Load Distribution in the Lumbar Spine During Modeled Compression Depends on Lordosis

Identification of a lumped-parameter model of the intervertebral joint from experimental data

Through predictive simulations, multibody models can aid the treatment of spinal pathologies by identifying optimal surgical procedures. Critical to achieving accurate predictions is the definition of the intervertebral joint. The joint pose is often defined by virtual palpation. Intervertebral joint stiffnesses are either derived from literature, or specimen-specific stiffnesses are calculated with optimisation methods. This study tested the feasibility of an optimisation method for determining the specimen-specific stiffnesses and investigated the influence of the assigned joint pose on the subject-specific estimated stiffness. Furthermore, the influence of the joint pose and the stiffness on the accuracy of the predicted motion was investigated. A computed tomography based model of a lumbar spine segment was created. Joints were defined from virtually palpated landmarks sampled with a Latin Hypercube technique from a possible Cartesian space. An optimisation method was used to determine specimen-specific stiffnesses for 500 models. A two-factor analysis was performed by running forward dynamic simulations for ten different stiffnesses for each successfully optimised model. The optimisations calculated a large range of stiffnesses, indicating the optimised specimen-specific stiffnesses were highly sensitive to the assigned joint pose and related uncertainties. A limited number of combinations of optimised joint stiffnesses and joint poses could accurately predict the kinematics. The two-factor analysis indicated that, for the ranges explored, the joint pose definition was more important than the stiffness. To obtain kinematic prediction errors below 1 mm and 1° and suitable specimen-specific stiffnesses the precision of virtually palpated landmarks for joint definition should be better than 2.9 mm.

Biomechanical analysis of the tandem spinal external fixation in a multiple-level noncontiguous lumbar fractures model: a finite element analysis

Objective

This study aimed to investigate the biomechanical characteristics of the tandem spinal external fixation (TSEF) for treating multilevel noncontiguous spinal fracture (MNSF) using finite element analysis and provide a theoretical basis for clinical application.

Methods

We constructed two models of L2 and L4 vertebral fractures that were fixed with the TSEF and the long-segment spinal inner fixation (LSIF). The range of motion (ROM), maximum stresses at L2 and L4 vertebrae, the screws and rods, and the intervertebral discs of the two models were recorded under load control. Subsequently, the required torque, the maximum stress at L2 and L4 vertebrae, the screws and rods, and the intervertebral discs were analyzed under displacement control.

Results

Under load control, the TSEF model reserved more ROM than the LSIF model. The maximum stresses of screws in the TSEF model were increased, while the maximum stresses of rods were reduced compared to the LSIF model. Moreover, the maximum stresses of L2 and L4 vertebrae and discs in the TSEF model were increased compared to the LSIF model. Under displacement control, the TSEF model required fewer moments (N·mm) than the LSIF model. Compared to the LSIF model, the maximum stresses of screws and rods in the TSEF model have decreased; the maximum stresses at L2 and L4 in the TSEF model were increased. In the flexion condition, the maximum stresses of discs in the TSEF model were less than the LSIF model, while the maximum stresses of discs in the TSEF model were higher in the extension condition.

Conclusion

Compared to LSIF, the TSEF has a better stress distribution with higher overall mobility. Theoretically, it reduces the stress concentration of the connecting rods and the stress shielding of the fractured vertebral bodies.

Musculoskeletal spine modeling in large patient cohorts: how morphological individualization affects lumbar load estimation

Introduction: Achieving an adequate level of detail is a crucial part of any modeling process. Thus, oversimplification of complex systems can lead to overestimation, underestimation, and general bias of effects, while elaborate models run the risk of losing validity due to the uncontrolled interaction of multiple influencing factors and error propagation. Methods: We used a validated pipeline for the automated generation of multi-body models of the trunk to create 279 models based on CT data from 93 patients to investigate how different degrees of individualization affect the observed effects of different morphological characteristics on lumbar loads. Specifically, individual parameters related to spinal morphology (thoracic kyphosis (TK), lumbar lordosis (LL), and torso height (TH)), as well as torso weight (TW) and distribution, were fully or partly considered in the respective models according to their degree of individualization, and the effect strengths of these parameters on spinal loading were compared between semi- and highly individualized models. T-distributed stochastic neighbor embedding (T-SNE) analysis was performed for overarching pattern recognition and multiple regression analyses to evaluate changes in occurring effects and significance. Results: We were able to identify significant effects (p < 0.05) of various morphological parameters on lumbar loads in models with different degrees of individualization. Torso weight and lumbar lordosis showed the strongest effects on compression (β ≈ 0.9) and anterior-posterior shear forces (β ≈ 0.7), respectively. We could further show that the effect strength of individual parameters tended to decrease if more individual characteristics were included in the models. Discussion: The induced variability due to model individualization could only partly be explained by simple morphological parameters. Our study shows that model simplification can lead to an emphasis on individual effects, which needs to be critically assessed with regard to in vivo complexity. At the same time, we demonstrated that individualized models representing a population-based cohort are still able to identify relevant influences on spinal loading while considering a variety of influencing factors and their interactions.

Invasiveness of decompression surgery affects modeled lumbar spine kinetics in patients with degenerative spondylolisthesis

Introduction: The surgical treatment of degenerative spondylolisthesis with accompanying spinal stenosis focuses mainly on decompression of the spinal canal with or without additional fusion by means of a dorsal spondylodesis. Currently, one main decision criterion for additional fusion is the presence of instability in flexion and extension X-rays. In cases of mild and stable spondylolisthesis, the optimal treatment remains a subject of ongoing debate. There exist different opinions on whether performing a fusion directly together with decompression has a potential benefit for patients or constitutes overtreatment. As X-ray images do not provide any information about internal biomechanical forces, computer simulation of individual patients might be a tool to gain a set of new decision criteria for those cases. Methods: To evaluate the biomechanical effects resulting from different decompression techniques, we developed a lumbar spine model using forward dynamic-based multibody simulation (FD_MBS). Preoperative CT data of 15 patients with degenerative spondylolisthesis at the level L4/L5 who underwent spinal decompression were identified retrospectively. Based on the segmented vertebrae, 15 individualized models were built. To establish a reference for comparison, we simulated a standardized flexion movement (intact) for each model. Subsequently, we performed virtual unilateral and bilateral interlaminar fenestration (uILF, bILF) and laminectomy (LAM) by removing the respective ligaments in each model. Afterward, the standardized flexion movement was simulated again for each case and decompression method, allowing us to compare the outcomes with the reference. This comprehensive approach enables us to assess the biomechanical implications of different surgical approaches and gain valuable insights into their effects on lumbar spine functionality. Results: Our findings reveal significant changes in the biomechanics of vertebrae and intervertebral discs (IVDs) as a result of different decompression techniques. As the invasiveness of decompression increases, the moment transmitted on the vertebrae significantly rises, following the sequence intact ➝ uILF ➝ bILF ➝ LAM. Conversely, we observed a reduction in anterior-posterior shear forces within the IVDs at the levels L3/L4 and L4/L5 following LAM. Conclusion: Our findings showed that it was feasible to forecast lumbar spine kinematics after three distinct decompression methods, which might be helpful in future clinical applications.

Effect of neglecting passive spinal structures: a quantitative investigation using the forward-dynamics and inverse-dynamics musculoskeletal approach

Purpose: Inverse-dynamics (ID) analysis is an approach widely used for studying spine biomechanics and the estimation of muscle forces. Despite the increasing structural complexity of spine models, ID analysis results substantially rely on accurate kinematic data that most of the current technologies are not capable to provide. For this reason, the model complexity is drastically reduced by assuming three degrees of freedom spherical joints and generic kinematic coupling constraints. Moreover, the majority of current ID spine models neglect the contribution of passive structures. The aim of this ID analysis study was to determine the impact of modelled passive structures (i.e., ligaments and intervertebral discs) on remaining joint forces and torques that muscles must balance in the functional spinal unit. Methods: For this purpose, an existing generic spine model developed for the use in the demoa software environment was transferred into the musculoskeletal modelling platform OpenSim. The thoracolumbar spine model previously used in forward-dynamics (FD) simulations provided a full kinematic description of a flexion-extension movement. By using the obtained in silico kinematics, ID analysis was performed. The individual contribution of passive elements to the generalised net joint forces and torques was evaluated in a step-wise approach increasing the model complexity by adding individual biological structures of the spine. Results: The implementation of intervertebral discs and ligaments has significantly reduced compressive loading and anterior torque that is attributed to the acting net muscle forces by -200% and -75%, respectively. The ID model kinematics and kinetics were cross-validated against the FD simulation results. Conclusion: This study clearly shows the importance of incorporating passive spinal structures on the accurate computation of remaining joint loads. Furthermore, for the first time, a generic spine model was used and cross-validated in two different musculoskeletal modelling platforms, i.e., demoa and OpenSim, respectively. In future, a comparison of neuromuscular control strategies for spinal movement can be investigated using both approaches.

Multibody Models of the Thoracolumbar Spine: A Review on Applications, Limitations, and Challenges

Numerical models of the musculoskeletal system as investigative tools are an integral part of biomechanical and clinical research. While finite element modeling is primarily suitable for the examination of deformation states and internal stresses in flexible bodies, multibody modeling is based on the assumption of rigid bodies, that are connected via joints and flexible elements. This simplification allows the consideration of biomechanical systems from a holistic perspective and thus takes into account multiple influencing factors of mechanical loads. Being the source of major health issues worldwide, the human spine is subject to a variety of studies using these models to investigate and understand healthy and pathological biomechanics of the upper body. In this review, we summarize the current state-of-the-art literature on multibody models of the thoracolumbar spine and identify limitations and challenges related to current modeling approaches.

Augmenting the Cobb angle: Three-dimensional analysis of whole spine shapes using Bézier curves

BACKGROUND AND OBJECTIVE

The identification and classification of pathological spinal deformities poses a major challenge to any diagnostician. First, available medical images are usually two-dimensional projections, obscuring elaborated spatial information. Second, several measurement techniques with different thresholds for certain clinical syndromes make it difficult to classify measured results. Here, a method is presented to augment and standardize the analysis of spinal shapes in three dimensions.

METHODS

Regarding the first limitation, (semi-)automatic, three-dimensional segmentation techniques of medical images have already been developed. To overcome the second, we propose here a representation of the whole spine by a Bézier curve using the vertebral centers as control points. After normalization, a differential-geometric approach yields information on curvature and torsion at each spinal level as well as in between.

RESULTS

Based on literature data and multi-body simulations, we show how these quantities alter with individual posture and during motion. Robustness with respect to missing data is investigated. Approaches towards the identification of spinal disorders are motivated.

CONCLUSION

Our results emphasize the need for individualizable identification and classification of spinal deformities and give an outlook on how it might be achieved. The presented methodology constitutes the first fully three-dimensional analysis of spinal shapes, i.e. without the requirement of certain physiological planes (e.g. the sagittal plane) or landmarks (e.g. the apex vertebra).