Name: viscoelastic characterization of soft tissue-mimicking gelatin phantoms using indentation and magnetic resonance elastography
Uploaded: 2022-05-10T15:00:00.000+00:00
Duration: 7 min 57 s
Description: Watch this Scientific Journal Video about Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography at JoVE.com

Funding support from the National Natural Science Foundation of China (grant 31870941), Natural Science Foundation of Shanghai (grant 22ZR1429600), and the Science and Technology Commission of Shanghai Municipality (grant 19441907700) is acknowledged.

1. Gelatin phantom preparation
<ol>
	<li>Weigh gelatin, glycerol, and water according to Table 1. Mix the gelatin powder with water to obtain the gelatin solution. 
	NOTE: The concentrations of the individual components for preparing the two phantoms are shown in Table 1. The higher the concentration of gelatin, the stiffer the phantom.</li>
	<li>Heat the gelatin solution to 60 &#176;C in a water bath. Add glycerol to the gelatin solution while maintaining the temperature. 
	NOTE: Glycerol stabilizes gelatin mixtures by increasing their melting temperature and shear modulus17.</li>
	<li>Stir the solution and heat it to 60 &#176;C again. Pour the mixed solution into a container that will be used for MRE and indentation tests. Cool the solution to room temperature and wait till the solution is solidified.</li>
</ol>
2. MRE test
<ol>
	<li>Put the vibration plate on top of the gelatin phantom. Ensure that the contact between the phantom and the vibration plate is firm (Figure 1A). 
	NOTE: The vibration plate is made of Polyamide with a dimension of 50 x 50 x 5 mm3.</li>
	<li>Place the gelatin phantom into the head coil. Put sponges and sandbags around the gelatin phantom to make sure the phantom is firmly placed. Use a custom-built electromagnetic actuator with a transmission bar14,18. Mount an electromagnetic actuator on the head coil. Connect the transmission bar to the vibration plate (Figure 1B).</li>
	<li>Connect the power lines of the actuator with the amplifier. Connect the control lines with the controller (Figure 1C).</li>
	<li>Actuator and MRI scan parameter settings
	<ol>
		<li>Set the waveform, vibration frequency, and amplitude in the function generator. Set the desired vibration amplitude by adjusting the power amplifier. 
		NOTE: Here, the waveform is set to sinusoidal in the function generator; the vibration frequency is set to 40 Hz or 50 Hz, and the amplitude is set to 1.5 Vpp. In the power amplifier, the amplification ratio is set to 40%.</li>
		<li>Set the function generator to work in the trigger mode. Connect the trigger line to the external trigger port of the MRI machine.</li>
		<li>Set the MRE scanning (actuator) frequency the same as that from the function generator, so that the motion encoding gradient is synchronized with the motion of the vibration plate.</li>
	</ol>
	</li>
	<li>Data measurement and analysis
	<ol>
		<li>Follow the routine imaging positioning procedures. Use a 2D gradient-echo (GRE) based MRE sequence for imaging of the gelatin phantom20. Set the GRE-MRE imaging parameters as follows: Flip-angle = 30&#176;; TR/TE = 50/31 ms; Field-of-view = 300 mm; Slice thickness = 5 mm; Voxel size = 2.34 x 2.34 mm2.</li>
		<li>Measure the phase images at four temporal points in one sinusoidal cycle. Apply both positive and negative motion encoding gradients at each time point.</li>
		<li>Based on the phase image acquired, remove the background phase by subtracting the positive and negative encoded phase images. Unwrap the phase with a reliability sorting-based algorithm21.</li>
		<li>Extract the principal component of the motion by applying fast Fourier Transform to the unwrapped phase images. Filter the phase image with a digital bandpass filter. Estimate the shear modulus with a 2D direct inversion (DI) algorithm to obtain storage modulus G&#39; and loss modulus G&#39;&#39;13,14. 
		&#8203;NOTE: The cut-off frequency of the bandpass filter is [0.04 0.08]. The size of the fitting window of the DI algorithm is 11 x 11.</li>
	</ol>
	</li>
</ol>
3. Indentation test
<ol>
	<li>Use a circular punch or surgical blade to trim the gelatin phantom into a cylindrical or cuboid sample, respectively. Make sure that the sample thickness is between 3 and 10 mm and the diameter of the cylindrical sample or the long side of the cuboid is larger than 4 mm. Use a sharp blade to trim the surface of the sample to make it as smooth as possible for indentation.</li>
	<li>Turn on the power of the indentation tester. Perform the following using the indenter control program designed to automate the indenter contact procedure (custom program; see Table of Materials).
	<ol>
		<li>Click on the Back off button in the GUI to initialize the calibration process (Figure 2B). Read the value from the laser sensor and type the value in the BaseLine box. 
		NOTE: During the calibration process, the distance between the laser sensor and the baffle plate is adjusted to a specific pre-defined value.</li>
		<li>Place a glass slide on the baffle plate and record the value shown by the laser sensor. Next, put the sample on the glass slide and place them together on the baffle plate. Read the value from the laser sensor and type this value in the Sample+Slide box. 
		NOTE: The laser sensor is used to record the displacement of the indentation, but it is also used to measure the sample thickness before the test.</li>
		<li>Take the difference between the two values obtained in step 3.2.2 as the sample thickness at the region of interest (ROI).</li>
		<li>Carefully place the sample along with the underlying glass slide right below the indenter, and then click on the Contact button to initiate automatic contact between the indenter and the sample surface. 
		NOTE: If the automatic contact is not satisfactory, i.e., the indenter presses deep into the sample or does not have a contact, adjust the indenter position by typing a value in the range of 0.05-0.1 mm in the Offset box and repeat steps 1.2.1-1.2.4.</li>
		<li>Based on the measured sample thickness (step 3.2.3), estimate the indentation displacement (i.e., total indentation depth) by multiplying the thickness with the indented testing strain (here, it is set to &#8804;8% to keep the indentation within the small strain assumption).</li>
		<li>Type the displacement values (step 3.2.5) in the Displacement (mm) box. Set the relaxation time to 180 s in the Dwell Time box. Click on the Indentation button. The displacement and reactive force during the ramp-hold procedure will be automatically recorded and saved in a file at the specified File Path. 
		NOTE: The File Path can be pre-defined as the path for saving testing data.</li>
	</ol>
	</li>
	<li>Export the indentation data to a spreadsheet. Use a two-term Prony series <img alt="Equation 1" src="/files/ftp_upload/63770/63770eq01.jpg" style="margin: auto;" /> to fit the force relaxation curve1,3,11: 
	<img alt="Equation 2" src="/files/ftp_upload/63770/63770eq02.jpg" style="margin: auto;" /></li>
	<li>Estimate the instantaneous shear modulus (G0) and long-term shear modulus (G&#8734;) based on the fitted parameters: 
	<img alt="Equation 3" src="/files/ftp_upload/63770/63770eq03.jpg" style="margin: auto;" /> 
	NOTE: In the above equations, C0, Ci, and &#964;i are model parameters of the Prony series, F is the indentation force, R is the radius of the indenter, X is the compensation factor for the infinite half space assumption, V is the indentation velocity, t is the time variable, and tR is the ramp time.</li>
</ol>

<ol>
	<li>Qiu, S., 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=Viscoelastic+characterization+of+injured+brain+tissue+after+controlled+cortical+impact+(CCI)+using+a+mouse+model.">Viscoelastic characterization of injured brain tissue after controlled cortical impact (CCI) using a mouse model.</a> Journal of Neuroscience Methods. 330, 108463 (2020).</li><li>Garcia, K. E., 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=Dynamic+patterns+of+cortical+expansion+during+folding+of+the+preterm+human+brain.">Dynamic patterns of cortical expansion during folding of the preterm human brain.</a> Proceedings of the National Academy of Sciences of the United States of America. 115 (12), 3156-3161 (2018).</li><li>Qiu, S., 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=Characterizing+viscoelastic+properties+of+breast+cancer+tissue+in+a+mouse+model+using+indentation.">Characterizing viscoelastic properties of breast cancer tissue in a mouse model using indentation.</a> Journal of Biomechanics. 69, 81-89 (2018).</li><li>Yin, Z., 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=A+new+method+for+quantification+and+3D+visualization+of+brain+tumor+adhesion+using+slip+interface+imaging+in+patients+with+meningiomas.">A new method for quantification and 3D visualization of brain tumor adhesion using slip interface imaging in patients with meningiomas.</a> European Radiology. 31 (8), 5554-5564 (2021).</li><li>Streitberger, K. -. 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=How+tissue+fluidity+influences+brain+tumor+progression.">How tissue fluidity influences brain tumor progression.</a> Proceedings of the National Academy of Sciences of the United States of America. 117 (1), 128 (2020).</li><li>Bunevicius, A., Schregel, K., Sinkus, R., Golby, A., Patz, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=REVIEW:+MR+elastography+of+brain+tumors.">REVIEW: MR elastography of brain tumors.</a> NeuroImage: Clinical. 25, 102109 (2020).</li><li>Namani, R., 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=Elastic+characterization+of+transversely+isotropic+soft+materials+by+dynamic+shear+and+asymmetric+indentation.">Elastic characterization of transversely isotropic soft materials by dynamic shear and asymmetric indentation.</a> Journal of Biomechanical Engineering. 134 (6), 061004 (2012).</li><li>Potter, S., 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=A+novel+small-specimen+planar+biaxial+testing+system+with+full+in-plane+deformation+control.">A novel small-specimen planar biaxial testing system with full in-plane deformation control.</a> Journal of Biomechanical Engineering. 140 (5), 0510011 (2018).</li><li>Zhang, W., Feng, Y., Lee, C. -. H., Billiar, K. L., Sacks, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+generalized+method+for+the+analysis+of+planar+biaxial+mechanical+data+using+tethered+testing+configurations.">A generalized method for the analysis of planar biaxial mechanical data using tethered testing configurations.</a> Journal of Biomechanical Engineering. 137 (6), 064501 (2015).</li><li>Delaine-Smith, R. M., Burney, S., Balkwill, F. R., Knight, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+validation+of+a+flat+punch+indentation+methodology+calibrated+against+unconfined+compression+tests+for+determination+of+soft+tissue+biomechanics.">Experimental validation of a flat punch indentation methodology calibrated against unconfined compression tests for determination of soft tissue biomechanics.</a> Journal of the Mechanical Behavior of Biomedical Materials. 60, 401-415 (2016).</li><li>Chen, Y., 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=Comparative+analysis+of+indentation+and+magnetic+resonance+elastography+for+measuring+viscoelastic+properties.">Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties.</a> Acta Mechanica Sinica. 37 (3), 527-536 (2021).</li><li>Garteiser, P., Doblas, S., Van Beers, B. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Magnetic+resonance+elastography+of+liver+and+spleen:+Methods+and+applications.">Magnetic resonance elastography of liver and spleen: Methods and applications.</a> NMR in Biomedicine. 31 (10), 3891 (2018).</li><li>Arani, A., Manduca, A., Ehman, R. L., Huston Iii, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Harnessing+brain+waves:+a+review+of+brain+magnetic+resonance+elastography+for+clinicians+and+scientists+entering+the+field.">Harnessing brain waves: a review of brain magnetic resonance elastography for clinicians and scientists entering the field.</a> British Journal of Radiolology. 94 (1119), 20200265 (2021).</li><li>Qiu, S., 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=An+electromagnetic+actuator+for+brain+magnetic+resonance+elastography+with+high+frequency+accuracy.">An electromagnetic actuator for brain magnetic resonance elastography with high frequency accuracy.</a> NMR in Biomedicine. 34 (12), 4592 (2021).</li><li>Hiscox, L. V., 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=Standard-space+atlas+of+the+viscoelastic+properties+of+the+human+brain.">Standard-space atlas of the viscoelastic properties of the human brain.</a> Human Brain Mapping. 41 (18), 5282-5300 (2020).</li><li>Seyedpour, S. M., 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=Application+of+magnetic+resonance+imaging+in+liver+biomechanics:+A+systematic+review.">Application of magnetic resonance imaging in liver biomechanics: A systematic review.</a> Frontiers in Physiology. 12, 733393 (2021).</li><li>Okamoto, R. J., Clayton, E. H., Bayly, P. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Viscoelastic+properties+of+soft+gels:+comparison+of+magnetic+resonance+elastography+and+dynamic+shear+testing+in+the+shear+wave+regime.">Viscoelastic properties of soft gels: comparison of magnetic resonance elastography and dynamic shear testing in the shear wave regime.</a> Physics in Medicine and Biology. 56 (19), 6379-6400 (2011).</li><li>Feng, Y., 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=A+multi-purpose+electromagnetic+actuator+for+magnetic+resonance+elastography.">A multi-purpose electromagnetic actuator for magnetic resonance elastography.</a> Magnetic Resonance Imaging. 51, 29-34 (2018).</li><li>Zeng, W., 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=Nonlinear+inversion+MR+elastography+with+low-frequency+actuation.">Nonlinear inversion MR elastography with low-frequency actuation.</a> IEEE Transactions on Medical Imaging. 39 (5), 1775-1784 (2020).</li><li>Wang, R., 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=Fast+magnetic+resonance+elastography+with+multiphase+radial+encoding+and+harmonic+motion+sparsity+based+reconstruction.">Fast magnetic resonance elastography with multiphase radial encoding and harmonic motion sparsity based reconstruction.</a> Physics in Medicine and Biology. 67 (2), (2022).</li><li>Herraez, M. A., Burton, D. R., Lalor, M. J., Gdeisat, 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=Fast+two-dimensional+phase-unwrapping+algorithm+based+on+sorting+by+reliability+following+a+noncontinuous+path.">Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path.</a> Applied Optics. 41 (35), 7437-7444 (2002).</li><li>Gordon-Wylie, S. W., 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=MR+elastography+at+1+of+gelatin+phantoms+using+3D+or+4D+acquisition.">MR elastography at 1 of gelatin phantoms using 3D or 4D acquisition.</a> Journal of Magnetic Resonance. 296, 112-120 (2018).</li><li>McGarry, M., 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=Uniqueness+of+poroelastic+and+viscoelastic+nonlinear+inversion+MR+elastography+at+low+frequencies.">Uniqueness of poroelastic and viscoelastic nonlinear inversion MR elastography at low frequencies.</a> Physics in Medicine and Biology. 64 (7), 075006 (2019).</li><li>Zampini, M. A., Guidetti, M., Royston, T. J., Klatt, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+viscoelastic+parameters+in+Magnetic+Resonance+Elastography:+a+comparison+at+high+and+low+magnetic+field+intensity.">Measuring viscoelastic parameters in Magnetic Resonance Elastography: a comparison at high and low magnetic field intensity.</a> Journal of the Mechanical Behavior of Biomedical Materials. 120, 104587 (2021).</li><li>Ozkaya, E., 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=Brain-mimicking+phantom+for+biomechanical+validation+of+motion+sensitive+MR+imaging+techniques.">Brain-mimicking phantom for biomechanical validation of motion sensitive MR imaging techniques.</a> Journal of the Mechanical Behavior of Biomedical Materials. 122, 104680 (2021).</li><li>Guidetti, M., 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=Axially-+and+torsionally-polarized+radially+converging+shear+wave+MRE+in+an+anisotropic+phantom+made+via+Embedded+Direct+Ink+Writing.">Axially- and torsionally-polarized radially converging shear wave MRE in an anisotropic phantom made via Embedded Direct Ink Writing.</a> Journal of the Mechanical Behavior of Biomedical Materials. 119, 104483 (2021).</li><li>Badachhape, A. 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=The+relationship+of+three-dimensional+human+skull+motion+to+brain+tissue+deformation+in+magnetic+resonance+elastography+studies.">The relationship of three-dimensional human skull motion to brain tissue deformation in magnetic resonance elastography studies.</a> Journal of Biomechanical Engineering. 139 (5), 0510021 (2017).</li></ol>

Authors declare no conflicts of interest.

Gelatin phantoms are commonly used as tissue-mimicking materials for testing and validation of algorithms and devices17,19,22,23,24,25,26,27. One of the pioneering studies using the gelatin phantom to compare MRE and dynamic shear testing was presented by O...

Most of the soft biological tissues appear to have viscoelastic properties that are important to understand their injury and development1,2. In addition, viscoelastic properties are important biomarkers in the diagnosis of a variety of diseases such as fibrosis and cancer3,4,5,6. Therefore, the characterization of viscoelastic properties of soft tissues is crucial. Among the many characterization techniques used, ex vivo mechanical testing of tissue samples and in vivo elastography using biomedical imaging are the two widely used methods.
Although various mechanical testing techniques have been used for soft tissue characterization, the requirements for sample size and testing conditions are not easy to be satisfied. For example, shear testing needs to have samples fixed firmly between the shear plates7. Biaxial testing is more suitable for membrane tissue and has specific clamping requirements8,9. A compression test is commonly used for tissue testing, but cannot characterize specific positions within one sample10. The indentation test does not have additional requirements to fix the tissue sample and can be used to measure many biological tissue samples such as the brain and liver. In addition, with a small indenter head, regional properties within a sample could be tested. Therefore, indentation tests have been adopted to test a variety of soft tissues1,3,11.
Characterizing the biomechanical properties of soft tissues in vivo is important for translational studies and clinical applications of biomechanics. Biomedical imaging modalities such as ultrasound (US) and magnetic resonance (MR) imaging are the most used techniques. Although US imaging is relatively cheap and easy to carry out, it suffers from low contrast and is hard to measure organs such as the brain. Capable of imaging deep structures, MR Elastography (MRE) could measure a variety of soft tissues6,12, especially the brain13,14. With applied external vibration, MRE could measure the viscoelastic properties of soft tissues at a specific frequency.
Studies have shown that at 50-60 Hz, the shear modulus of the normal brain is ~1.5-2.5kPa5,6,13,14,15 and ~2-2.5 kPa for normal liver16. Therefore, gelatin phantoms that have similar biomechanical properties have been widely used for mimicking soft tissues for testing and validation17,18,19. In this protocol, gelatin phantoms with two different concentrations were prepared and tested. Viscoelastic properties of the gelatin phantoms were characterized using a custom-built electromagnetic MRE device14 and an indentation device1,3. The testing protocols could be used for testing many soft tissues such as the brain or liver.

<table><tbody><tr><td>24-channel head &amp;amp; Neck coil</td><td>United Imaging Healthcare</td><td>100120</td><td>Equipment</td></tr><tr><td>3T MR Scanner</td><td>United Imaging Healthcare</td><td>uMR 790</td><td>Equipment</td></tr><tr><td>Acquisition board</td><td>Advantech Co</td><td>PCI-1706U</td><td>Equipment</td></tr><tr><td>Computer-Windows</td><td>HP</td><td>790-07</td><td>Equipment</td></tr><tr><td>Electromagnetic actuator</td><td>Shanghai Jiao Tong University</td><td></td><td>Equipment</td></tr><tr><td>Function generator</td><td>RIGOL</td><td>DG1022Z</td><td>Equipment</td></tr><tr><td>Gelatin</td><td>CARTE D&amp;rsquo;OR</td><td></td><td>Reagent</td></tr><tr><td>Glycerol</td><td>Vance Bioenergy Sdn.Bhd</td><td></td><td>Reagent</td></tr><tr><td>Indenter control program</td><td>custom-designed</td><td></td><td>Software; accessed via: https://github.com/aaronfeng369/FengLab_indentation_code.</td></tr><tr><td>Laser sensor</td><td>Panasonic</td><td>HG-C1050</td><td>Equipment</td></tr><tr><td>Load cell</td><td>Transducer Technique</td><td>GSO-10</td><td>Equipment</td></tr><tr><td>MATLAB</td><td>Mathworks</td><td></td><td>Software</td></tr><tr><td>Power amplifier</td><td>Yamaha</td><td>A-S201</td><td>Equipment</td></tr><tr><td>Voice coil electric motor</td><td>SMAC Corporation</td><td>DB2583</td><td>Equipment</td></tr></tbody></table>

viscoelastic characterization of soft tissue-mimicking gelatin phantoms using indentation and magnetic resonance elastography

Characterization of biomechanical properties of soft biological tissues is important to understand the tissue mechanics and explore the biomechanics-related mechanisms of disease, injury, and development. The mechanical testing method is the most straightforward way for tissue characterization and is considered as verification for in vivo measurement. Among the many ex vivo mechanical testing techniques, the indentation test provides a reliable way, especially for samples that are small, hard to fix, and viscoelastic such as brain tissue. Magnetic resonance elastography (MRE) is a clinically used method to measure the biomechanical properties of soft tissues. Based on shear wave propagation in soft tissues recorded using MRE, viscoelastic properties of soft tissues can be estimated in vivo based on wave equation. Here, the viscoelastic properties of gelatin phantoms with two different concentrations were measured by MRE and indentation. The protocols of phantom fabrication, testing, and modulus estimation have been presented.

Following the MRE protocol, a clear shear wave propagation in the gelatin phantoms at 40 and 50 Hz were observed (Figure 3). The viscoelastic properties measured from MRE, and indentation tests are shown in Figure 4. The estimated G&#39; and G&#34; values at each testing for each phantom are summarized in Table 2. Following the indentation protocol, the viscoelastic properties of each phantom at each test point are summarized in Table 3<...

Watch this Scientific Journal Video about Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography at JoVE.com

Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography

This article presents a demonstration and summary of protocols of making gelatin phantoms that mimic soft tissues, and the corresponding viscoelastic characterization using indentation and magnetic resonance elastography.

Characterization of biomechanical properties of soft biological tissues is important to understand the tissue mechanics and explore the ...

viscoelastic-characterization-soft-tissue-mimicking-gelatin-phantoms

Universidad de Cartagena UDEC

Research

JoVE Journal

Bioengineering

2.0K Views.  Shanghai Jiao Tong University. This article presents a demonstration and summary of protocols of making gelatin phantoms that mimic soft tissues, and the corresponding viscoelastic characterization using indentation and magnetic resonance elastography.

Video: Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth

Traditional mechanical testing often results in the destruction of the sample, and in the case of long term tissue engineered construct studies, the use of destructive assessment is not acceptable. A proposed alternative is the use of an imaging process called magnetic resonance elastography. Elastography is a nondestructive method for determining the engineered outcome by measuring local mechanical property values (i.e., complex shear modulus), which are essential markers for identifying the structure and functionality of a tissue. As a noninvasive means for evaluation, the monitoring of engineered constructs with imaging modalities such as magnetic resonance imaging (MRI) has seen increasing interest in the past decade1. For example, the magnetic resonance (MR) techniques of diffusion and relaxometry have been able to characterize the changes in chemical and physical properties during engineered tissue development2. The method proposed in the following protocol uses microscopic magnetic resonance elastography (&mu;MRE) as a noninvasive MR based technique for measuring the mechanical properties of small soft tissues3. MRE is achieved by coupling a sonic mechanical actuator with the tissue of interest and recording the shear wave propagation with an MR scanner4. Recently, &mu;MRE has been applied in tissue engineering to acquire essential growth information that is traditionally measured using destructive mechanical macroscopic techniques5. In the following procedure, elastography is achieved through the imaging of engineered constructs with a modified Hahn spin-echo sequence coupled with a mechanical actuator. As shown in Figure 1, the modified sequence synchronizes image acquisition with the transmission of external shear waves; subsequently, the motion is sensitized through the use of oscillating bipolar pairs. Following collection of images with positive and negative motion sensitization, complex division of the data produce a shear wave image. Then, the image is assessed using an inversion algorithm to generate a shear stiffness map6. The resulting measurements at each voxel have been shown to strongly correlate (R2&gt;0.9914) with data collected using dynamic mechanical analysis7. In this study, elastography is integrated into the tissue development process for monitoring human mesenchymal stem cell (hMSC) differentiation into adipogenic and osteogenic constructs as shown in Figure 2.

The procedure demonstrates the methodology of magnetic resonance elastography for monitoring the engineered outcome of adipose and osteogenic tissue engineered constructs through noninvasive local assessment of the mechanical properties using microscopic magnetic resonance elastography (&mu;MRE).

Traditional mechanical testing often results in the destruction of the sample, and in the case of long term tissue engineered construct studies, the use ...

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(&#969;). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.

Particle-tracking microrheology can be used to non-destructively quantify and spatially map changes in extracellular matrix mechanical properties in 3D tumor models.

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and ...

Rapid and Non-Destructive Characterization of Biofilm Elastic Properties

Quantifying Elastic Properties of Environmental Biofilms using Optical Coherence Elastography

Biofilms are complex biomaterials comprising a well-organized network of microbial cells encased in self-produced extracellular polymeric substances (EPS). This paper presents a detailed account of the implementation of optical coherence elastography (OCE) measurements tailored for the elastic characterization of biofilms. OCE is a non-destructive optical technique that enables the local mapping of the microstructure, morphology, and viscoelastic properties of partially transparent soft materials with high spatial and temporal resolution. We provide a comprehensive guide detailing the essential procedures for the correct implementation of this technique, along with a methodology to estimate the bulk Young's modulus of granular biofilms from the collected measurements. These consist of the system setup, data acquisition, and postprocessing. In the discussion, we delve into the underlying physics of the sensors used in OCE and explore the fundamental limitations regarding the spatial and temporal scales of OCE measurements. We conclude with potential future directions for advancing the OCE technique to facilitate elastic measurements of environmental biofilms.

Author Spotlight: Characterizing Environmental Biofilm Mechanics Using Optical Coherence Elastography and its Applications in Wastewater Treatment

This paper highlights the optical coherence elastography (OCE) technique's efficacy in rapidly and non-destructively characterizing biofilm elastic properties. We elucidate critical OCE implementation procedures for accurate measurements and present Young's modulus values for two granular biofilms.

Biofilms are complex biomaterials comprising a well-organized network of microbial cells encased in self-produced extracellular polymeric substances ...

Environment

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing

Regenerative medicine aims to engineer materials to replace or restore damaged or diseased organs. The mechanical properties of such materials should mimic the human tissues they are aiming to replace; to provide the required anatomical shape, the materials must be able to sustain the mechanical forces they will experience when implanted at the defect site. Although the mechanical properties of tissue-engineered scaffolds are of great importance, many human tissues that undergo restoration with engineered materials have not been fully biomechanically characterized. Several compressive and tensile protocols are reported for evaluating materials, but with large variability it is difficult to compare results between studies. Further complicating the studies is the often destructive nature of mechanical testing. Whilst an understanding of tissue failure is important, it is also important to have knowledge of the elastic and viscoelastic properties under more physiological loading conditions.
This report aims to provide a minimally destructive protocol to evaluate the compressive and tensile properties of human soft tissues. As examples of this technique, the tensile testing of skin and the compressive testing of cartilage are described. These protocols can also be directly applied to synthetic materials to ensure that the mechanical properties are similar to the native tissue. Protocols to assess the mechanical properties of human native tissue will allow a benchmark by which to create suitable tissue-engineered substitutes.

Tissue biomechanics is important for maintaining cell shape and function and for determining phenotype. This report demonstrates non-destructive mechanical protocols for characterizing elastic and viscoelastic properties of human soft tissues, which can be directly applied to tissue-engineered substrates to allow a close matching of engineered materials to native tissue.

Regenerative medicine aims to engineer materials to replace or restore damaged or diseased organs. The mechanical properties of such materials should ...

Agarose-based Tissue Mimicking Optical Phantoms for Diffuse Reflectance Spectroscopy

This protocol describes how to make agarose-based tissue-mimicking phantoms and demonstrates how to determine their optical properties using a conventional optical system with an integrating sphere. Measuring systems for the acquisition of the diffuse reflectance and total transmittance spectra are constructed with a broadband white light source, a light guide, an achromatic lens, an integrating sphere, a sample holder, an optical fiber probe, and a multi-channel spectrometer. An acrylic mold consisting of two rectangular acrylic pieces and a U-shaped acrylic piece is constructed to create an epidermal phantom and a dermal phantom with whole blood. The application of a sodium dithionite (Na2S2O4) solution to the dermal phantom enables the researcher to deoxygenate hemoglobin in red blood cells distributed in the dermal phantom. The inverse Monte Carlo simulation with the diffuse reflectance and total transmittance spectra measured by a spectrometer with an integrating sphere is performed to determine the absorption coefficient spectrum &#181;a(&#955;) and the reduced scattering coefficient spectrum &#181;s&#39;(&#955;) of each layer phantom. A two-layered phantom mimicking the diffuse reflectance of human skin tissue is also demonstrated by piling up the epidermal phantom on the dermal phantom.

Here, we demonstrate how agarose-based tissue-mimicking optical phantoms are made and how their optical properties are determined using a conventional optical system with an integrating sphere.

This protocol describes how to make agarose-based tissue-mimicking phantoms and demonstrates how to determine their optical properties using a ...

Manufacturing Abdominal Aorta Hydrogel Tissue-Mimicking Phantoms for Ultrasound Elastography Validation

Ultrasound (US) elastography, or elasticity imaging, is an adjunct imaging technique that utilizes sequential US images of soft tissues to measure the tissue motion and infer or quantify the underlying biomechanical characteristics. For abdominal aortic aneurysms (AAA), biomechanical properties such as changes in the tissue's elastic modulus and estimates of the tissue stress may be essential for assessing the need for the surgical intervention. Abdominal aortic aneurysms US elastography could be a useful tool to monitor AAA progression and identify changes in biomechanical properties characteristic of high-risk patients.
A preliminary goal in the development of an AAA US elastography technique is the validation of the method using a physically relevant model with known material properties. Here we present a process for the production of AAA tissue-mimicking phantoms with physically relevant geometries and spatially modulated material properties. These tissue phantoms aim to mimic the US properties, material modulus, and geometry of the abdominal aortic aneurysms. Tissue phantoms are made using a polyvinyl alcohol cryogel (PVA-c) and molded using 3D printed parts created using computer aided design (CAD) software. The modulus of the phantoms is controlled by altering the concentration of PVA-c and by changing the number of freeze-thaw cycles used to polymerize the cryogel. The AAA phantoms are connected to a hemodynamic pump, designed to deform the phantoms with the physiologic cyclic pressure and flows. Ultra sound image sequences of the deforming phantoms allowed for the spatial calculation of the pressure normalized strain and the identification of mechanical properties of the vessel wall. Representative results of the pressure normalized strain are presented.

Here we describe a method to manufacture aneurysmal, aortic tissue-mimicking phantoms for the use in testing ultrasound elastography. The combined use of computer-aided design (CAD) and 3-dimensional (3D) printing techniques produce aortic phantoms with predictable, complex geometries to validate the elastographic imaging algorithms with controlled experiments.

Ultrasound (US) elastography, or elasticity imaging, is an adjunct imaging technique that utilizes sequential US images of soft tissues to measure the ...

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

To design and engineer materials inspired by the properties of the brain, whether for mechanical simulants or for tissue regeneration studies, the brain tissue itself must be well characterized at various length and time scales. Like many biological tissues, brain tissue exhibits a complex, hierarchical structure. However, in contrast to most other tissues, brain is of very low mechanical stiffness, with Young&#39;s elastic moduli E on the order of 100s of Pa. This low stiffness can present challenges to experimental characterization of key mechanical properties. Here, we demonstrate several mechanical characterization techniques that have been adapted to measure the elastic and viscoelastic properties of hydrated, compliant biological materials such as brain tissue, at different length scales and loading rates. At the microscale, we conduct creep-compliance and force relaxation experiments using atomic force microscope-enabled indentation. At the mesoscale, we perform impact indentation experiments using a pendulum-based instrumented indenter. At the macroscale, we conduct parallel plate rheometry to quantify the frequency dependent shear elastic moduli. We also discuss the challenges and limitations associated with each method. Together these techniques enable an in-depth mechanical characterization of brain tissue that can be used to better understand the structure of brain and to engineer bio-inspired materials.

We present a set of techniques to characterize the viscoelastic mechanical properties of brain at the micro-, meso-, and macro-scales.

To design and engineer materials inspired by the properties of the brain, whether for mechanical simulants or for tissue regeneration studies, the brain ...

Neuroscience

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Nanoindentation refers to a class of experimental techniques where a micrometric force probe is used to quantify the local mechanical properties of soft biomaterials and cells. This approach has gained a central role in the fields of mechanobiology, biomaterials design&#160;and tissue engineering, to obtain a proper mechanical characterization of soft materials with a resolution comparable to the size of single cells (&#956;m). The most popular strategy to acquire such experimental data is to employ an atomic force microscope (AFM); while this instrument offers an unprecedented resolution in force (down to pN) and space (sub-nm), its usability is often limited by its complexity that prevents routine measurements of integral indicators of mechanical properties, such as Young&#39;s Modulus (E). A new generation of nanoindenters, such as those based on optical fiber sensing technology, has recently gained popularity for its ease of integration while allowing to apply sub-nN forces with &#181;m spatial resolution, therefore being suitable to probe local mechanical properties of hydrogels and cells.
In this protocol, a step-by-step guide detailing the experimental procedure to acquire nanoindentation data on hydrogels and cells using a commercially available ferrule-top optical fiber sensing nanoindenter is presented. Whereas some steps are specific to the instrument used herein, the proposed protocol can be taken as a guide for other nanoindentation devices, granted some steps are adapted according to the manufacturer&#39;s guidelines. Further, a new open-source Python software equipped with a user-friendly graphical user interface for the analysis of nanoindentation data is presented, which allows for screening of incorrectly acquired curves, data filtering, computation of the contact point through different numerical procedures, the conventional computation of E, as well as a more advanced analysis particularly suited for single-cell nanoindentation data.

The protocol presents a complete workflow for soft material nanoindentation experiments, including hydrogels and cells. First, the experimental steps to acquire force spectroscopy data are detailed; then, the analysis of such data is detailed through a newly developed open-source Python software, which is free to download from GitHub.

Nanoindentation refers to a class of experimental techniques where a micrometric force probe is used to quantify the local mechanical properties of soft ...

Addressing Practical Issues in Atomic Force Microscopy-Based Micro-Indentation on Human Articular Cartilage Explants

Without a doubt, atomic force microscopy (AFM) is currently one of the most powerful and useful techniques to assess micro and even nano-cues in the biological field. However, as with any other microscopic approach, methodological challenges can arise. In particular, the characteristics of the sample, sample preparation, type of instrument, and indentation probe can lead to unwanted artifacts. In this protocol, we exemplify these emerging issues on healthy as well as osteoarthritic articular cartilage explants. To this end, we first show via a step-by-step approach how to generate, grade, and visually classify ex vivo articular cartilage discs according to different stages of degeneration by means of large 2D mosaic fluorescence imaging of the whole tissue explants. The major strength of the ex vivo model is that it comprises aged, native, human cartilage that allows the investigation of osteoarthritis-related changes from early onset to progression. In addition, common pitfalls in tissue preparation, as well as the actual AFM procedure together with the subsequent data analysis, are also presented. We show how basic but crucial steps such as sample preparation and processing, topographic sample characteristics caused by advanced degeneration, and sample-tip interaction can impact data acquisition. We also subject to scrutiny the most common problems in AFM and describe, where possible, how to overcome them. Knowledge of these limitations is of the utmost importance for correct data acquisition, interpretation, and, ultimately, the embedding of findings into a broad scientific context.

We present a step-by-step approach to identify and address the most common problems associated with atomic force microscopy micro-indentations. We exemplify the emerging problems on native human articular cartilage explants characterized by various degrees of osteoarthritis-driven degeneration.

Without a doubt, atomic force microscopy (AFM) is currently one of the most powerful and useful techniques to assess micro and even nano-cues in the ...

Fabrication of a Stable, Biologically Relevant Phantom Material

A Stable Phantom Material for Optical and Acoustic Imaging

Establishing tissue-mimicking biophotonic phantom materials that provide long-term stability are imperative to enable the comparison of biomedical imaging devices across vendors and institutions, support the development of internationally recognized standards, and assist the clinical translation of novel technologies. Here, a manufacturing process is presented that results in a stable, low-cost, tissue-mimicking copolymer-in-oil material for use in photoacoustic, optical, and ultrasound standardization efforts.
The base material consists of mineral oil and a copolymer with defined Chemical Abstract Service (CAS) numbers. The protocol presented here yields a representative material with a speed of sound c(f) = 1,481 &#177; 0.4 m&#183;s-1 at 5 MHz (corresponds to the speed of sound of water at 20 &#176;C), acoustic attenuation &#945;(f) = 6.1 &#177; 0.06 dB&#183;cm-1 at 5 MHz, optical absorption &#181;a(&#955;) = 0.05 &#177; 0.005 mm-1 at 800 nm, and optical scattering &#181;s&#39;(&#955;) = 1 &#177; 0.1 mm-1 at 800 nm. The material allows independent tuning of the acoustic and optical properties by respectively varying the polymer concentration or light scattering (titanium dioxide) and absorbing agents (oil-soluble dye). The fabrication of different phantom designs is displayed and the homogeneity of the resulting test objects is confirmed using photoacoustic imaging.
Due to its facile, repeatable fabrication process and durability, as well as its biologically relevant properties, the material recipe has high promise in multimodal acoustic-optical standardization initiatives.

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging  

This protocol describes the fabrication of a stable, biologically relevant phantom material for optical and acoustic biomedical imaging applications, featuring independently tunable acoustic and optical properties.

Establishing tissue-mimicking biophotonic phantom materials that provide long-term stability are imperative to enable the comparison of biomedical imaging ...