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中华诊断学电子杂志 ›› 2026, Vol. 14 ›› Issue (02) : 133 -137. doi: 10.3877/cma.j.issn.2095-655X.2026.02.010

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综述

多模态影像学检查技术与AI放射组学在诊断输尿管肿瘤中的研究进展
张敏洁, 刘艳龙()   
  1. 010050 呼和浩特,内蒙古医科大学附属医院超声科
  • 收稿日期:2025-12-13 出版日期:2026-05-26
  • 通信作者: 刘艳龙
  • 基金资助:
    内蒙古医科大学面上项目(YKD2022MS063)

Advances in multimodal imaging techniques and AI radiomics for the diagnosis of ureteral tumors

Minjie Zhang, Yanlong Liu()   

  1. Department of Ultrasound, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010050, China
  • Received:2025-12-13 Published:2026-05-26
  • Corresponding author: Yanlong Liu
引用本文:

张敏洁, 刘艳龙. 多模态影像学检查技术与AI放射组学在诊断输尿管肿瘤中的研究进展[J/OL]. 中华诊断学电子杂志, 2026, 14(02): 133-137.

Minjie Zhang, Yanlong Liu. Advances in multimodal imaging techniques and AI radiomics for the diagnosis of ureteral tumors[J/OL]. Chinese Journal of Diagnostics(Electronic Edition), 2026, 14(02): 133-137.

输尿管肿瘤因发病隐匿、早期症状不典型,易出现漏诊、误诊,精准诊断是改善患者预后的关键。多模态影像学检查技术凭借互补优势为该病诊断提供全面依据,其中计算机体层成像尿路造影以高空间分辨率成为病灶检出与分期的核心手段;多参数磁共振尿路成像在软组织评估中独具优势;超声和正电子发射断层扫描则在初筛与转移灶检测中发挥重要作用。AI放射组学通过提取影像中量化特征,结合机器学习算法实现肿瘤良恶性鉴别、分级分期及预后评估,显著提升诊断精准度与效率。笔者综述多模态影像学技术的应用现状及AI放射组学的研究进展,分析二者联合应用的临床价值与现存挑战,为输尿管肿瘤的精准诊断提供参考。

Owing to their insidious onset and atypical early symptoms, ureteral tumors are prone to missed diagnoses and misdiagnoses. Accurate diagnosis is crucial for improving patient prognosis. Multimodal imaging techniques provide comprehensive diagnostic evidence through their complementary advantages. Among them, computed tomography urography (CTU) has become the core method for lesion detection and staging due to its high spatial resolution; multi-parametric magnetic resonance urography (MRU) has unique advantages in soft tissue evaluation; ultrasonography and positron emission tomography-computed tomography (PET/CT) play important roles in preliminary screening and metastatic lesion detection, respectively. AI-based radiomics enhances diagnostic accuracy and efficiency by extracting quantitative features from images and integrating machine learning algorithms to facilitate the differentiation of benign and malignant tumors, tumor grading and staging, as well as prognostic evaluation. This review summarizes the application status of multimodal imaging techniques and the technical progress of AI-based radiomics, analyzes the clinical value and existing challenges of their combined application, and provides a reference for the accurate diagnosis of ureteral tumors.

图1 AI放射组学研究技术路线图注:AI为人工智能;CTU为计算机体层成像尿路造影;MRU为磁共振尿路成像
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