Dynamic simulation of knee joint mechanics: individualized multi-moment finite element modelling of patellar tendon stress during landing.

Journal: Journal of biomechanics
Published Date:

Abstract

Patellar tendinopathy is prevalent in sports requiring high jumping demands, and understanding the in vivo biomechanical behavior of the patellar tendon (PT) during landing is crucial for developing effective injury prevention and rehabilitation strategies. This study investigates the in vivo biomechanical behavior of the PT during the landing phase of a stop-jump task, integrating musculoskeletal modelling, finite element analysis (FEA), and a high-speed dual fluoroscopic imaging system (DFIS). A subject-specific knee joint model was constructed from CT, MRI, and dynamic X-ray data for a 27-year-old male (178 cm, 68 kg) at six time points during landing. Musculoskeletal simulations were used to estimated knee joint moments and quadriceps muscle forces, which were then applied to the finite element models. DFIS ensured accurate 3D spatial alignment of the models. Ridge regression analysis explored the relationship between applied biomechanical loads and the maximum equivalent (von Mises) stress in the PT. Maximum PT stress was observed at the bone attachment sites, with the highest stress (94.44 MPa) at initial ground contact, decreasing to a minimum of 16.37 MPa during landing. Regression analysis demonstrated a significant correlation (R = 0.859, P < 0.001) between knee flexion moments, quadriceps muscle forces, and maximum PT stress, identifying these factors as key determinants of PT loading. This study underscores the importance of knee flexion moments and quadriceps muscle forces in influencing PT stress during landing. Future studies should include larger cohort to validate these results and explore the potential of machine learning for real-time injury risk prediction.

Authors

  • Fengping Li
    Faculty of Sports Science, Ningbo University, Ningbo, China.
  • Dong Sun
    Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong 999077, China. medsun@cityu.edu.hk.
  • Yang Song
    Biomedical and Multimedia Information Technology (BMIT) Research Group, School of IT, University of Sydney, NSW 2006, Australia. Electronic address: yson1723@uni.sydney.edu.au.
  • Zhanyi Zhou
    Faculty of Sports Science, Ningbo University, Ningbo, China.
  • Dongxu Wang
    Department of Gastroenterology, The 983rd Hospital of Joint Logistic Support Force of PLA, Tianjin, China.
  • Xuanzhen Cen
    Faculty of Sports Science, Ningbo University, Ningbo, China.
  • Qiaolin Zhang
    Doctoral School on Safety and Security Sciences, Óbuda University, Budapest, Hungary.
  • Zixiang Gao
    Center for Digital Dentistry, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digi-tal Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Research Center of Engineering and Technology for Computerized Dentistry, Beijing 100081, China.
  • Yaodong Gu
    Faculty of Sports Science, Ningbo University, Ningbo 315211, China.