Evidence map›Paper›PMID 39614021›Full record

ArticleInsights into imaging2024

Contrast-enhanced US Bosniak Classification: intra- and inter-rater agreement, confounding features, and diagnostic performance.

Dong-Dong Jin, Bo-Wen Zhuang, Ke Lin, Nan Zhang, Bin Qiao, Xiao-Yan Xie, Xiao-Hua Xie, Yan Wang

Abstract read
In one paragraph

Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Dong-Dong Jin *Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China.
Bo-Wen Zhuang *Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China.
Ke LinDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China.
Nan ZhangDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China.
Bin QiaoDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China.
Xiao-Yan XieDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China.
Xiao-Hua XieDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China. xiexhua@mail.sysu.edu.cn.
Yan WangDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No.58 Zhongshan Road 2, Guangzhou, 510080, People's Republic of China. wyan29@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0003-2685-7590

Funding

National Natural Science Foundation of China 82102047
6 · The paper itself

Abstract

backgroundThe contrast-enhanced US (CEUS) Bosniak classification, proposed by the European Federation for Ultrasound in Medicine and Biology (EFSUMB) in 2020, predicts malignancy in cystic renal masses (CRMs). However, intra- and inter-rater reproducibility for CEUS features has not been well investigated. PURPOSE: To explore intra- and inter-rater agreement for US features, identify confounding features, and assess the diagnostic performance of CEUS Bosniak classification. MATERIALS AND

methodsThis retrospective study included patients with complex CRMs who underwent CEUS examination from January 2013 to August 2023. Radiologists (3 experts and 3 novices) evaluated calcification, echogenic content, wall, septa, and internal nodules of CRMs using CEUS Bosniak classification. Intra- and inter-rater agreements were assessed using the Gwet agreement coefficient (Gwet's AC). Linear regression identified features associated with discrepancies in Bosniak category assignment. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC).

resultsA total of 103 complex CRMs were analyzed in 103 patients (mean age, 50 ± 15 years; 66 males). Intra-rater agreement for the Bosniak category was substantial to almost perfect (Gwet's AC 0.73-0.87). Inter-rater agreement was substantial for the Bosniak category (Gwet's AC 0.75) and moderate to almost perfect for US features (Gwet's AC 0.44-0.94). Nodule variation (i.e., absence vs. obtuse margin vs. acute margin) explained 84% of the variability in the Bosniak category assignment. CEUS Bosniak classification showed good diagnostic performance, with AUCs ranging from 0.78 to 0.90 for each rater.

conclusionsCEUS Bosniak classification demonstrated substantial intra- and inter-rater reproducibility and good diagnostic performance in predicting the malignancy potential of CRMs. Nodule variations significantly predicted differences in Bosniak category assignments. CRITICAL RELEVANCE STATEMENT: Contrast-enhanced US Bosniak classification reliably predicts malignancy in cystic renal masses, demonstrating substantial reproducibility and diagnostic accuracy. This improves clinical decision-making and patient management. KEY POINTS: Intra- and inter-rater reproducibility for contrast-enhance US features for Bosniak classification have not been well investigated. Substantial inter-rater agreements for the Bosniak category and variable agreements for determining imaging features were found. Contrast-enhanced US Bosniak classification is reproducible and has good diagnostic performance for predicting malignancy in cystic renal masses.

Indexed as

Bosniak classificationContrast-enhanced USCystic renal massesDiagnostic performanceReproducibility

Identifiers

PMID39614021
PMCPMC11607359

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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.