Evidence map›Paper›PMID 34738219›Full record

ArticleEuropean radiology experimental2021

Multiparametric prostate MRI quality assessment using a semi-automated PI-QUAL software program.

Francesco Giganti, Sydney Lindner, Jonathan W Piper, Veeru Kasivisvanathan, Mark Emberton, Caroline M Moore, Clare Allen

Open access · goldAbstract read
In one paragraph

Article in European radiology experimental, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Integrating Artificial Intelligence into Prostate MR Imaging: Technical Foundations, Clinical Applications, and Workflow Implications.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026
    Review
  3. AI in Prostate MRI: A Task-Based Review.Journal of the Korean Society of Radiology · 2025
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Tasks for artificial intelligence in prostate MRI.European radiology experimental · 2022
    Review
  11. Review
  12. Review
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

7 authors at 3 institutions in 2 countries.

Francesco GigantiDepartment of Radiology, University College London Hospital NHS Foundation Trust, London, UK. f.giganti@ucl.ac.uk.ORCID 0000-0001-5218-6431
Sydney LindnerMIM Software Inc., Cleveland, OH, USA.
Jonathan W PiperMIM Software Inc., Cleveland, OH, USA.
Veeru KasivisvanathanDivision of Surgery & Interventional Science, University College London, 3rd Floor, Charles Bell House, 43-45 Foley St., W1W 7TS, London, UK.
Mark EmbertonDepartment of Urology, University College London Hospital NHS Foundation Trust, London, UK.
Caroline M MooreDivision of Surgery & Interventional Science, University College London, 3rd Floor, Charles Bell House, 43-45 Foley St., W1W 7TS, London, UK.
Clare AllenDepartment of Radiology, University College London Hospital NHS Foundation Trust, London, UK.
University College London Hospitals NHS Foundation Trust · GBRHAMM Technologies (United States) · USUniversity College Hospital · GB

Funding

Department of Health
6 · The paper itself

Abstract

The technical requirements for the acquisition of multiparametric magnetic resonance imaging (mpMRI) of the prostate have been clearly outlined in the Prostate Imaging Reporting and Data System (PI-RADS) guidelines, but there is still huge variability in image quality among centres across the world. It has been difficult to quantify what constitutes a good-quality image, and a first attempt to address this matter has been the publication of the Prostate Imaging Quality (PI-QUAL) score and its dedicated scoring sheet. This score includes the assessment of technical parameters that can be obtained from the DICOM files along with a visual evaluation of certain features on prostate MRI (e.g., anatomical structures). We retrospectively analysed the image quality of 10 scans from different vendors and magnets using a semiautomated dedicated PI-QUAL software program and compared the time needed for assessing image quality using two methods (semiautomated assessment versus manual filling of the scoring sheet). This semiautomated software is able to assess the technical parameters automatically, but the visual assessment is still performed by the radiologist. There was a significant reduction in the reporting time of prostate mpMRI quality according to PI-QUAL using the dedicated software program compared to manual filling (5'54″ versus 7'59″; p = 0.005). A semiautomated PI-QUAL software program allows the radiologist to assess the technical details related to the image quality of prostate mpMRI in a quick and reliable manner, allowing clinicians to have more confidence that the quality of mpMRI of the prostate is sufficient to determine patient care.

Indexed as

Multiparametric Magnetic Resonance ImagingProstatic NeoplasmsHumansMagnetic Resonance ImagingMaleProstateRetrospective StudiesSoftwareMultiparametric magnetic resonance imagingProstatic neoplasmsQuality improvementsSoftware

Identifiers

PMID34738219
PMCPMC8568748
OpenAlexW3210816284

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.