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生物力学与血管硬化有关


[ 作者:Admin     来源:运动解剖学课程网站      点击数:     更新时间:2013/09/08     文章录入:Admin ]



     

      胶原纤维、弹力纤维和平滑肌细胞构成了血管生物力学的基本要素。研究发现,如果血管结构和组成发生变化,不仅可能使血管硬化,也会导致血管病态舒张。年龄增长和疾病都会使动脉血管壁逐渐硬化并失去弹性,进而变厚,形成血管腔狭窄。而动脉血管的这一病变对人体健康甚至生命影响重大。为了探索动脉血管自然变化及产生病变的规律,预防动脉血管病变,开展动脉血管生物力学特性分析研究十分必要。通过实验材料数据和计算机模拟,动脉血管这一复杂生物力学过程,发现生物力学与血管硬化的关系。动脉血管中的弹力纤维决定血管壁弹性,胶原纤维决定血管壁韧性和强度,其结构改变会导致血管壁承受能力发生变化。胶原纤维是胶原蛋白行使生理作用的基本形态。在健康和病变状态下,动脉血管中胶原纤维排列状态有着明显差距,健康血管壁中的胶原纤维呈螺旋状排列,方向一致,但病变血管壁中的胶原纤维排列十分散乱。
 


                    Quantitative assessment of collagen fibre orientations from two-dimensional images of soft biological tissues

                                                                   Journal of The Royal Society Interface  2012-7-30

      In this work, we outline an automated method for the extraction and quantification of material parameters characterizing collagen fibre orientations from two-dimensional images. Morphological collagen data among different length scales were obtained by combining the established methods of Fourier power spectrum analysis, wedge filtering and progressive regions of interest splitting. Our proposed method yields data from which we can determine parameters for computational modelling of soft biological tissues using fibre-reinforced constitutive models and gauge the length scales most appropriate for obtaining a physically meaningful measure of fibre orientations, which is representative of the true tissue morphology of the two-dimensional image. Specifically, we focus on three parameters quantifying different aspects of the collagen morphology: first, using maximum-likelihood estimation, we extract location parameters that accurately determine the angle of the principal directions of the fibre reinforcement (i.e. the preferred fibre directions); second, using a dispersion model, we obtain dispersion parameters quantifying the collagen fibre dispersion about these principal directions; third, we calculate the weighted error entropy as a measure of changes in the entire fibre distributions at different length scales, as opposed to their average behaviour. With fully automated imaging techniques (such as multiphoton microscopy) becoming increasingly popular (which often yield large numbers of images to analyse), our method provides an ideal tool for quickly extracting mechanically relevant tissue parameters which have implications for computational modelling (e.g. on the mesh density) and can also be used for the inhomogeneous modelling of tissues.