Neuroplastic Mechanisms Underlying Augmented Neuromuscular Training

Study Overview
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Brief Summary
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The purpose of this proposal is to determine the neural mechanisms of augmented neuromuscular training (aNMT). Participants will complete a 6-week course of neuromuscular training with either aNMT biofeedback or sham biofeedback. An MRI will be performed before and after the training program.

Detailed Description
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Anterior cruciate ligament (ACL) injury is a common and debilitating knee injury affecting over 350,000 children or young adults each year, drastically reducing their chances for an active and healthy life. Annual direct costs exceed $13 billion, and the long-term indirect costs far exceed that figure, as ACL injury is also linked to accelerated development of disabling osteoarthritis within a few years after injury. The National Public Health Agenda for Osteoarthritis recommends expanding and refining evidence-based ACL injury prevention to reduce this burden. The investigators have identified modifiable risk factors that predict ACL injury in young female athletes. This neuromuscular training targets those factors and shows statistical efficacy in high-risk athletes, but meaningful transfer of low-risk mechanics to the field of play has been limited, as current approaches are not yet decreasing national ACL injury rates in young female athletes. The key gap is how to target mechanisms that allow transfer of risk-reducing motor control strategies from the intervention to the athletic field. The mechanisms that ultimately make such transfer possible are neural, but thus far injury prevention training focusing on neuromuscular control has not utilized neural outcomes. The investigators published and new preliminary data on neuroplasticity related to injury and neuromuscular training demonstrate the proficiency to capture these neural outcomes and future capability to target these neural mechanisms to improve the rate of motor transfer. The data support this proposal's central hypothesis that increased sensory, visual and motor planning activity to improve motor cortex efficiency is the neural mechanism of adaptation transfer to realistic scenarios. The ability to target the neural mechanisms to increase risk-reducing motor transfer from the clinic to the world could revolutionize ACL injury prevention. The transformative, positive impact of such innovative strategies will enhance the delivery of biofeedback to optimize training and increase the potential for sport transfer. This contribution will be significant for ACL injury prevention and associated long-term sequelae in young females. This unique opportunity to enhance ACL injury prevention by targeting neural mechanisms of neuromuscular adaptation and transfer will reduce the incidence of injuries that cause costly and long-term disabling osteoarthritis. Participants from the parent study Real-time Sensorimotor Feedback for Injury Prevention Assessed in Virtual Reality will be eligible to participate in this study. In the parent study, participants are randomized to receive augmented neuromuscular training (aNMT) or sham biofeedback training. Enrolled participants will complete MRI testing before and after the study training program. The entire MRI protocol will include high resolution T1-weighted 3D images, a 61 direction diffusion tensor imaging sequence, resting state functional magnetic resonance imaging (fMRI), and task-based fMRI. The fMRI tasks will be focused on motor function, participants will be asked to complete lower extremity movements including knee flexion and extension and a combined hip and knee flexion and extension.

Official Title
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Neuroplastic Mechanisms Underlying Augmented Neuromuscular Training

Conditions
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Anterior Cruciate Ligament Injuries

Intervention / Treatment
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* Other: aNMT Biofeedback
* Other: Sham Biofeedback


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: - enrolled in parent study Real-time Sensorimotor Feedback for Injury Prevention Assessed in Virtual Reality Exclusion Criteria: - contraindications to MRI scan

Ages Eligible for Study
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Minimum Age: 12 Years
Maximum Age: 19 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Prevention
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Triple


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: aNMT Biofeedback<br>Participants randomized to receive a neuromuscular training intervention that incorporates biofeedback training. | Other: aNMT Biofeedback<br>* aNMT biofeedback is created by calculating kinematic and kinetic data in real-time from the athlete's own movements. These values determine realtime transformations of the stimulus shape the athlete views via augmented-reality (AR) glasses during movement performance. The athlete's task is to move so as to create (animate) a particular stimulus shape that corresponds to desired values of the biomechanical parameters targeted by the intervention. The aNMT biofeedback occurs during neuromuscular training sessions. The neuromuscular training is a 12-week, pre-season training program occurring over 6 weeks.<br>|
| Sham Comparator: Sham Biofeedback<br>Participants randomized to receive a neuromuscular training intervention with sham feedback training. | Other: Sham Biofeedback<br>* Sham biofeedback provides a similar phenomenological experience to aNMT biofeedback for athletes-both groups experience a shape that changes with their movements-but the sham biofeedback will not provide usable information to modify movement parameters during critical movement phases. The sham biofeedback occurs during neuromuscular training sessions. The neuromuscular training is a 12-week, pre-season training program occurring over 6 weeks.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in Tract-Based Spatial Statistics (TBSS) measured change in diffusion tensor imaging (DTI) regions of interest | Tract-Based Spatial Statistics (TBSS) measured change in diffusion tensor imaging (DTI) regions of interest will be assessed with the pre- and post-intervention MRI scans. | Baseline (pre-training testing), Week 6 (post-training testing) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in TBSS measured change in fMRI regions of interest | TBSS change in fMRI measures observed between pre- and post-intervention MRI scans will be assessed. | Baseline (pre-training testing), Week 6 (post-training testing) |