Zhu Hongtian, Lee Woowon, Miller Emily Y, Seifert Jennifer, Clauw Andrew, Moreland Larry W, Neu Corey P
Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, 1111 Engineering Drive, UCB 427, Boulder, CO, 80309, USA.
Biomedical Engineering Program, University of Colorado Boulder, Boulder, CO, USA.
Sci Rep. 2025 Sep 2;15(1):32351. doi: 10.1038/s41598-025-17316-3.
Identifying and diagnosing early-stage rheumatoid arthritis (RA) has remained an unmet challenge in medicine and a roadblock to identifying treatments at time points when disease-modifying therapies may be most effective. Recent studies have demonstrated that imaging the response of cartilage under mechanical loading, as well as alterations in matrix macro- and micro-molecule composition, could serve as potential biomarkers to identify tissue degeneration. Therefore, the objective of this paper was to identify RA-related cartilage degeneration in human wrists using novel MRI techniques. We applied in vivo displacement-encoded MRI to human wrists during cyclic radioulnar deviation, along with the quantitative MRI methods (T1ρ, T2, T2*) during a static condition, to a small healthy and RA patient cohort (6 healthy, 4 RA). We then used a linear mixed-effects model to identify key factors affecting the results. We found that the RA patients had wrists with higher torsional stiffness by approximately 2-fold compared to the control group. The RA group showed lower intercarpal joint displacements by roughly half of the control group, and some joint regions indicated tissue softening. We also found that the quantitative MRI metrics showed non-significant differences between control and RA groups (the T2 and T2* of the RA group was roughly 10% and 5% more than the control group, respectively), however, differences were detected among regions in T2 and T2* metrics. This study demonstrated that displacement-encoded MRI may be a promising method to distinguish functional and noninvasive metrics between RA and healthy wrists, and may provide a means to distinguish the disease state compared to conventional imaging methods.
识别和诊断早期类风湿性关节炎(RA)一直是医学上尚未解决的挑战,也是在疾病改善疗法可能最有效的时间点确定治疗方法的障碍。最近的研究表明,对机械负荷下软骨的反应以及基质大分子和小分子组成的变化进行成像,可以作为识别组织退化的潜在生物标志物。因此,本文的目的是使用新型MRI技术识别人类手腕中与RA相关的软骨退化。我们在环枢尺侧偏斜期间对人类手腕应用了体内位移编码MRI,并在静态条件下对一小群健康人和RA患者(6名健康人,4名RA患者)应用了定量MRI方法(T1ρ、T2、T2*)。然后,我们使用线性混合效应模型来确定影响结果的关键因素。我们发现,与对照组相比,RA患者手腕的扭转刚度大约高2倍。RA组的腕间关节位移比对照组低约一半,并且一些关节区域显示组织软化。我们还发现,定量MRI指标在对照组和RA组之间没有显著差异(RA组的T2和T2分别比对照组高约10%和5%),然而,在T2和T2指标的区域之间检测到了差异。这项研究表明,位移编码MRI可能是一种有前途的方法,用于区分RA和健康手腕之间的功能和非侵入性指标,并且与传统成像方法相比,可能提供一种区分疾病状态的手段。