Department of Biomedical Engineering, Pennsylvania State University.
Department of Biomedical Engineering, Amirkabir University of Technology.
J Vis Exp. 2023 Jan 27(191). doi: 10.3791/64921.
There is considerable scientific interest in understanding the strains that tendon cells experience in situ and how these strains influence tissue remodeling. Based on this interest, several analytical techniques have been developed to measure local tissue strains within tendon explants during loading. However, in several cases, the accuracy and sensitivity of these techniques have not been reported, and none of the algorithms are publicly available. This has made it difficult for the more widespread measurement of local tissue strains in tendon explants. Therefore, the objective of this paper was to create a validated analysis tool for measuring local tissue strains in tendon explants that is readily available and easy to use. Specifically, a publicly available augmented-Lagrangian digital image correlation (ALDIC) algorithm was adapted for measuring 2D strains by tracking the displacements of cell nuclei within mouse Achilles tendons under uniaxial tension. Additionally, the accuracy of the calculated strains was validated by analyzing digitally transformed images, as well as by comparing the strains with values determined from an independent technique (i.e., photobleached lines). Finally, a technique was incorporated into the algorithm to reconstruct the reference image using the calculated displacement field, which can be used to assess the accuracy of the algorithm in the absence of known strain values or a secondary measurement technique. The algorithm is capable of measuring strains up to 0.1 with an accuracy of 0.00015. The technique for comparing a reconstructed reference image with the actual reference image successfully identified samples that had erroneous data and indicated that, in samples with good data, approximately 85% of the displacement field was accurate. Finally, the strains measured in mouse Achilles tendons were consistent with the prior literature. Therefore, this algorithm is a highly useful and adaptable tool for accurately measuring local tissue strains in tendons.
科学界对于了解肌腱细胞在体内所承受的张力以及这些张力如何影响组织重塑非常感兴趣。基于这种兴趣，已经开发出几种分析技术来测量加载过程中肌腱标本内的局部组织应变。然而，在某些情况下，这些技术的准确性和灵敏度尚未得到报道，并且这些算法都没有公开。这使得肌腱标本中局部组织应变的更广泛测量变得困难。因此，本文的目的是创建一种经过验证的分析工具，用于测量肌腱标本中的局部组织应变，该工具易于获取且易于使用。具体而言，对一种公开的增广拉格朗日数字图像相关（ALDIC）算法进行了改进，通过跟踪在单轴拉伸下小鼠跟腱细胞核的位移来测量 2D 应变。此外，通过分析数字转换图像以及将应变值与独立技术（即光漂白线）确定的值进行比较，验证了计算应变的准确性。最后，将一种技术整合到算法中，使用计算出的位移场重建参考图像，这可用于在没有已知应变值或二次测量技术的情况下评估算法的准确性。该算法可以测量高达 0.1 的应变，其精度为 0.00015。用于比较重建参考图像与实际参考图像的技术成功识别出了具有错误数据的样本，并表明在具有良好数据的样本中，大约 85%的位移场是准确的。最后，在小鼠跟腱中测量的应变与之前的文献一致。因此，该算法是一种非常有用且适应性强的工具，可用于准确测量肌腱中的局部组织应变。
