Development of a movement performance assessment to predict ACL re-injury

Approximately 1 in 4 young athletes who return to a high-risk sport after primary ACL reconstruction (ACLR) will go on to sustain another ACL injury. Interestingly, 60-70% of ACL injuries (initial or secondary) occur as a result of non-contact mechanisms. The fact that movement-related impairments are thought to underlie non-contact ACL injuries, highlights the need to assess movement behavior to better determine readiness to return to sport.The lack of a comprehensive clinical assessment to quantify an athlete?s readiness to return to sport following ACLR led to the development of the video-based Movement Performance Assessment (MPA). Although the MPA has been developed and is being used clinically, it remains unknown if the 2D measures of the MPA represent/predict 3D measures. In addition, it is not known whether the movement constructs that comprise the MPA are important for predicting ACL re-injury. This dissertation sought to answer these questions as a first step in establishing the MPA as a potential clinical tool to assess an athlete?s readiness to return to sport following ACLR.The purpose of Chapters 3-6 (Aim 1) was to determine if the 2D movement variables established for the MPA are representative of the 3D variables related to ACL injury risk based on laboratory-based studies. Thirty-nine healthy athletes (15 males and 24 females) performed 6 tasks conceptualized for the MPA (step down, drop jump, lateral shuffle, deceleration, triple hop, and side-step-cut) while 3D kinematics/kinetics and 2D video were collected simultaneously. Specific 2D angular measurements and the corresponding 3D kinematic and kinetic variables were quantified during the deceleration/lowering phase of each task. Linear regression or correlation analysis was used to assess the relationship between 2D and 3D metrics. Agreement between 2D and 3D angles was assessed using Bland Altman plots, when relevant.Validation of the kinetic constructs of the MPA (knee strategy and shock absorption) are presented in Chapters 3 and 4. The purpose of Chapter 3 was to determine whether the difference between sagittal plane trunk and tibia orientations obtained from 2D video (2D trunk-tibia) at peak knee flexion could be used to predict the average hip/knee extensor moment ratio during the deceleration/lowering phase of each of the 6 MPA tasks. For each task, an increase in the 2D trunk-tibia angle (representing a more forward trunk relative to the tibia) predicted an increase in the average hip/knee extensor moment ratio when adjusted for body mass (all p < .013, R2 = 0.17-0.77). The purpose of Chapter 4 was to determine whether the 2D thigh angle at peak knee flexion relative to the vertical could be used to predict the peak vertical ground reaction force (vGRF) and vGRF impulse during the tasks that involved impact with the ground (all except step down). For all impact tasks except for cutting, an increase in the 2D thigh angle (which is representative of increased hip and knee flexion) predicted a lower peak vGRF (R2 = 0.17 to 0.47, all p < 0.01). However, an increase in the 2D thigh angle predicted a lower vGRF impulse for all MPA impact that involved impact (R2 = 0.13 to 0.39, all p < 0.025).Validation MPA constructs that involved kinematic constructs (trunk stability, pelvis stability, and knee stability) are presented in Chapters 5-6. The purpose of Chapter 5 was to determine whether the 2D frontal plane angles of the trunk and pelvis at peak knee flexion were associated with the corresponding 3D angles during the MPA tasks that involved single limb contact with the ground. In addition, agreement between 2D/3D angles was assessed. 2D and 3D frontal plane angles for all tasks were correlated in a positive direction at the pelvis (r = 0.54 to 0.73, all p < 0.001) and trunk (r = 0.81 to 0.92, all p < 0.001). Absolute agreement in the frontal plane for all tasks and angles was below 5�. However, the 95% limits of agreement across tasks ranged from -12.8� to 21.3� for the pelvis and -11.8� to 9.4� for the trunk.The purpose of Chapter 6 was to establish whether the 2D frontal plane projection angle (FPPA) at peak knee flexion could be used to predict frontal plane knee moments (peak moment, average moment, moment at peak knee flexion) during each of the 6 MPA tasks. An increased FPPA (inward collapse of the knee) significantly predicted the peak frontal plane knee moment for 2 tasks (deceleration and side-step-cut, R2 = 0.12 to 0.25), average frontal plane knee moment for 5 tasks (drop jump, shuffle, deceleration, triple hop, side-step-cut, R2 = 0.15 to 0.40), and frontal plane knee moment at peak knee flexion for 5 tasks (drop jump, shuffle, deceleration, triple hop, side-step-cut, R2 = 0.16 to 0.45).Following concurrent validation of the 2D MPA metrics, Chapter 7 sought to determine if the movement domains evaluated as part of the MPA were relevant for predicting non-contact ACL re-injury (ipsilateral or contralateral). Female athletes who previously underwent ACL reconstruction (ACLR) (N=345) and who had previously undergone return to sport testing using the MPA were surveyed. The survey response rate was 53%. Females who sustained an ipsilateral or contralateral ACL re-injury (non-contact) within 36 months of returning to sport were considered as cases (n=23) and matched with 2-3 non-injured controls (n=61) based on age, graft type, sport level, and athletic exposures.Cluster analysis was conducted to separate female athletes in each movement domain into 2 subgroups, which were operationally defined as ?high injury risk? and ?low injury risk.? The underlying 2D angular measurements between subgroups differed significantly from each other (all p < 0.034), with a consistent pattern across tasks. Results from logistic regression analysis revealed that only the knee strategy movement domain was predictive of ACL re-injury. Compared to the ?low knee extensor bias? subgroup (defined by high 2D trunk-tibia angles across tasks), the odds of ACL re-injury were increased in the ?high knee extensor bias? subgroup (defined by low 2D trunk-tibia angles across tasks) (adjusted OR = 3.19, 95% CI: 1.02, 9.96, p = 0.046). A receiver operating characteristic curve showed an area under the curve of 78%, indicating fair prediction accuracy.Taken together, the results of this dissertation support the use of 2D video analysis across a wide range of athletic tasks to quantify movement impairments that have been hypothesized to be associated with elevated risk of ACL re-injury. Specifically, 2D measures to quantify pelvis stability, trunk stability, knee stability, shock absorption, and knee strategy can be used as reasonable clinical surrogates for more complex 3D measures obtained in a laboratory setting. In terms of predicting ACL re-injury (ipsilateral or contralateral), the movement domain that quantified use of the knee extensors relative to the hip extensors (knee strategy) was found to be relevant, with female athletes with a high knee extensor bias being at increased risk compared to those with a low knee extensor bias. Future studies are needed to verify these injury prediction results in prospective studies, establish task importance for quantifying knee strategy, and determine cutoffs that can be used in the clinical setting to distinguish between a high vs. low knee extensor bias.

Topic: Knee injuries and reconstruction techniques
Subfield: Surgery
Field: Medicine
Domain: Health Sciences