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Radiomics analysis using magnetic resonance imaging of bone marrow edema for diagnosing knee osteoarthritis

Authors :
Xuefei Li
Wenhua Chen
Dan Liu
Pinghua Chen
Pan Li
Fangfang Li
Weina Yuan
Shiyun Wang
Chen Chen
Qian Chen
Fangyu Li
Suxia Guo
Zhijun Hu
Source :
Frontiers in Bioengineering and Biotechnology, Vol 12 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

This study aimed to develop and validate a bone marrow edema model using a magnetic resonance imaging-based radiomics nomogram for the diagnosis of osteoarthritis. Clinical and magnetic resonance imaging (MRI) data of 302 patients with and without osteoarthritis were retrospectively collected from April 2022 to October 2023 at Longhua Hospital affiliated with the Shanghai University of Traditional Chinese Medicine. The participants were randomly divided into two groups (a training group, n = 211 and a testing group, n = 91). We used logistic regression to analyze clinical characteristics and established a clinical model. Radiomics signatures were developed by extracting radiomic features from the bone marrow edema area using MRI. A nomogram was developed based on the rad-score and clinical characteristics. The diagnostic performance of the three models was compared using the receiver operating characteristic curve and Delong’s test. The accuracy and clinical application value of the nomogram were evaluated using calibration curve and decision curve analysis. Clinical characteristics such as age, radiographic grading, Western Ontario and McMaster Universities Arthritis Index score, and radiological features were significantly correlated with the diagnosis of osteoarthritis. The Rad score was constructed from 11 radiological features. A clinical model was developed to diagnose osteoarthritis (training group: area under the curve [AUC], 0.819; testing group: AUC, 0.815). Radiomics models were used to effectively diagnose osteoarthritis (training group,: AUC, 0.901; testing group: AUC, 0.841). The nomogram model composed of Rad score and clinical characteristics had better diagnostic performance than a simple clinical model (training group: AUC, 0.906; testing group: AUC, 0.845; p < 0.01). Based on DCA, the nomogram model can provide better diagnostic performance in most cases. In conclusion, the MRI-bone marrow edema-based radiomics-clinical nomogram model showed good performance in diagnosing early osteoarthritis.

Details

Language :
English
ISSN :
22964185
Volume :
12
Database :
Directory of Open Access Journals
Journal :
Frontiers in Bioengineering and Biotechnology
Publication Type :
Academic Journal
Accession number :
edsdoj.55564c376248cbae9ab65faeb66e4f
Document Type :
article
Full Text :
https://doi.org/10.3389/fbioe.2024.1368188