Proposal for a New Vesical Imaging-Reporting and Data System (VI-RADS)-Based Algorithm for the Management of Bladder Cancer: A Paradigm Shift From the Current Transurethral Resection of Bladder Tumor (TURBT)-Dependent Practice.


Journal

Clinical genitourinary cancer
ISSN: 1938-0682
Titre abrégé: Clin Genitourin Cancer
Pays: United States
ID NLM: 101260955

Informations de publication

Date de publication:
08 2022
Historique:
received: 29 01 2022
revised: 27 02 2022
accepted: 01 03 2022
pubmed: 30 3 2022
medline: 27 7 2022
entrez: 29 3 2022
Statut: ppublish

Résumé

Transurethral resection of bladder tumor (TURBT) is the essential first step in the current algorithm for the management of bladder cancer (BC). However, despite its necessity and significance, TURBT has several limitations, including cost, hospitalization, anesthesia, potential complications such as bladder perforation, and delay to radical cystectomy. The Vesical Imaging Reporting and Data System (VI-RADS) was developed to standardize the reporting of multiparametric magnetic resonance imaging for BC, and its diagnostic accuracy to predict muscle invasion has been validated. Given the high sensitivity of VI-RADS ≥ 3 and high specificity of VI-RADS ≥ 4 as clinically relevant cutoff values, we herein propose a new VI-RADS-based algorithm for the management of BC. Using this algorithm, patients with VI-RADS ≤ 2 may not need to undergo sampling of the detrusor muscle nor second TURBT even if there is no muscle in the initial TURBT specimen, whereas patients with VI-RADS ≥ 4 may skip conventional TURBT aimed at pathologic confirmation of muscle invasion and immediately undergo radical cystectomy. Our newly proposed algorithm enables the avoidance of unnecessary deep resection or second TURBT as well as delay to radical cystectomy. The VI-RADS-based algorithm enables a paradigm shift from the current TURBT-dependent practice in the management of BC.

Identifiants

pubmed: 35346591
pii: S1558-7673(22)00047-7
doi: 10.1016/j.clgc.2022.03.002
pii:
doi:

Banques de données

ISRCTN
['ISRCTN35296862']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e291-e295

Informations de copyright

Copyright © 2022. Published by Elsevier Inc.

Auteurs

Satoru Taguchi (S)

Department of Urology, Kyorin University School of Medicine, Tokyo, Japan. Electronic address: satorutaguchi33@gmail.com.

Masanaka Watanabe (M)

Department of Radiology, Kyorin University School of Medicine, Tokyo, Japan.

Mitsuhiro Tambo (M)

Department of Urology, Kyorin University School of Medicine, Tokyo, Japan.

Haruhiko Machida (H)

Department of Radiology, Tokyo Women's Medical University Medical Center East, Tokyo, Japan.

Kenichi Yokoyama (K)

Department of Radiology, Kyorin University School of Medicine, Tokyo, Japan.

Hiroshi Fukuhara (H)

Department of Urology, Kyorin University School of Medicine, Tokyo, Japan.

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Classifications MeSH