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A Development on the Musculoskeletal Modeling of the Spine Using Image- based Kinematics to Predict Intervertebral Loads

Eskandari, Amir Hossein | 2019

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 51851 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Farahmand, Farzam; Arjmand, Navid
  7. Abstract:
  8. pain is one of the most common musculoskeletal (MS) disorders and the most important cause of functional disability in developed and developing countries. Several studies showed that the most important factor in development of the low back pain is loads and stresses in different parts of the spine. While non-invasive measurement of these internal loads and stresses, as a tool to estimate the risk of injury, is very difficult and costly, biomechanical models of the spine are the best meansfor analyzing the risk of injury in various in-vivo activities. In order to develop a spine model, it is necessary to measure the kinematics of the vertebrae for the specified activity. In previous studies, skin-mounted devices were used for this purpose. These devices do not have the ability to measure the kinematics of the individual lumbar vertebrae and, in addition, they have a considerable error due to the movement of the device on the skin. Therefore, the aim of this study was to develop a musculoskeletal model that uses image-based kinematics to predict intervertebral loads.
    While traditional spine models use force-displacement-control approach (by applying rotational kinematics, external loads and then calculating muscle forces), recent advances in medical imaging techniques have allowed pure displacement-control trunk models to estimate spinal loads with no need to calculate muscle forces. Sensitivity of these models to the errors in post-imaging evaluation of displacements (reported to be ~0.4-0.9° and 0.2–0.3 mm in vertebral displacements) has not yet been investigated. A Monte Carlo analysis was therefore used to assess the sensitivity of results in both musculoskeletal (MS) and passive finite element (FE) spine models to errors in measured displacements. Six static activities in upright standing, flexed, and extended postures were initially simulated using a force-control hybrid MS-FE model. Computed vertebral displacements were subsequently used to drive two distinct fully displacement-control MS and FE models. Effects of alterations in the reference vertebral displacements (at 3 error levels with SD (standard deviation) = 0.1, 0.2, and 0.3 mm in input translations together with, respectively, 0.2, 0.4, and 0.6° in input rotations) were investigated on the model predictions. Results indicated that outputs of both models had substantial taskdependent sensitivities to errors in the measured vertebral translations. For instance, L5-S1 intradiscal pressures (IDPs) were considerably affected (SD values reaching 1.05 MPa) and axial compression and shear forces even reversed directions as translation errors increased to 0.3 mm. Outputs were however generally much less sensitive to errors in measured vertebral rotations. Accounting for the accuracies in image-based kinematics measurements, therefore, it is concluded that the current measured vertebral translation errors at and beyond 0.1 mm are too large to drive biomechanical models of the spine.
    At the next step, due to the high sensitivity of the pur displacement-control models to the translational errors, an image-based kinematics measurement approach was used to drive a subject-specific (musculature, geometry, mass, and center of masses) MS models using force-displacement-control approach. Kinematics of the thorax, pelvis, and individual lumbar vertebrae as well as disc inclinations, gravity loading, and musculature were all measured via different imaging techniques. The model estimated muscle and lumbar forces in various upright and flexed postures in which kinematics were obtained using upright fluoroscopy via 2D/3D image registration. Predictions of this novel image-kinematics-driven model (Img-KD) were compared with those of the traditional kinematics-driven (T-KD) model in which individual lumbar vertebral rotations were assumed based on thorax-pelvis orientations. Results indicated that while differences between Img-KD and T-KD models remained small for the force in the global muscles (attached to the thoracic cage) (<15%), L4-S1 compression (<15%), and shear (<20%) forces in average for all the simulated tasks, they were relatively larger for the force in the local muscles (attached to the lumbar vertebrae). Assuming that the skin-based measurements of thorax and pelvis kinematics are accurate enough, the T-KD model predictions of spinal forces remain reliable
  9. Keywords:
  10. Musculoskeletal Modeling ; Image Registration ; Sensitivity Analysis ; Monte Carlo Method ; Spinal Loads

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