Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

Summary

This paper describes an open-source digital image correlation algorithm for measuring local 2D tissue strains within tendon explants. The accuracy of the technique has been validated using multiple techniques, and it is available for public use.

Abstract

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.

Introduction

Tendons are mechanosensitive tissues that adapt and degenerate in response to mechanical loading^1,2,3,4. Due to the role that mechanical stimuli play in tendon cell biology, there is a large interest in understanding the strains that tendon cells experience in the native tissue environment during loading. Several experimental and analytical techniques have been developed to measure local tissue strains in tendons. These include 2D/3D digital image correlation (DIC) analyses of surface strains using either speckle patterns or photobleached li....

Protocol

This study was approved by the Pennsylvania State University Institutional Animal Care and Use Committee.

1. Tissue preparation

1. For this protocol, harvest the Achilles tendons from 2-4 month old male C57BL/6 mice.
   NOTE: Different tendons or ligaments from mice or other small animals could also be used.
   1. Make an incision to the skin superficial to the Achilles tendon to expose the plantaris tendon and the surrounding connective tissue. Then, remove them using a surgical blade.
   2. Separate the exposed soleus and gastrocnemius muscles from the hind limb, and carefully scrape them off the A....

Results

Prior to analyzing the strain fields in actual tissue samples, the ALDIC protocol was first validated using digitally strained/transformed images of nuclei within mouse Achilles tendons. Specifically, the images were transformed to digitally produce uniform strains in the x-direction of 2%, 4%, 6%, 8%, and 10% strain with a simulated Poisson's ratio of 1^15,16. The accuracy of the ALDIC algorithm was then assessed by comparing the mean calculated strain values.......

Discussion

The objective of this paper was to provide an open-source, validated method to measure the 2D strain fields in tendons under tensile load. The foundation of the software was based on a publicly available ALDIC algorithm¹². This algorithm was embedded into a larger MATLAB code with the added functionality of incremental (versus cumulative) strain analysis. This adapted algorithm was then applied to the tensile testing of tendons, and its accuracy was assessed by two different techniques (i.e., digi.......

Materials

Name	Company	Catalog Number	Comments
5-DTAF (5-(4,6-Dichlorotriazinyl) Aminofluorescein), single isomer	ThermoFisher	D16
Calipers	Mitutoyo	500-196-30
Confocal Microscope	Nikon	A1R HD
Corning LSE Vortex Mixer	Coning	6775
DRAQ5 Fluorescent Probe Solution (5 mM)	ThermoFisher	62554
MATLAB	MathWorks	R2022b
Tensile Loading Device	N/A	N/A	Tensile loading device described in Peterson et al, 2020. (ref 13)
Tube Revolver Rotator	ThermoFisher	88881001