Name: measuring local tissue strains in tendons via open-source digital image correlation
Uploaded: 2023-01-27T14:30:00
Description: Watch this Scientific Journal Video about Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation at JoVE.com

This work was funded by the National Institutes of Health (R21 AR079095) and the National Science Foundation (2142627).

This study was approved by the Pennsylvania State University Institutional Animal Care and Use Committee.
1. Tissue preparation
<ol>
	<li>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.
	<ol>
		<li>Make an incision to the skin superficial to the Achilles tendon to expose the plantaris tendon and the surrounding connective tissue. Then, remove...

<ol>
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J., Andarawis-Puri, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Novel+image+analysis+methods+for+quantification+of+in+situ+3-D+tendon+cell+and+matrix+strain.">Novel image analysis methods for quantification of in situ 3-D tendon cell and matrix strain.</a> Journal of Biomechanics. 67, 184-189 (2018).</li><li>Yang, J., Bhattacharya, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Augmented+Lagrangian+digital+image+correlation.">Augmented Lagrangian digital image correlation.</a> Experimental Mechanics. 59 (2), 187-205 (2019).</li><li>Peterson, B. E., Szczesny, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dependence+of+tendon+multiscale+mechanics+on+sample+gauge+length+is+consistent+with+discontinuous+collagen+fibrils.">Dependence of tendon multiscale mechanics on sample gauge length is consistent with discontinuous collagen fibrils.</a> Acta Biomaterialia. 117, 302-309 (2020).</li><li>Humphrey, J. D., O'Rourke, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> An Introduction to Biomechanics. , (2015).</li><li>Reese, S. P., Weiss, J. 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B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micromechanical+poroelastic+finite+element+and+shear-lag+models+of+tendon+predict+large+strain+dependent+Poisson's+ratios+and+fluid+expulsion+under+tensile+loading.">Micromechanical poroelastic finite element and shear-lag models of tendon predict large strain dependent Poisson's ratios and fluid expulsion under tensile loading.</a> Acta Biomaterialia. 22, 83-91 (2015).</li><li>Szczesny, S. E., Elliott, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interfibrillar+shear+stress+is+the+loading+mechanism+of+collagen+fibrils+in+tendon.">Interfibrillar shear stress is the loading mechanism of collagen fibrils in tendon.</a> Acta Biomaterialia. 10 (6), 2582-2590 (2014).</li><li>Han, W. 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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...

Tendons are mechanosensitive tissues that adapt and degenerate in response to mechanical loading1,2,3,4. 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 lines (PBLs)5,6,7,8, measurement of the changes in the centroid-to-centroid distance of individual nuclei within the tissue9,10, and a recent full-field 3D DIC method that considers out-of-plane motion and 3D deformations11. However, the accuracy and sensitivity of these techniques have been reported in only a few cases, and none of these techniques have been made publicly available, which makes the widespread adoption and utilization of these techniques difficult.
The objective of this work was to create a validated analysis tool for measuring local tissue strains in tendon explants that is readily available and easy to use. The chosen method is based on a publicly available augmented-Lagrangian digital image correlation (ALDIC) algorithm written in MATLAB that was developed by Yang and Bhattacharya12. This algorithm was adapted for analyzing tendon samples and validated by applying it to digitally transformed images and by comparing the strains measured in actual tendon samples to the results obtained from photobleached lines. Furthermore, additional functionality was implemented in the algorithm to confirm the accuracy of the calculated displacement field even in the absence of known strain values or a secondary measurement technique. Therefore, this algorithm is a highly useful and adaptable tool for accurately measuring local 2D tissue strains in tendons.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>5-DTAF (5-(4,6-Dichlorotriazinyl) Aminofluorescein), single isomer</td>
			<td>ThermoFisher</td>
			<td>D16</td>
			<td></td>
		</tr>
		<tr>
			<td>Calipers</td>
			<td>Mitutoyo</td>
			<td>500-196-30</td>
			<td></td>
		</tr>
		<tr>
			<td>Confocal Microscope</td>
			<td>Nikon</td>
			<td>A1R HD</td>
			<td></td>
		</tr>
		<tr>
			<td>Corning LSE Vortex Mixer</td>
			<td>Coning</td>
			<td>6775</td>
			<td></td>
		</tr>
		<tr>
			<td>DRAQ5 Fluorescent Probe Solution (5 mM)</td>
			<td>ThermoFisher</td>
			<td>62554</td>
			<td></td>
		</tr>
		<tr>
			<td>MATLAB</td>
			<td>MathWorks</td>
			<td>R2022b</td>
			<td></td>
		</tr>
		<tr>
			<td>Tensile Loading Device</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Tensile loading device described in Peterson et al, 2020. (ref 13)&#160;</td>
		</tr>
		<tr>
			<td>Tube Revolver Rotator</td>
			<td>ThermoFisher</td>
			<td>88881001</td>
			<td></td>
		</tr>
	</tbody>
</table>

measuring local tissue strains in tendons via open-source digital image correlation

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.

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&#39;s ratio of 115,16. The accuracy of the ALDIC algorithm was then assessed by comparing the mean calculated strain values...

Watch this Scientific Journal Video about Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation at JoVE.com

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

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.

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

There is considerable scientific interest in understanding the strains that tendon cells experience in situ and how these strains influence tissue ...

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.

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