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肌肉浸润性膀胱癌的综合磁共振成像：综述

Integrated Magnetic Resonance Imaging in Muscle-Invasive Bladder Cancer: A Comprehensive Review.

作者信息

Ibraheem Nazeer, Abosheisha Mohamed, Alemam Ahmed, Abbas Mahmoud, Abdelglil Momen, Tamanna Rezuana, Yasser Elnaggar Mohamed, Swealem Ahmed, Ismaiel Mohamed

机构信息

Urology, The Royal Wolverhampton NHS Trust, New Cross Hospital, Wolverhampton, GBR.

General Surgery, Leicester Royal Infirmary Hospital, University Hospitals of Leicester, Leicester, GBR.

出版信息

Cureus. 2025 Aug 14;17(8):e90077. doi: 10.7759/cureus.90077. eCollection 2025 Aug.

DOI:10.7759/cureus.90077
PMID:40955208
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12433690/
Abstract

The integration of multiparametric MRI (mpMRI) into the diagnosis and treatment of muscle-invasive bladder cancer (MIBC) has significantly enhanced decision-making. This review highlights advancements in mpMRI, including its applications in tumor grading, treatment response assessment, and post-treatment surveillance. The use of artificial intelligence further enhances predictive capabilities. However, challenges remain, particularly regarding accessibility and interobserver variability. mpMRI represents a pivotal, noninvasive tool that supports precision medicine and bladder-preserving strategies in MIBC care.

摘要

多参数磁共振成像（mpMRI）在肌肉浸润性膀胱癌（MIBC）诊断和治疗中的整合显著改善了决策制定。本综述强调了mpMRI的进展，包括其在肿瘤分级、治疗反应评估和治疗后监测中的应用。人工智能的使用进一步增强了预测能力。然而，挑战依然存在，尤其是在可及性和观察者间变异性方面。mpMRI是一种关键的非侵入性工具，支持MIBC治疗中的精准医学和膀胱保留策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/5185c753688c/cureus-0017-00000090077-i04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/1ff7fbc0fb73/cureus-0017-00000090077-i01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/df85d8c65501/cureus-0017-00000090077-i02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/909347598d8d/cureus-0017-00000090077-i03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/5185c753688c/cureus-0017-00000090077-i04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/1ff7fbc0fb73/cureus-0017-00000090077-i01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/df85d8c65501/cureus-0017-00000090077-i02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/909347598d8d/cureus-0017-00000090077-i03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/009d/12433690/5185c753688c/cureus-0017-00000090077-i04.jpg

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本文引用的文献

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Medicina (Kaunas). 2025 Mar 7;61(3):469. doi: 10.3390/medicina61030469.
2
Deep learning on T2WI to predict the muscle-invasive bladder cancer: a multi-center clinical study.基于T2WI的深度学习预测肌层浸润性膀胱癌：一项多中心临床研究。
Sci Rep. 2025 Mar 22;15(1):9942. doi: 10.1038/s41598-024-82909-3.
3
Multiparametric MRI for Bladder Cancer: A Practical Approach to the Clinical Application of VI-RADS.
膀胱癌的多参数磁共振成像：VI-RADS临床应用的实用方法
Radiology. 2025 Mar;314(3):e233459. doi: 10.1148/radiol.233459.
4
Randomized Comparison of Magnetic Resonance Imaging Versus Transurethral Resection for Staging New Bladder Cancers: Results From the Prospective BladderPath Trial.磁共振成像与经尿道切除术用于新诊断膀胱癌分期的随机对照比较：前瞻性膀胱路径试验的结果
J Clin Oncol. 2025 Apr 20;43(12):1417-1428. doi: 10.1200/JCO.23.02398. Epub 2025 Jan 14.
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