Insights into Acute Muscle Strain Injury Obtained with In Vivo Imaging and Finite Element Modeling

Author:
Fiorentino, Niccolo, Mechanical and Aerospace Engineering - School of Engineering and Applied Science, University of Virginia
Advisor:
Blemker, Silvia, Department of Biomedical Engineering, University of Virginia
Abstract:

Acute muscle strain injury is a prevalent and significant problem for professional, collegiate and recreational athletes, particularly in sports that involve high-speed running. Acute muscle strain injury is characterized by the sudden onset of intense pain caused by tearing of muscle fibers. Injury requires weeks to months away from sport, and previous injury increases the chance of future injury. Despite the established frequency and consequences of strain injury, decades of scientific inquiry have provided relatively little insight into the factors that cause tissue injury and what makes an individual more susceptible to injury. The goals of this work were to use in vivo imaging for measuring local tissue strains during dynamic knee joint motion and to use finite element modeling for predicting local tissue strain while running at high speeds.

The hamstring muscles in the posterior thigh suffer injury most often, because the hamstring muscles simultaneously lengthen and actively generate force during the late swing phase of running gait. Of the three hamstrings muscles, the biceps femoris long head (BFlh) is injured most frequently. We imaged the BFlh of a group of healthy subjects without a history of injury. Static MR images were used to measure the width of the proximal aponeurosis, which is where muscle fibers originate and muscle tissue is frequently injured. Dynamic MR images acquired during dynamic knee extension provided spatially varying 1st principal strain measurements. We found that local tissue strain was higher when the BFlh was actively generating force and lengthening versus passively lengthening, which suggests that high-localized strain is the acute strain injury mechanism. In addition, we found that local tissue strain was higher for subjects with a relatively narrower proximal aponeurosis, demonstrating that musculotendon dimensions can influence an individual’s strain injury susceptibility.

To study the BFlh while running at high speeds, a series of finite element (FE) models were constructed based on the musculotendon dimensions of track and field athletes at the University of Virginia. In addition, to verify model predictions with in vivo measurements, a FE model was generated based on the group of healthy subjects in the previous study, and simulations were performed of active and passive lengthening. Simulations of sprinting were based on the output of forward dynamic simulations, which provided muscle activation and muscle-tendon length change during the swing phase of sprinting. Muscle activation and muscle-tendon length change were applied to the muscle and distal end of BFlh FE mesh, respectively. Model simulations of increasing sprinting speed (70%, 85% and 100% of maximum speed) showed that local muscle tissue strain increases at faster sprinting speeds, which provides an explanation for why muscles are injured more often during high-speed sports. To assess the influence of musculotendon variability on strain injury susceptibility during sprinting, additional model simulations varied the proximal aponeurosis width, muscle width and proximal aponeurosis length over a physiological range. Simulation results showed that the structures’ dimensions influence local muscle tissue strain magnitude during sprinting.

By measuring local tissue strain during active lengthening and predicting strain while sprinting, the results of this dissertation make significant contributions to our understanding of acute strain injury. Insights into the acute strain injury mechanism and the factors that contribute to strain injury susceptibility have the potential to help the development of training and rehabilitation programs aimed at reducing injury incidence.

Degree:
PHD (Doctor of Philosophy)
Keywords:
MRI, measurement, computer model, athletes, running
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2013/04/25