Evidence map›Paper›PMID 36415216›Full record

ArticleJournal of the Belgian Society of Radiology2022

A Comparative Study of Multiparametric MRI Sequences in Measuring Prostate Cancer Index Lesion Volume.

Omer Bagcilar, Deniz Alis, Mustafa Seker, Servet Erdemli, Umut Karaarslan, Aylin Kus, Cavit Kayhan, Yesim Saglican, Ali Kural, Ercan Karaarslan

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In one paragraph

Article in Journal of the Belgian Society of Radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Omer BagcilarSilivri State Hospital, TR.ORCID https://orcid.org/0000-0002-0639-0287
Deniz AlisAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0002-7045-1793
Mustafa SekerAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0001-7664-5786
Servet ErdemliAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0001-5545-768X
Umut KaraarslanAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0001-6559-8996
Aylin KusAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0003-4843-3860
Cavit KayhanAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0001-5754-9289
Yesim SaglicanAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0002-7666-9021
Ali KuralAcibadem Mehmet Ali Aydinlar University, TR.ORCID https://orcid.org/0000-0003-3488-0571
Ercan KaraarslanAcibadem Mehmet Ali Aydinlar University, School of Medicine, TR.ORCID https://orcid.org/0000-0002-4581-4273

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To compare the effectiveness of individual multiparametric prostate MRI (mpMRI) sequences-T2W, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE)-in assessing prostate cancer (PCa) index lesion volume using whole-mount pathology as the ground-truth; to assess the impact of an endorectal coil (ERC) on the measurements. Materials and Methods: We retrospectively enrolled 72 PCa patients who underwent 3T mpMRI with (n = 39) or without (n = 33) an ERC. A pathologist drew the index lesion borders on whole-mount pathology using planimetry (whole-mount Results: The median T2W Conclusion: T2W

Indexed as

comparative studymagnetic resonance imagingprostate cancerWhole-mount pathology

Identifiers

PMID36415216
PMCPMC9650977

What OpenQuestion holds

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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.