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Pictorial review of multiparametric MRI in bladder urothelial carcinoma with variant histology: pearls and pitfalls

  • Yuki Arita
  • , Sungmin Woo
  • , Thomas C. Kwee
  • , Keisuke Shigeta
  • , Ryo Ueda
  • , Sunny Nalavenkata
  • , Hiromi Edo
  • , Kosuke Miyai
  • , Jeeban Das
  • , Pamela I.Causa Andrieu
  • , Hebert Alberto Vargas

研究成果: Article査読

抄録

Bladder cancer (BC), predominantly comprising urothelial carcinomas (UCs), ranks as the tenth most common cancer worldwide. UCs with variant histology (variant UC), including squamous differentiation, glandular differentiation, plasmacytoid variant, micropapillary variant, sarcomatoid variant, and nested variant, accounting for 5–10% of cases, exhibit more aggressive and advanced tumor characteristics compared to pure UC. The Vesical Imaging-Reporting and Data System (VI-RADS), established in 2018, provides guidelines for the preoperative evaluation of muscle-invasive bladder cancer (MIBC) using multiparametric magnetic resonance imaging (mpMRI). This technique integrates T2-weighted imaging (T2WI), dynamic contrast-enhanced (DCE)-MRI, and diffusion-weighted imaging (DWI) to distinguish MIBC from non-muscle-invasive bladder cancer (NMIBC). VI-RADS has demonstrated high diagnostic performance in differentiating these two categories for pure UC. However, its accuracy in detecting muscle invasion in variant UCs is currently under investigation. These variant UCs are associated with a higher likelihood of disease recurrence and require precise preoperative assessment and immediate surgical intervention. This review highlights the potential value of mpMRI for different variant UCs and explores the clinical implications and prospects of VI-RADS in managing these patients, emphasizing the need for careful interpretation of mpMRI examinations including DCE-MRI, particularly given the heterogeneity and aggressive nature of variant UCs. Additionally, the review addresses the fundamental MRI reading procedures, discusses potential causes of diagnostic errors, and considers future directions in the use of artificial intelligence and radiomics to further optimize the bladder MRI protocol. Graphical abstract: (Figure presented.)

本文言語English
ページ(範囲)2797-2811
ページ数15
ジャーナルAbdominal Radiology
49
8
DOI
出版ステータスPublished - 2024 8月

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

  1. SDG 3 - すべての人に健康と福祉を
    SDG 3 すべての人に健康と福祉を

ASJC Scopus subject areas

  • 放射線技術および超音波技術
  • 放射線学、核医学およびイメージング
  • 消化器病学
  • 泌尿器学

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