Quality of motion considerations in numerical analysis of motion restoring implants of the spine
Introduction
It is well-established through experimental testing that the spine demonstrates a nonlinear “quality of motion”. This term is meant to represent the characteristically nonlinear mechanical response when spinal segments are loaded at physiologic magnitudes. Ideally, non-fusion surgical treatment modalities for the spine such as dynamic stabilization/motion preservation, and more recently (Khoueir et al., 2007), motion restoration should also adequately capture this quality of motion in to reflect implant loading, spine kinematics and tissue load sharing. It is important for the instrumented spines to capture not only the range of motion (motion endpoints), but also mimic as closely as possible, the characteristic nonlinear profile of the moment vs angular displacement pattern. Given that finite element analysis (FEA) is gaining widespread use during the design process for spinal devices, it is of utmost importance that FEA also be able to accurately reflect spine segment quality of motion.
Currently accepted model validation and subsequent analysis of these models typically involves review of single point response behaviors at range of motion endpoints or peak tissue stresses (Noailly et al., 2005, Vadapalli et al., 2006). Most current finite element models of the spine incorporate nonlinearity through cartilaginous facet contact and in the material representations of the ligaments or annulus fibrosus. Single point responses are not capable of fully describing the nonlinear quality of motion experienced by these models during physiologic loading. Furthermore, using single point response metrics to analyze results prevents the modeler from determining the effect of nonlinear contributions from the multiple soft tissues that comprise a spinal motion segment or multiple-functional spinal units. Information from finite element models regarding the array of kinematic responses is critical to motion restoring spine arthroplasty devices and may also be relevant to understanding the behavior of partially fused treatments (Bono et al., 2007).
Finite element models can be powerful tools when used during design optimization stages and for evaluation of designs during device development (Denoziere and Ku, 2006). Motion restoring technologies have been designed to physiologically reproduce the biomechanics of the healthy spine post implantation. Reproduction of the limits of motion during activities of daily living as a design objective, rather than reproduction of the whole motion path, could result in a non-physiologic loading of the implants and surrounding tissues, and lead to morphological, pathological and load sharing changes in the tissues due to disuse or overload during the duty cycle of the device after implantation. The goals of motion restoring therapies are distinct from those of traditional fusion devices and necessitate a broader and more descriptive means to characterize the biomechanical performance of the natural and pathological anatomy, as well as that of the surgically reconstructed spinal segment. These devices are designed not only to restore the physiological range or limits of motion, but also to properly restore the “quality of motion” of the operated segment to that of an intact spinal segment.
Though some recent finite element analyses have included validation of the kinematic quality of motion (Guan et al., 2006, Rohlmann et al., 2006), the origins of nonlinearity in lumbar spine biomechanics have not been fully explored nor validated. The highly nonlinear nature of lumbar spine kinematics, especially in flexion–extension and lateral bending, are a result of the interaction of the multiple nonlinear subsystems of the spine, such as ligaments, intervertebral discs, nucleus pulposus, muscles and cartilaginous facet contact. Therefore, the objective of this study was to characterize the effects of individual soft tissue structures on lumbar spine nonlinearity in a finite element model calibrated against the full quality of motion of intact spine experimental data. We hypothesized that the annulus fibrosus plays the dominant role in contributing to model nonlinearity.
Section snippets
Index finite element model
A previously validated (Bowden and Villarraga, 2006) finite element model of a lower lumbar (L4–L5) motion segment was used as the index model in this study (Fig. 1). The geometry of the model was based on commercially available skeletal surface models of the spine representative of an average 50th percentile male (Digimation, St. Rose, LA, USA). Cancellous bone and intervertebral disc structures were meshed using structured hexahedral elements. Cortical bone, vertebral endplates, cartilage and
Results
Our previously reported work showed that the index configuration of the lumbar FSU model accurately reproduced the range of motion endpoints and intradiscal pressures of the cadaveric tests (Fig. 2). However, in contrast to the well-reported bi-concave sigmoidal shape seen experimentally, the resulting flexion–extension quality of motion was mostly linear. Subsequent changes in soft tissue constitutive models and material parameters provided varying degrees of improvement in the quality of
Discussion
Clinical relevance must be considered during development of any biomechanical experiment, whether numerical, laboratory, or in vivo (An and Masuda, 2006). In the case of motion restoring spinal implants, it is important to look beyond single point validation metrics, especially since typical human motions are not conducted at one extreme of motion or another, but rather at various intermediate stages of motion. A motion restoring implant must be effective and biomechanically accurate at all
Acknowledgement
Research funding for this project was provided by Archus Orthopedics.
References (40)
- et al.
In situ biomechanics of total facet replacement using finite element analysis
Spine J.
(2006) - et al.
Biomechanical properties of spinal ligaments and a histological study of the supraspinal ligament in traction
J. Biomech.
(1985) - et al.
Biomechanical comparison between fusion of two vertebrae and implantation of an artificial intervertebral disc
J. Biomech.
(2006) - et al.
Degeneration affects the fiber reorientation of human annulus fibrosus under tensile load
J. Biomech.
(2006) - et al.
Contribution of disc degeneration to osteophyte formation in the cervical spine: a biomechanical investigation
J. Orthop. Res.
(2001) - et al.
Trabecular bone modulus-density relationships depend on anatomic site
J. Biomech.
(2003) - et al.
Response of Charite total disc replacement under physiologic loads: prosthesis component motion patterns
Spine J.
(2005) - et al.
Effect of compressive follower preload on the flexion–extension response of the human lumbar spine
J. Orthop. Res.
(2003) - et al.
Determination of trunk muscle forces for flexion and extension by using a validated finite element model of the lumbar spine and measured in vivo data
J. Biomech.
(2006) - et al.
Relevance of in vitro and in vivo models for intervertebral disc degeneration
J. Bone Joint Surg. Am.
(2006)
Role of intra-abdominal pressure in the unloading and stabilization of the human spine during static lifting tasks
Eur. Spine J.
Finite Element Procedures
Residual sagittal motion after lumbar fusion: a finite element analysis with implications on radiographic flexion–extension criteria
Spine
A finite element model of the L5–S1 functional spinal unit: development and comparison with biomechanical tests in vitro
Comput. Meth. Biomech. Biomed. Eng.
The use of helical axis of motion and facet joint load information in the evaluation of nonfusion spinal implants: concept and preliminary results
Roundtable Spine Surg.
New insight into the mechanics of the lumbar interspinous ligament
Spine
An anisotropic constitutive model for annulus tissue and enhanced finite element analysis of intact lumbar disc bodies
Comput. Meth. Biomech. Biomed. Eng.
Multi-segment FEA of the human lumbar spine including the heterogeneity of the annulus fibrosus
Comput. Mech.
Anisotropic and inhomogeneous tensile behavior of the human anulus fibrosus: experimental measurement and material model predictions
J. Biomech. Eng.
The effect of nucleotomy on lumbar spine mechanics in compression and shear loading
Spine
Cited by (47)
Intuitive assessment of modeled lumbar spinal motion by clustering and visualization of finite helical axes
2021, Computers in Biology and MedicineCitation Excerpt :There has been a long-standing discussion to standardize test protocols for spinal device testing before implantation [55]. Motion-preserving implants are being particularly favored due to better clinical outcomes [56,57]. Computational analysis is one integral part of proposed and established test protocols.
Finite Element Based-Analysis for Pre and Post Lumbar Fusion of Adult Degenerative Scoliosis Patients
2019, Spine DeformityCitation Excerpt :The orientations of the collagen fibers were defined with a 30° or 150° angle from the horizontal surface defined by the bottoms of intervertebral discs [24,33]. All seven major ligaments (anterior longitudinal ligament, posterior longitudinal ligament, flaval ligament, facet capsular ligament, intertransverse ligament, interspinous ligament, and supraspinous ligament) were meshed by 4-node shell elements [34]. The mechanical behaviors of the ligaments were described using nonlinear stress-strain curves [34].
Finite element method-based study of pedicle screw–bone connection in pullout test and physiological spinal loads
2019, Medical Engineering and PhysicsCitation Excerpt :The screw-inserted vertebrae contained from 259,834 to 357,136 elements when inserted with non-simplified screws and 221,762 elements when inserted with simplified screw. Rigid connections between the pedicle screws and rods were assigned in this study [26,27]. Bonded connections were assumed between the ligaments and bony tissues.
Stress distribution in vertebral bone and pedicle screw and screw–bone load transfers among various fixation methods for lumbar spine surgical alignment: A finite element study
2019, Medical Engineering and PhysicsCitation Excerpt :The facet cartilage joints were modeled as a soft frictionless contact with an initial gap of 0.5 mm (Zander et al., 2009). All seven major ligaments (anterior longitudinal ligament (ALL), posterior longitudinal ligament (PLL), flaval ligament (FL), facet capsular ligament (CL), intertransverse ligament (ITL), interspinous ligament (ISL), and suspraspinous ligament (SSL)) were meshed by 4-node shell elements (Bowden et al., [24]). Local muscle forces and upper body weight in lumbar spine were simulated by a compressive follower load with optimized path through the vertebrae (Dreischarf et al., [25]).
Efficient probabilistic finite element analysis of a lumbar motion segment
2017, Journal of BiomechanicsFinite element method-based study for effect of adult degenerative scoliosis on the spinal vibration characteristics
2017, Computers in Biology and Medicine
- 1
Current address: Brigham Young University, Department of Mechanical Engineering, Provo, UT, USA.