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计算机断层尿路造影：现状与展望。

Computed Tomography Urography: State of the Art and Beyond.

机构信息

Radiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Piazza Principessa Clotilde 3, 20121 Milan, Italy.

Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy.

出版信息

Tomography. 2023 Apr 30;9(3):909-930. doi: 10.3390/tomography9030075.

DOI:10.3390/tomography9030075
PMID:37218935
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10204399/
Abstract

Computed Tomography Urography (CTU) is a multiphase CT examination optimized for imaging kidneys, ureters, and bladder, complemented by post-contrast excretory phase imaging. Different protocols are available for contrast administration and image acquisition and timing, with different strengths and limits, mainly related to kidney enhancement, ureters distension and opacification, and radiation exposure. The availability of new reconstruction algorithms, such as iterative and deep-learning-based reconstruction has dramatically improved the image quality and reducing radiation exposure at the same time. Dual-Energy Computed Tomography also has an important role in this type of examination, with the possibility of renal stone characterization, the availability of synthetic unenhanced phases to reduce radiation dose, and the availability of iodine maps for a better interpretation of renal masses. We also describe the new artificial intelligence applications for CTU, focusing on radiomics to predict tumor grading and patients' outcome for a personalized therapeutic approach. In this narrative review, we provide a comprehensive overview of CTU from the traditional to the newest acquisition techniques and reconstruction algorithms, and the possibility of advanced imaging interpretation to provide an up-to-date guide for radiologists who want to better comprehend this technique.

摘要

计算机断层尿路造影（CTU）是一种多期 CT 检查，专门用于对肾脏、输尿管和膀胱进行成像，辅以对比后排泄期成像。有多种对比剂给药和图像采集及定时方案可供选择，各有优缺点，主要与肾脏增强、输尿管扩张和显影以及辐射暴露有关。新的重建算法，如迭代和基于深度学习的重建，已经显著提高了图像质量，同时降低了辐射暴露。双能 CT 在这种类型的检查中也有重要作用，具有肾结石特征化的可能性，提供合成的非增强相位以减少辐射剂量，以及碘图的可用性，以更好地解释肾脏肿块。我们还描述了 CTU 的新人工智能应用，重点是放射组学，以预测肿瘤分级和患者的治疗结果，实现个性化的治疗方法。在这篇叙述性综述中，我们从传统到最新的采集技术和重建算法全面概述了 CTU，并探讨了高级成像解释的可能性，为希望更好地理解这项技术的放射科医生提供了最新的指南。

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