Muscle strain injuries are one of the most common conditions seen in sports medicine clinics. However, methods of treatment are variable and re-injury rates tend to be high which, in part, reflects a lack of fundamental understanding of the factors that influence injury risk. The prevailing theory is that injury occurs as a result of excessive strain of active muscle fibers. The goal of this study is to develop novel biocomputational tools to predict and analyze the strain distributions within skeletal muscles during movements associated with injury. Model predictions will be compared with strain measures obtained using state-of-the-art dynamic magnetic resonance imaging experiments. Once validated, we will use the biocomputational tools to investigate how morphology and coordination influence hamstring injury risk during running. Following are the specific aims.
Aim 1 will use a dynamic magnetic resonance imaging technique to measure the strain distributions within the individual hamstring muscles during lengthening contractions, a loading condition commonly associated with injury. Comparisons between muscles will provide new insights into the propensity for hamstring injury to occur in the biceps femoris long head.
Aim 2 will build a biocomputational framework to predict muscle strain distributions during movement. The framework will couple finite-element simulations of muscle tissue behavior with dynamic simulations of whole body movement. The methods will be validated by comparing strain predictions with those determined from the dynamic images in Aim 1. We will then use the framework to investigate the relationship between muscle excitations, hamstring tissue strains and skeletal movement during running.
Aim 3 will evaluate whether computational models predict re-injury prevention strategies. We will build and validate models of subjects who exhibit residual changes in tissue structures as a result of a previous hamstring injury. We will then use the software framework to identify how movement coordination can be adapted to accommodate injury-induced changes in morphology. This research will establish a biocomputational framework that reveals the complex relationship between muscle morphology, coordination and injury risk, thus providing a new paradigm for identifying rehabilitation and injury prevention strategies. Muscle strain injuries are one of the most common conditions seen in sports medicine clinics. However, methods of treating muscle injuries are variable and re-injury rates tend to be high. This proposal couples novel biocomputational tools and imaging techniques to establish a scientific basis for preventing and rehabilitating hamstring muscle injuries. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR056201-02
Application #
7496067
Study Section
Special Emphasis Panel (ZRG1-BST-E (50))
Program Officer
Boyce, Amanda T
Project Start
2007-09-15
Project End
2011-08-31
Budget Start
2008-09-01
Budget End
2009-08-31
Support Year
2
Fiscal Year
2008
Total Cost
$297,204
Indirect Cost
Name
University of Wisconsin Madison
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Handsfield, Geoffrey G; Inouye, Joshua M; Slane, Laura C et al. (2017) A 3D model of the Achilles tendon to determine the mechanisms underlying nonuniform tendon displacements. J Biomech 51:17-25
Slane, Laura Chernak; Thelen, Darryl G (2015) Achilles tendon displacement patterns during passive stretch and eccentric loading are altered in middle-aged adults. Med Eng Phys 37:712-6
Fiorentino, Niccolo M; Blemker, Silvia S (2014) Musculotendon variability influences tissue strains experienced by the biceps femoris long head muscle during high-speed running. J Biomech 47:3325-33
Frisch, Kayt E; Marcu, David; Baer, Geoffrey S et al. (2014) The influence of partial and full thickness tears on infraspinatus tendon strain patterns. J Biomech Eng 136:051004
Frisch, Kayt E; Marcu, David; Baer, Geoffrey S et al. (2014) Influence of tendon tears on ultrasound echo intensity in response to loading. J Biomech 47:3813-9
Fiorentino, Niccolo M; Rehorn, Michael R; Chumanov, Elizabeth S et al. (2014) Computational models predict larger muscle tissue strains at faster sprinting speeds. Med Sci Sports Exerc 46:776-86
Rehorn, Michael R; Schroer, Alison K; Blemker, Silvia S (2014) The passive properties of muscle fibers are velocity dependent. J Biomech 47:687-93
Chernak, L A; DeWall, R J; Lee, K S et al. (2013) Length and activation dependent variations in muscle shear wave speed. Physiol Meas 34:713-21
Choi, Hon Fai; Blemker, Silvia S (2013) Skeletal muscle fascicle arrangements can be reconstructed using a Laplacian vector field simulation. PLoS One 8:e77576
Kaiser, Jarred; Bradford, Robert; Johnson, Kevin et al. (2013) Measurement of tibiofemoral kinematics using highly accelerated 3D radial sampling. Magn Reson Med 69:1310-6

Showing the most recent 10 out of 27 publications