Evidence map›Paper›PMID 34850354›Full record

ArticleLa Radiologia medica2022

The impact of multiparametric MRI features to identify the presence of prevalent cribriform pattern in the peripheral zone tumors.

Caterina Gaudiano, Lorenzo Bianchi, Antonio De Cinque, Beniamino Corcioni, Francesca Giunchi, Riccardo Schiavina, Michelangelo Fiorentino, Eugenio Brunocilla, Rita Golfieri

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Article in La Radiologia medica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 27% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Caterina GaudianoDepartment of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy. caterina.gaudiano@aosp.bo.it.ORCID http://orcid.org/0000-0002-3849-8428
Lorenzo BianchiDivision of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Antonio De CinqueDepartment of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Beniamino CorcioniDepartment of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Francesca GiunchiDepartment of Pathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Riccardo SchiavinaDivision of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Michelangelo FiorentinoDepartment of Specialty, Diagnostic and Experimental Medicine, University of Bologna, Via Massarenti 9, Bologna, Italy.
Eugenio BrunocillaDivision of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Rita GolfieriDepartment of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy.
Azienda USL di Bologna · ITUniversity of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas). MATERIAL AND

methodsWe retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative (n = 25) and positive (n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP.

resultsConsidering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56-0.81P, p = 0.003) and 0.72 (95% CI 0.62-0.82P, p = 0.001), respectively.

conclusionsThe mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa.

Indexed as

AgedHumansMaleMiddle AgedMultiparametric Magnetic Resonance ImagingProstateProstatectomyProstatic NeoplasmsRetrospective StudiesCribriform patternGleason PatternMultiparametric magnetic resonance imagingPI-RADS version 2.1Prostate cancer

Identifiers

PMID34850354
OpenAlexW3217396210

What OpenQuestion holds

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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.