ECSS Paris 2023: OP-BM11
INTRODUCTION: Quantification of the anatomical cross-sectional area (ACSA) of the patellar tendon is clinically relevant for monitoring tendon adaptations, injuries, and rehabilitation outcomes. Although several openly available and validated tools exist for automatic segmentation of muscle ACSA, no open-source and peer-reviewed solution is currently available for the patellar tendon. Therefore, the aim of this study was to develop and evaluate an automatic approach for patellar tendon ACSA segmentation from ultrasound images and to compare its performance with manual analysis. METHODS: Ultrasound images were obtained from 30 participants (age: 46.87 ± 6.03 years; BMI: 25.45 ± 4.14 kg/m²). Transverse images were acquired at 25%, 50%, and 75% of the patellar tendon length. To determine the consistency of the reference method, intra-rater and inter-session reliability were assessed using manual ACSA segmentation. A total of 497 labeled images were used to train and test three neural networks for automatic segmentation. Model performance was evaluated by comparing automatic and manual measurements using intraclass correlation coefficients (ICC), standard error of measurement (SEM), mean absolute error (MAE), and standardized mean difference (SMD). Additionally, model inter-session reliability was also examined. RESULTS: Manual intra-rater reliability was good (ICC = 0.804; 95% CI: 0.628–0.902), with SEM = 0.05 cm² (0.03–0.07) and MAE = 0.05 cm² (0.04–0.07). Inter-session reliability of manual segmentation was excellent (ICC = 0.980; 95% CI: 0.970–0.987), with SEM = 0.02 cm² (0.02–0.02) and MAE = 0.02 cm² (0.01–0.02). After exclusion of erroneous automatic predictions, agreement between automatic and manual segmentation was excellent (ICC = 0.918; 95% CI: 0.821-0.955), with SEM = 0.05 cm² (0.04–0.07) and MAE = 0.05 cm² (0.05–0.06). A small standardized mean difference was observed (SMD = 0.53; 95% CI: 0.33–0.75). Model inter-session reliability was moderate (ICC = 0.708; 95% CI: 0.471–0.849). Automatic analysis time per image ranged from 0.302 to 0.414 s. CONCLUSION: The proposed automatic segmentation approach enables rapid and less operator-dependent assessment of patellar tendon ACSA from ultrasound images. While some differences between manual and automatic measurements and moderate model inter-session reliability were observed, the method demonstrates acceptable agreement and substantial time efficiency. With cautious implementation and appropriate quality control, this open-source tool may provide valuable support for clinical assessment and research applications involving patellar tendon morphology.
Read CV Alberto GuzziECSS Paris 2023: OP-BM11
INTRODUCTION: The mechanical properties of the Achilles tendon (AT) are fundamental to elastic energy storage and athletic performance. However, conventional assessment methods are often limited to static, single-point measurements or require cumbersome laboratory setups, failing to capture the tendon's behavior across its functional range of motion. This study aimed to establish a standardized "Functional Stiffness Spectrum" of the AT in elite male athletes using a portable force-ultrasound fusion device and to evaluate its reliability and sensitivity in detecting sport-specific adaptations. METHODS: Sixty elite male athletes (ranking top 8 in national-level, e.g., basketball, volleyball, football, sprint, long distance running and tennis) participated. AT shear modulus (G) was quantified using a portable force-ultrasound fusion system (M5, Xijian Technology, Beijing, China) employing a novel biomechanical inverse analysis algorithm to ensure measurement precision. A custom-designed protocol was employed to assess the tendon under six distinct conditions: a relaxed baseline and five fixed ankle angles (0°, 20° plantarflexion (PF), 40° PF, 20° dorsiflexion (DF), 40°DF), stabilized by an adjustable rigid boot. Intra-trial reliability was assessed using the coefficient of variation (CV). Linear mixed models (LMM) were used to analyze the effects of ankle angle, sport type and limb dominance on tendon stiffness. RESULTS: The protocol successfully mapped a non-linear increase in stiffness from PF (slack) to DF (tension) (p < 0.001). Crucially, a significant Angle × Sport interaction (p = 0.049) was observed, indicating that stiffness adaptations are angle-specific rather than uniform. Post-hoc analyses revealed that differences were most pronounced in the mid-range of the spectrum: At 20° PF: Basketball players (ES=0.58) and Long-distance runners (ES=0.62 ) exhibited significantly higher tendon stiffness compared to Tennis players (p < 0.05). At Neutral Position (0°): Basketball players continued to display significantly higher stiffness than Tennis players (ES= 0.66). At 40° Plantarflexion (Slack): no significant differences were found among sports, suggesting a convergence of mechanical properties under minimal load. Intra-trial reliability was high (CV < 0.25) within these functional ranges. CONCLUSION: This study demonstrates that AT stiffness is not a singular constant but a dynamic spectrum that adapts specifically to sport demands. Basketball players and Long-distance runners possess stiffer tendons at functional plantarflexion angles (20°PF and 0°), likely an adaptation to enhance elastic energy return during repetitive sagittal-plane activities (jumping and running). In contrast, Tennis players exhibit greater compliance in this range, potentially to accommodate multi-directional court movements. Consequently, athletic screening must assess stiffness across the functional spectrum, as single-point measurements may fail to capture these critical, sport-specific mechanical signatures.
Read CV Wenpu YangECSS Paris 2023: OP-BM11
INTRODUCTION: The lumbar multifidus muscle is fundamental for spinal stabilization and trunk movement, and changes in its mechanical properties, particularly stiffness, have been associated with low back pain [1,2]. Shear wave elastography by SuperSonic Imaging (SSI) offers a non-invasive method to assess in vivo muscle stiffness through the shear modulus (μ) [3]. Although static stretching is commonly prescribed to alleviate symptoms and improve mobility, no studies have investigated changes in muscle stiffness during stretching. Therefore, this study aimed to examine the behavior of the lumbar multifidus µ in both superficial and deep layers at the L4–L5 level before, during, and after a session of static stretching.. METHODS: Twenty-two healthy men participated in the study. The study was approved by the Ethical Committee (nº 3.672.989), and all participants provided informed consent. Participants had not engaged in stretching practice for at least one year and had no history of low back pathology. The protocol included SSI elastography assessment of lumbar multifidus stiffness at rest, during, and after a single 3-minute static stretching intervention, where they sat on their heels, with maximum trunk flexion and arms extended forward. Functional test (Schober test) was performed before and after stretching. RESULTS: Functional test performance improved significantly after stretching. No significant differences in μ were observed between layers before the intervention. However, immediately after stretching, multifidus μ was significantly lower in the deep layer than in the superficial layer. Considering the change in μ from the first to the last minute of stretching for each layer, K-means clustering identified two response patterns during stretching: responders (reduction in µ) and non-responders (increase µ). For the superficial layer, half of the participants were classified as responders and the remaining half as non-responders, whereas in the deep layer, 75% were classified as responders. CONCLUSION: A single 3-minute session of static trunk flexion stretching improved functional mobility, which may be attributed to other muscles and connective tissues involved in the stretching maneuver. The multifidus deep layer exhibited lower stiffness than the superficial layer only after stretching, suggesting a region-specific effect of the intervention. During stretching, distinct response patterns were observed among participants, with most showing a tendency toward decreased stiffness in the deep layer. These findings support the use of SSI elastography to assess individual tissue behavior during the intervention and highlight the importance of considering interindividual variability in responses to stretching. REFERENCES: 1. Masaki M et al. Clin Biomech, 2017. 2. Koppenhaver et al. Musculoskelet Sci Prat, 2020. 3. Gennisson et al. Diagn Interv Imaging, 2013.
Read CV Liliam OliveiraECSS Paris 2023: OP-BM11