ECSS Paris 2023: OP-BM01
INTRODUCTION: Muscle mechanical action underpinning our movements is mostly determined by its architecture (1). The muscle architecture has been extensively examined in vivo by ultrasonography (2), but its use is limited to certain small muscles because of a limited field of view (3). We still poorly understand how giant muscles in the deep part of the body form and act in living humans. By a novel 3D architectural analysis based on MRI, we examined in-vivo architecture and the potential action of the human adductor magnus (AM), one of the giant leg muscles classified as a hip adductor. We hypothesized that the primary action of AM is hip “extension” rather than adduction, considering its configuration similar to hamstrings. METHODS: For 14 healthy young adults (9 males), thousands of muscle fascicles were automatically reconstructed over the whole AM at the hip neutral position with diffusion tensor MRI and tractography (4,5). The muscle physiological cross-sectional area, and each fascicle’s line of action and moment arm length about the hip joint were determined for the medial/proximal/lateral region divided based on insertion positions. Then, the product of these parameters was calculated as an estimate of the maximal isometric torque-generating capacity (potential torque: PT). The peak torque during maximal voluntary contraction for the isometric hip extension/adduction was measured at the hip neutral and 45° flexed positions on a dynamometer. The paired t-test and linear regression analyses were performed. RESULTS: Most AM fascicles ran parallel to the femur, showing hamstring-like orientations in 3D. The proximal and lateral regions showed comparable PTs between the hip extension and adduction. In the medial region, however, the hip extension PT was 6-fold greater than the adduction PT (p<0.01). Consequently, the whole AM (sum of all regions) had a greater PT for the hip extension (42±15 Nm) than adduction (29±15 Nm, p=0.02). The hip extension PT of the whole AM was strongly correlated with dynamometer-measured hip extension peak torque at both hip neutral and flexed positions (r=0.71–0.87, p≤0.01), but that was not the case for the hip adduction (r=0.42–0.59, p≥0.05). CONCLUSION: The results clearly indicate that AM primarily acts for hip extension rather than adduction, although it has been assumed a major adductor. The AM may thus play as a strong motor rather than a stabilizer in human locomotion such as sprint running demanding forceful hip extension. The present study redefining muscular action through the in-vivo 3D architectural analysis would motivate us to rename human muscles (e.g., “extensor” magnus) and rethink their functional role, providing novel insights into proper exercise selection for effectively improving motor performance in sports and rehabilitation. REFERENCES 1) Lieber & Friden, Muscle Nerve, 2000 2) Narici et al., J Appl Physiol, 2003 3) Franchi et al., Ultrasound Med Biol, 2018 4) Takahashi et al., J Anat, 2022 5) Takahashi et al., Med Sci Sports Exerc, 2023
Read CV Katsuki TakahashiECSS Paris 2023: OP-BM01
INTRODUCTION: Over the last 20 years, several studies showed that muscle-tendon interactions play a major role in movements (1). However, it remains unknown how the changes in muscle architecture due to training could influence these interactions. Eccentric studies have demonstrated an increase of the fascicle length following training in various muscles of the lower limb (2), and recently the benefits of training at high muscle length has been highlighted to induce more muscle adaptations, like hypertrophy or increase in fascicle length (3). Thus, the first aim of the current study is to investigate the potential change of fascicle behavior and tendon properties following an eccentric training at different muscle length. The second aim is to explore how these changes impact muscle-tendon interactions in vertical jump and running. METHODS: 28 participants were randomised in two groups, High Length (HL) vs Short Length (SL). They performed 8 weeks (24 sessions) of eccentric training on the calf muscles at different range of motion (ROM). Measurements were made PRE and POST training. Fascicle length of the gastrocnemius medialis (GM) was measured with an ultrasound apparatus during maximal voluntary contractions (MVC) at 5 angles, eccentric contraction and through rate of force development (RFD) explosive contractions. We also estimated the stiffness of the Achilles tendon (AT) during ramp and RFD contractions. Finally, we measured the fascicle behavior of the GM during maximal vertical jumps (hopping and countermovement jump) and submaximal running. RESULTS: We found a significant change of the fascicle length for HL group (+7%, p<0,05) during passive condition, but only before the slack length. No difference was found for the SL group. Torque increased in both groups in isometric (HL +8%, SL +13% at 0°, p<0,01) and eccentric contraction (HL +18,7%, SL +12,9%, p<0,01) but no interactions group x time were found. No significant change in fascicle length was observed during MVC, and no change in optimal length was detected in both groups. RFD did not change in both groups after training. AT Stiffness increased significantly for HL group (+29,9%, p<0,05) but not in SL group. Data from vertical jumps and running are still in processing. CONCLUSION: No significant effects were found for fascicle-tendon interactions during maximal monoarticular contractions (RFD, MVC), suggesting that changes in muscle-tendon behavior (tendon stiffness and fascicle length) found in HL group does not impact the dynamic behavior of fascicles. We assume that these two factors offset each other’s influence during contractions. Multi-joint maximal (jumps) and submaximal (running) tasks will provide a deeper understanding of the training effects on fascicle-tendon interactions. REFERENCES: 1) Ishikawa & Komi, Exerc. Sport Sci. Rev., 2008 2) Duclay et al., Muscle and Nerve, 2009 3) Marusic et al., SJMSS, 2020
Read CV Tristan TallioECSS Paris 2023: OP-BM01
INTRODUCTION: Return-to-sport (RTS) assessments often involve evaluations of movement execution, e.g. in jump landings, to identify deficits in movement control and connected risks for re-injury [1]. For RTS after anterior cruciate ligament (ACL) injury, the current literature offers a plethora of kinematic variables in various jump tests that clinicians may use to guide the RTS decision [1]. To better integrate RTS movement assessments in fast-paced clinical decision-making, it may be useful to investigate the most sensitive jump test and variable combinations for detecting movement deficits. The purpose of the current study was to compare the sensitivity of three commonly used jump tests for detecting movement characteristics influenced by either an ACL injury history, a provoked fatigue status, or a combination of both. METHODS: A total of 43 volunteers were recruited into ACL group (n=21, 11 females) and control group (n=22, 12 females). 3D motion data (Vicon, 250 Hz) were recorded during a single-leg hop (SLH), unilateral counter movement jump (uCMJ) and a unilateral cross-over hop (COH) before and after a fatigue-inducing intervention (single-leg squats and step ups). Thirteen joint angles from lower body, trunk and pelvis (50ms after initial contact) representing the landing posture were calculated through inverse kinematics in OpenSim. One combined principal component (PC) analysis was computed for all three jumps to characterize kinematic synergies. Six distinct logistic regression models (three jumps, fatigued/non-fatigued, alpha = .05) were calculated to predict ACL injury history. Three additional models predicted fatigue status. The predictors consisted of twelve PC scores. RESULTS: In all three jump landings, the logistic regression models were able to detect an ACL injury history (Chi²= 4.974, p<.026) but not fatigue status (Chi²=2.165, p>.141). When predicting ACL injury history, the highest sensitivity (76%) and classification rates (77%) were achieved for SLH (p<.001) and uCMJ (p<.001) when participants were fatigued. The worst sensitivity (67%) and classification (63%) was achieved for non-fatigued COH (p=.026). The SLH and uCMJ models consistently relied on the same two PCs, which described the correlation between frontal and transverse knee, hip and trunk angles. CONCLUSION: In our data-driven analysis, the SLH and uCMJ appear more sensitive for detecting movement characteristics related to a previous ACL injury compared to the COH. Furthermore, our results support the recommendation to include fatigued conditions during RTS tests post-ACL injury [2]. The finding that our approach could not predict fatigue status could mean that (1) fatigue effects were non-systematic or (2) the between-subject variance in PC scores blurred smaller within-subject fatigue effects. Either way, the observation of an unsuccessful prediction makes it less likely that the classification by injury history was due to chance. [1] Kaplan, Sports Health, 2019 [2] Dingenen, Sports Med, 2017
Read CV Maité CalistiECSS Paris 2023: OP-BM01