Associations between isometric quadriceps strength characteristics, knee flexion angles, and knee extension moments during single leg step down and landing tasks after anterior cruciate ligament reconstruction

Clinical Biomechanics 70 (2019) 231–236

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Associations between isometric quadriceps strength characteristics, knee flexion angles, and knee extension moments during single leg step down and landing tasks after anterior cruciate ligament reconstruction

T

Caroline Liseea, , Thomas Birchmeiera, Arthur Yanb, Christopher Kuenzea,b ⁎

a b

Michigan State University, Department of Kinesiology, College of Education, East Lansing, MI, USA Michigan State University, Division of Sports Medicine, College of Osteopathic Medicine, East Lansing, MI, USA

ARTICLE INFO

ABSTRACT

Keywords: Peak knee extension torque Rate of torque development Biomechanics ACLR

Background: It is unclear of how peak knee extension torque and early rate of torque development outcomes are related to lower extremity loading and sagittal plane movement in activities of daily living and landing tasks despite consistent deficits after anterior cruciate ligament reconstruction. The purpose of this cross-section study is to assess the ability of quadriceps strength characteristics to predict movement patterns during a step down and single leg drop crossover hopping tasks. Methods: Fifty-two individuals with a unilateral history of anterior cruciate ligament reconstruction completed three trials of the step down and crossover hopping tasks on their involved limb. Participants completed three isometric knee extension contractions at 90° knee flexion with visual feedback to assess peak knee extension torque and rate of torque development during the first 0–100 ms and 100–200 ms of the contraction. Findings: Peak knee extension torque explained the greatest variance in peak knee extension moment (R2 = 40.4%, p < 0.001) and knee flexion angle (R2 = 46.7%, p < 0.001) during the crossover hop landing. Rate of torque development (0–100 ms) was the only predictor of knee flexion angle (R2 = 19.8%, p = 0.01) at initial contact during the crossover hopping landing. Rate of torque development (100–200 ms) explained 17.6% of the variance in peak knee extension moment during the step down (p = .03). Interpretation: Peak knee extension torque and early rate of torque development outcomes demonstrate limited relationships between movement of activities of daily living and sport-specific tasks. These limitations should be considered when interpreting the results of isometric strength testing in a clinical setting.

1. Introduction Individuals with a history of anterior cruciate ligament reconstruction (ACLR) are at a six times greater risk of sustaining a secondary anterior cruciate ligament (ACL) injury within two years of surgery (Paterno et al., 2014) and a four times greater risk of developing knee osteoarthritis (OA) (Muthuri et al., 2011) within two decades of surgery compared to individuals without a history of ACLR. Mechanisms underlying the elevated risk of injury and development of chronic disease are complex and poor quadriceps function has been identified as a key modifiable risk factor for both processes (Grindem et al., 2016; Oiestad et al., 2015). Involved limb knee extension peak torque and quadriceps rate of torque development (RTD) outcomes provide unique information about the functional capacity of the quadriceps femoris muscle group; especially in its role as a sagittal plane knee joint stabilizer during activities of daily living (ADLs) and ⁎

sport-specific movements. Peak knee extension torque quantifies the overall ability of the quadriceps muscle to produce torque whereas RTD outcomes quantify how quickly the quadriceps muscle can produce peak torque. Early phases of quadriceps RTD during the first 100 (RTD100) and 200 (RTD200) milliseconds explain submaximal force production during the initial phases of muscle contraction. Unfortunately, many individuals with a history of ACLR experience persistent deficits in involved limb quadriceps function, including knee extension peak torque weakness and slower rate of torque development outcomes, for years after surgery (Kline et al., 2015; Tengman et al., 2014). Prospective studies (Paterno et al., 2010) and video analysis (Carlson et al., 2016) have identified high-risk movement patterns during maximal intensity sport specific movement associated with ACL injury. While the mechanism of ACL injury is multiplanar, lesser knee flexion angles and internal knee extension moments, especially during

Corresponding author at: Michigan State University, Department of Kinesiology, 308 W. Circle Drive #1, East Lansing, MI 48824, USA. E-mail address: [email protected] (C. Lisee).

https://doi.org/10.1016/j.clinbiomech.2019.10.012 Received 16 May 2019; Accepted 15 October 2019 0268-0033/ © 2019 Published by Elsevier Ltd.

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the earliest phases of ground contact, are associated with an increased risk of secondary ACL injury (Paterno et al., 2010; Yu and Garrett, 2007). Many ACL injuries occur during single leg landing tasks (Krosshaug et al., 2007) and assessments of the involved limb of single leg tasks reduce the masking of high-risk compensations from support of the contralateral limb (Wang, 2011). Peak knee extension torque is associated with this peak knee flexion angles during maximal intensity tasks such as landing (Ward et al., 2018) but may not capture how the muscle group helps control movement during early time points of landing such as at initial contact. Quadriceps RTD100 and RTD200 milliseconds may better quantify the ability of the quadriceps muscle group to control sagittal plane movement at initial ground contact. Understanding the roles that peak torque and RTD play in determining knee joint movement and loading characteristics during a demanding sport-related task would aid in clarifying the role that restoring quadriceps function may play in reduction of secondary in risk following ACLR. It is hypothesized that small magnitude alterations in lower extremity kinematics and kinetics during high volume ADLs may contribute to the development of knee post-traumatic OA (PTOA) after injury and subsequent ACLR (Andriacchi et al., 2009). This hypothesis is corroborated by studies identifying relationships impulsive loading, slow loading rates, and metabolic indicators of articular cartilage degeneration after ACLR (Pietrosimone et al., 2016a; Pietrosimone et al., 2017). Smaller knee flexion angles and knee extension moments are also associated with imaging-based indicators of poor knee articular cartilage joint health as early as one year after ACLR (Culvenor et al., 2016; Pamukoff et al., 2018). Poor quadriceps RTD100, and RTD200 is correlated with greater heel strike transient vertical ground reaction force (vGRF) and slower loading rates during ADLs among individuals with a history of ACLR (Blackburn et al., 2016). However, the relative contributions of peak knee extension torque and RTD outcomes have not been investigated among this population and remains unclear. Additionally, previous research (Blackburn et al., 2016; Pietrosimone et al., 2018) has focused on the relationships between quadriceps function and gait movement patterns, but it is important to also assess biomechanics of other submaximal tasks that are representative of common activities such as descending stairs. Based on these limitations in currently available knowledge, it may be helpful to better understand how quadriceps function effects knee joint biomechanics and lower extremity loading patterns during ADLs, as quadriceps function is clinically modifiable through structured strength training. Understanding which specific aspects of quadriceps function predict high-risk knee loading movement patterns after ACLR may help provide insight into impairment-based rehabilitation approaches dependent on tasks of varying intensity. Therefore, the purpose of this study is to assess which aspects of quadriceps function (peak knee extension torque, RTD100, and RTD200) are predictive of lower extremity loading (peak vGRF and linear loading rate), sagittal plane kinematics (knee flexion angle at initial contact and peak), and sagittal plane kinetics (knee extension moment at initial contact and peak) during a single leg step down (SLSD) and single leg drop crossover hop (SLC) task in individuals with a history of ACLR.

were recruited through advertisements on the university campus and local sports medicine clinics. Participants who sustained medial collateral ligament injuries (n = 5) or received concomitant surgical meniscal procedures (n = 28) at the time of ACLR were still included in the study. Participants were excluded if they had a history of bilateral ACLR, sustained a lower extremity injury within 6-week prior to testing, or had a chronic condition that impeded their ability to complete the single leg tasks. 2.2. Single leg task biomechanical assessment During the first session, participants completed the SLSD and SLC tasks. The two tasks completed in this study are representative of ADLs and sport specific movements, respectively. The SLSD is a submaximal intensity movement practiced early during rehabilitation and regularly completed during daily activities while the SLC task is a maximal intensity movement involving total body deceleration and change in direction. Biomechanical assessments of sagittal plane kinematic and kinetic outcomes (knee, hip, and trunk flexion excursion, hip and knee extension moment, and peak vGRF) were collected utilizing a tencamera motion capture system (Vicon Motion Systems Ltd., Oxford, UK) and a single embedded digital force plate (Advanced Medical Technology Inc., Watertown, USA). Kinematic and kinetic data were sampled at 240 Hz and 1200 Hz respectively. A total of eight clusters of four passive 14.0 mm reflective markers were affixed to the participants utilizing adhesive tape. Clusters were placed on the upper thoracic and lumber spine, lateral aspects of both thighs and shanks, and the dorsal surface of both feet (Chang et al., 2017). A stylus with four reflective markers was used to identify the 7th cervical spinous process, 5th lumbar spinous process, medial and lateral tibiofemoral joint lines, the inferior aspect of the medial and lateral malleoli and the tip of the second toe on each foot to estimate joint centers using a centroid method (Chang et al., 2017). The Bell method was used to calculate joint centers by identifying the right and left anterior superior iliac spine (Bell et al., 1990). Participants completed both tasks by stepping or jumping off a 30 cm box that was placed 40 cm away from the center of the force plate. For the SLSD task, participants were instructed to step down off the box onto the force plate and continue walking forward as if stepping off the final step of a set of stairs. A trial was considered successful if the participant's entire foot landed on the force plate after descending the step. For SLC task, participants were instructed to jump off the involved limb from a 30 cm box landing onto the force plate with the same limb. Immediately after landing on the force plate, participants hopped as far as possible diagonally along a line projecting 45° from the center of the force plate (Supplementary Fig. 1). A landing trial was considered successful if the participant was able to maintain balance on one leg upon landing. When the participants were instructed to land on their right limb, they hopped diagonally to the left and vice versa when instructed to land on their left limb. The distance of the hop was measured from the center of the force plate to the back of the participant's heel. Participants were offered the opportunity to practice the SLSD and SLC tasks until they felt confident, and then they successfully completed three trials of each task on involved limb. Right-handed Euler angle sequences with the order of rotation Y (sagittal plane), Z (frontal plane) and X (transverse plane) and inverse dynamics were used to calculate knee sagittal kinematics, knee sagittal kinetics and loading kinetics of the SLSD and SLC tasks which were imported and processed using the Motion Monitor software platform (Innovative Sports Training Inc., Chicago, USA). Data were filtered through a 4th order low pass Butterworth filter with a cut-off of 12 Hz for kinematic data and 100 Hz for kinetic data (Chang et al., 2017). The stance phase of both the SLSD and SLC tasks were defined as the point of initial contact with the force plate (vGRF > 10 N) to toe-off (vGRF < 10 N). Peak vGRF, knee extension moment and knee flexion angle were identified during the stance phase of both tasks. Knee

2. Methods This cross-sectional laboratory study included two sessions taking place at least 72 h apart (average amount of days between sessions = 8.3, SD = 4.4). The study was approved by the university's institutional review board and all participants who completed the study provided written informed consent before beginning the first session. 2.1. Participants Participants between the ages of 18 and 40 years old with a history of unilateral ACLR (average months since surgery = 37.8, SD = 23.8) 232

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extension moment and knee flexion angle were also identified at initial contact of both tasks. To improve interpretation, positive sagittal plane kinetic outcomes were set to indicate knee extension moment and negative outcomes were set to indicate knee flexion moment. All kinetic outcomes (vGRF, loading rate, and knee extension moment) were normalized to body weight (x BW). Linear loading rate was calculated as the slope of change in vGRF over change in time (x BW*s−1) during the stance phase of both tasks.

plane knee kinematics. The ability of quadriceps function outcomes to predict sagittal plane kinematics and kinetics during the SLSD and SLC were assessed using separate multiple linear regression models with forward entry. Sex defined as a dichotomous variable (0 = females, 1 = males) and time since surgery defined as a continuous variable were controlled for during the regression analyses. Multicollinearity was assessed using the variation inflation factor (VIF). A VIF greater than five indicates presence of multicollinearity among variables (Kutner and Neter, 2004). If multicollinearity exists, the quadriceps strength characteristic with a lower correlation to the biomechanical outcome will be removed from the analysis. Previous literature recommends including ten participants per predictor variable (Harrell Jr. et al., 1996). The current study which includes four potential predictor variables which requires a minimum of 40 participants to sufficiently evaluate the predictive relationships stated in the study hypotheses. Our study included 52 participants which exceeds the 40 participants necessary to power the study.

2.3. Quadriceps function assessment During the second session, participants completed a series of isometric knee extension contractions on a multi-mode dynamometer (Biodex Medical Systems Inc., Shirley, USA) to assess peak knee extension torque, RTD100, and RTD200. Isometric knee extension torque data were collected at 2000 Hz and exported to a lab computer via an A/D board (USB-6211, National Instruments, Austin, TX). Data were displayed using a customized Labview program (National Instruments, Austin, TX) which allowed participants to visualize real-time torque data on a nearby monitor during testing (Luc et al., 2016). Participants were seated in the dynamometer with 85° of hip flexion and 90° of knee flexion. Straps were placed securely over the participant's chest, hip, and thigh to reduce excessive movement during testing (Roberts et al., 2012). Participants warmed up by performing three trials of knee extension isometric contractions held for 5 s at 25%, 50% and 75% of perceived maximal exertion. The purpose of the warmup was to familiarize the participants with the isometric knee extension task and real-time visual feedback that they received throughout the test. Next, participants were instructed to complete maximal contractions by kicking out as hard and as fast as possible, sustaining a maximal isometric knee extension contraction for at least 3 s. Participants subsequently completed the knee extension contraction with oneminute rest in between each trial until the participant could no longer produce a peak torque larger than the previous trial. The greatest peak torque from the previous trials used to generate visual targets in the same customized Labview program during the final phase of testing. The first target line represented the peak knee extension torque achieved in the previous trial and the second target line represented 10% greater than the peak torque value. Participants were asked to complete two additional successful knee extension contraction trials with one-minute rest in between each repetition using the real-time visual feedback targets generated from the previous set of contractions (Luc et al., 2016). A trial was considered successful if the participants achieve torque greater than the torque of the first target line. Peak knee extension torque, RTD100, and RTD200 were calculated from the final two trials performed during the quadriceps strength assessment. Torque data were filtered using a 2nd order low pass Butterworth filter with a cutoff of 0.1 Hz. Knee extension contraction initiation was determined using a moving average filter that identified the first frame in which a change in torque > 3.0 Nm occurred within a 50-frame sampling window. Peak knee extension torque was calculated as the maximal torque produced during a trial. RTD100 was calculated as the slope of the torque-time curve from the point of contraction initiation to the data point corresponding with 100 ms following contraction initiation (Blackburn et al., 2016). RTD200 was calculated as the slope of the torque-time curve between the data points corresponding with 100 ms and 200 ms after contraction initation (Blackburn et al., 2016). The last two trials of all quadriceps strength characteristics (peak knee extension torque, RTD100, and RTD200) were averaged together and normalized to bodyweight (Nm/kg/s).

3. Results A total of 15 men and 37 women completed the two-session study. Participant characteristics, quadriceps strength outcomes, and task biomechanics are reported in Tables 1, 2 and 3 respectively. 3.1. SLSD task RTD200 explained 17.6% of the variance in peak knee extension moment during the SLSD task. Peak knee extension torque was entered in to the model and only explained 11.8% of the variance in linear loading rate, but it did not significantly contribute during the SLSD task. Quadriceps strength characteristics were not significantly predictive of vGRF, knee extension moment at initial contact, knee flexion angle at initial contact and peak knee flexion angle during the SLSD task (Table 4). 3.2. SLC task At least one quadriceps strength characteristic predicted each of the sagittal plane kinematic and kinetic variables. RTD100 explained 19.8% of the variance of knee flexion angle at initial contact during the SLC task. Together peak knee extension torque and RTD100 explained 57.9% of the variance in peak knee flexion angle during the SLC task. Peak knee extension torque also explained 16.4% and 40.4% of the variance in knee extension moment at initial contact and peak knee extension torque during the SLC task, respectively. Quadriceps strength characteristics were not significantly predictive of vGRF or linear loading rate during the SLC task (Table 5). 4. Discussion The purpose of this study was to assess whether measures of peak knee extension torque and quadriceps RTD are predictive of lower extremity loading characteristics, sagittal plane knee kinetics and sagittal Table 1 Participant and surgical characteristics (n = 52, 15 men/37 women).

2.4. Statistical analysis Means, standard deviations and ranges were calculated for all participant characteristics, quadriceps strength characteristics, lower extremity loading characteristics, sagittal plane knee kinetics and sagittal

Participant and surgical characteristics

Mean (SD)

Range

Age (years) Time since surgery (months) Height (m) Mass (kg) Graft source (n)

22.6 (4.4) [18, 36] 37.8 (23.8) [6, 90] 1.7 (0.1) [1.6, 2.0] 73.8 (12.1) [52.0, 98.3] 25 BPTB/19 HT/5 QT/2 ALLO

Abbreviations: SD = standard deviation, BPTP = bone patella tendon bone autograft, HS = hamstring autograft, QT = quadriceps tendon autrograft, ALLO = allograft. 233

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During the early phases of rehabilitation, clinicians incorporate rehabilitation interventions focused on reestablishing pain free walking and stair descent in individuals with ACLR (van Rossom et al., 2018). Despite clinician efforts, asymmetrical movement patterns still exist during these tasks. Involved limb internal knee extension moments, which are indicative of the quadriceps response to loading, are consistently smaller during walking (Slater et al., 2017) and descending stairs (Hajizadeh et al., 2016) when compared to the contralateral limb after ACLR. Previous research indicates that smaller knee extension moments during activities of daily living such as walking, are associated with the presence of MRI-based patellofemoral knee PTOA two years after ACLR (Culvenor et al., 2016). Therefore, regaining involved limb knee extension moments may help improve factors of mechanical loading associated with knee PTOA, but are difficult to assess clinically. In our study, quadriceps RTD200 explained 17.6% of the variance in peak knee extension moment during the SLSD task. These findings are consistent with those of Blackburn et al. (Blackburn et al., 2016) that reported small to moderate relationships between RTD100, RTD200 and high-risk movement patterns associated with knee PTOA development during walking, but no relationships with peak isometric knee extension torque. These results suggest that RTD measures may provide stronger assessments of movement patterns during activities of daily living compared to peak measures, but more sensitive assessment techniques should be developed. Non-contact ACL injury is hypothesized to occur within the first 50 milliseconds after initial contact during landing or cutting (Carlson et al., 2016). Symmetrical knee extension peak torque between limbs is associated with a reduced risk of ipsilateral and contralateral ACLR injury, but there is only a 3% injury risk reduction per every 1% percentage increase in knee extension torque symmetry (Grindem et al., 2016). Based on these findings, patients who restore involved limb peak knee extension torque may protect individuals from secondary ACL injury, but it is possible that other assessments of quadriceps function may demonstrate stronger relationships to high-risk movement patterns during the first 50 ms of landing. Furthermore ACL strain is greatest at knee flexion angles < 3009 which often occurs before individuals achieve peak knee flexion during landing or rapid directional change while running. In this study, all the participants demonstrated knee flexion angles < 300 at initial contact during the SLC task compared to only one participant who landed with < 300 degrees of peak knee flexion. Therefore, RTD measures of quadriceps strength, such as RTD100, have stronger relationships with knee flexion angles during early periods of landing near initial contact compared to maximal quadriceps strength outcomes. As individuals with ACLR continue through knee flexion range of motion during the task, our results indicate that peak knee extension torque is the primary explanatory quadriceps strength characteristic of peak knee flexion angle (R2 = 46.7%) with RTD100 to a lesser extent (∆R2 = 11.2%). Peak knee extension torque is also the only predictor of peak knee extension moment (R2 = 40.4%) during landing. Peak quadriceps strength outcomes demonstrate stronger association with peak sagittal plane

Table 2 Quadriceps strength characteristics during both tasks and hopping performance. Quadriceps strength characteristics

Mean (SD)

Range

Peak knee extension torque (Nm/kg) RTD100 (Nm/kg/s) RTD200 (Nm/kg/s) SLC Hop Distance (m)

2.72 7.55 8.67 1.25

[1.18, [3.32, [3.90, [0.70,

(0.78) (2.36) (2.63) (0.37)

4.49] 13.13] 15.32] 2.72]

Abbreviations: SD = standard deviation, RTD = rate of torque development, RTD100 = RTD within first 100 ms, RTD200 = RTD within first 100 to 200 ms.

plane knee kinematics during two different single leg tasks in a cohort of individuals with ACLR. Our primary findings indicate that greater peak knee extension torque is predictive of peak knee extension moment (R2 = 40.4%) and peak knee flexion angle (R2 = 46.7%) during the sport-related SLC task. Quadriceps strength characteristics including peak knee extension torque and RTD200 predicted linear loading rate (R2 = 11.8%) and peak knee extension moment (R2 = 17.6%) during the SLSD task, but the strength of these associations was weaker than the SLC task. Quadriceps strength characteristics are consistently associated with lower extremity loading characteristics, sagittal plane knee kinetics and sagittal plane knee kinematics in individuals with a history of ACLR, but the magnitude of these relationships are small. Isometric knee extension torque is one of the most commonly used assessment techniques during ACLR recovery to monitor a patient's rehabilitation progress (Curran et al., 2018) and guide return to play decisions due to the association between quadriceps weakness and risk of second ACL injury (Gokeler et al., 2017). The results of the study suggest that there are limitations in the ability of isometric knee extension torque to explain dynamic sagittal plane knee movement and knee joint loading during activities of daily living and sport specific tasks. The strongest association observed in the study was reported between peak knee extension torque and peak knee flexion angle during landing, but peak knee extension torque fails to explain > 50% of the variance of peak knee flexion angle. Furthermore, a weaker association exists between RTD measures of isometric strength and movement patterns of the SLSD task. Peak knee extension moments during activities of daily living demonstrate smaller magnitude relationships to isometric strength outcomes (R2 = 17.6%). Despite these limitations, isometric knee extension torque assessment should not be discouraged after ACLR due to its relationships to secondary knee injury risk (Grindem et al., 2016), self-reported knee function (Kuenze et al., 2015a; Pietrosimone et al., 2016b), and OA development (Oiestad et al., 2010). This assessment is clinically feasible, time-efficient and can be completed using an isokinetic or handheld dynamometer (Grindstaff et al., 2019). It also is a single test that can provides maximal rate and capacity assessments of quadriceps muscular capabilities through measures of early RTD outcomes and peak knee extension torque.

Table 3 Lower extremity loading, sagittal plane knee kinematics and sagittal plane knee kinetics during both tasks. Biomechanical outcomes

vGRF (x BW) Linear LR (x BW*s−1) Knee Ext. Moment at IC (x BW) Peak Knee Ext. Moment (x BW) Knee Flexion Angle at IC (°) Peak Knee Flexion Angle (°)

SLSD

SLC

Mean (SD)

Range

Mean (SD)

Range

1.85 (0.35) 18.47 (7.80) −0.06 (0.06) 0.92 (0.40) 2.50 (4.34) 39.07 (5.46)

[1.12, 2.84] [1.75, 41.63] [−0.25, 0.13] [0.20, 1.79] [−9.62, 8.84] [26.55, 50.10]

3.40 (0.53) 58.28 (16.11) −0.24 (0.11) 2.44 (0.63) 9.95 (5.76) 55.05 (11.79)

[1.97, 4.35] [25.33, 100.57] [−0.49, −0.03] [0.78, 3.46] [−2.31, 25.92] [27.58, 84.99]

Abbreviations: vGRF = vertical ground reaction force, LR = loading rate, BW = body weight, SLSD = single leg step down, SLC = single leg drop crossover hop, SD = standard deviation.

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Table 4 Multiple linear regression results for biomechanics of the SLSD. Variable

Predictor variables

Unstandardized β coefficients

Variance inflation factor

R2

p value

vGRF (x BW) Linear LR (x BW⁎s−1) Knee ext. moment at IC (⁎BW) Peak knee ext. moment (⁎BW) Knee flexion angle at IC (°) Peak knee flexion angle (°)

– Peak Knee Ext. Torque – RTD200 – –

– 3.946 – 0.066 – –

– 1.349 – 1.149 – –

– 0.118 – 0.176 – –

– 0.107 – 0.025 – –

Abbreviations : Ext = Extension, RTD = rate of torque development. ⁎ =p-value < .05. Table 5 Multiple linear regression results for biomechanics of the SLC. Variable

Predictor variables

Unstandardized β coefficients

Variation inflation factor

R2

p value

vGRF (x BW) Linear LR (x BW⁎s−1) Knee ext. moment at IC (⁎BW) Peak knee ext. moment (⁎BW) Knee flexion angle at IC (°) Peak knee flexion angle (°)

– – Peak knee ext. Torque Peak knee ext. Torque RTD100 Peak knee ext. Torque RTD100

– – 0.058 0.495 0.721 8.517 1.489

– – 1.349 1.349 1.049 1.422 1.105

– – 0.164 0.404 0.198 0.467 0.579

– – 0.034 < 0.001 0.013 < 0.001 < 0.001

Abbreviations: vGRF = vertical ground reaction force, LR = loading rateExt = Extension, RTD = rate of torque development, BW = body weight (N). ⁎ =p-value < .05.

kinematics and kinetics. Participants with poorer quadriceps RTD100 landed with smaller knee flexion angles at initial contact during the SLC task of which quadriceps RTD100 was the only significant predictor, though in a limited manner (R2 = 19.8%). Greater RTD100 of the vastus lateral muscle is associated with greater muscle activation and theoretically representative of improved neural drive and efferent motor output (Andersen et al., 2010). While static measures of isometric quadriceps contraction do not reflect dynamic knee stability, it does support extensive literature indicating neural quadriceps deficits after ACLR. Individuals with ACLR need to produce greater neural drive to overcome cortical inhibition (Lepley et al., 2015) which results in slower and delayed contraction of the quadriceps muscle. Poor voluntary quadriceps muscle activation has been associated with involved limb peak knee flexion angles during a bilateral landing task in individuals with ACLR (Ward et al., 2018). However, future research should explore the potential relationship between learned movement pattern of “stiff” landing mechanics during the initial phases of landing related to elevated injury risk (Paterno et al., 2010) and sensitive measures of quadriceps neural activation (i.e. corticomotor excitability, and spinal reflex excitability that are persistently decreased after ACLR (Kuenze et al., 2015b; Lepley et al., 2015). Some limitations should be considered when interpreting the results of this study. The method used for identifying quadriceps muscle contraction initiation differed from other studies which may limit the comparison of results between the studies (Blackburn et al., 2016). This study also did not incorporate the use of EMG assessment which has the benefit of recording muscle group activation during dynamic tasks (Capin et al., 2017). Instead, this study sought to utilize clinical measures of muscular strength to improve translation of results to the clinical setting. Prior studies have utilized manual identification of contraction initiation (Blackburn et al., 2016), but we utilized a moving filter to identify the first change > 3 Nm of raw torque signal within 50 frames. We believe this method improves intra- and inter-rater reliability that may introduced through manual identification. Additionally, RTD100 and RTD200 have previously been associated with quadriceps neural activation and muscle morphology but were not measured in this study.

5. Conclusions Peak knee extension torque and early quadriceps RTD outcomes are associated lower extremity loading characteristics and sagittal plane knee biomechanics during ADLs and more challenging sport-related movements in individuals with a history of ACLR. More specifically, these results provide preliminary evidence of associations between RTD strength outcomes and movement patterns during activities of daily living and sport-specific landing tasks, while peak strength outcomes are only associated with peak outcomes during sport-specific landing task. Regardless, the magnitudes of these relationships are small to moderate depending on the task and more sensitive measures should be assessed in future studies. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.clinbiomech.2019.10.012. Funding sources Funding: This work was supported by National Athletic Trainers' Association Research and Education Foundation Professional Football Athletic Trainers Society Doctoral Grant (Grant #1617DGP007), USA. Declaration of competing interest None. References Andersen, L.L., Andersen, J.L., Zebis, M.K., Aagaard, P., 2010. Early and late rate of force development: differential adaptive responses to resistance training? Scand. J. Med. Sci. Sports 20 (1), e162–e169. https://doi.org/10.1111/j.1600-0838.2009.00933.x. Andriacchi, T.P., Koo, S., Scanlan, S.F., 2009. Gait mechanics influence healthy cartilage morphology and osteoarthritis of the knee. J. Bone Joint Surg. Am. 91 (Suppl. 1), 95–101. https://doi.org/10.2106/JBJS.H.01408. Bell, A.L., Pedersen, D.R., Brand, R.A., 1990. A comparison of the accuracy of several hip center location prediction methods. J. Biomech. 23 (6), 617–621. Blackburn, J.T., Pietrosimone, B., Harkey, M.S., Luc, B.A., Pamukoff, D.N., 2016. Quadriceps function and gait kinetics after anterior cruciate ligament reconstruction. Med. Sci. Sports Exerc. 48 (9), 1664–1670. https://doi.org/10.1249/mss. 0000000000000963. Capin, J.J., Khandha, A., Zarzycki, R., Manal, K., Buchanan, T.S., Snyder-Mackler, L., 2017. Gait mechanics and second ACL rupture: implications for delaying return-to-

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