Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Summary

We describe the use of digital image correlation to characterize the local surface strain field on vascular tissue samples subjected to uniaxial tensile testing. These measurements facilitate precise quantification of the sample mechanical response and the generation of constitutive stress-strain relations.

Abstract

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and product development. Stress-strain relationships are typically obtained from mechanical testing data to enable comparative assessment among samples and in some cases identification of constitutive mechanical properties. However, errors may be introduced through the use of average strain measures, as significant heterogeneity in the strain field may result from geometrical non-uniformity of the sample and stress concentrations induced by mounting/gripping of soft tissues within the test system. When strain field heterogeneity is significant, accurate assessment of the sample mechanical response requires measurement of local strains. This study demonstrates a novel biomechanical testing protocol for calculating local surface strains using a mechanical testing device coupled with a high resolution camera and a digital image correlation technique. A series of sample surface images are acquired and then analyzed to quantify the local surface strain of a vascular tissue specimen subjected to ramped uniaxial loading. This approach can improve accuracy in experimental vascular biomechanics and has potential for broader use among other native soft tissues, engineered soft tissues, and soft hydrogel/polymeric materials. In the video, we demonstrate how to set up the system components and perform a complete experiment on native vascular tissue.

Introduction

A rich history of research spanning over 50 years has been focused on quantifying the mechanical properties of vascular tissues. These studies allow us to better understand both the physiological and pathological behavior of blood vessels, provide a basis for evaluating the efficacy/compatibility of endovascular devices, and aid in the design and fabrication of engineered vascular constructs^1-6. Accurate measurement of the mechanical response of soft tissues and constitutive modeling of their mechanical properties is inherently challenging due to the mechanical heterogeneity, anisotropy, and nonlinearity exhibited by most tissue types. Moreover, experimental measurements are often confounded by local complexities introduced at sample-grip interfaces in the course of mechanical testing (i.e., bending, friction, stress concentrations, tearing) and the inevitable transition of mechanical properties once tissue is excised from the living animal.

A uniaxial tensile experiment is among the simplest mechanical tests that can be performed on a specimen made of a solid material, and is often used to assess the mechanical response of vascular tissue. Results from these experiments provide useful preliminary information for both native and engineered tissue sources, and can be used to compare the effects of certain treatments, disease states, or pharmacological compounds on the mechanical behavior of the vascular wall ^7-11.

Uniaxial mechanical testing of soft tissues is typically performed on samples with relatively uniform geometries, which are most commonly dog-bone or ring shaped ^7,8,12-14. However, significant departure from these idealized geometries can occur due to challenges associated with tissue dissection, isolation, and clamping within the testing system. Any non-uniformity in geometry will ultimately give rise to heterogeneous stress and strain fields when the sample is subjected to uniaxial extension, with the degree of heterogeneity dependent on actual sample shape, as well as sample size (relative to the grips) and the mechanical properties of the material ^9,15,16. When field heterogeneities are significant, sample strain calculations based on the relative grip positions are inaccurate and thus an insufficient basis for assessing mechanical behavior.

Video analysis systems have been widely used for strain measurements of soft tissues, often using high contrast dye markers applied to the specimen surface ^17,18. Digital image correlation, an optical metrological technique which measures full-field surface strain by comparing gray level intensity values on the specimen's surface before and after deformation, has been used in conjunction with video analyses of soft tissues ^19-21. There are several advantages of digital image correlation compared to interferometric methods that may be employed for measurements. First, as a non-contacting measurement technique, it minimizes the confounding effects of modifying material properties due to the way in which the measurement system affects the specimen. Second, it requires a much less stringent measurement environment and has a wider range of sensitivity and resolution than other methods. Third, endowed with the capability of capturing a full field of view, this technique can characterize both the average and the local mechanical responses. For detailed explanation of the method, readers are encouraged to see the book by Sutton ²².

To obtain strain fields on the specimen surface, a two-dimensional digital image correlation technique (2D-DIC) can be used. In short, images of the specimen are captured at unloaded and various loaded states. The first image is divided into small squares called subsets (M×M pixels) which form a mesh for subsequent calculation of 2D strain fields. The position of each square in the deformed specimen is obtained using an image matching algorithm. The motion of each square is then tracked, image-by-image, yielding displacement fields which can then be used to derive deformation gradients and strains via a variety of methods, including polynomial fitting or finite element interpolation. In the present manuscript, we provide a detailed methodology for assessment of the surface strain fields on native vascular tissues via integration of uniaxial tensile testing and 2D-DIC.

Protocol

NOTE: The procedures described below were performed as part of a protocol approved by the Institutional Animal Care and Use Committee at the University of South Carolina in Columbia, South Carolina.

1. Tissue Acquisition and Dissection

1. Sterilize all surgical tools prior to tissue dissection. Autoclave surgical scissors and fine standard forceps as well as surgical blades under pressure of 15 psi and temperature of 121 °C for 15 min.
2. Acquire one set of fresh porcine (7 month old Landrace males, 60-70 kg) kidneys with intact aorta from a local slaughterhouse. Transport tissue back to the laboratory in iced 1% phosphate buffered saline (PBS) solution.
3. Immediately upon arrival, isolate the abdominal aorta from surrounding tissue using surgical scissors and forceps.
4. Wash the vessel three times using a 50 ml syringe filled with PBS (pH 7.2). Using the scissors and forceps, remove as much perivascular tissue as possible without compromising the integrity of the sample.
5. Vertically position a sharp razor blade onto the middle section of the vessel and make sure it is perpendicular to the vessel longitudinal axis. Create two ring samples each with a width of approximately 20 mm by applying three sequential circumferential cuts with the razor blade.
6. Vertically position a sharp razor blade onto one ring sample such that the blade is oriented in the radial direction. Apply an acute force to yield a radial cut, which results in a strip-shaped sample for uniaxial mechanical testing. Place the sample in a 100 mm glass Petri dish and submerge in PBS until the application of surface speckling. Repeat for the second ring sample.

2. Creation of Surface Speckle Pattern

1. Connect the airbrush to the pressure valve.
2. Adjust the nozzle diameter of the airbrush to yield speckles of 60-100 µm (appropriate range for nozzle diameter should be determined from preliminary studies).
3. Pour approximately 2 ml of black tissue marking dye into the gravity feeder of the airbrush.
4. Place the airbrush approximately 0.5 m away from the sample.
5. Remove the sample from the Petri dish. Spray tissue marking dye on the intimal surface of the sample for approximately 5 sec under a spraying pressure of 100 psi. Repeat three times to ensure that the speckle pattern uniformly covers the sample surface.

3. Performance of Experiments

1. Attach each end of the sample to a plastic strip (1 cm width x 1 cm length x 0.5 cm thickness) using a tissue adhesive. Place the sample on a tissue cutting board. Position the sample such that it lies flat and measure its dimensions using a digital caliper.
2. Initiate system controls for mechanical testing. On the system controls home screen, select "Waveform" on the taskbar located on the "Setup" tab.
3. Adjust the position of the upper grip of the mechanical tester to -4 mm (4 mm extension relative to the designated initial position in the system). Gently secure one plastic strip (attached to the specimen in 3.1) into the upper grip of the mechanical tester and allow the sample to hang freely. Use the digital caliper to ensure that the distance between the sample and the upper grip is less than 2 mm.
4. Manually adjust the position of the lower grip so that the free end of the sample can be secured without extension. Gently secure the plastic strip attached to the free end of the sample into the lower grip of the mechanical tester.
   1. Use the digital caliper to ensure that the distance between the sample and the lower grip is less than 2 mm. Zero the system load cell. Measure the length of the sample and use this as the reference length for calculation of global circumferential strains.
5. Enter the mechanical testing protocol. The protocol used in this demonstration entails 4 uniaxial displacement cycles which extend the sample length by 18% at a displacement rate of 0.01 mm/sec.
6. Intermittently spray PBS on the sample throughout the remaining testing protocol to ensure that it remains hydrated.
7. Mount the camera (5 mega pixel camera, 100 mm lens, pixel size of 3.49 µm) onto a tripod which is positioned 1.5 m from the loading frame. Ensure the camera and sample surface are perpendicular by setting the camera to the lowest available field of depth and manipulating its alignment such that the entire field of view is in focus.
8. Open the image capture software.
9. Select "PGR-2" in the option "Select system".
10. Select the project path to save the images to be analyzed.
11. Click the "Time Square" icon and specify the acquisition interval as 5 sec.
12. Adjust the exposure, numerical aperture, and focus of the lens so as to get a clear view of the sample.
13. Adjust the position of LED to provide adequate lighting on the sample.
14. Click the "Start" icon in the image capture software to obtain an image of the specimen surface.
15. Open the image analysis software.
16. Import the image obtained. Zoom in on an individual speckle, and then count number of pixels within this individual speckle.
    Note: Identify a representative black speckle. Define the speckle size as the linear distance between pixels on both sides of the speckle that have similar high values. For an acceptable speckle size, the number of pixels across the width of a typical speckle should be greater than 3 pixels. To improve spatial resolution in the measurements, most speckles should have no more than 5-7 pixels across the width of the speckle, whenever possible. Thus, a typical speckle for this case would range between 10 μm at the smallest and 23 μm at the largest in linear dimension. To determine an appropriate subset size, a typical subset should have at least 3 white and 3 black speckles across its width. If a typical speckle is 5 pixels in linear dimension, then each 31x31 subset would be at least 105 μm in linear dimension. The spacing between subset centers should be at least 1/6 of the linear dimension. Thus, for a 31x31 subset size, the distance is 5 pixels which represents 18 μm in linear distance.
17. After verifying the quality of speckle pattern, simultaneously click the "Run" icon in the system and "Start" icon in the image capture software to start the test.
18. Capture a series of images throughout testing using the camera and image capture software.

4. Clean-up Procedures after the Experiment

1. Place the discarded sample in biohazard bag and close the bag. Call the Department of Environmental Health and Safety (EHS) at the University of South Carolina for proper disposal.
2. Prepare a phosphate-free disinfectant solution with a 1:64 dilution ratio of detergent disinfectant to distilled water. Soak the surgical tools in this solution for 20 min.
3. Thoroughly rinse the items described in 4.2 with distilled water. Dry the tools using a paper towel and then spray them with a 70% ethanol solution. Once again dry the surgical tools using a paper towel and put them back in the surgical toolbox.

5. Image Analysis to Measure the Local Strain Field

1. Open the image analysis software.
2. Click the "Speckle images" tab, select all images which need to be analyzed.
3. Click on rectangle tool and select the area of interest in the first image.
4. Enter subset size 41×41 pixels and step size 5 pixels.
5. Click start analysis tab in the software, select the interpolation as optimized 8-trap; select the criterion as zero-normalized squared differences and subset weights option as Gaussian.
6. Set the threshold options as default in the software.
7. Click on post-processing sub tab in start analysis tab. Click option strain computation and leave filter size and type of filter as default in software. Select tensor type Lagrange.
8. Select data tab and then select any analyzed image for visualization of the surface strain field.

Results

The mechanical data acquired from a ramped uniaxial extension test on vascular tissue consists of load versus applied sample displacement relationships at a given displacement rate. In this study, 2D-DIC in conjunction with uniaxial mechanical testing is used to measure the surface strain fields of the specimen in orthogonal directions at various deformed states. The viscoelastic nature of vascular tissue is manifested by the notable degree of hysteresis in the load-displacement curves pr...

Discussion

Although previous studies have used a wide-range of dye-tracking video methods to assess sample strain ^{18,20,21,23,24}, our present aim is to provide a comprehensive methodology to couple uniaxial tensile testing with 2D-DIC for assessment of surface strains on vascular tissue samples. With a high resolution camera and in-house image analysis software, the strain field can be measured within a predetermined surface region as the sample undergoes uniaxial loading. Of particular relevance to mechanical testing of...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Uniaxial tensile mechanical tester	Enduratec	3230 AT/HR
Blue tissue marking dye	http://www.ebay.com/itm/Tissue-Marking-Dye-in-Bottles-2oz-Bottle-1-ea-/201193551510?pt=LH_DefaultDomain_0&hash=item2ed811f696
Sprayer	Anest-iwata	CM-B	Custom Micron B
Camera	Point Grey	GS2-GE-50S5M-C
Lens	Tokina	AT-X M100
Vascular tissue	Caughman Inc
0.9% Sodium Chloride Injection PBS	BAXTER HEALTHCARE CORP.
Vic_snap	Correlated Solutions
Vic_2D	Correlated Solutions
Wintest 4.1	Bose ElectroForce
Tissue adhesive	3M Vetbond	1469SB
Disinfectant	Fisher Scientific	04-355-13	Decon BDD Bacdown Detergent Disinfectant