医学
图像质量
前列腺
神经组阅片室
前列腺癌
医学物理学
介入放射学
放射科
磁共振成像
人工智能
计算机科学
癌症
图像(数学)
神经学
精神科
内科学
作者
Maarten de Rooij,Clare Allen,Jasper Jonathan Twilt,Linda C.P. Thijssen,Patrick Asbach,Tristan Barrett,Giorgio Brembilla,Mark Emberton,Rajan T. Gupta,Masoom A. Haider,Veeru Kasivisvanathan,Vibeke Løgager,Caroline M. Moore,Anwar R. Padhani,Valeria Panebianco,Philippe Puech,Andrei S. Purysko,Raphaële Renard‐Penna,Jonathan Richenberg,Georg Salomon
出处
期刊:European Radiology
[Springer Science+Business Media]
日期:2024-05-24
卷期号:34 (11): 7068-7079
被引量:31
标识
DOI:10.1007/s00330-024-10795-4
摘要
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 .
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