Toward a Refined PI-RADS: The Feasibility and Limitations of More Informative Metrics in Reviewing MRI Scans.

IF 3.3 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Omer Tarik Esengur, Hunter Stecko, Emma Stevenson, Baris Turkbey
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引用次数: 0

Abstract

The Prostate Imaging-Reporting and Data System (PI-RADS) is a widely-adopted framework for assessing prostate cancer risk using multiparametric MRI. However, as advancements in imaging and data analytics emerge, PI-RADS faces pressure to integrate novel quantitative techniques, enhanced imaging protocols, and artificial intelligence (AI) solutions to improve diagnostic accuracy. This review examines the recent innovations in advanced imaging, clinical, and AI methods that can provide more informative MRI scans and discuss their potential incorporation into PI-RADS. Techniques like multi-shot echo-planar imaging and reduced field-of-view DWI show promise in improving scan quality, but may present challenges with respect to technical complexity, cost, and standardization. Others, like restriction spectrum imaging and luminal water imaging, offer new possibilities for lesion characterization, yet remain difficult to implement consistently across clinical settings. In addition, integrating clinical parameters and AI-driven tools within PI-RADS could enhance risk stratification, but may introduce greater complexity, potentially impacting ease-of-use. We discuss the implications of these advancements for PI-RADS, balancing the potential diagnostic benefits with the challenges of maintaining accessibility and reproducibility in clinical practice. This review provides a comprehensive overview of how emerging MRI techniques and AI may redefine prostate cancer imaging standards. Evidence Level: 5. Technical Efficacy: Stage 5.

向完善的PI-RADS迈进:更多信息指标在回顾MRI扫描中的可行性和局限性。
前列腺成像报告和数据系统(PI-RADS)是一种广泛采用的框架,用于使用多参数MRI评估前列腺癌风险。然而,随着成像和数据分析技术的进步,PI-RADS面临着整合新型定量技术、增强成像协议和人工智能(AI)解决方案以提高诊断准确性的压力。本文综述了先进成像、临床和人工智能方法的最新创新,这些方法可以提供更多信息的MRI扫描,并讨论了将它们纳入PI-RADS的可能性。多镜头回波平面成像和缩小视场DWI等技术有望提高扫描质量,但在技术复杂性、成本和标准化方面可能存在挑战。其他技术,如限制光谱成像和腔内水成像,为病变表征提供了新的可能性,但仍然难以在临床环境中一致实施。此外,在PI-RADS中整合临床参数和人工智能驱动的工具可以增强风险分层,但可能会引入更大的复杂性,潜在地影响易用性。我们讨论了这些进展对PI-RADS的影响,平衡了潜在的诊断益处与在临床实践中保持可及性和可重复性的挑战。这篇综述全面概述了新兴的MRI技术和人工智能如何重新定义前列腺癌成像标准。证据等级:5。技术功效:第5阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.70
自引率
6.80%
发文量
494
审稿时长
2 months
期刊介绍: The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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