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膝关节骨关节炎疾病进展的特征:来自综合多尺度建模方法的见解,一项概念验证。

Signatures of disease progression in knee osteoarthritis: insights from an integrated multi-scale modeling approach, a proof of concept.

作者信息

Mohout Ikram, Elahi Seyed Ali, Esrafilian Amir, Killen Bryce A, Korhonen Rami K, Verschueren Sabine, Jonkers Ilse

机构信息

Department of Movement Science, Human Movement Biomechanics Research Group, Leuven, Belgium.

Mechanical Engineering Department, Soft Tissue Biomechanics Group, Leuven, Belgium.

出版信息

Front Bioeng Biotechnol. 2023 Jul 27;11:1214693. doi: 10.3389/fbioe.2023.1214693. eCollection 2023.

Abstract

Knee osteoarthritis (KOA) is characterized by articular cartilage degeneration. It has been widely accepted that the mechanical joint environment plays a significant role in the onset and progression of this disease. In silico models have been used to study the interplay between mechanical loading and cartilage degeneration, hereby relying mainly on two key mechanoregulatory factors indicative of collagen degradation and proteoglycans depletion. These factors are the strain in collagen fibril direction (SFD) and maximum shear strain (MSS) respectively. In this study, a multi-scale in silico modeling approach was used based on a synergy between musculoskeletal and finite element modeling to evaluate the SFD and MSS. These strains were evaluated during gait based on subject-specific gait analysis data collected at baseline (before a 2-year follow-up) for a healthy and progressive early-stage KOA subject with similar demographics. The results show that both SFD and MSS factors allowed distinguishing between a healthy subject and a KOA subject, showing progression at 2 years follow-up, at the instance of peak contact force as well as during the stance phase of the gait cycle. At the peak of the stance phase, the SFD were found to be more elevated in the KOA patient with the median being 0.82% higher in the lateral and 0.4% higher in the medial compartment of the tibial cartilage compared to the healthy subject. Similarly, for the MSS, the median strains were found to be 3.6% higher in the lateral and 0.7% higher in the medial tibial compartment of the KOA patient compared to the healthy subject. Based on these intersubject SFD and MSS differences, we were additionally able to identify that the tibial compartment of the KOA subject at risk of progression. We confirmed the mechanoregulatory factors as potential biomarkers to discriminate patients at risk of disease progression. Future studies should evaluate the sensitivity of the mechanoregulatory factors calculated based on this multi-scale modeling workflow in larger patient and control cohorts.

摘要

膝关节骨关节炎(KOA)的特征是关节软骨退变。机械性关节环境在该疾病的发生和发展中起重要作用,这一点已被广泛接受。计算机模拟模型已被用于研究机械负荷与软骨退变之间的相互作用,在此主要依赖于两个指示胶原蛋白降解和蛋白聚糖消耗的关键机械调节因子。这些因子分别是胶原纤维方向应变(SFD)和最大剪切应变(MSS)。在本研究中,基于肌肉骨骼建模和有限元建模之间的协同作用,采用了多尺度计算机模拟建模方法来评估SFD和MSS。基于在基线(2年随访前)收集的特定受试者步态分析数据,在步态过程中对这些应变进行了评估,该数据来自一名健康且处于疾病进展早期的KOA受试者,其人口统计学特征相似。结果表明,SFD和MSS因子都能够区分健康受试者和KOA受试者,在2年随访时、峰值接触力时以及步态周期的站立期均显示出进展情况。在站立期峰值时,发现KOA患者的SFD升高更为明显,与健康受试者相比,胫骨软骨外侧隔室的中位数高0.82%,内侧隔室高0.4%。同样,对于MSS,与健康受试者相比,KOA患者胫骨外侧隔室的中位数应变高3.6%,内侧隔室高0.7%。基于这些受试者间SFD和MSS的差异,我们还能够识别出有进展风险的KOA受试者的胫骨隔室。我们证实了这些机械调节因子作为区分有疾病进展风险患者的潜在生物标志物。未来的研究应在更大的患者和对照组队列中评估基于这种多尺度建模工作流程计算出的机械调节因子的敏感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46a1/10413555/a4499d4c25d7/fbioe-11-1214693-g001.jpg

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