126-4731
Antonio FrancoDepartment of Urology, Rush University Medical Center, Chicago, IL, USA.
Celeste ManfrediDepartment of Urology, Rush University Medical Center, Chicago, IL, USA.
Alessandro VecciaDepartment of Urology, University of Verona, Verona, Italy.
Massimo ValerioUrology Department, Lausanne University Hospital, Lausanne, Switzerland.
Laura BukavinaDepartment of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
Lucas B ZukowskiDepartment of Urology, Rush University Medical Center, Chicago, IL, USA.
Srinivas VourgantiDepartment of Urology, Rush University Medical Center, Chicago, IL, USA.
Arnuf StenzlDepartment of Urology, University Hospital Tuebingen, Tuebingen, Germany.
Gerald L AndrioleJohns Hopkins Medicine, Sibley Memorial Hospital, Washington, DC, USA.
Alessandro AntonelliDepartment of Urology, University of Verona, Verona, Italy.
Cosimo De NunzioDepartment of Urology, Sant'Andrea Hospital, La Sapienza University, Rome, Italy.ORCID 0000-0002-2190-512X
Riccardo AutorinoDepartment of Urology, Rush University Medical Center, Chicago, IL, USA. ricautor@gmail.com.ORCID 0000-0001-7045-7725

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultiparametric magnetic resonance imaging (mpMRI) provides enhanced diagnostic accuracy in the detection of prostate cancer, but is not devoid of limitations. Given the recent evolution of non-MRI imaging techniques, this critical review of the literature aimed at summarizing the available evidence on ultrasound-based and nuclear medicine imaging technologies in the initial diagnosis of PCa.

methodsThree databases (PubMed®, Web of Science™, and Scopus®) were queried for studies examining their diagnostic performance in the primary diagnosis of PCa, weighted against a histological confirmation of PCa diagnosis, using a free-text protocol. Retrospective and prospective studies, both comparative and non-comparative, systematic reviews (SR) and meta-analysis (MA) were included. Based on authors' expert opinion, studies were selected, data extracted, and results qualitatively described.

resultsMicro-ultrasound (micro-US) appears as an appealing diagnostic strategy given its high accuracy in detection of PCa, apparently non-inferior to mpMRI. The use of multiparametric US (mpUS) likely gives an advantage in terms of effectiveness coming from the combination of different modalities, especially when certain modalities are combined. Prostate-specific membrane antigen (PSMA) PET/CT may represent a whole-body, one-step approach for appropriate diagnosis and staging of PCa. The direct relationship between lesions avidity of radiotracers and histopathologic and prognostic features, and its valid diagnostic performance represents appealing characteristics. However, intrinsic limits of each of these techniques exist and further research is needed before definitively considering them reliable tools for accurate PCa diagnosis. Other novel technologies, such as elastography and multiparametric US, currently relies on a limited number of studies, and therefore evidence about them remains preliminary.

conclusionEvidence on the role of non-MRI imaging options in the primary diagnosis of PCa is steadily building up. This testifies a growing interest towards novel technologies that might allow overcoming some of the limitations of current gold standard MRI imaging.

Indexed as

Elasticity Imaging TechniquesProstatic NeoplasmsHumansMagnetic Resonance ImagingMalePositron Emission Tomography Computed TomographyProspective StudiesRetrospective Studies

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.