Evidence map›Paper›PMID 36601020›Full record

ReviewTherapeutic advances in urology

Multiparametric ultrasound of prostate: role in prostate cancer diagnosis.

Masatomo Kaneko, Maria Sarah L Lenon, Lorenzo Storino Ramacciotti, Luis G Medina, Aref S Sayegh, Anibal La Riva, Laura C Perez, Alireza Ghoreifi, Maria Lizana, Donya S Jadvar and 3 more

Abstract readReview
In one paragraph

Review in Therapeutic advances in urology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Masatomo KanekoCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0002-1205-807X
Maria Sarah L LenonCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Lorenzo Storino RamacciottiCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Luis G MedinaCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Aref S SayeghCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0001-9320-2987
Anibal La RivaCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0003-2198-833X
Laura C PerezCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Alireza GhoreifiCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Maria LizanaCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0002-0648-6043
Donya S JadvarDornsife School of Letters and Science, University of Southern California, Los Angeles, CA, USA.
Amir H LebastchiCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Giovanni E CacciamaniCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Andre Luis AbreuCenter for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology and Catherine & Joseph Aresty.ORCID https://orcid.org/0000-0002-9167-2587

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in ultrasonography (US) technology established modalities, such as Doppler-US, HistoScanning, contrast-enhanced ultrasonography (CEUS), elastography, and micro-ultrasound. The early results of these US modalities have been promising, although there are limitations including the need for specialized equipment, inconsistent results, lack of standardizations, and external validation. In this review, we identified studies evaluating multiparametric ultrasonography (mpUS), the combination of multiple US modalities, for prostate cancer (PCa) diagnosis. In the past 5 years, a growing number of studies have shown that use of mpUS resulted in high PCa and clinically significant prostate cancer (CSPCa) detection performance using radical prostatectomy histology as the reference standard. Recent studies have demonstrated the role mpUS in improving detection of CSPCa and guidance for prostate biopsy and therapy. Furthermore, some aspects including lower costs, real-time imaging, applicability for some patients who have contraindication for magnetic resonance imaging (MRI) and availability in the office setting are clear advantages of mpUS. Interobserver agreement of mpUS was overall low; however, this limitation can be improved using standardized and objective evaluation systems such as the machine learning model. Whether mpUS outperforms MRI is unclear. Multicenter randomized controlled trials directly comparing mpUS and multiparametric MRI are warranted.

Indexed as

multiparametric ultrasonographyprostate biopsyprostate cancer

Identifiers

PMID36601020
PMCPMC9806443

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.