Name: using digital image correlation to characterize local strains on vascular tissue specimens
Uploaded: 2016-01-24T14:00:00
Description: Watch this Scientific Journal Video about Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens at JoVE.com

The software and technical support were courtesy of Correlated Solutions Incorporated (www.correlatedsolutions.com).

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
<ol>
	<li>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 &#176;C for 15 min.</li>
	<li>Acquire one set of fresh porcine (7 month old Landrace ...

<ol>
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A., Altman, P., Buzard, K., Choe, K. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Strip+extensiometry+for+comparison+of+the+mechanical+response+of+bovine,+rabbit,+and+human+corneas.">Strip extensiometry for comparison of the mechanical response of bovine, rabbit, and human corneas.</a> J Biomech Eng. 114, 202-215 (1992).</li><li>Guo, X., Kassab, G. 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D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+improved+panoramic+digital+image+correlation+method+for+vascular+strain+analysis+and+material+characterization.">An improved panoramic digital image correlation method for vascular strain analysis and material characterization.</a> J Mech Behav Biomed Mater. 27, 132-142 (2013).</li><li>Wang, C. C., Deng, J. M., Ateshian, G. A., Hung, C. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+automated+approach+for+direct+measurement+of+two-dimensional+strain+distributions+within+articular+cartilage+under+unconfined+compression.">An automated approach for direct measurement of two-dimensional strain distributions within articular cartilage under unconfined compression.</a> J Biomech Eng. 124, 557-567 (2002).</li><li>Ning, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deformation+measurements+and+material+property+estimation+of+mouse+carotid+artery+using+a+microstructure-based+constitutive+model.">Deformation measurements and material property estimation of mouse carotid artery using a microstructure-based constitutive model.</a> J Biomech Eng. 132, 121010 (2010).</li><li>Sutton, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Strain+field+measurements+on+mouse+carotid+arteries+using+microscopic+three-dimensional+digital+image+correlation.">Strain field measurements on mouse carotid arteries using microscopic three-dimensional digital image correlation.</a> J Biomed Mater Res A. 84, 178-190 (2008).</li><li>Sutton, M. A., Orteu, J. J., Schreier, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications. , (2009).</li><li>Verhulp, E., van Rietbergen, B., Huiskes, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+three-dimensional+digital+image+correlation+technique+for+strain+measurements+in+microstructures.">A three-dimensional digital image correlation technique for strain measurements in microstructures.</a> J Biomech. 37, 1313-1320 (2004).</li><li>Wang, C. C., Deng, J. M., Ateshian, G. A., Hung, C. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+automated+approach+for+direct+measurement+of+two-dimensional+strain+distributions+within+articular+cartilage+under+unconfined+compression.">An automated approach for direct measurement of two-dimensional strain distributions within articular cartilage under unconfined compression.</a> Journal of Biomechanical Engineering. 124, 557-567 (2002).</li><li>Franck, C., Hong, S., Maskarinec, S., Tirrell, D., Ravichandran, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+full-field+measurements+of+large+deformations+in+soft+materials+using+confocal+microscopy+and+digital+volume+correlation.">Three-dimensional full-field measurements of large deformations in soft materials using confocal microscopy and digital volume correlation.</a> Exp Mech. 47, 427-438 (2007).</li><li>Garcia, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+study+and+constitutive+modelling+of+the+passive+mechanical+properties+of+the+porcine+carotid+artery+and+its+relation+to+histological+analysis:+Implications+in+animal+cardiovascular+device+trials.">Experimental study and constitutive modelling of the passive mechanical properties of the porcine carotid artery and its relation to histological analysis: Implications in animal cardiovascular device trials.</a> Med Eng Phys. 33, 665-676 (2011).</li><li>Miller, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+to+test+very+soft+biological+tissues+in+extension?.">How to test very soft biological tissues in extension?.</a> J Biomech. 34, 651-657 (2001).</li><li>Sutton, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Springer handbook of experimental solid mechanics. , 565-600 (2008).</li><li>Han, H. C., Fung, Y. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Longitudinal+strain+of+canine+and+porcine+aortas.">Longitudinal strain of canine and porcine aortas.</a> J Biomech. 28, 637-641 (1995).</li><li>Sokolis, D. 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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...

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 constructs1-6. 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&#39;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&#215;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.

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			<td height="42" style="height:42px;width:216px;">Uniaxial tensile mechanical tester</td>
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using digital image correlation to characterize local strains on vascular tissue specimens

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.

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...

Watch this Scientific Journal Video about Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens at JoVE.com

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

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.

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and ...

The overall goal of this protocol is to characterize the local surface strain field on vascular tissue samples. This is accomplished using a digital image correlation technique with uniaxial tensile testing. This method can help answer key questions in the field of soft tissue mechanics and specifically provide information to identify and invalidate increasingly sophisticated computational and mathematical models of vascular tissue.The main advantage of this technique that facilitates precise quantification of a strain field heterogeinity on the sample surface, which is a function of inherent material properties, symbol geometry and employed testing modality. As soon as the tissue arrives at the lab, isolate the abdominal aorta from surrounding tissue using surgical scissors and forceps. Then, wash the vessel three times using a syringe filled with PBS.Following the washes, use scissors and forceps to remove as much perivascular tissue as possible, without compromising the integrity of the sample. Then, onto the middle section of the vessel, position a sharp razor blade, perpendicular to the vessel's longitudinal axis and chop the vessel three times to make two ring samples. Next, position a blade onto one of the rings to make a radial cut.Firmly slice the ring to make a strip shaped sample for uniaxial mechanical testing. Do this to both rings. Temporarily store the two samples in a 100 mm glass petri dish submerged in PBS.To speckle the sample surface have an air brush ready to spray tissue marking dye. Connect the air brush to a pressure valve set to produce 100 psi. Next, add the tissue marking dye.The nozzle diameter must be calibrated for speckle diameters between 60 and 100 microns. Then, spray tissue marking dye on the intimal surface of the sample for approximately five seconds. Do this three times to ensure that the speckle pattern uniformly covers the sample surface.To begin, mount the sample to the testing apparatus. First, attach each end of the sample to a plastic strip using a tissue adhesive. Place plastic on both the top and bottom of the sample with the adhesive, making a sandwich.Place the sample flat on a tissue cutting board then measure it's dimensions using a digital caliper. Next, initiate the system controls for the test apparatus. On the system control's home screen, select waveform on the task bar located on the set up tab.Then, adjust the position of the upper grip of the mechanical tester to negative four mm to provide a 4 mm extension relative to the designated initial position in the system. Now, gently secure one plastic strip into the upper grip of the mechanical tester and allow the sample to hang freely. Next, adjust the position of the lower grip so that the free end of the sample can be secured without extension.Then, gently secure the plastic strip attached to the free end, into the lower grip of the tester. With the sample mounted, zero the system load cell. Then measure the length of the sample and use this as the reference length when calculating global circumferential strains.Now, in the software control, enter the mechanical testing protocol. Here, four uniaxial displacement cycles are applied. Each cycle extends the sample length by 18 percent at a displacement rate of 0.01 mm per second.To document the test, take a photo every few seconds. Position a camera 1.5 m from the loading frame, perpendicular to the sample and focus it on the sample. In the image capture software, in the option select system"select PGR2, then set the project path to save the images to be analyzed.Click the time square icon and specify the acquisition interval as 5 seconds. Now, import the image obtained. Zoom in on an individual speckle and then count the number of pixels within this individual speckle.After verifying the quality of the speckle pattern, simultaneously click the run"icon in the system and the start"icon in the image capture software to start the test. Throughout the protocol, intermittently spray PBS on the sample so it does not dry out. However, do this whenever it is in the unloaded state not during data acquisition.After opening the image analysis software, click the speckle images"tab and select all images which need to be analyzed. Then, click on the rectangle tool and select the area of interest in the first image. Next, enter a 31 by 31 pixel subset size and a step size of five pixels.Now click the start analysis"tab in the software and set the interpolation to be an optimized 8 trap. Also, set the criterion as zero normalized square differences and the subset weights option as Gaucian. Check the threshold options.They should be on the default. Next, click on the post processing sub tab under the start analysis tab. Select the option, string computation"and leave filter size and type of filter as the default.Set the tensor type to Lagrange. Finally, select the data tab and then select an analyzed image to visualize the surface strain field. 2D DIC in conjunction with uniaxial mechanical testing, was used to measure the surface strain field of a vascular tissue specimen, at various deformed states.The viscoelastic nature of the tissue was notable by the degree of hysteresis in the low displacement curves prior to the mechanical preconditioning. However, with preconditioning, the hysteresis was gradually diminished. As expected, the local circumferential strain values increased with applied sample displacement.Circumferential strain was generally less near the center of the sample as compared to near the sample grip interface. In the longitudinal direction, the resultant, non-uniform compressive strain on the sample intimal surface increased as the sample was gradually extended. The color changes within the contours for the full field strain measurements, clearly show the high heterogeneous nature of the aorta when subjected to nominally, uniaxial tensile loading.The coefficients of variation of the surface strain fields in orthogonal directions were then calculated in each experimental state. The variation in the surface strain was found to have an inverse relationship with the samples extension. The high level of heterogeneity in the material response is quantified in the table by the coefficent of variation, or CV.After watching this video, you should have good understanding of how to quantify the local surface mechanical response using digital image correlation coupled with uniaxial tensile testing of vascular tissue samples.After it's development, this technique paved the way for researchers in the field of soft tissue mechanics to explore physiological, pathological and modulated mechanical response of vascular tissue.

Research

JoVE Journal

Biology

Isolation and Differentiation of Stromal Vascular Cells to Beige/Brite Cells

Brown adipocytes have the ability to uncouple the  respiratory chain in mitochondria and dissipate chemical energy as heat.  Development of UCP1-positive ...

Easy Measurement of Diffusion Coefficients of EGFP-tagged Plasma Membrane Proteins Using k-Space Image Correlation Spectroscopy

Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new ...

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

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Magnetic-Activated Cell Sorting Strategies to Isolate and Purify Synovial Fluid-Derived Mesenchymal Stem Cells from a Rabbit Model

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Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography

It is necessary to accurately quantify the anatomical structures of maize materials based on high-throughput image analysis techniques. Here, we provide a ...

Using En Face Immunofluorescence Staining to Observe Vascular Endothelial Cells Directly

Aberrant changes in endothelial phenotype and morphology are considered to be initial events in the pathogenesis of atherosclerosis. Direct observation of ...

Human Adipose Tissue Micro-fragmentation for Cell Phenotyping and Secretome Characterization

In the past decade, adipose tissue transplants have been widely used in plastic surgery and orthopaedics to enhance tissue repletion and/or regeneration. ...

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

The root microbiome plays an important role in plant growth and environmental adaptation. Network analysis is an important tool for studying communities, ...

Detection of Protein Aggregation using Fluorescence Correlation Spectroscopy

Protein aggregation is a hallmark of neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's ...

In Vivo Vascular Permeability Detection in Mouse Submandibular Gland

In Vivo Vascular Permeability Detection in Mouse Submandibular Gland

Saliva plays an important role in oral and overall health. The intact endothelial barrier function of blood vessels enables saliva secretion, whereas the ...