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

作者：Xuefei Li, Wenhua Chen, Dan Liu, Pinghua Chen, Li Pan, Fangfang Li, Weina Yuan, Shiyun Wang, Chen Chen, Qian Chen, Fangyu Li, Suxia Guo, Zhijun Hu · 发表于：Frontiers in Bioengineering and Biotechnology · 年份：2024 · DOI：10.3389/fbioe.2024.1368188 · 被引用次数：8 · 研究领域：Radiomics and Machine Learning in Medical Imaging、Bone and Joint Diseases、Osteoarthritis Treatment and Mechanisms

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). Radiomi...