Evidence map›Paper›PMID 32885299›Full record

ArticleEuropean radiology2021

Quantitation of bladder cancer for the prediction of muscle layer invasion as a complement to the vesical imaging-reporting and data system.

Hyungwoo Ahn, Sung Il Hwang, Hak Jong Lee, Gheeyoung Choe, Jong Jin Oh, Seong Jin Jeong, Seok-Soo Byun, Jung Kwon Kim

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In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
5.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

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  7. Development of modified multi-parametric CT algorithms for diagnosing clear-cell renal cell carcinoma in small solid renal masses.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Hyungwoo AhnDepartment of Radiology, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do, South Korea.
Sung Il HwangDepartment of Radiology, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do, South Korea. hwangsi49@gmail.com.ORCID http://orcid.org/0000-0001-7516-5369
Hak Jong LeeDepartment of Radiology, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do, South Korea.
Gheeyoung ChoeDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Jong Jin OhDepartment of Urology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Seong Jin JeongDepartment of Urology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Seok-Soo ByunDepartment of Urology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Jung Kwon KimDepartment of Urology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea.
Seoul National University Bundang Hospital · KR

Funding

Ministry of Science, Information and Communications Technology, Republic of Korea NRF-2013R1A1A2011398Seoul National University Bundang Hospital Research Fund 11-2010-008
6 · The paper itself

Abstract

objectivesTo examine the diagnostic performance of Vesical Imaging-Reporting and Data System (VIRADS) and to find a quantitative indicator for predicting muscle layer invasion of bladder cancer.

methods3-T MRI of 82 patients performed before transurethral resection of bladder tumors or radical cystectomy between July 2018 and June 2019 were retrospectively analyzed. For one index lesion of each patient, two radiologists independently assigned VIRADS score and measured tumor-wall interface (contact length between tumor and bladder wall) on T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI. Inter-reader agreement was assessed, and logistic regression analysis was performed to find indicators of muscle layer invasion. Comparison of indicators' diagnostic performance was done with receiver operating characteristic (ROC) curve and generalized linear model analyses. Optimal cutoff point was determined by the Youden index J.

resultsInter-reader agreement was at least substantial for VIRADS categorization (κ 0.77-0.81), and almost perfect for tumor-wall interface (intraclass correlation coefficient 0.88-0.90). Tumor-wall interface (odds ratio [OR] 1.90-2.00) and VIRADS score (OR 8.59-8.89) were independently associated with muscle layer invasion (p ≤ 0.02). For VIRADS, area under the ROC curve (AUROC) was 0.94, and the accuracy was 0.93 at score 3, the optimal threshold for predicting muscle layer invasion. Depending on the MRI sequence, tumor-wall interface showed AUROCs of 0.90-0.92 and accuracy of 0.84-0.90 at suggested thresholds (3 ± 0.3 cm). Tumor-wall interface showed insignificant differences in accuracy compared with VIRADS (p > 0.10), except as measured on diffusion-weighted images (p = 0.01).

conclusionsVIRADS is a good predictor of muscle layer invasion. As an independent quantitative indicator, tumor-wall interface may complement VIRADS to enhance prediction. KEY POINTS: • Vesical Imaging-Reporting and Data System (VIRADS) is a promising predictor of muscle invasion of bladder cancer with good reproducibility, as suggested by previous studies. • VIRADS score and the tumor-wall interface (curvilinear contact length between the tumor and the bladder wall) are independent predictors of muscle layer invasion. • As an easy-to-use quantitative indicator, tumor-wall interface is expected to be used as an indicator complementary to VIRADS, a qualitative indicator.

Indexed as

Urinary Bladder NeoplasmsHumansMusclesNeoplasm InvasivenessNeoplasm StagingReproducibility of ResultsRetrospective StudiesCarcinomaMagnetic resonance imagingNeoplasm stagingtransitional cellUrinary bladder neoplasms

Identifiers

PMID32885299
OpenAlexW3083242334

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.