A 3D reconstruction of individual fibres in vascular tissue is necessary to understand the microstructure properties of the vessel wall. The objective of this study is to determine the 3D microstructure of elastin fibres in the adventitia of coronary arteries. Quantification of fibre geometry is challenging due to the complex interwoven structure of the fibres. In particular, accurate linking of gaps remains a significant challenge, and complex features such as long gaps and interwoven fibres have not been adequately addressed by current fibre reconstruction algorithms. We use a novel line Laplacian deformation method, which better deals with fibre shape uncertainty to reconstruct elastin fibres in the coronary adventitia of five swine. A cost function, based on entropy and Euler Spiral, was used in the shortest path search. We find that mean diameter of elastin fibres is 1.67 ± 1.42 μ m and fibre orientation is clustered around two major angles of 8.9˚ and 81.8˚. Comparing with CT‐FIRE, we find that our method gives more accurate estimation of fibre width. To our knowledge, the measurements obtained using our algorithm represent the first investigation focused on the reconstruction of full elastin fibre length. Our data provide a foundation for a 3D microstructural model of the coronary adventitia to elucidate the structure–function relationship of elastin fibres.

中文翻译：

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冠状动脉外膜弹性蛋白纤维的 3D 重建

血管组织中单个纤维的 3D 重建对于了解血管壁的微观结构特性是必要的。本研究的目的是确定冠状动脉外膜中弹性蛋白纤维的 3D 微观结构。由于纤维的复杂交织结构，纤维几何形状的量化具有挑战性。特别是，间隙的准确连接仍然是一个重大挑战，当前的纤维重建算法还没有充分解决诸如长间隙和交织纤维等复杂特征。我们使用一种新颖的拉普拉斯线变形方法，它更好地处理了纤维形状的不确定性，以重建五头猪冠状外膜中的弹性蛋白纤维。在最短路径搜索中使用了基于熵和欧拉螺旋的成本函数。我们发现弹性蛋白纤维的平均直径为 1.67 ± 1.42 μ m，纤维取向聚集在两个主要角度 8.9° 和 81.8° 周围。与 CT-FIRE 相比，我们发现我们的方法可以更准确地估计纤维宽度。据我们所知，使用我们的算法获得的测量值代表了第一项专注于全弹性蛋白纤维长度重建的研究。我们的数据为冠状外膜的 3D 显微结构模型提供了基础，以阐明弹性蛋白纤维的结构 - 功能关系。使用我们的算法获得的测量值代表了第一项针对全弹性蛋白纤维长度重建的研究。我们的数据为冠状外膜的 3D 显微结构模型提供了基础，以阐明弹性蛋白纤维的结构 - 功能关系。使用我们的算法获得的测量值代表了第一项针对全弹性蛋白纤维长度重建的研究。我们的数据为冠状外膜的 3D 显微结构模型提供了基础，以阐明弹性蛋白纤维的结构 - 功能关系。