PI-QUAL version 2: an update of a standardised scoring system for the assessment of image quality of prostate MRI.

Magnetic resonance imaging Prostatic neoplasms Quality control

Journal

European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774

Informations de publication

Date de publication:
24 May 2024
Historique:
received: 26 02 2024
accepted: 20 04 2024
revised: 17 04 2024
medline: 24 5 2024
pubmed: 24 5 2024
entrez: 24 5 2024
Statut: aheadofprint

Résumé

Multiparametric MRI is the optimal primary investigation when prostate cancer is suspected, and its ability to rule in and rule out clinically significant disease relies on high-quality anatomical and functional images. Avenues for achieving consistent high-quality acquisitions include meticulous patient preparation, scanner setup, optimised pulse sequences, personnel training, and artificial intelligence systems. The impact of these interventions on the final images needs to be quantified. The prostate imaging quality (PI-QUAL) scoring system was the first standardised quantification method that demonstrated the potential for clinical benefit by relating image quality to cancer detection ability by MRI. We present the updated version of PI-QUAL (PI-QUAL v2) which applies to prostate MRI performed with or without intravenous contrast medium using a simplified 3-point scale focused on critical technical and qualitative image parameters. CLINICAL RELEVANCE STATEMENT: High image quality is crucial for prostate MRI, and the updated version of the PI-QUAL score (PI-QUAL v2) aims to address the limitations of version 1. It is now applicable to both multiparametric MRI and MRI without intravenous contrast medium. KEY POINTS: High-quality images are essential for prostate cancer diagnosis and management using MRI. PI-QUAL v2 simplifies image assessment and expands its applicability to prostate MRI without contrast medium. PI-QUAL v2 focuses on critical technical and qualitative image parameters and emphasises T2-WI and DWI.

Identifiants

DOI: 10.1007/s00330-024-10795-4 PMID: 38787428
pubmed: 38787428
doi: 10.1007/s00330-024-10795-4
pii: 10.1007/s00330-024-10795-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

Références

van der Leest M, Cornel E, Israel B et al (2019) Head-to-head comparison of transrectal ultrasound-guided prostate biopsy versus multiparametric prostate resonance imaging with subsequent magnetic resonance-guided biopsy in biopsy-naive men with elevated prostate-specific antigen: a large prospective multicenter clinical study. Eur Urol 75:570–578
doi: 10.1016/j.eururo.2018.11.023 pubmed: 30477981
Rouvière O, Puech P, Renard-Penna R et al (2019) Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy-naive patients (MRI-FIRST): a prospective, multicentre, paired diagnostic study. Lancet Oncol 20:100–109
doi: 10.1016/S1470-2045(18)30569-2 pubmed: 30470502
Kasivisvanathan V, Stabile A, Neves JB et al (2019) Magnetic resonance imaging-targeted biopsy versus systematic biopsy in the detection of prostate cancer: a systematic review and meta-analysis. Eur Urol 76:284–303
Ahmed HU, El-Shater Bosaily A, Brown LC et al (2017) Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 389:815–822
doi: 10.1016/S0140-6736(16)32401-1 pubmed: 28110982
Mottet N, van den Bergh RCN, Briers E et al (2021) EAU-EANM-ESTRO-ESUR-SIOG guidelines on prostate cancer-2020 update. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol 79:243–262
doi: 10.1016/j.eururo.2020.09.042 pubmed: 33172724
Barrett T, de Rooji M, Giganti F, Allen C, Barentsz JO, Padhani AR (2023) Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway. Nat Rev Urol 20:9–22
doi: 10.1038/s41585-022-00648-4 pubmed: 36168056
Padhani AR, Schoots IG, Turkbey B, Giannarini G, Barentsz JO (2021) A multifaceted approach to quality in the MRI-directed biopsy pathway for prostate cancer diagnosis. Eur Radiol 31:4386–4389
doi: 10.1007/s00330-020-07527-9 pubmed: 33241520
Dinneen E, Allen C, Strange T et al (2022) Negative mpMRI rules out extra-prostatic extension in prostate cancer before robot-assisted radical prostatectomy. Diagnostics (Basel) 12:1057
Turkbey B, Rosenkrantz AB, Haider MA et al (2019) Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. Eur Urol 76:340–351
doi: 10.1016/j.eururo.2019.02.033 pubmed: 30898406
Sackett J, Shih JH, Reese SE et al (2020) Quality of prostate MRI: Is the PI-RADS standard sufficient? Acad Radiol 28:199–207
Giganti F, Ng A, Asif A et al (2023) Global variation in magnetic resonance imaging quality of the prostate. Radiology 309:e231130
doi: 10.1148/radiol.231130 pubmed: 37815448
Burn PR, Freeman SJ, Andreou A, Burns-Cox N, Persad R, Barrett T (2019) A multicentre assessment of prostate MRI quality and compliance with UK and international standards. Clin Radiol 74:894.e19–894.e25
Lin Y, Yilmaz EC, Belue MJ, Turkbey B (2023) Prostate MRI and image quality: it is time to take stock. Eur J Radiol 161:110757
doi: 10.1016/j.ejrad.2023.110757 pubmed: 36870241 pmcid: 10493032
Woernle A, Englman C, Dickinson L et al (2023) Picture perfect: the status of image quality in prostate MRI. J Magn Reson Imaging. https://doi.org/10.1002/jmri.29025
de Rooij M, Israël B, Tummers M et al (2020) ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists’ training. Eur Radiol 30:5404–5416
doi: 10.1007/s00330-020-06929-z pubmed: 32424596 pmcid: 7476997
Purysko AS, Tempany C, Macura KJ et al (2023) American College of Radiology initiatives on prostate magnetic resonance imaging quality. Eur J Radiol 165:110937
doi: 10.1016/j.ejrad.2023.110937 pubmed: 37352683
Giganti F, Allen C, Emberton M et al (2020) Prostate imaging quality (PI-QUAL): a new quality control scoring system for multiparametric magnetic resonance imaging of the prostate from the PRECISION trial. Eur Urol Oncol 3:615–619
doi: 10.1016/j.euo.2020.06.007 pubmed: 32646850
Kasivisvanathan V, Rannikko AS, Borghi M et al (2018) MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med 378:1767–1777
doi: 10.1056/NEJMoa1801993 pubmed: 29552975 pmcid: 9084630
Barrett T, Lee KL, de Rooij M, Giganti F (2024) Update on optimization of prostate MR imaging technique and image quality. Radiol Clin North Am 62:1–15
doi: 10.1016/j.rcl.2023.06.006 pubmed: 37973236
de Rooij M, Barentsz JO (2022) PI-QUAL v.1: the first step towards good-quality prostate MRI. Eur Radiol 32:876–878
doi: 10.1007/s00330-021-08399-3 pubmed: 34842957
Forookhi A, Laschena L, Pecoraro M et al (2023) Bridging the experience gap in prostate multiparametric magnetic resonance imaging using artificial intelligence: a prospective multi-reader comparison study on inter-reader agreement in PI-RADS v2.1, image quality and reporting time between novice and expert readers. Eur J Radiol 161:110749
doi: 10.1016/j.ejrad.2023.110749 pubmed: 36812699
Karanasios E, Caglic I, Zawaideh JP, Barrett T (2022) Prostate MRI quality: clinical impact of the PI-QUAL score in prostate cancer diagnostic work-up. Br J Radiol 95:20211372
doi: 10.1259/bjr.20211372 pubmed: 35179971 pmcid: 10993954
Slough RA, Caglic I, Hansen NL, Patterson AJ, Barrett T (2018) Effect of hyoscine butylbromide on prostate multiparametric MRI anatomical and functional image quality. Clin Radiol 73:216.e9–216.e14
doi: 10.1016/j.crad.2017.07.013 pubmed: 28803622
Sundaram KM, Rosenberg J, Syed AB, Chang ST, Loening AM (2023) Assessment of T2-weighted image quality at prostate MRI in patients with and those without intramuscular injection of glucagon. Radiol Imaging Cancer 5:e220070
doi: 10.1148/rycan.220070 pubmed: 37171269 pmcid: 10240243
Ullrich T, Quentin M, Schmaltz AK et al (2018) Hyoscine butylbromide significantly decreases motion artefacts and allows better delineation of anatomic structures in mp-MRI of the prostate. Eur Radiol 28:17–23
doi: 10.1007/s00330-017-4940-7 pubmed: 28687912
Engelbrecht MR, Jager GJ, Laheij RJ, Verbeek AL, van Lier HJ, Barentsz JO (2002) Local staging of prostate cancer using magnetic resonance imaging: a meta-analysis. Eur Radiol 12:2294–2302
doi: 10.1007/s00330-002-1389-z pubmed: 12195484
Prabhakar S, Schieda N (2023) Patient preparation for prostate MRI: a scoping review. Eur J Radiol 162:110758
doi: 10.1016/j.ejrad.2023.110758 pubmed: 36905717
Robertson SH, Owenby E, Beasley C et al (2023) Optimization of non-endorectal prostate MR image quality using PI-QUAL: a multidisciplinary team approach. Eur J Radiol 166:110998
doi: 10.1016/j.ejrad.2023.110998 pubmed: 37506475
de Rooij M, Hamoen EH, Witjes JA, Barentsz JO, Rovers MM (2016) Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis. Eur Urol 70:233–245
doi: 10.1016/j.eururo.2015.07.029 pubmed: 26215604
Abreu-Gomez J, Shabana W, McInnes MDF, O’Sullivan JP, Morash C, Schieda N (2019) Regional standardization of prostate multiparametric MRI performance and reporting: Is there a role for a director of prostate imaging? AJR Am J Roentgenol 213:844–850
doi: 10.2214/AJR.19.21111 pubmed: 31180739
Giganti F, Cole AP, Fennessy FM et al (2023) Promoting the use of the PI-QUAL score for prostate MRI quality: results from the ESOR Nicholas Gourtsoyiannis teaching fellowship. Eur Radiol 33:461–471
doi: 10.1007/s00330-022-08947-5 pubmed: 35771247
Wang R, Pinto D, Liu T et al (2023) Effect of a dedicated PI-QUAL curriculum on the assessment of prostate MRI quality. Eur J Radiol 164:110865
doi: 10.1016/j.ejrad.2023.110865 pubmed: 37167684
Belue MJ, Law YM, Marko J et al (2023) Deep learning-based interpretable AI for prostate T2W MRI quality evaluation. Acad Radiol 31:1429–1437
Cipollari S, Guarrasi V, Pecoraro M et al (2022) Convolutional neural networks for automated classification of prostate multiparametric magnetic resonance imaging based on image quality. J Magn Reson Imaging 55:480–490
doi: 10.1002/jmri.27879 pubmed: 34374181

Auteurs

Maarten de Rooij (M)

Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.

Clare Allen (C)

Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK.

Jasper J Twilt (JJ)

Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.

Linda C P Thijssen (LCP)

Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.

Patrick Asbach (P)

Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.

Tristan Barrett (T)

Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.

Giorgio Brembilla (G)

Department of Radiology, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.

Mark Emberton (M)

Division of Surgery and Interventional Science, University College London, London, UK.
Department of Urology, University College London Hospital NHS Foundation Trust, London, UK.

Rajan T Gupta (RT)

Department of Radiology, Duke University Medical Center, Durham, NC, USA.

Masoom A Haider (MA)

Joint Department of Medical Imaging, Sinai Health System, Lunenfeld Tanenbaum Research Institute, University of Toronto, Toronto, Canada.

Veeru Kasivisvanathan (V)

Division of Surgery and Interventional Science, University College London, London, UK.
Department of Urology, University College London Hospital NHS Foundation Trust, London, UK.

Vibeke Løgager (V)

Department of Radiology, Herlev Gentofte University Hospital, Herlev, Denmark.

Caroline M Moore (CM)

Division of Surgery and Interventional Science, University College London, London, UK.
Department of Urology, University College London Hospital NHS Foundation Trust, London, UK.

Anwar R Padhani (AR)

Paul Strickland Scanner Centre, Mount Vernon Hospital, Northwood, Middlesex, UK.

Valeria Panebianco (V)

Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy.

Philippe Puech (P)

Department of Radiology, CHU Lille, University Lille, Lille, France.

Andrei S Purysko (AS)

Abdominal Imaging Section and Nuclear Radiology Department, Diagnostic Institute, and Glickman Urological and Kidney Institute Cleveland Clinic, Cleveland, OH, USA.

Raphaële Renard-Penna (R)

AP-HP, Radiology, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France.

Jonathan Richenberg (J)

Department of Imaging, Sussex universities Hospitals NHS Foundation Trust, Brighton, UK.

Georg Salomon (G)

Martini Clinic (Prostate Cancer Centre), University of Hamburg, Hamburg, Germany.

Francesco Sanguedolce (F)

Department of Medicine, Surgery and Pharmacy, Università degli Studi di Sassari, Sassari, Italy.
Department of Urology, Fundació Puigvert, Barcelona, Spain.

Ivo G Schoots (IG)

Department of Radiology & Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands.
Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands.

Harriet C Thöny (HC)

Department of Diagnostic and Interventional Radiology, Fribourg Cantonal Hospital, Fribourg, Switzerland.

Baris Turkbey (B)

Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Geert Villeirs (G)

Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium.

Jochen Walz (J)

Department of Urology, Institut Paoli-Calmettes Cancer Centre, Marseille, France.

Jelle Barentsz (J)

Andros Clinics, Arnhem, The Netherlands.

Francesco Giganti (F)

Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK. f.giganti@ucl.ac.uk.
Division of Surgery and Interventional Science, University College London, London, UK. f.giganti@ucl.ac.uk.
ORCID: 0000-0001-5218-6431

Classifications MeSH