ArticleDiagnostic and interventional radiology (Ankara, Turkey)2022
Prospective assessment of VI-RADS score in multiparametric MRI in bladder cancer: accuracy and the factors affecting the results.
Article in Diagnostic and interventional radiology (Ankara, Turkey), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Interobserver agreement of non-parallel transmission technology zoomed-diffusion-weighted imaging (DWI) for ordinal biparametric Vesical Imaging-Reporting and Data System (VI-RADS)-based scoring in bladder cancer lesions ≥1 cm.Quantitative imaging in medicine and surgery · 2026Article
- Diagnostic accuracy of the Vesical Imaging Reporting and Data System for muscle-invasive bladder cancer and its role in reducing repeat transurethral resection of bladder tumor: A systematic review.Bladder (San Francisco, Calif.) · 2025Review
- Implementing VIRADS score for image-guided assessment of muscle invasiveness in bladder cancer pre-TURBT: An updated meta-analysis.Arab journal of urology · 2025Review
- MRI evaluation of vesical imaging reporting and data system for bladder cancer after neoadjuvant chemotherapy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Clinical application of bladder MRI and the Vesical Imaging-Reporting and Data System.Nature reviews. Urology · 2024Review
- Magnetic resonance radiographic features which might lead to misdiagnosis of muscle-invasive bladder cancer based on vesical imaging reporting and data system: the application experience of a single center.Quantitative imaging in medicine and surgery · 2023Article
- Letter to the Editor: "Prospective assessment of VI-RADS score in multiparametric MRI in bladder cancer: accuracy and the factors affecting the results"Diagnostic and interventional radiology (Ankara, Turkey) · 2023Article
- Review
- Synergy of PET and MR imaging in the local and regional staging of bladder cancer.Therapeutic advances in urologyReview
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Authors and funding
10 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
PURPOSE We aimed to investigate the accuracy of Vesical Imaging - Reporting and Data System (VI-RADS) in the detection of muscle-invasive bladder cancer (MIBC) and to determine which factors affect the results of this scoring system. METHODS A prospective data analysis of 80 patients who were detected to have bladder tumor was performed between March 2019 and October 2020. VI-RADS scoring was used to determine the probability of muscle invasion. The scores were compared with pathological results to evaluate the accuracy of the VI-RADS scoring system. Interobserver agreement was assessed by VI-RADS scoring of 20 randomly chosen patients by a different experienced radiologist. RESULTS Using the VI-RADS scoring system, the sensitivity, specificity, positive predictive value, and negative predictive value of multiparametric magnetic resonance imaging (mpMRI) were 87.5%, 87.5%, 63.6%, and 96.6%, respectively. The interobserver agreement expressed as the interclass correlation coefficient (ICC) was 0.72 (95% CI: 0.44-0.84, P < .001). In addition, the flat appearance of the tumor was an important factor affecting the accuracy of the VI-RADS score (odds ratio: 5.3 [95% CI: 1.1-27.0] and relative risk: 1.87 [95% CI: 1.24-2.82]). CONCLUSION The mpMRI, used in conjunction with VI-RADS, has proven to be an effective imaging method for detecting muscle invasion in cases of bladder cancer. VI-RADS scoring system can distinguish whether there is a muscle-invasive and non-muscle invasive bladder cancer with acceptable accuracy. In addition, the flat appearance of the tumor is an important entity that can affect the accuracy of the VI-RADS scoring system.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.