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首页> 外文期刊>Journal of Biomechanics >A biomechanical model for fibril recruitment: Evaluation in tendons and arteries
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A biomechanical model for fibril recruitment: Evaluation in tendons and arteries

机译:一种原纤维招聘生物力学模型:肌腱和动脉评估

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摘要

Simulations of soft tissue mechanobiological behaviour are increasingly important for clinical prediction of aneurysm, tendinopathy and other disorders. Mechanical behaviour at low stretches is governed by fibril straightening, transitioning into load-bearing at recruitment stretch, resulting in a tissue stiffening effect. Previous investigations have suggested theoretical relationships between stress-stretch measurements and recruitment probability density function (PDF) but not derived these rigorously nor evaluated these experimentally. Other work has proposed image-based methods for measurement of recruitment but made use of arbitrary fibril critical straightness parameters. The aim of this work was to provide a sound theoretical basis for estimating recruitment PDF from stress-stretch measurements and to evaluate this relationship using image-based methods, clearly motivating the choice of fibril critical straightness parameter in rat tail tendon and porcine artery. Rigorous derivation showed that the recruitment PDF may be estimated from the second stretch derivative of the first Piola-Kirchoff tissue stress. Image based fibril recruitment identified the fibril straightness parameter that maximised Pearson correlation coefficients (PCC) with estimated PDFs. Using these critical straightness parameters the new method for estimating recruitment PDF showed a PCC with image-based measures of 0.915 and 0.933 for tendons and arteries respectively. This method may be used for accurate estimation of fibril recruitment PDF in mechanobiological simulation where fibril-level mechanical parameters are important for predicting cell behaviour. (C) 2018 Elsevier Ltd. All rights reserved.
机译:软组织力学行为的仿真对于动脉瘤,肌腱病变和其他疾病的临床预测越来越重要。低伸展时的机械性能由原纤维矫直管来控制,在招生伸展时转化为承载,导致组织加强效果。以前的研究表明应力拉伸测量和招聘概率密度函数(PDF)之间的理论关系,但未严格地衍生,也没有评估这些实验。其他工作已经提出了基于图像的招生测量方法,而是使用任意原纤维临界直线度参数。这项工作的目的是为估计来自压力拉伸测量的招募PDF提供良好的理论依据,并使用基于图像的方法评估这种关系,显然激发了大鼠尾肌腱和猪动脉的原纤维临界直线度参数的选择。严格的衍生显示,可以从第一Piola-Kirchoff组织应力的第二拉伸衍生物估计招募PDF。基于图像的原纤维募集鉴定了具有估计PDF的Pearson相关系数(PCC)的纤维直线参数。使用这些关键直线度参数估算募集PDF的新方法显示了PCC,分别具有0.915和0.933的基于图像的措施的PCC。该方法可用于精确地估计用于预测细胞行为的原纤维水平机械参数在机动学模拟中的原纤维募集PDF。 (c)2018年elestvier有限公司保留所有权利。

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