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特定主题的自适应机械加载在小鼠尾椎骨缺损中的骨愈合应用。

Application of subject-specific adaptive mechanical loading for bone healing in a mouse tail vertebral defect.

机构信息

Institute for Biomechanics, ETH Zurich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland.

出版信息

Sci Rep. 2021 Jan 21;11(1):1861. doi: 10.1038/s41598-021-81132-8.

Abstract

Methods to repair bone defects arising from trauma, resection, or disease, continue to be sought after. Cyclic mechanical loading is well established to influence bone (re)modelling activity, in which bone formation and resorption are correlated to micro-scale strain. Based on this, the application of mechanical stimulation across a bone defect could improve healing. However, if ignoring the mechanical integrity of defected bone, loading regimes have a high potential to either cause damage or be ineffective. This study explores real-time finite element (rtFE) methods that use three-dimensional structural analyses from micro-computed tomography images to estimate effective peak cyclic loads in a subject-specific and time-dependent manner. It demonstrates the concept in a cyclically loaded mouse caudal vertebral bone defect model. Using rtFE analysis combined with adaptive mechanical loading, mouse bone healing was significantly improved over non-loaded controls, with no incidence of vertebral fractures. Such rtFE-driven adaptive loading regimes demonstrated here could be relevant to clinical bone defect healing scenarios, where mechanical loading can become patient-specific and more efficacious. This is achieved by accounting for initial bone defect conditions and spatio-temporal healing, both being factors that are always unique to the patient.

摘要

方法来修复创伤、切除或疾病引起的骨缺损,继续受到追捧。循环机械加载被很好地确立为影响骨(再)塑造活性,其中骨形成和吸收与微尺度应变相关。基于此,跨骨缺损应用机械刺激可以改善愈合。然而,如果忽略有缺陷骨的机械完整性,加载方案很有可能造成损伤或无效。本研究探索了实时有限元(rtFE)方法,该方法使用来自微计算机断层扫描图像的三维结构分析,以在特定于主体和时变的方式估计有效峰值循环载荷。它在周期性加载的小鼠尾部椎骨骨缺损模型中演示了这一概念。使用 rtFE 分析结合自适应机械加载,与未加载对照相比,小鼠骨愈合显著改善,且没有发生椎骨骨折。这里展示的基于 rtFE 驱动的自适应加载方案可能与临床骨缺损愈合情况相关,在这些情况下,机械加载可以针对患者变得更加个体化和有效。这是通过考虑初始骨缺损条件和时空愈合来实现的,这两个因素对于每个患者来说都是独特的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c63/7820598/c5f0d1add3ee/41598_2021_81132_Fig1_HTML.jpg

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