Name: subject-specific musculoskeletal model for studying bone strain during dynamic motion
Uploaded: 2018-04-11T12:30:00
Description: Watch this Scientific Journal Video about Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion at JoVE.com

Department of the Army #W81XWH-08-1-0587, #W81XWH-15-1-0006; Ball State University 2010 ASPiRE grant.

The experiment was conducted under the Helsinki Declaration. Prior to data collection, the subject reviewed and signed the consent form approved by the University Institutional Review Board before participating in the study.
1. CT Imaging Protocol
<ol>
	<li>Take the participant to a facility where a CT scanner is housed. Prior to the CT scan, configure the CT machine with the following parameters: CT slice thickness of 0.625 mm, CT field of view of 15 cm x 15 cm, and auto setting for paramet...

<ol>
	<li>Brukner, P., Bennell, K., Matheson, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Stress fracture. , (1999).</li><li>Zadpoor, A., Nikooyan, A. <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+between+lower-extremity+stress+fractures+and+the+ground+reaction+force:+A+systematic+review.">The relationship between lower-extremity stress fractures and the ground reaction force: A systematic review.</a> Clin Biomech. 26, 23-28 (2011).</li><li>Matheson, G. O., Clement, D. B., McKenzie, D. C., Taunton, J. E., Lioyd-Smith, D. R., Maclntyre, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stress+fractures+in+athletes.+A+study+of+320+cases.">Stress fractures in athletes. A study of 320 cases.</a> Am J Sports Med. 15, 46-58 (1987).</li><li>Bennell, K., Grimston, S., Burr, D., Milgrom, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Risk+factors+for+developing+stress+fractures.">Risk factors for developing stress fractures.</a> Musculoskeletal fatigue and stress fractures. , 15-33 (2001).</li><li>Milgrom, C., Giladi, M., Stein, M., Kashtan, H., Margulies, J. Y., Chisin, R., Stenberg, R., Aharonson, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stress+fractures+in+military+recruits.+A+prospective+study+showing+an+unusually+high+incidence.">Stress fractures in military recruits. A prospective study showing an unusually high incidence.</a> J Bone Joint Surg Br. 67, 732-735 (1985).</li><li>Almeida, S. A., Williams, K. M., Shaffer, R. A., Brodine, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epidemiological+patterns+of+musculoskeletal+injuries+and+physical+training.">Epidemiological patterns of musculoskeletal injuries and physical training.</a> Med Sci Sports Exerc. 31, 1176-1182 (1999).</li><li>Jones, B. H., Knapik, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physical+training+and+exercise-related+injuries,+surveillance,+research+and+injury+prevention+in+military+populations.">Physical training and exercise-related injuries, surveillance, research and injury prevention in military populations.</a> Sports Med. 27, 111-125 (1999).</li><li>Jones, B. H., Thacker, S., Gilchrist, J., Kimsey, C. D., Sosin, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevention+of+lower+extremity+stress+fractures+in+athletes+and+soldiers:+a+systematic+review.">Prevention of lower extremity stress fractures in athletes and soldiers: a systematic review.</a> Epidemiol Rev. 24, 228-247 (2002).</li><li>Voloshin, A., Wosk, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+in+vivo+study+of+low+back+pain+and+shock+absorption+in+the+human+locomotor+system.">An in vivo study of low back pain and shock absorption in the human locomotor system.</a> J Biomech. 15, 21-27 (1982).</li><li>Burr, D. B., Milgrom, C., Fyhrie, D., Forwood, M., Nyska, M., Finestone, A., Hoshaw, S., Saiag, E., Simkin, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+measurement+of+human+tibial+strains+during+vigorous+activity.">In vivo measurement of human tibial strains during vigorous activity.</a> Bone. 18, 405-410 (1996).</li><li>Ekenman, I., Halvorsen, K., Westblad, P., Fellander-Tsai, L., Rolf, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+reliability+and+validity+of+an+instrumented+staple+system+for+in+vivo+measurement+of+local+bone+deformation.+An+in+vitro+study.">The reliability and validity of an instrumented staple system for in vivo measurement of local bone deformation. An in vitro study.</a> Scand J Med Sci Sports. 8, 172-176 (1998).</li><li>Lanyon, L. E., Hampson, W. G., Goodship, A. E., Shah, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bone+deformation+recorded+in+vivo+from+strain+gauges+attached+to+the+human+tibial+shaft.">Bone deformation recorded in vivo from strain gauges attached to the human tibial shaft.</a> Acta Orthop Scand. 46, 256-268 (1975).</li><li>Ekenman, I., Halvorsen, K., Westblad, P., Tsai, L. F., Rolf, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Local+bone+deformation+at+two+predominant+sites+for+stress+fractures+of+the+tibia:+an+in+vivo+study.">Local bone deformation at two predominant sites for stress fractures of the tibia: an in vivo study.</a> Foot Ankle Int. 19, 479-484 (1998).</li><li>Milgrom, C., Finestone, A., Levi, Y., Simkin, A., Ekenman, I., Mendelson, S., Millgram, M., Nyska, M., Benjuya, N., Burr, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Do+high+impact+exercises+produce+higher+tibial+strains+than+running?.">Do high impact exercises produce higher tibial strains than running?.</a> Br J Sports Med. 34, 195-199 (2000).</li><li>Milgrom, C., Finestone, A., Simkin, A., Ekenman, I., Mendelson, S., Millgram, M., Nyska, M., Larsson, E., Burr, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-vivo+strain+measurements+to+evaluate+the+strengthening+potential+of+exercises+on+the+tibial+bone.">In-vivo strain measurements to evaluate the strengthening potential of exercises on the tibial bone.</a> J Bone Joint Surg Br. 82, 591-594 (2000).</li><li>Al Nazer, R., Rantalainen, T., Heinonen, A., Sievanen, H., Mikkola, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flexible+multibody+simulation+approach+in+the+analysis+of+tibial+strain+during+walking.">Flexible multibody simulation approach in the analysis of tibial strain during walking.</a> J Biomech. 41, 1036-1043 (2008).</li><li>Al Nazer, R., Klodowski, A., Rantalainen, T., Heinonen, A., Sievanen, H., Mikkola, 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+full+body+musculoskeletal+model+based+on+flexible+multibody+simulation+approach+utilised+in+bone+strain+analysis+during+human+locomotion.">A full body musculoskeletal model based on flexible multibody simulation approach utilised in bone strain analysis during human locomotion.</a> Comput Method Biomec. 14, 573-579 (2011).</li><li>Johnson, M. A., Moradi, M. H., Crowe, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> PID control: new identification and design methods. , 543 (2005).</li><li>Craig, R. R., Bampton, M. C. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coupling+of+substructures+for+dynamics+analysis.">Coupling of substructures for dynamics analysis.</a> American Institute of Aeronautics and Astronautics Journal. 6, 1313-1319 (1968).</li><li>Wasfy, T. M., Noor, A. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+strategies+for+flexible+multibody+systems.">Computational strategies for flexible multibody systems.</a> Appl Mech Rev. 56, 553-613 (2003).</li><li>Kadaba, M. P., Ramakrishnan, H. k., Wootten, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+lower+extremity+kinematics+during+level+walking.">Measurement of lower extremity kinematics during level walking.</a> J Orthop Res. 8, 383-392 (1990).</li><li>Schwartz, M. H., Rozumalski, 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+new+method+for+estimating+joint+parameters+from+motion+data.">A new method for estimating joint parameters from motion data.</a> J Biomech. 38, 107-116 (2005).</li><li>Devita, P., Skelly, W. 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The purpose of this study was to develop a non-invasive method to determine tibia deformation during high impact activities. Quantifying tibia strain due to impact loading will lead to a better understanding of tibia stress fracture. In this study, a subject-specific musculoskeletal model was developed, and computer simulations were run to duplicate the drop-landing movements performed in a laboratory setting. The effect of drop-landing height on tibial strain was examined. In this study, we observed that as the drop-lan...

Bone stress injuries, such as stress fractures, are severe overuse injuries requiring long periods of recovery and incurring significant medical cost1,2. Stress fractures are common both in athletic and military populations. Among all sports related injuries, stress fractures account for 10% of the total3. In particular, track athletes face a higher injury rate at 20%4. Soldiers also experience a high rate of stress fractures. For instance, a 6% injury rate was reported for the US Army1 and a 31% injury rate was reported in the Israeli Army5. Among all reported stress fractures, tibia stress fracture is the most common one6,7,8.
Sports and physical trainings with a higher risk of tibia stress fracture are normally associated with high ground impacts (e.g., jumping, landing, and cutting). During locomotion, a ground impact force is applied to the body when the foot contacts the ground. This impact force is dissipated by the musculoskeletal system and footwear. The skeletal system serves as a series of levers allowing muscles to apply forces to absorb the ground impact9. When the leg muscles cannot adequately reduce the ground impact, lower-body bones must absorb the residual force. Bone structure will experience deformation during this process. Repetitive absorption of residual impact force may result in microdamages in the bone, which will accumulate and become stress fractures. To date, information related to bone reaction to external ground impact forces is limited. It is important to study how the tibia bone responds to the mechanical load introduced by high impact forces during dynamic motions. Examining tibia bone deformation during high impact activities could lead to a better understanding of the mechanism of tibia stress fracture.
Conventional techniques used to measure bone deformation in vivo rely on instrumented strain gauges10,11,12,13,14,15. Surgical procedures are needed to implant strain gauges on bone surface. Due to the invasive nature, in vivo studies are limited by a small sample of volunteers. In addition, the strain gauge can only monitor a small region of the bone surface. Recently, a non-invasive method utilizing computer simulation to analyze bone strain was introduced16,17. This methodology allows for the ability to combine musculoskeletal modeling and computational simulations to study bone strain during human movement.
A musculoskeletal model is represented by a skeleton and skeletal muscles. The skeleton consists of bone segments, which are rigid or non-deformable bodies. Skeletal muscles are modeled as controllers using the progressive-integral-derivative (PID) algorithm. The three-term PID control uses errors in estimation to improve the output accuracy18. In essence, PID controllers representing muscles try to duplicate body movements by developing necessary forces to produce length changes of the muscles over time. The PID controller uses the error in the length/time curve to modify the force for reproducing the movement. This simulation process creates a feasible solution to coordinate all muscles to work together to move the skeleton and produce the body movement.
One or more segments in the skeleton of the musculoskeletal model can be modeled as flexible bodies to allow measurement of deformation. For instance, the tibia bone can be broken down into a finite number of elements, which consists of thousands of elements and nodes. The effect of mechanical loading on the flexible tibia can be examined through finite element (FE) analysis. The FE analysis calculates the loading response of individual elements over time. As the number of bone elements and nodes increase, the computation time of the FE analysis will significantly increase.
To reduce computational cost with accurate evaluation of flexible bodies&#39; deformation, modal FE analysis has been developed and used within the automotive and aerospace industry19,20. Instead of analyzing individual FE elements&#39; responses to mechanical load in the time domain, this procedure assesses an object&#39;s mechanical responses based on different vibrational frequencies in the frequency domain. This method results in a significant reduction in computation time while providing accurate measurement of deformation20. Although modal FE analysis has been widely used to study mechanical fatigue in automotive and aerospace areas, the application of this method has been very limited in human movement science. Al Nazer et al., used a modal FE analysis to examine tibial deformation during human gait and reported encouraging results16,17. However, their method was greatly affected by only using limited kinematic data from an experiment to drive the computer simulations; There were no real ground impact forces used to assist the simulations. This approach may be reasonable for studying low impact slow motions such as walking, but it is not a feasible solution to study high ground impact movements. Thus, in order to examine lower-body bone reactions during dynamic high impact activities, it is essential to develop an innovative approach to address the limitations associated with the previously reported method. Specifically, a method utilizing accurate experimental kinematic data and real ground impact forces must be developed. Therefore, the goal of this study was to develop a subject-specific musculoskeletal model to perform multibody dynamic simulations with modal FE analysis to examine tibial strain during high impact activities. A dynamic high impact movement represented by drop-landings from different heights was selected to test the method.

<table border="0" cellpadding="0" cellspacing="0" width="575">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:143px;">CT Scanner</td>
			<td style="width:123px;">GE Medical System</td>
			<td style="width:107px;">N/A</td>
			<td style="width:203px;">Light Speed VCT. For performing tibia CT scan.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Motion Capture System</td>
			<td>Vicon Inc</td>
			<td>N/A</td>
			<td>Vicon FX40 high speed cameras. For performing 3D motion capture.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Force plates</td>
			<td>AMTI Inc</td>
			<td>N/A</td>
			<td>Collecting 3D ground reaction forces</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Vicon Nexus</td>
			<td>Vicon Inc</td>
			<td>N/A</td>
			<td>Motion capture software program. For processing visual marker trajectory data.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Visual 3D</td>
			<td>C-Motion Inc</td>
			<td>N/A</td>
			<td>Biomechanics analysis software. For computing 3D kinematics and kinetics of human movements.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MATLAB</td>
			<td>Mathworks Inc</td>
			<td>N/A</td>
			<td>Computer programming software. For performing raw data filtering, data conversion, and data processing.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">ADAMS 2012</td>
			<td>MSC Software Inc</td>
			<td>N/A</td>
			<td>Multibody dynamic computer simulation program.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">LifeMOD</td>
			<td>Lifemodeler Inc</td>
			<td>N/A</td>
			<td>A software Plug-in in ADAMS. For building human body musculo-skeletal models.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MIMICS 13</td>
			<td>Materialise Inc</td>
			<td>N/A</td>
			<td>Image processing program. A 3D modeling tool to process imaging data. For creating 3D tibia model from CT scans.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MARC 2012</td>
			<td>MSC Software Inc</td>
			<td>N/A</td>
			<td>Finite element analysis software. For performing volumn meshing, generating tibia FE model, and running modal FE analysis.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SPSS 19</td>
			<td>IBM Inc</td>
			<td>N/A</td>
			<td>Statistical analysis software.</td>
		</tr>
	</tbody>
</table>

subject-specific musculoskeletal model for studying bone strain during dynamic motion

Bone stress injuries are common in sports and military trainings. Repetitive large ground impact forces during training could be the cause. It is essential to determine the effect of high ground impact forces on lower-body bone deformation to better understand the mechanisms of bone stress injuries. Conventional strain gauge measurement has been used to study in vivo tibia deformation. This method is associated with limitations including invasiveness of the procedure, involvement of few human subjects, and limited strain data from small bone surface areas. The current study intends to introduce a novel approach to study tibia bone strain under high impact loading conditions. A subject-specific musculoskeletal model was created to represent a healthy male (19 years, 80 kg, 1,800 mm). A flexible finite element tibia model was created based on a computed tomography (CT) scan of the subject&#39;s right tibia. Laboratory motion capture was performed to obtain kinematics and ground reaction forces of drop-landings from different heights (26, 39, 52 cm). Multibody dynamic computer simulations combined with a modal analysis of the flexible tibia were performed to quantify tibia strain during drop-landings. Calculated tibia strain data were in good agreement with previous in vivo studies. It is evident that this non-invasive approach can be applied to study tibia bone strain during high impact activities for a large cohort, which will lead to a better understanding of injury mechanism of tibia stress fractures.

A healthy Caucasian male (19 years, height 1,800 mm, mass 80 kg) volunteered for the study. Prior to data collection, the subject reviewed and signed the consent form approved by the University Institutional Review Board before participating in the study. The experiment was conducted under the Helsinki Declaration. The experiment was performed based on the following protocol.
In order to verify the accuracy of the forward dynami...

Watch this Scientific Journal Video about Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion at JoVE.com

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

During landing, lower-body bones experience large mechanical loads and are deformed. It is essential to measure bone deformation to better understand the mechanisms of bone stress injuries associated with impacts. A novel approach integrating subject-specific musculoskeletal modeling and finite element analysis is used to measure tibial strain during dynamic movements.

Bone stress injuries are common in sports and military trainings. Repetitive large ground impact forces during training could be the cause. It is ...

The overall goal of this procedure is to create a Subject-specific Musculoskeletal Model for Bone Strain analysis. This method can help answer key questions in the biomedical engineering field such as quantifying human bone deformation during dynamic motion. The main advantage of this technique is that a non-invasive approach is implemented to study bone strength during dynamic physical activities.Demonstrating the procedure will be Marisa Loo and Kerstyn Hall, graduate students from my laboratory. To begin this procedure perform CT scanning and anthropometric measurement on the subject. After this, place 14mm reflective markers on the participants'body as outlined in the text protocol.Place semi rigid plastic plates with four marker clusters on the participants'thighs and shanks. After entering the subjects'information into the motion capture program, ask them to stand motionless in the center of the calibrated room with their feet shoulder width apart. Then ask them to extend their upper extremities laterally so that all of the reflective markers are well exposed to the cameras.In the main program window, open the tools pane, click the subject preparation tab. In the subject capture section, click start to record a three second motion trial to be the static calibration trial. To begin determining the functional hip joint center, ask the participant to stand on one leg while fully extending the other leg slightly forward.Instruct the participant to move the extended leg around the hip joint anteriorly and return to neutral. Anterior laterally and return to neutral. And then laterally and return to neutral.After this have the participant move the same leg around the hip joint posterior laterally and return to neutral. Posteriorly and return to neutral. And then in a circumduction motion.In the main program window, open the tools pane, click the capture tab, then in the capture section click start to record a motion trial for each functional hip motion. To begin determining the functional knee joint center, ask the participant to stand on one leg while maintaining a 30 degree hip hyperextension of the other leg. Next, instruct the participant to perform a 45 degree knee flexion with the non weight bearing leg.Have them repeat this five times. In the capture section of the tools pane, click start to record a motion trial for each functional knee motion. Place the height adjusted wood box on an area of the floor covered by a rubber mat, making sure that it is approximately 11cm from the edges of the force plates.Next, ask the participant to stand on top of the box. Instruct the participant to extend their dominant foot directly in front of the box, then have them shift their weight forward and step off the box. Both of the participants legs should land on the ground at the same time with each foot striking a separate force plate, ask the participant to remain standing until the motion capture of the trial is complete.Repeat the motion capture three times to collect three motion trials for each height. First, open a motion capture software program. In the main window, go to the communications pane, click the data management tab and select one of the recorded motion trials.Open the trial data in the program. In the tools pane, click the pipeline tab. From the current pipeline list, select the reconstruct pipeline, click the run button to start reconstruction process to obtain three dimension trajectories of the reflective markers.Navigate to the tools pane and click the label edit tab, in the manual labeling section select individual marker names and label the corresponding 3D trajectories. When labeling is complete, click the save button on the tool bar. To begin creating a lower body skeletal model, open the multi-body dynamic simulation software program with the human body modeling plug in installed.At the splash screen, double click the new model icon to open the model building control panel, in the anthropometric database library section of the main modeling panel, choose the generic body from the drop down list, specify the body mass, body height, gender and age. In the body configuration section of the main modeling panel click the lower body radio button, in the units drop down list select mm, kg, Newton;click the apply button in the create body measurement table section to accept the body measurements. Continue to click the apply button in the create human segment section to create a lower body skeletal base model.To begin modeling the lower body joints, open the main menu drop down list in the main modeling panel and select joints to open the joint configuration panel. In the joint rotation element section of the joint configuration panel, click the button next for prepare model with recording joints. In the spring dampers and joint limits properties section enter the parameters for nominal joint stiffness, nominal joint damping and joint stop stiffness as shown here.Continue to select left leg and right leg by checking corresponding radio buttons, click the apply button to accept the joint configurations. After this, open the main menu drop down list in the main modeling panel and select workflow, in the sub menus drop down list select gait and calibrate, in the joint center data section enter the participants lower body joint center file. Then click the load button to import the data and modify the locations of the joint centers, in the load static trial section enter the static calibration motion capture trial.Click the load button to import the file and parametrize the lower body skeletal model. To begin modeling the skeletal muscles, open the main menu drop down in the main modeling panel and select soft tissues, after this open the sub menu drop down and select create base tissue set. In the muscle contract tile element section, click prepare model with recording muscle elements.Next, in the global recording element muscle properties section, click the radio button corresponding to updated 45 muscle set then accept the default settings for muscle properties as shown here. Check the radio buttons for left leg and right leg for muscle assignments, then click the apply button to accept the configurations. In this study, a non-invasive method is used to determine tibia deformation during high impact activities.The accuracy of the forward dynamic simulation is verified by comparing the lower body joint angles from the simulation to the corresponding joint angles as measured for motion capture data. These comparisons are completed for the ankle angle, knee angle and hip angle at all three drop heights where the vertical lines represent moments of impact. As can be seen, the simulation and experimental data largely agree, demonstrating that the simulation itself has a high degree of accuracy.Statistical analysis software is then used to calculate the cross-correlation coefficients between the experimental and simulation joint angles at zero lag. The peak strains at the antero medial region of the mid tibial shaft are recorded while the subject lands from three different heights. The 52cm landing condition demonstrates the largest peak maximum principal, peak minimum principal and peak maximum shear strains.The peak maximum principal strains are also seen to increase as the drop height increases. After it's development, this technique paved the way for researchers in the field of biomedical engineering, to explore mechanisms of bone stress injuries in athletes and military trainees.

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Unit 1

Transformations of Stress and Strain

Musculoskeletal System

SCIENTISTS IN ACTION

Microfabricated Platforms for Mechanically Dynamic Cell Culture

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or fundamental cell biology studies is limited by current bioreactor technologies, which cannot simultaneously apply a variety of mechanical stimuli to cultured cells. In order to address this issue, we have developed a series of microfabricated platforms designed to screen for the effects of mechanical stimuli in a high-throughput format. In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and further demonstrate how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

In this protocol, we demonstrate the fabrication of a microactuator array of vertically displaced posts on which the technology is based, and how this base technology can be modified to conduct high-throughput mechanically dynamic cell culture in both two-dimensional and three-dimensional culture paradigms.

The ability to systematically probe in vitro cellular response to combinations of mechanobiological stimuli for tissue engineering, drug discovery or ...

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, direct visualization of individual viral complexes in their host cellular environment with cryoET is challenging2, due to the infrequent and dynamic nature of viral entry, particularly in the case of HIV-1. While time-lapse live-cell imaging has yielded a great deal of information about many aspects of the life cycle of HIV-13-7, the resolution afforded by live-cell microscopy is limited (~ 200 nm). Our work was aimed at developing a correlation method that permits direct visualization of early events of HIV-1 infection by combining live-cell fluorescent light microscopy, cryo-fluorescent microscopy, and cryoET. In this manner, live-cell and cryo-fluorescent signals can be used to accurately guide the sampling in cryoET. Furthermore, structural information obtained from cryoET can be complemented with the dynamic functional data gained through live-cell imaging of fluorescent labeled target.
In this video article, we provide detailed methods and protocols for structural investigation of HIV-1 and host-cell interactions using 3D correlative high-speed live-cell imaging and high-resolution cryoET structural analysis. HeLa cells infected with HIV-1 particles were characterized first by confocal live-cell microscopy, and the region containing the same viral particle was then analyzed by cryo-electron tomography for 3D structural details. The correlation between two sets of imaging data, optical imaging and electron imaging, was achieved using a home-built cryo-fluorescence light microscopy stage. The approach detailed here will be valuable, not only for study of virus-host cell interactions, but also for broader applications in cell biology, such as cell signaling, membrane receptor trafficking, and many other dynamic cellular processes.

We describe a correlative microscopy method that combines high-speed 3D live-cell fluorescent light microscopy and high-resolution cryo-electron tomography. We demonstrate the capability of the correlative method by imaging dynamic, small HIV-1 particles interacting with host HeLa cells.

Cryo-electron tomography (cryoET) allows 3D visualization of cellular structures at molecular resolution in a close-to-physiological state1. However, ...

Home-Based Monitor for Gait and Activity Analysis

Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical evaluators. These measures are slightly subjective and are performed during a visit to a clinic or hospital and constitute therefore a point assessment. Point assessments can be influenced by daily patient condition or factors such as fatigue, motivation, and intercurrent illness. To enable home-based monitoring of gait and activity, a wearable magneto-inertial sensor (WMIS) has been developed. This device is a movement monitor composed of two very light watch-like sensors and a docking station. Each sensor contains a tri-axial accelerometer, gyroscope, magnetometer, and a barometer that record linear acceleration, angular velocity, the magnetic field of the movement in all directions, and barometric altitude, respectively. The sensors can be worn on the wrist, ankle, or wheelchair to record the subject&#8217;s movements during the day. The docking station enables data uploading and recharging of sensor batteries during the night. Data are analyzed using proprietary algorithms to compute parameters representative of the type and intensity of the performed movement. This WMIS can record a set of digital biomarkers, including cumulative variables, such as total number of meters walked, and descriptive gait variables, such as the percentage of the most rapid or longest stride that represents the top performance of patient over a predefined period of time.

This innovative device uses magneto-inertial sensors to permit gait and activity analysis in uncontrolled environments. Currently in the qualification process as an outcome measure in the European Medical Agency, one of the applications will be to serve as a clinical endpoint in clinical trials in neuromuscular diseases.

Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical ...

Calvarial Model of Bone Augmentation in Rabbit for Assessment of Bone Growth and Neovascularization in Bone Substitution Materials

The basic principle of the rabbit calvarial model is to grow new bone tissue vertically on top of the cortical part of the skull. This model allows assessment of bone substitution materials for oral and craniofacial bone regeneration in terms of bone growth and neovascularization support. Once animals are anesthetized and ventilated (endotracheal intubation), four cylinders made of polyether ether ketone (PEEK) are screwed onto the skull, on both sides of the median and coronal sutures. Five intramedullary holes are drilled within the bone area delimited by each cylinder, allowing influx of bone marrow cells. The material samples are placed into the cylinders which are then closed. Finally, the surgical site is sutured, and animals are awaken. Bone growth may be assessed on live animals by using microtomography. Once animals are euthanized, bone growth and neovascularization may be evaluated by using microtomography, immune-histology and immunofluorescence. As the evaluation of a material requires maximum standardization and calibration, the calvarial model appears ideal. Access is very easy, calibration and standardization are facilitated by the use of defined cylinders and four samples may be assessed simultaneously. Furthermore, live tomography may be used and ultimately a large decrease in animals to be euthanized may be anticipated.

Here we present a surgical protocol in rabbits with the aim to assess bone substitution materials in terms of bone regeneration capacities. By using PEEK cylinders fixed onto rabbit skulls, osteoconduction, osteoinduction, osteogenesis and vasculogenesis induced by the materials may be evaluated either on live or euthanized animals.

The basic principle of the rabbit calvarial model is to grow new bone tissue vertically on top of the cortical part of the skull. This model allows ...

A Human 3D Extracellular Matrix-Adipocyte Culture Model for Studying Matrix-Cell Metabolic Crosstalk

The extracellular matrix (ECM) plays a central role in regulating tissue homeostasis, engaging in crosstalk with cells and regulating multiple aspects of cellular function. The ECM plays a particularly important role in adipose tissue function in obesity, and alterations in adipose tissue ECM deposition and composition are associated with metabolic disease in mice and humans. Tractable in vitro models that permit dissection of the roles of the ECM and cells in contributing to global tissue phenotype are sparse. We describe a novel 3D in vitro model of human ECM-adipocyte culture that permits study of the specific roles of the ECM and adipocytes in regulating adipose tissue metabolic phenotype. Human adipose tissue is decellularized to isolate ECM, which is subsequently repopulated with preadipocytes that are then differentiated within the ECM into mature adipocytes. This method creates ECM-adipocyte constructs that are metabolically active and retain characteristics of the tissues and patients from which they are derived. We have used this system to demonstrate disease-specific ECM-adipocyte crosstalk in human adipose tissue. This culture model provides a tool for dissecting the roles of the ECM and adipocytes in contributing to global adipose tissue metabolic phenotype and permits study of the role of the ECM in regulating adipose tissue homeostasis.

We describe a 3D human extracellular matrix-adipocyte in vitro culture system that permits dissection of the roles of the matrix and adipocytes in contributing to adipose tissue metabolic phenotype.

The extracellular matrix (ECM) plays a central role in regulating tissue homeostasis, engaging in crosstalk with cells and regulating multiple aspects of ...

Controlled Strain of 3D Hydrogels under Live Microscopy Imaging

External forces are an important factor in tissue formation, development, and maintenance. The effects of these forces are often studied using specialized in vitro stretching methods. Various available systems use 2D substrate-based stretchers, while the accessibility of 3D techniques to strain soft hydrogels, is more restricted. Here, we describe a method that allows external stretching of soft hydrogels from their circumference, using an elastic silicone strip as the sample carrier. The stretching system utilized in this protocol is constructed from 3D-printed parts and low-cost electronics, making it simple and easy to replicate in other labs. The experimental process begins with polymerizing thick (&#62;100 &#956;m) soft fibrin hydrogels (Elastic Modulus of ~100 Pa) in a cut-out at the center of a silicone strip. Silicone-gel constructs are then attached to the printed-stretching device and placed on the confocal microscope stage. Under live microscopy the stretching device is activated, and the gels are imaged at various stretch magnitudes. Image processing is then used to quantify the resulting gel deformations, demonstrating relatively homogenous strains and fiber alignment throughout the gel&#8217;s 3D thickness (Z-axis). Advantages of this method include the ability to strain extremely soft hydrogels in 3D while executing in situ microscopy, and the freedom to manipulate the geometry and size of the sample according to the user&#8217;s needs. Additionally, with proper adaptation, this method can be used to stretch other types of hydrogels (e.g., collagen, polyacrylamide or polyethylene glycol) and can allow for analysis of cells and tissue response to external forces under more biomimetic 3D conditions.

The presented method involves uniaxial stretching of 3D soft hydrogels embedded in silicone rubber while allowing live confocal microscopy. Characterization of the external and internal hydrogel strains as well as fiber alignment are demonstrated. The device and protocol developed can assess the response of cells to various strain regimes.

External forces are an important factor in tissue formation, development, and maintenance. The effects of these forces are often studied using specialized ...

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

The shoulder is one of the human body's most complex joint systems, with motion occurring through the coordinated actions of four individual joints, multiple ligaments, and approximately 20 muscles. Unfortunately, shoulder pathologies (e.g., rotator cuff tears, joint dislocations, arthritis) are common, resulting in substantial pain, disability, and decreased quality of life. The specific etiology for many of these pathologic conditions is not fully understood, but it is generally accepted that shoulder pathology is often associated with altered joint motion. Unfortunately, measuring shoulder motion with the necessary level of accuracy to investigate motion-based hypotheses is not trivial. However, radiographic-based motion measurement techniques have provided the advancement necessary to investigate motion-based hypotheses and provide a mechanistic understanding of shoulder function. Thus, the purpose of this article is to describe the approaches for measuring shoulder motion using a custom biplanar videoradiography system. The specific objectives of this article are to describe the protocols to acquire biplanar videoradiographic images of the shoulder complex, acquire CT scans, develop 3D bone models, locate anatomical landmarks, track the position and orientation of the humerus, scapula, and torso from the biplanar radiographic images, and calculate the kinematic outcome measures. In addition, the article will describe special considerations unique to the shoulder when measuring joint kinematics using this approach.

Biplane videoradiography can quantify shoulder kinematics with a high degree of accuracy. The protocol described herein was specifically designed to track the scapula, humerus, and the ribs during planar humeral elevation, and outlines the procedures for data collection, processing, and analysis. Unique considerations for data collection are also described.

The shoulder is one of the human body's most complex joint systems, with motion occurring through the coordinated actions of four individual joints, ...

Cantilever Bending of Murine Femoral Necks

Fractures in the femoral neck are a common occurrence in individuals with osteoporosis. Many mouse models have been developed to assess disease states and therapies, with biomechanical testing as a primary outcome measure. However, traditional biomechanical testing focuses on torsion or bending tests applied to the midshaft of the long bones. This is not typically the site of high-risk fractures in osteoporotic individuals. Therefore, a biomechanical testing protocol was developed that tests the femoral necks of murine femurs in cantilever bending loading to replicate better the types of fractures experienced by osteoporosis patients. Since the biomechanical outcomes are highly dependent on the flexural loading direction relative to the femoral neck, 3D printed guides were created to maintain a femoral shaft at an angle of 20&#176; relative to the loading direction. The new protocol streamlined the testing by reducing variability in alignment (21.6&#176; &plusmn; 1.5&#176;, COV = 7.1%, n = 20) and improved reproducibility in the measured biomechanical outcomes (average COV = 26.7%). The new approach using the 3D printed guides for reliable specimen alignment improves rigor and reproducibility by reducing the measurement errors due to specimen misalignment, which should minimize sample sizes in mouse studies of osteoporosis.

The present protocol describes the development of a reproducible testing platform for murine femoral necks in a cantilever bending set-up. Custom 3D printed guides were used to consistently and rigidly fix the femurs in optimal alignment.

Fractures in the femoral neck are a common occurrence in individuals with osteoporosis. Many mouse models have been developed to assess disease states and ...

Construction of a Human Aorta Smooth Muscle Cell Organ-On-A-Chip Model for Recapitulating Biomechanical Strain in the Aortic Wall

Conventional two-dimensional cell culture techniques and animal models have been used in the study of human thoracic aortic aneurysm and dissection (TAAD). However, human TAAD sometimes cannot be characterized by animal models. There is an apparent species gap between clinical human studies and animal experiments that may hinder the discovery of therapeutic drugs. In contrast, the conventional cell culture model is unable to simulate in vivo biomechanical stimuli. To this end, microfabrication and microfluidic techniques have developed greatly in recent years, providing novel techniques for establishing organoids-on-a-chip models that replicate the biomechanical microenvironment. In this study, a human aorta smooth muscle cell organ-on-a-chip (HASMC-OOC) model was developed to simulate the pathophysiological parameters of aortic biomechanics, including the amplitude and frequency of cyclic strain experienced by human aortic smooth muscle cells (HASMCs) that play a vital role in TAAD. In this model, the morphology of HASMCs became elongated in shape, aligned perpendicularly to the strain direction, and presented a more contractile phenotype under strain conditions than under static conventional conditions. This was consistent with the cell orientation and phenotype in native human aortic walls. Additionally, using bicuspid aortic valve-related TAAD (BAV-TAAD) and tricuspid aortic valve-related TAAD (TAV-TAAD) patient-derived primary HASMCs, we established BAV-TAAD and TAV-TAAD disease models, which replicate HASMC characteristics in TAAD. The HASMC-OOC model provides a novel in vitro platform that is complementary to animal models for further exploring the pathogenesis of TAAD and discovering therapeutic targets.

Here, we developed a human aorta smooth muscle cell organ-on-a-chip model to replicate the in vivo biomechanical strain of smooth muscle cells in the human aortic wall.

Conventional two-dimensional cell culture techniques and animal models have been used in the study of human thoracic aortic aneurysm and dissection ...

A GMP-Compliant Procedure for the Generation of Gene-Modified T cells

The field of Adoptive Cell Therapy (ACT) has been revolutionized by the development of genetically modified cells, specifically Chimeric Antigen Receptor (CAR)-T cells. These modified cells have shown remarkable clinical responses in patients with hematologic malignancies. However, the high cost of producing these therapies and conducting extensive quality control assessments has limited their accessibility to a broader range of patients. To address this issue, many academic institutions are exploring the feasibility of in-house manufacturing of genetically modified cells, while adhering to guidelines set by national and international regulatory agencies.
Manufacturing genetically modified T cell products on a large scale presents several challenges, particularly in terms of the institution's production capabilities and the need to meet infusion quantity requirements. One major challenge involves producing large-scale viral vectors under Good Manufacturing Practice (GMP) guidelines, which is often outsourced to external companies. Additionally, simplifying the T cell transduction process can help minimize variability between production batches, reduce costs, and facilitate personnel training. In this study, we outline a streamlined process for lentiviral transduction of primary human T cells with a fluorescent marker as the gene of interest. The entire process adheres to GMP-compliant standards and is implemented within our academic institution.

This protocol outlines the process of transducing primary human T cells with a gene of interest, ensuring compatibility with Good Manufacturing Practice (GMP) standards.

The field of Adoptive Cell Therapy (ACT) has been revolutionized by the development of genetically modified cells, specifically Chimeric Antigen Receptor ...