The current approach to assess hamstring strain injury (HSI) risk and recovery is
suboptimal. Many player-games are lost in American Football due to the lack of a clear
understanding of the risk factors for HSI and the absence of effective methods to
minimize re-injury.
The investigators propose that the key issues are: 1) every athlete is unique; therefore,
a "one-size-fits-all" approach to HSI risk assessment will not work; 2) clinicians have
limited relevant information on the potential injury risk for a specific athlete; 3)
current methods to assess the extent of injury in a specific athlete are largely
qualitative, limiting the ability to determine re-injury risk; and 4) current use of
biologic injections is common, yet studies to quantify their effects are lacking. In this
study, the investigators will address these four critical barriers by combining
state-of-the-art quantitative imaging, on-field biomechanics, and computational analytics
into the largest-of-its-kind study of elite collegiate football players.
The study will be conducted in 4 Division I collegiate men's football teams over a 3-year
period. All student-athletes enrolled in this study will complete preseason hamstring
strength testing, inertial measurement units (IMU)-based sprinting biomechanics, and
undergo baseline magnetic resonance imaging (MRI). Student-athletes will be monitored by
athletic trainers throughout the school year, who will record injuries and participation
(e.g., time in practice, game).
Student-athletes who sustain an HSI will undergo a clinical assessment at the time of
injury along with an MRI examination. Following completion of a rehabilitation program,
hamstring strength will be re-evaluated and imaging will be repeated, along with
performance measurements.
This study will provide the most detailed understanding of the physiological causes and
effects of HSI, advancing our understanding of the processes affecting muscle function
and improving our ability to evaluate, treat, and prevent HSI. This study represents what
will be the largest, most quantitative prospective cohort study ever into HSI. Data
gathered as part of this study will be used to develop a quantitative Hamstring Injury
(HAMIR) index such that the medical and scientific communities can identify an individual
athlete's propensity for HSI, and, more importantly, identify targets for injury
mitigation, thereby reducing the global burden of HSI.
Aim 1. Develop a risk prediction model for HSI based on morphological, architectural,
biomechanical and clinical factors in National Collegiate Athletic Association (NCAA) D1
college football players. The goal is to test the predictive capacity of innovative
measures of risk for initial HSI in the largest prospective cohort study ever conducted
in HSI. The outcome will be the establishment of a quantitative HAMIR index that is based
on multiple athlete-specific measures. This aim will also identify potential future
targets for injury risk mitigation and prophylactic strategies.
Aim 2. Develop a risk prediction model for recurrent HSI based on morphological,
architectural, biomechanical and clinical factors (identified in Aim 1) in NCAA D1
college football players by completing the largest ever analysis of re-injury data. The
investigators will track players who sustain an HSI, both immediately after injury and
longitudinally. Quantification of injury metrics (e.g., volume of initial edema and
volume, shape and location of long-term scar) will be incorporated into the analytics
framework to develop a new "re-injury" HAMIR index. Similar to Aim 1, this aim will
identify potential future targets for re-injury risk mitigation and prophylactic
approaches.