Anterior Cruciate Ligament Injuries
Conditions
Brief summary
The purpose of this study 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
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 that will be evaluated using 3D biomechanical assessments. Enrolled participants into the current ancillary project will complete MRI testing before and after the study training program. The MRI protocol will include high resolution T1-weighted 3D images, motor task-based functional magnetic resonance imaging (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.
Interventions
OTHERaNMT Biofeedback
aNMT biofeedback is created by calculating kinematic and kinetic data in real-time from the athlete's own movements. These values determine real-time 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 18 session, pre-season training program occurring over 6 weeks.
OTHERSham Biofeedback
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 18 session, pre-season training program occurring over 6 weeks.
Sponsors
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Emory University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
TRIPLE (Subject, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
FEMALE
Age
12 Years to 19 Years
Healthy volunteers
Yes
Inclusion criteria
\- enrolled in parent study Real-time Sensorimotor Feedback for Injury Prevention Assessed in Virtual Reality
Exclusion criteria
\- contraindications to MRI scan
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Neural Mechanisms for Injury-resistant Movement Pattern Acquisition | Baseline (pre-training testing), Week 7 (post-training testing) | Sensorimotor brain activity was measured in task-based fMRI (% Blood Oxygen Level Dependent (BOLD) Signal change of knee sensorimotor network regions from baseline between rest and move blocks at each respective time point- the standard measure to determine brain activity during a condition is to contrast to rest to remove confounds make the data interpretable across conditions and individuals) and was associated with knee joint biomechanics (knee sagittal and frontal plane angle and moments) captured during landing task during standard laboratory landing assessment pre- and post-intervention. |
| Knee Joint Biomechanics During Landing Task | Baseline (pre-training testing), Week 7 (post-training testing) | Knee joint biomechanics (knee angle) captured during a standard laboratory landing task assessment was reported pre- and post-intervention. The degree of knee angle is the peak knee flexion angle during drop vertical jump landing. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Neural Mechanisms for Injury-resistant Movement Pattern Transfer to VR-simulated Sport | Baseline (pre-training testing), Week 7 (post-training testing) | Sensorimotor brain activity during task-based fMRI (% Blood Oxygen Level Dependent (BOLD) Signal change of knee sensorimotor network regions from baseline between rest and move blocks at each respective time point- the standard measure to determine brain activity during a condition is to contrast to rest to remove confounds make the data interpretable across conditions and individuals) was assessed and compared to biomechanical movement patterns (knee angle) measured during VR-simulated sport. |
| Knee Joint Biomechanics During VR-simulated Sport | Baseline (pre-training testing), Week 7 (post-training testing) | Biomechanical movement patterns (knee angle) were measured during VR-simulated sport at pre- and post-intervention. The degree of knee angle is the peak knee flexion angle during a sport specific landing task. |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| aNMT Biofeedback Female basketball, soccer and volleyball player enrolled in high school or club teams were randomized to receive a neuromuscular training intervention that incorporates biofeedback training. | 48 |
| Sham Biofeedback Female basketball, soccer and volleyball players enrolled in high school or club teams were randomized to receive a neuromuscular training intervention that incorporates Sham biofeedback training. | 45 |
| Total | 93 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 |
|---|---|---|---|
| Overall Study | Cut from team | 0 | 2 |
| Overall Study | Lost to Follow-up | 0 | 2 |
| Overall Study | Orthodontia | 1 | 0 |
| Overall Study | Prior Injury | 1 | 0 |
| Overall Study | Withdrawal by Subject | 0 | 1 |
Baseline characteristics
| Characteristic | aNMT Biofeedback | Total | Sham Biofeedback |
|---|---|---|---|
| Age, Continuous | 15.39 years STANDARD_DEVIATION 1.22 | 15.47 years STANDARD_DEVIATION 1.47 | 15.55 years STANDARD_DEVIATION 1.3 |
| Ethnicity (NIH/OMB) Hispanic or Latino | 8 Participants | 17 Participants | 9 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 39 Participants | 74 Participants | 35 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 1 Participants | 2 Participants | 1 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 1 Participants | 1 Participants | 0 Participants |
| Race (NIH/OMB) Asian | 1 Participants | 2 Participants | 1 Participants |
| Race (NIH/OMB) Black or African American | 4 Participants | 10 Participants | 6 Participants |
| Race (NIH/OMB) More than one race | 0 Participants | 2 Participants | 2 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 1 Participants | 2 Participants | 1 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 10 Participants | 19 Participants | 9 Participants |
| Race (NIH/OMB) White | 31 Participants | 57 Participants | 26 Participants |
| Region of Enrollment United States | 48 participants | 93 participants | 45 participants |
| Sex: Female, Male Female | 48 Participants | 93 Participants | 45 Participants |
| Sex: Female, Male Male | 0 Participants | 0 Participants | 0 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk |
|---|---|---|
| deaths Total, all-cause mortality | 0 / 48 | 0 / 45 |
| other Total, other adverse events | 0 / 48 | 0 / 45 |
| serious Total, serious adverse events | 0 / 48 | 0 / 45 |
Outcome results
Primary
Knee Joint Biomechanics During Landing Task
Knee joint biomechanics (knee angle) captured during a standard laboratory landing task assessment was reported pre- and post-intervention. The degree of knee angle is the peak knee flexion angle during drop vertical jump landing.
Time frame: Baseline (pre-training testing), Week 7 (post-training testing)
Population: Number of participants at week 7 post-training includes subjects that were able to attend and complete the visit.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| aNMT Biofeedback | Knee Joint Biomechanics During Landing Task | Knee angle at Baseline (pre-training testing) | 83.49 Degrees | Standard Deviation 10 |
| aNMT Biofeedback | Knee Joint Biomechanics During Landing Task | Knee angle at Week 7 (post-training testing) | 86.06 Degrees | Standard Deviation 10.81 |
| Sham Biofeedback | Knee Joint Biomechanics During Landing Task | Knee angle at Baseline (pre-training testing) | 80.50 Degrees | Standard Deviation 9.77 |
| Sham Biofeedback | Knee Joint Biomechanics During Landing Task | Knee angle at Week 7 (post-training testing) | 83.48 Degrees | Standard Deviation 10.36 |
Primary
Neural Mechanisms for Injury-resistant Movement Pattern Acquisition
Sensorimotor brain activity was measured in task-based fMRI (% Blood Oxygen Level Dependent (BOLD) Signal change of knee sensorimotor network regions from baseline between rest and move blocks at each respective time point- the standard measure to determine brain activity during a condition is to contrast to rest to remove confounds make the data interpretable across conditions and individuals) and was associated with knee joint biomechanics (knee sagittal and frontal plane angle and moments) captured during landing task during standard laboratory landing assessment pre- and post-intervention.
Time frame: Baseline (pre-training testing), Week 7 (post-training testing)
Population: Number of participants at week 7 post-training includes subjects that were able to attend and complete the visit.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| aNMT Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Acquisition | Baseline (pre-training testing) | 0.28 % BOLD Signal change | Standard Deviation 0.11 |
| aNMT Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Acquisition | Week 7 (post-training testing) | 0.26 % BOLD Signal change | Standard Deviation 0.17 |
| Sham Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Acquisition | Baseline (pre-training testing) | 0.26 % BOLD Signal change | Standard Deviation 0.17 |
| Sham Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Acquisition | Week 7 (post-training testing) | 0.21 % BOLD Signal change | Standard Deviation 0.1 |
Secondary
Knee Joint Biomechanics During VR-simulated Sport
Biomechanical movement patterns (knee angle) were measured during VR-simulated sport at pre- and post-intervention. The degree of knee angle is the peak knee flexion angle during a sport specific landing task.
Time frame: Baseline (pre-training testing), Week 7 (post-training testing)
Population: Number of participants at week 7 post-training includes subjects that were able to attend and complete the visit.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| aNMT Biofeedback | Knee Joint Biomechanics During VR-simulated Sport | Knee angle at Baseline (pre-training testing) | 68.43 Degrees | Standard Deviation 10.93 |
| aNMT Biofeedback | Knee Joint Biomechanics During VR-simulated Sport | Knee angle at Week 7 (post-training testing) | 73.27 Degrees | Standard Deviation 12.76 |
| Sham Biofeedback | Knee Joint Biomechanics During VR-simulated Sport | Knee angle at Baseline (pre-training testing) | 68.93 Degrees | Standard Deviation 12.1 |
| Sham Biofeedback | Knee Joint Biomechanics During VR-simulated Sport | Knee angle at Week 7 (post-training testing) | 71.89 Degrees | Standard Deviation 12.09 |
Secondary
Neural Mechanisms for Injury-resistant Movement Pattern Transfer to VR-simulated Sport
Sensorimotor brain activity during task-based fMRI (% Blood Oxygen Level Dependent (BOLD) Signal change of knee sensorimotor network regions from baseline between rest and move blocks at each respective time point- the standard measure to determine brain activity during a condition is to contrast to rest to remove confounds make the data interpretable across conditions and individuals) was assessed and compared to biomechanical movement patterns (knee angle) measured during VR-simulated sport.
Time frame: Baseline (pre-training testing), Week 7 (post-training testing)
Population: Number of participants at week 7 post-training includes subjects that were able to attend and complete the visit.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| aNMT Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Transfer to VR-simulated Sport | Baseline (pre-training testing) | 0.31 % of BOLD signal change | Standard Deviation 0.14 |
| aNMT Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Transfer to VR-simulated Sport | Week 7 (post-training testing) | 0.26 % of BOLD signal change | Standard Deviation 0.13 |
| Sham Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Transfer to VR-simulated Sport | Baseline (pre-training testing) | 0.26 % of BOLD signal change | Standard Deviation 0.13 |
| Sham Biofeedback | Neural Mechanisms for Injury-resistant Movement Pattern Transfer to VR-simulated Sport | Week 7 (post-training testing) | 0.31 % of BOLD signal change | Standard Deviation 0.11 |