Evidence map›Paper›PMID 35548894›Full record

ArticleDiagnostic and interventional radiology (Ankara, Turkey)2022

Arterial input function for quantitative dynamic contrast-enhanced MRI to diagnose prostate cancer.

Farid Ziayee, Anja Mueller-Lutz, Janina Gross, Tim Ullrich, Michael Quentin, Christian Arsov, Gerald Antoch, Hans-Jörg Wittsack, Lars Schimmöller

Open access · greenAbstract read
In one paragraph

Article in Diagnostic and interventional radiology (Ankara, Turkey), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

9 authors at 1 institution in 1 country.

Farid ZiayeeDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Anja Mueller-LutzDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Janina GrossDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Tim UllrichDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Michael QuentinDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Christian ArsovDepartment of Urology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Gerald AntochDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Hans-Jörg WittsackDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Lars SchimmöllerDepartment of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Düsseldorf University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PURPOSE This study aims to analyze the ability of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to distinguish between prostate cancer (PCa) and benign lesions in transition zone (TZ) and peripheral zone (PZ) using different methods for arterial input function (AIF) determination. Study endpoints are identification of a standard AIF method and optimal quantitative perfusion parameters for PCa detection. METHODS DCE image data of 50 consecutive patients with PCa who underwent multiparametric MRI were analyzed retrospectively with three different methods of AIF acquisition. First, a region of interest was manually defined in an artery (AIFm); second, an automated algorithm was used (AIFa); and third, a population-based AIF (AIFp) was applied. Values of quantitative parameters after Tofts (Ktrans, ve, and kep) in PCa, PZ, and TZ in the three different AIFs were analyzed. RESULTS Ktrans and kep were significantly higher in PCa than in benign tissue independent from the AIF method. Whereas in PZ, Ktrans and kep could differentiate PCa (P < .001), in TZ only kep using AIFpdemonstrated a significant difference (P = .039). The correlations of the perfusion parameters that resulted from AIFm and AIFa were higher than those that resulted from AIFp, and the absolute values of Ktrans, kep, and ve were significantly lower when using AIFp. The values of quantitative perfusion parameters for PCa were similar regardless of whether PCa was located in PZ or TZ. CONCLUSION Ktrans and kep were able to differentiate PCa from benign PZ independent of the AIF method. AIFaseems to be the most feasible method of AIF determination in clinical routine. For TZ, none of the quantitative perfusion parameters provided satisfying results.

Indexed as

Contrast MediaProstatic NeoplasmsAlgorithmsArteriesHumansMagnetic Resonance ImagingMaleRetrospective StudiesContrast Media

Identifiers

PMID35548894
PMCPMC12278924
OpenAlexW4280611020

What OpenQuestion holds

Textmetadata
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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.