PI-QUAL version 2 : an update of a standardised scoring system for the assessment of image quality of prostate MRI
de Rooij, Maarten (Radboud University Medical Center)
Allen, Clare (University College London Hospital NHS Foundation Trust)
Twilt, Jasper J. (Radboud University Medical Center)
Thijssen, Linda C.P. (Radboud University Medical Center)
Asbach, Patrick (Charité-Universitätsmedizin Berlin)
Barrett, Tristan (Addenbrookes Hospital (Cambridge, Regne Unit))
Brembilla, Giorgio (Vita-Salute San Raffaele University)
Emberton, Mark (University College London Hospital NHS Foundation Trust)
Gupta, Rajan T. (Duke University Medical Center)
Haider, Masoom A. (University of Toronto)
Kasivisvanathan, Veeru (University College London Hospital NHS Foundation Trust)
Løgager, Vibeke (Herlev Gentofte University Hospital)
Moore, Caroline (University College London Hospital NHS Foundation Trust)
Padhani, Anwar R. (Mount Vernon Hospital)
Panebianco, Valeria (Sapienza University/Policlinico Umberto I)
Puech, Philippe (University Lille)
Purysko, Andrei S. (Kidney Institute Cleveland Clinic)
Renard-Penna, Raphaële (Sorbonne University)
Richenberg, Jonathan (Sussex universities Hospitals NHS Foundation Trust)
Salomon, Georg (Martini Clinic (Prostate Cancer Centre))
Sanguedolce, Francesco (Institut de Recerca Sant Pau)
Schoots, Ivo G. (The Netherlands Cancer Institute (Amsterdam, Països Baixos))
Thöny, Harriet C. (Fribourg Cantonal Hospital)
Turkbey, Baris (National Institutes of Health (Bethesda, Estats Units d'Amèrica))
Villeirs, Geert (Universitair Ziekenhuis Gent)
Walz, Jochen (Institut Paoli-Calmettes Cancer Centre)
Barentsz, Jelle (Andros Clinics)
Giganti, Francesco (University College London)
Universitat Autònoma de Barcelona

Date:	2024
Abstract:	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.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Magnetic resonance imaging ; Prostatic neoplasms ; Quality control
Published in:	European radiology, Vol. 34 Núm. 11 (november 2024) , p. 7068-7079, ISSN 1432-1084

DOI: 10.1007/s00330-024-10795-4
PMID: 38787428

12 p, 1.2 MB

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Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Institut de Recerca Sant Pau
Articles > Research articles
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