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

This protocol enables the measurements of the local tissue strains within a tendon during loading. It is useful to understand how tendons behave mechanically and adapt to their loading environment. The main advantage of this technique is that the software used is publicly available online and provides feedback on the measurement accuracy even when the true tissue strains are unknown.

Measuring local tissue strains in a tendon is valuable to understand how cells remodel tissue during tendon degeneration and repair. Demonstrating this procedure will be Stanton Godshall, an undergraduate student, and Krishna Pedaprolu, a PhD student in my laboratory. After staining the harvested Achilles tendons in DTAF, transfer the tissue from the DTAF solution to the DRAQ5 solution and incubate the tissues in a dark space for 10 minutes at room temperature.

Place the tendon into the grips of the tensile loading device. Before mounting the grips in the loading device, use digital calipers to measure the distance between the calcaneus attachment and the opposite grip. Mount the grips into the loading device containing PBS to maintain tissue hydration.

Align the tendon as best as possible with either the x-axis or y-axis of the microscope images so that the X strain and Y strain outputs of the algorithm correspond with the tendon axis. Preload the tendon with one gram of tension. If desired, photobleach a set of four lines spaced 80 microns apart in the center region of the tissue, and repeat the process on the left and right extremes near the grips.

The change in distance between the lines in each tissue region is a secondary measurement of the local tissue strains that can be used to validate the data. Next, using the confocal microscope, acquire volumetric images of the DTAF and DRAQ5 fluorescence at one gram of preload. Perform a strain ramp to 2%strain at 0.5%per second.

Note that the strain rate and incremental strain magnitude can be adjusted. After allowing the tissue to stress relax for 10 minutes, take another volumetric image of the tissue after the deformation. Repeat the process for as many strain increments as desired.

To create the digitally transformed images, download the code digital_strain. m from GitHub. After downloading, open and run the code.

When prompted, insert desired values for the maximum applied strain, applied strain increment, and Poisson's ratio before pressing OK.Then when prompted again, select the undeformed reference image. For each strain increment, an overlay of the reference image and the transformed image is displayed. The digitally transformed images will be saved to the directory named digitally transformed X percent strain where X is the strain increment.

Open the script with the displayed name and click Run to begin image analysis. When prompted, alter the values for the augmented Lagrangian digital image correlation or ALDIC parameters as desired. After being prompted, select the yes checkbox to automatically save the mean value, standard deviation, and 2D map for the desired collection of variables.

When prompted, select the desired variables like X strain, Y strain, shear strain, bad regions, et cetera, and press OK.Following the next prompt, select the folder that contains the renamed max intensity Z projections. The software automatically performs incremental ALDIC to determine the strain fields of the deformed images. When prompted, left click to create a four-point polygon to define the region of interest for measuring the strains.

The folder nuclear tracking results, which can be renamed by adjusting lines 555 and 556, stores all the plots specified previously. This folder also contains a spreadsheet named results, which stores all the means and standard deviations specified before. When validated using digitally strained images, the ALDIC algorithm consistently underestimated the mean X strain and the error magnitude increased with increasing applied strain.

The Y strain was also mostly underestimated. However, in all cases, the magnitude of the strain error was very small. The standard deviation of the calculated X strain and Y strain, although low in magnitude, increased with increasing applied strain.

Bad region analysis revealed that the number of bad regions having invalid strain calculations in the digitally transformed images analyzed using the cumulative method increased consistently after 6%applied strain, while the incremental quantity remained at 1%In one of the four samples, which was treated as an outlier, nearly half of the image was identified as bad at the maximum strain increment. The X strains calculated by ALDIC were larger than those determined from the PBLs, the difference being within 0.005 which is similar to the standard deviation for the PBL data averaged across all the samples. Determining the magnitudes and spatial distributions of the local strains in the tendons under tensile load showed that across all samples, the X strain consistently remained below the applied strains.

The mean strain in the Y direction was approximately zero for all the increments, but the standard deviation was high. The mean shear strain increased steadily throughout the strain increments. The most important point to remember is to save the images prior to applying a greater strain.

The images, if not saved, are lost and cannot be recovered. While this technique is specifically validated for measuring tissue strains within tendons, it can provide insight into mechanical biology and mechanics of many other animal and human tissues.