Tendon Strain Measurements With Dynamic Ultrasound Images: Evaluation of Digital Image Correlation

Article (PDF Available)inJournal of Biomechanical Engineering 134(2):024504 · February 2012with54 Reads
DOI: 10.1115/1.4006116 · Source: PubMed
Abstract
Strain is an essential metric in tissue mechanics. Strains and strain distributions during functional loads can help identify damaged and pathologic regions as well as quantify functional compromise. Noninvasive strain measurement in vivo is difficult to perform. The goal of this in vitro study is to determine the efficacy of digital image correlation (DIC) methods to measure strain in B-mode ultrasound images. The Achilles tendons of eight male Wistar rats were removed and mechanically cycled between 0 and 1% strain. Three cine video images were captured for each specimen: (1) optical video for manual tracking of optical markers; (2) optical video for DIC tracking of optical surface markers; and (3) ultrasound video for DIC tracking of image texture within the tissue. All three imaging modalities were similarly able to measure tendon strain during cyclic testing. Manual/ImageJ-based strain values linearly correlated with DIC (optical marker)-based strain values for all eight tendons with a slope of 0.970. DIC (optical marker)-based strain values linearly correlated with DIC (ultrasound texture)-based strain values for all eight tendons with a slope of 1.003. Strain measurement using DIC was as accurate as manual image tracking methods, and DIC tracking was equally accurate when tracking ultrasound texture as when tracking optical markers. This study supports the use of DIC to calculate strains directly from the texture present in standard B-mode ultrasound images and supports the use of DIC for in vivo strain measurement using ultrasound images without additional markers, either artificially placed (for optical tracking) or anatomically in view (i.e., bony landmarks and/or muscle-tendon junctions).
Tendon Strain Measurements With
Dynamic Ultrasound Images:
Evaluation of Digital Image Correlation
Gregory Okotie
Sarah Duenwald-Kuehl
Department of Orthopedics and Rehabilitation,
Department of Biomedical Engineering,
University of Wisconsin-Madison,
Madison, WI 53705
Hirohito Kobayashi
Department of Orthopedics and Rehabilitation,
University of Wisconsin-Madison,
Madison, WI 53705
Mon-Ju Wu
Department of Orthopedics and Rehabilitation,
Materials Science Program,
University of Wisconsin-Madison,
Madison, WI 53705
Ray Vanderby
1
Department of Orthopedics and Rehabilitation,
Department of Biomedical Engineering,
Materials Science Program,
Room 5059, 1111 Highland Ave.,
University of Wisconsin-Madison,
Madison, WI 53705
e-mail: vanderby@ortho.wisc.edu
Strain is an essential metric in tissue mechanics. Strains and strain
distributions during functional loads can help identify damaged
and pathologic regions as well as quantify functional compromise.
Noninvasive strain measurement in vivo is difficult to perform. The
goal of this in vitro study is to determine the efficacy of digital
image correlation (DIC) methods to measure strain in B-mode
ultrasound images. The Achilles tendons of eight male Wistar rats
were removed and mechanically cycled between 0 and 1% strain.
Three cine video images were captured for each specimen: (1) opti-
cal video for manual tracking of optical markers; (2) optical video
for DIC tracking of optical surface markers; and (3) ultrasound
video for DIC tracking of image texture within the tissue. All three
imaging modalities were similarly able to measure tendon strain
during cyclic testing. Manual/ImageJ-based strain values linearly
correlated with DIC (optical marker)-based strain values for all
eight tendons with a slope of 0.970. DIC (optical marker)-based
strain values linearly correlated with DIC (ultrasound texture)-
based strain values for all eight tendons with a slope of 1.003.
Strain measurement using DIC was as accurate as manual image
tracking methods, and DIC tracking was equally accurate when
tracking ultrasound texture as when tracking optical markers. This
study supports the use of DIC to calculate strains directly from the
texture present in standard B-mode ultrasound images and supports
the use of DIC for in vivo strain measurement using ultrasound
images without additional markers, either artificially placed (for
optical tracking) or anatomically in view (i.e., bony landmarks and/
or muscle-tendon junctions). [DOI: 10.1115/1.4006116]
Keywords: digital image correlation (DIC), tendon, ultrasound
tracking
Introduction
The response of musculoskeletal tissues such as ligaments and
tendons to loading characterizes the tissue and elucidates its me-
chanical environment. Such data are essential to advance muscu-
loskeletal tissue engineering, to gain insight into injury
mechanisms, and to design and evaluate treatment options that
optimize healing. Strain behavior is one way to evaluate tissue
such as rotator cuff tendons [1]; not only can altered strain behav-
ior identify abnormal (i.e., partially torn) regions [2], but it can
also indicate regions susceptible to tear propagation [3,4].
The importance of strain behavior in pathologies such as tears
of rotator cuff tendons has led to a number of ex vivo investiga-
tions; many of these utilize optical strain tracking methods using
surface markers [1,46]. Others have used invasive methods such
as intra-operative transducer implantation [7].
Image-based strain measurements hold promise for measuring
strains in vivo, and thus transitioning more easily to clinical appli-
cations. A digital image pixel tracking algorithm digital image
correlation (DIC), originally developed for displacement field
evaluation of optically captured images, has become a popular
method for evaluating strain [811]. DIC has been used in the past
to study strain in biological soft tissues such as sheep bone callus
[12], human tympanic membrane [13] and stapedial tendon [14],
bovine cornea [15], mouse carotid arteries [16], and a human soft
tissue phantom [17]. As an optical registration algorithm, DIC
enables noncontact measurement of strain on material surfaces.
Strain can be tracked using features inherent in the tissue [18];
however, this can be technically challenging in soft tissues
because of the uniform white appearance of the collagen fibers in
normal light [19], and tracking thus often requires the use of opti-
cal markers [20]. Polarized light imaging has been used to gener-
ate texture on tendons to allow DIC strain measurement [21].
Ultrasound is commonly used to image tissues in the body,
including musculoskeletal tissues. Researchers have used land-
marks such as bony markers to measure the deformation of such tis-
sues to estimate strain response to load [2225]; however, tracking
of the texture of the ultrasound image itself would allow more free-
dom in locations as well as the ability to compare relative strain dis-
tributions in a tissue. Such feature tracking is reported for in vivo
cardiac ultrasound [26,27], but not tendon tissue.
The goal of this study is to demonstrate the efficacy of using
DIC to calculate strains directly from the texture present in clini-
cal B-mode ultrasound images by comparing strains measured
using this technique with strains measured using optical surface
markers (using DIC and manual tracking methods).
Methods
Animal Preparation. This study was approved by the Univer-
sity of Wisconsin Institutional Animal Use and Care Committee.
Eight skeletally mature male Wistar rats (weight 275 299 g)
were used in this study. Rats were anesthetized with isoflourane
immediately prior to euthanasia by overdose injection of sodium-
pentobarbital (150 mg/kg). Rats were stored at 80
C until time
of testing. Achilles tendons were dissected and surrounding tissue
excised with care to keep the calcaneal insertion site intact. Ten-
dons were kept hydrated using phosphate-buffered saline (PBS) at
all times during dissection.
Mechanical Testing. Tendons were tested in a custom-
designed load frame that held and loaded tendons along the
1
Corresponding author.
Contributed by the Bioengineering Division of ASME for publication in the
J
OURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received January 31, 2012;
final manuscript received February 1, 2012; accepted manuscript posted February
21, 2012; published online March 14, 2012. Editor: Michael Sacks.
Journal of Biomechanical Engineering FEBRUARY 2012, Vol. 134 / 024504-1Copyright
V
C
2012 by ASME
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longitudinal axis of the tissue. The calcaneus was trimmed and
press-fit into a custom bone grip. The soft tissue end was fixed
with adhesive (super glue gel; Ace Hardware Corporation, Oak
Brook, Illinois) to strips of Tyvek (McMaster-Carr, Elmhurst, Illi-
nois), which were held between two plates of the soft-tissue grip.
Tendons were immersed in a PBS bath during testing to prevent
dehydration and facilitate ultrasound wave propagation from
transducer to tissue. Graphite-impregnated silicone markers were
placed on the surface of the tendon to serve as optical markers for
strain measurement, with one marker on the calcaneal insertion
site and another at the soft tissue grip for overall displacement
measurement.
Mechanical testing was performed at room temperature. A pre-
load of 0.1 N was applied to obtain a uniform zero point [28], and
tendon length was measured using digital calipers. Tendons were
then preconditioned (20 cycles at 0.5 Hz) to 0.5%. Following a
10-min rest period (to allow for viscoelastic recovery), cyclic test-
ing between 0 and 1% strain was performed. During testing, force
and displacement information from the test frame was recorded
while a camera (Sony 3CCD color video camera; Sony Corpora-
tion, Tokyo, Japan) simultaneously recorded the marker move-
ments. This process was repeated twice (with a 10-min rest
between tests to allow for viscoelastic recovery) before repeating
the procedure, while substituting an ultrasound transducer
(12L-RS linear probe, connected to GE Logiq e portable ultra-
sound system; General Electric Healthcare, Milwaukee, Wiscon-
sin) for the camera during the two subsequent tests. Cyclic testing
was, therefore, performed four times to accommodate strain calcu-
lation using both optical video and dynamic ultrasound.
ImageJ Tracking. ImageJ (National Institutes of Health) was
used to measure the distance between markers in the first recorded
frame (l
0
) and in each subsequent frame during loading (l) from
the optical images by converting the images to black and white,
determining the centroid coordinates of the markers, and calculat-
ing the length of the vector connecting the centroids. The optical
strain for the tendon substance was computed as:
e ¼
l l
0
ðÞ
l
0
(1)
Digital Image Correlation Tracking of Optical Images. A
custom
MATLAB (The MathWorks Inc., Natick, Massachusetts)
algorithm utilizing the DIC method measured the initial location
of the silicone markers and tracked the location of the markers in
subsequent frames by minimizing the feature difference of
selected data sets describing the pixel intensity of a “disk” of pix-
els (radius ¼ 5 pixels, centered around the initial selected pixel) in
different frames using the relationship:
Correlation ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
R
i
R
j
AðX
i
; Y
j
ÞBðX
i
; Y
j
Þ
hi
2
r
(2)
Supposing that arrays A and B are corresponding subsets in two
digital images, and coordinates ðX
i
; Y
j
Þ and ðX
i
; Y
j
Þ are related by
the deformation that occurs between two images, then AðX
i
; Y
j
Þ,
BðX
i
; Y
j
Þ are the individual intensity of point ðX
i
; Y
j
Þ and ðX
i
; Y
j
Þ
in each subset. Assuming small subsets from the intensity pattern
stored in array B are related to small subsets of the same size in
array A by a homogeneous linear mapping, the correlation is the
square root of the sum of the squared intensity difference between
corresponding pixels. DIC relates the corresponding pixels
ðX
i
; Y
j
Þ and ðX
i
; Y
j
Þ by optimizing (minimizing) the correlation
value. The distance between points in each frame (l) was auto-
matically calculated using the pixel coordinates to measure, and
strain was calculated using Eq. (1).
Digital Image Correlation Tracking of Ultrasound
Images. An algorithm utilizing the DIC method measured and
tracked the distance between two pixels selected at each end of
the tendon of the initial frame. The pixels were selected to corre-
spond to the location of the silicone markers in the optical videos.
DIC displacement and strain measurements were calculated by
the method previously described.
Results
All imaging modalities were able to measure tendon strain dur-
ing cyclic testing. Strain calculated by methods using tracked sur-
face markers (both with ImageJ and DIC) from a representative
specimen is plotted in Fig. 1. The correlation between ImageJ-
based and DIC (optical marker)-based strain values for all eight
tendons with a 95% confidence interval is shown in Fig. 2; the
mean intercept and slope of the linear correlation were 0.000 and
0.970, respectively. Strain values calculated using the same
markers were not significantly different between DIC and manual
tracking methods (p ¼ 0.9113).
Strain calculated by methods using DIC, utilizing surface
markers and ultrasound texture, from a representative specimen is
plotted in Fig. 3. The correlation between DIC (optical marker)-
based and DIC (ultrasound texture)-based strain values for all
eight tendons with a 95% confidence interval is shown in Fig. 4;
the mean intercept and slope of the linear correlation were 0.000
and 1.003, respectively. A summary of the results of both correla-
tions with 95% confidence intervals can be found in Table 1.
Discussion
In this study, we demonstrate in a uniformly loaded tendon that
strain values calculated using DIC methods are not significantly
different than those calculated using standard manual tracking
methods when tracking the same surface markers (p ¼ 0.9113),
and that DIC tracking is as accurate when tracking ultrasound tex-
ture from longitudinal sections as when tracking optical surface
markers (R
2
¼ 0.803), thus demonstrating the efficacy of using
Fig. 1 Optical tracking results using ImageJ (open squares)
and DIC (open circles). There is a strong correlation between
values computed using manual (ImageJ) and DIC tracking of
optical videos (R
2
value of 0.955). Such a strong correlation
demonstrates the ability of DIC to track and calculate strain
measurements on optical videos of tissues as accurately as
manual methods. These findings were similar in the eight ten-
dons that were tracked; correlation shown in Fig. 2.
024504-2 / Vol. 134, FEBRUARY 2012 Transactions of the ASME
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DIC to calculate strains directly from the texture present in clini-
cal B-mode ultrasound images of tendons or ligaments.
Outside of cardiac applications, many in vivo ultrasound strain
estimates have relied on measuring distances between bony
markers or other landmarks [2225]. Other in vitro studies have
used DIC methods in conjunction with fluorescent-labeled cells
[29] or texture from static magnetoresistance magnetic resonance
(MR) images (un-deformed and deformed) to measure tissue
strain [30]. Fluorescent cell tracking is not available in the clinical
setting, and MR as an imaging modality has several inherent limi-
tations when compared to ultrasound including increased expense,
decreased portability, and lengthy image-acquisition time.
This study only examined controlled, uniform deformation in
an in vitro setting. Full validation of the use of DIC in clinical
applications will require tracking strain in the more difficult
in vivo environment, including images captured through other tis-
sues during nonuniform deformation.
Tracking strain from ultrasound image texture allows for direct
in vivo measurement of strain using ultrasound images without
requiring additional markers, either artificially placed (for optical
tracking) or anatomically in view (i.e. bony landmarks and/or
muscle-tendon junctions), for calculations. Thus, on-tissue strain,
and potentially strain in different regions, can be measured. These
strain measurements are particularly valuable in the assessment of
different tendon pathologies such as rotator cuff tears and tendino-
pathies in various locations, leading to better understanding and
management of such injuries.
Acknowledgment
Support by the National Science Foundation (award 0553016)
and National Institutes of Health (award R21 EB 008548) is grate-
fully acknowledged. The authors thank Ron McCabe for his tech-
nical assistance.
References
[1] Mazzocca, A. D., Rincon, L. M., O’Connor, R. W., Obopilwe, E., Andersen,
M., Geaney, L., and Arciero, R. A., 2008, “Intra-Articular Partial-Thickness
Rotator Cuff Tears,”Am. J. Sports Med., 36(1), pp. 110–116.
[2] Reilly, P., Amis, A. A., Wallace, A. L., and Emery, R. J. H., 2003,
“Supraspinatus Tears: Propagation and Strain Alteration,” J. Shoulder Elbow
Surg., 12(2), pp. 134–138.
[3] Matava, M. J., Purcell, D. B., and Rudzki, J. R., 2005, “Partial-Thickness Rota-
tor Cuff Tears,” Am. J. Sports Med., 33(9), pp. 1405–1417.
[4] Andarawis-Puri, N., Ricchetti, E. T., and Soslowsky, L. J., 2009, “Rotator Cuff
Tendon Strain Correlates With Tear Propagation,” J. Biomech., 42(2), pp.
158–163.
[5] Huang, C.-Y., Wang, V. M., Pawluk, R. J., Bucchieri, J. S., Levine, W. N.,
Bigliani, L. U., Mow, V. C., and Flatow, E. L., 2005, “Inhomogeneous Mechan-
ical Behavior of the Human Supraspinatus Tendon Under Uniaxial Loading,”
J. Orthop. Res., 23(4), pp. 924–930.
Fig. 2 Linear correlation between strain values calculated
manually (using ImageJ) and using DIC tracking methods, plot-
ted with a 95% confidence interval. A strong correlation is
shown, with mean intercept and slope of the eight tendons of
0.000 and 0.970, respectively.
Fig. 3 DIC tracking results using optical video with markers
and ultrasound videos demonstrating correlation (R
2
value of
0.803). These findings were similar in all tested tendons. Such
strong correlation demonstrates the ability of DIC to track and
calculate strain measurements on ultrasound videos (using
only tissue texture) as accurately as when using optical marker
methods. Linear correlation is shown in Fig. 4.
Fig. 4 Linear correlation between strain values calculated by
DIC tracking of tendons using optical and ultrasound videos,
plotted. The mean intercept and slope of the six tendons ana-
lyzed were 0.000 and 1.003, respectively.
Table 1 Mean statistical parameters obtained in confidence
intervals (95%) from strain result comparisons of manual
(ImageJ) vs. DIC using optical markers, as well as DIC using op-
tical markers vs. DIC using ultrasound images
Confidence intervals (95%)
Means/averages Optical: ImageJ vs. DIC
DIC: Optical vs.
ultrasound
Offset error/intercept 0.000 0.000
Slope 0.970 1.003
Range of slope 0.051 0.270
R
2
0.932 0.700
Journal of Biomechanical Engineering FEBRUARY 2012, Vol. 134 / 024504-3
Downloaded From: http://biomechanical.asmedigitalcollection.asme.org/ on 04/25/2013 Terms of Use: http://asme.org/terms
[6] Itoi, E., Berglund, L. J., Grabowski, J. J., Schultz, F. M., Growney, E. S., Mor-
rey, B. F., and An, K.-N., 1995, “Tensile Properties of the Supraspinatus
Tendon,” J. Orthop. Res., 13(4), pp. 578–584.
[7] Reilly, P., Bull, A. M. J., Amis, A. S., Wallace, A. L., Richards, A., Hill, A. M.,
and Emery, R. J. H., 2004, “Passive Tension and Gap Formation of Rotator
Cuff Repairs,” J. Shoulder Elbow Surg., 13(6), pp. 664–667.
[8] Sutton, M., Wolters, W., Peters, W., Ranson, W., and McNeill, S., 1983,
“Determination of Displacements Using an Improved Digital Correlation Meth-
od,” Image Vision Comput., 1(3), pp. 133–139.
[9] Sutton, M., Mingqi, C., Peters, W., Chao, Y., and McNeill, S., 1986,
“Application of an Optimized Digital Correlation Method to Planar Deforma-
tion Analysis,” Image Vision Comput., 4(3), pp. 143–150.
[10] Siegel, S., and Castellan, N. J., Jr., 1988, Nonparametric Statistics for the Be-
havioral Scien ces , 2nd ed., McGraw-Hill Book Company, New York.
[11] Bruck, H. A., McNeill, S. R., Sutton, M. A., and Peters, W. H., 1989, “Digital
Image Correlation Using Newton-Raphson Method of Partial Differential
Correction,” Exp. Mech., 29, pp. 261–267.
[12] Thompson, M. S., Schell, H., Lienau, J., and Duda, G. N., 2007,
“Digital Image Correlation: A Technique for Determining Local Mechanical
Conditions Within Early Bone Callus,” Med. Eng. Phys., 29(7), pp.
820–823.
[13] Cheng, T., Dai, C., and Gan, R. Z., 2006, “Viscoelastic Properties of Human
Tympanic Membrane,” Ann. Biomed. Eng., 35, pp. 305–314.
[14] Cheng, T., and Gan, R. Z., 2007, “Mechanical Properties of Stapedial Tendon
in Human Middle Ear,” J. Biomech. Eng., 129(6), pp. 913–918.
[15] Boyce, B. L., Grazier, J. M., Jones, R. E., and Nguyen, T. D., 2008, “Full-Field
Deformation of Bovine Cornea Under Constrained Inflation Conditions,” Bio-
materials, 29(28), pp. 3896–3904.
[16] Sutton, M. A., Ke, X., Lessner, S. M., Goldbach, M., Yost, M., Zhao, F., and
Schreier, H. W., 2008, “Strain Field Measurements on Mouse Carotid Arteries
Using Microscopic Three-Dimensional Digital Image Correlation,” J. Biomed.
Mater. Res. Part A, 84(1), pp. 178–190.
[17] Moerman, K. M., Holt, C. A., Evans, S. L., and Simms, C. K., 2009, “Digital
Image Correlation and Finite Element Modelling as a Method to Determine Me-
chanical Properties of Human Soft Tissue In Vivo,” J. Biomech., 42(8), pp.
1150–1153.
[18] Bay, B. K., 1995, “Texture Correlation: A Method for the Measurement of
Detailed Strain Distributions Within Trabecular Bone,” J. Orthop. Res., 13(2),
pp. 258–267.
[19] Doehring, T. C., Kahelin, M., and Vesely, I., 2009, “Direct Measurement of
Nonuniform Large Deformations in Soft Tissues During Uniaxial Extension,”
J. Biomech. Eng., 131(6), p. 061001.
[20] Guan, E., Smilow, S., Rafailovich, M., and Sokolov, J., 2004, “Determining the
Mechanical Properties of Rat Skin With Digital Image Speckle Correlation,”
Dermatology, 208(2), pp. 112–119.
[21] Komolafe, O. A., and Doehring, T. C., 2010, “Fascicle-Scale Loading and Fail-
ure Behavior of the Achilles Tendon,” J. Biomech. Eng., 132(2), p. 021004.
[22] Farron, J., Varghese, T., and Thelen, D. G., 2009, “Measurement of Tendon
Strain During Muscle Twitch Contractions Using Ultrasound Elastography,”
IEEE Trans. Ultrason., Ferroelectr. Freq. Control, 56(1), pp. 27–35.
[23] Maganaris, C., 2005, “Validity of Procedures Involved in Ultrasound-Based
Measurement of Human Plantarflexor Tendon Elongation on Contraction,”
J. Biomech., 38(1), pp. 9–13.
[24] Maganaris, C., 2002, “Tensile Properties of In Vivo Human Tendinous Tissue,”
J. Biomech., 35(8), pp. 1019–1027.
[25] Onambe´le´, G. N. L., Burgess, K., and Pearson, S. J., 2007, “Gender-Specific
In Vivo Measurement of the Structural and Mechanical Properties of the
Human Patellar Tendon,” J. Orthop. Res. 25(12), pp. 1635–1642.
[26] Stefani, L., Toncelli, L., Gianassi, M., Manetti, P., Di Tante, V., Vono, M. R. C.,
Moretti, A., Cappelli, B., Pedrizzetti, G., and Galanti, G., 2007, “Two-
Dimensional Tracking and TDI Are Consistent Methods for Evaluating Myocar-
dial Longitudinal Peak Strain in Left and Right Ventricle Basal Segments in
Athletes,” Cardiovasc. Ultrasound, 5(1). Available at http://dx.doi.org/10.1186/
1476-7120-5-7.
[27] Notomi, Y., Lysyansky, P., Setser, R. M., Shiota, T., Popovic´, Z. B., Martin-
Miklovic, M., G., Weaver, J. A., Oryszak, S. J., Greenberg, N. L., White, R. D.,
and Thomas, J. D., 2005, “Measurement of Ventricular Torsion by Two-
Dimensional Ultrasound Speckle Tracking Imaging,” J. Am. Coll. Cardiol.,
45(12), pp. 2034–2041.
[28] Provenzano, P., Lakes, R., Keenan, T., and Vanderby, R., Jr., 2001, “Nonlinear
Ligament Viscoelasticity,” Ann. Biomed. Eng. 29(10), pp. 908–914.
[29] Wang, C. C.-B., Deng, J.-M., Ateshian, G. A., and Hung, C. T., 2002, “An
Automated Approach for Direct Measurement of Two-Dimensional Strain Dis-
tributions Within Articular Cartilage Under Unconfined Compression,” J. Bio-
mech. Eng., 124(5), pp. 557–567.
[30] Gilchrist, C. L., Xia, J. Q., Setton, L. A., and Hsu, E. W., 2004, “High-Resolu-
tion Determination of Soft Tissue Deformations Using MRI and First-Order
Texture Correlation,” IEEE Trans. Med. Imaging, 23(5), pp. 546–553.
024504-4 / Vol. 134, FEBRUARY 2012 Transactions of the ASME
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    • "To monitor engineered muscle tissue growth we recently proposed [8] the application of Digital Image Correlation (DIC) in combination with standard force measurement. DIC is a versatile methodology deriving from industrial and civil engineering [9, 10] that presents several advantages also for applications with biological tissues [11][12][13], such as the absence of contact with the specimen, the possibility to use the natural texture as the correlation pattern, and the opportunity to measure strains on a specific region of interest (ROI). The use of this technique allowed pinpointing the tissue nonhomogeneous zones, returning useful information for improving the tissue generation process. "
    [Show abstract] [Hide abstract] ABSTRACT: Tissue engineering is a multidisciplinary science based on the application of engineering approaches to biologic tissue formation. Engineered tissue internal organization represents a key aspect to increase biofunctionality before transplant and, as regarding skeletal muscles, the potential of generating contractile forces is dependent on the internal fiber organization and is reflected by some macroscopic parameters, such as the spontaneous contraction. Here we propose the application of digital image correlation (DIC) as an independent tool for an accurate and noninvasive measurement of engineered muscle tissue spontaneous contraction. To validate the proposed technique we referred to the X-MET, a promising 3-dimensional model of skeletal muscle. The images acquired through a high speed camera were correlated with a custom-made algorithm and the longitudinal strain predictions were employed for measuring the spontaneous contraction. The spontaneous contraction reference values were obtained by studying the force response. The relative error between the spontaneous contraction frequencies computed in both ways was always lower than 0.15%. In conclusion, the use of a DIC based system allows for an accurate and noninvasive measurement of biological tissues’ spontaneous contraction, in addition to the measurement of tissue strain field on any desired region of interest during electrical stimulation.
    Full-text · Article · Mar 2016
    • "DIC was applied to ultrasound breast images to identify cancerous tissue, based on its deformation and stiffness (Han et al. 2012). DIC with ultrasound images has also been used to measure in vivo deformation in tendons (Okotie et al. 2012) and lower limb muscles (Affagard et al. 2014). "
    [Show abstract] [Hide abstract] ABSTRACT: This paper offers an overview of the potentialities and limitations of digital image correlation (DIC) as a technique for measuring displacements and strain in biomechanical applications. This review is mainly intended for biomechanists who are not yet familiar with DIC. This review includes over 150 papers and covers different dimensional scales, from the microscopic level (tissue level) up to macroscopic one (organ level). As DIC involves a high degree of computation, and of operator-dependent decisions, reliability of displacement and strain measurements by means of DIC cannot be taken for granted. Methodological problems and existing solutions are summarized and compared, whilst open issues are addressed. Topics addressed include: preparation methods for the speckle pattern on different tissues; software settings; systematic and random error associated with DIC measurement. Applications to hard and soft tissues at different dimensional scales are described and analyzed in terms of strengths and limitations. The potentialities and limitations of DIC are highlighted, also in comparison with other experimental techniques (strain gauges, other optical techniques, digital volume correlation) and numerical methods (finite element analysis), where synergies and complementarities are discussed. In order to provide an overview accessible to different scientists working in the field of biomechanics, this paper intentionally does not report details of the algorithms and codes used in the different studies.
    Full-text · Article · Dec 2015
    • "As ultrasound is frequently used to image musculoskeletal tissue, this technique allows in vivo strain measurement. Several authors showed an excellent correlation between classic 2D DIC measurements and 2D ultrasound elastography [19,20,32]. "
    [Show abstract] [Hide abstract] ABSTRACT: Background Determining the mechanical behaviour of tendon and ligamentous tissue remains challenging, as it is anisotropic, non-linear and inhomogeneous in nature. Methods In this study, three-dimensional (3D) digital image correlation (DIC) was adopted to examine the strain distribution in the human Achilles tendon. Therefore, 6 fresh frozen human Achilles tendon specimens were mounted in a custom made rig for uni-axial loading. 3D DIC measurements of each loading position were obtained and compared to 2 linear variable differential transformers (LVDT’s). Results 3D DIC was able to calculate tendon strain in every region of all obtained images. The scatter was found to be low in all specimens and comparable to that obtained in steel applications. The accuracy of the 3D DIC measurement was higher in the centre of the specimen where scatter values around 0.03% strain were obtained. The overall scatter remained below 0.3% in all specimens. The spatial resolution of 3D DIC on human tendon tissue was found to be 0.1 mm2. The correlation coefficient between the 3D DIC measurements and the LVDT measurements showed an excellent linear agreement in all specimens (R2 = 0.99). Apart from the longitudinal strain component, an important transverse strain component was revealed in all specimens. The strain distribution of both components was of a strongly inhomogeneous nature, both within the same specimen and amongst different specimens. Conclusion DIC proved to be a very accurate and reproducible tool for 3D strain analysis in human tendon tissue.
    Full-text · Article · Jun 2014
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