Evidence map›Paper›PMID 38315274›Full record

ArticleInsights into imaging2024

Broken-fat pad sign: a characteristic radiographic finding to distinguish between knee rheumatoid arthritis and osteoarthritis.

Qizheng Wang, Weili Zhao, Xiaoxi Ji, Yongye Chen, Ke Liu, Yupeng Zhu, Ruixin Yan, Siyuan Qin, Peijin Xin, Ning Lang

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

The trial behind it

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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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Qizheng WangDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Weili ZhaoDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Xiaoxi JiDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Yongye ChenDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Ke LiuDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Yupeng ZhuDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Ruixin YanDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Siyuan QinDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Peijin XinDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China.
Ning LangDepartment of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, People's Republic of China. langning800129@126.com.ORCID http://orcid.org/0000-0003-1860-2918

Funding

National Natural Science Foundation of China 81971578)Natural Science Foundation of Beijing Municipality Z190020Proof of Concept Program of Zhongguancun Science City and Peking University Third Hospital HDCXZHKC2022202
6 · The paper itself

Abstract

objectivesDiagnostic imaging plays an important role in the pre-treatment workup of knee osteoarthritis (OA) and rheumatoid arthritis (RA). Herein, we identified a useful MRI sign of infrapatellar fat pad (IPFP) to improve diagnosis.

methodsEighty-one age- and sex-matched RA and OA patients each, with pathological diagnosis and pre-treatment MRI were retrospectively evaluated. All randomized MR images were blinded and independently reviewed by two radiologists. The assessment process included initial diagnosis, sign evaluation, and final diagnosis, with a 3-week interval between each assessment. Broken-fat pad (BFP) sign was assessed on sagittal T2-weighted-imaging in routine MRI. The area under the curve and Cohen's kappa (κ) were used to assess the classification performance. Two shape features were extracted from IPFP for quantitative interpretation.

resultsThe median age of the study population was 57.6 years (range: 31.0-78.0 years). The BFP sign was detected more frequently in patients with RA (72.8%) than those with OA (21.0%). Both radiologists achieved better performance by referring to the BFP sign, with accuracies increasing from 58.0 to 75.9% and 72.8 to 79.6%, respectively. The inter-reader correlation coefficient showed an increase from fair (κ = 0.30) to substantial (κ = 0.75) upon the consideration of the BFP sign. For quantitative analysis, the IPFP of RA had significantly lower sphericity (0.54 ± 0.04 vs. 0.59 ± 0.03, p < 0.01). Despite larger surface-volume-ratio of RA (0.38 ± 0.05 vs. 0.37 ± 0.04, p = 0.25) than that of OA, there was no statistical difference.

conclusionsThe BFP sign is a potentially important diagnostic clue for differentiating RA from OA with routine MRI and reducing misdiagnosis. CRITICAL RELEVANCE STATEMENT: With the simple and feasible broken-fat pad sign, clinicians can help more patients with early accurate diagnosis and proper treatment, which may be a valuable addition to the diagnostic workup of knee MRI assessment. KEY POINTS: • Detailed identification of infrapatellar fat pad alterations of patients may be currently ignored in routine evaluation. • Broken-fat pad sign is helpful for differentiating rheumatoid arthritis and osteoarthritis. • The quantitative shape features of the infrapatellar fat pad may provide a possible explanation of the signs. • This sign has good inter-reader agreements and is feasible for clinical application.

Indexed as

Infrapatellar fat padKneeMagnetic resonance imagingOsteoarthritisRheumatoid arthritis

Identifiers

PMID38315274
PMCPMC10844185

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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.