Lee Jinhee J, Namiri Nikan K, Astuto Bruno, Link Thomas M, Majumdar Sharmila, Pedoia Valentina
Center for Intelligent Imaging, University of California, San Francisco.
Arthritis Care Res (Hoboken). 2023 Mar;75(3):501-508. doi: 10.1002/acr.24877. Epub 2022 Dec 10.
Our study aimed to investigate the association between time to incidence of radiographic osteoarthritis (OA) and magnetic resonance imaging (MRI)-based structural phenotypes proposed by the Rapid Osteoarthritis MRI Eligibility Score (ROAMES).
A retrospective cohort of 2,328 participants without radiographic OA at baseline were selected from the Osteoarthritis Initiative study. Utilizing a deep-learning model, we automatically assessed the presence of inflammatory, meniscus/cartilage, subchondral bone, and hypertrophic phenotypes from MRIs acquired at baseline and 12-, 24-, 36-, 48-, 72-, and 96-month follow-up visits. In addition to 4 structural phenotypes, we examined severe knee injury history and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain scores as time dependent. We used Cox proportional hazards regression to analyze the association between 4 structural phenotypes and radiographic OA disease-free survival, both univariate and adjusted for known risk factors including age, sex, race, body mass index, presence of Heberden's nodes, and knee malalignment.
Inflammatory (hazard ratio [HR] 3.37 [95% confidence interval (95% CI) 2.45-4.63]), meniscus/cartilage (HR 1.55 [95% CI 1.21-1.98]), and subchondral bone (HR 1.84 [95% CI 1.63-2.09]) phenotypes were associated with time to radiographic OA at P < 0.05 when adjusted for the risk factors. Sex was a modifier of hypertrophic phenotype association with time to radiographic OA. Female participants with the hypertrophic phenotype were associated with 2.8 times higher risk of radiographic OA (95% CI 2.25-7.54) compared to male participants without the hypertrophic phenotype.
Four ROAMES phenotypes may contribute to time to radiographic OA incidence and if validated could be used as a promising tool for personalized OA management.
我们的研究旨在调查影像学骨关节炎（OA）发病时间与快速骨关节炎磁共振成像资格评分（ROAMES）提出的基于磁共振成像（MRI）的结构表型之间的关联。
从骨关节炎倡议研究中选取了2328名基线时无影像学OA的参与者组成回顾性队列。利用深度学习模型，我们自动评估了在基线以及12、24、36、48、72和96个月随访时获取的MRI中炎症、半月板/软骨、软骨下骨和肥大表型的存在情况。除了4种结构表型外，我们还将严重膝关节损伤史和西安大略和麦克马斯特大学骨关节炎指数（WOMAC）疼痛评分作为时间依赖性因素进行了研究。我们使用Cox比例风险回归分析4种结构表型与影像学OA无病生存期之间的关联，包括单变量分析以及针对已知风险因素（包括年龄、性别、种族、体重指数、赫伯登结节的存在情况和膝关节排列不齐）进行调整后的分析。
在对风险因素进行调整后，炎症（风险比[HR] 3.37 [95%置信区间（95%CI）2.45 - 4.63]）、半月板/软骨（HR 1.55 [95%CI 1.21 - 1.98]）和软骨下骨（HR 1.84 [95%CI 1.63 - 2.09]）表型与影像学OA发病时间相关，P < 0.05。性别是肥大表型与影像学OA发病时间关联的一个调节因素。与没有肥大表型的男性参与者相比，具有肥大表型的女性参与者发生影像学OA的风险高2.8倍（95%CI 2.25 - 7.54）。
ROAMES的四种表型可能与影像学OA发病时间有关，如果得到验证，可作为个性化OA管理的一种有前景的工具。
