Elsevier

Clinical Biomechanics

Volume 23, Issue 5, June 2008, Pages 536-544
Clinical Biomechanics

Quality of motion considerations in numerical analysis of motion restoring implants of the spine

https://doi.org/10.1016/j.clinbiomech.2007.12.010Get rights and content

Abstract

Background

Motion restoring implants function in a dynamic environment that encompasses the full range of spinal kinematics. Accurate assessment of the in situ performance of these devices using numerical techniques requires model verification and validation against the well-established nonlinear quality of motion of the spine, as opposed to the previous norm of matching kinematic endpoint metrics such as range of motion and intervertebral disc pressure measurements at a single kinematic reference point.

Methods

Experimental data was obtained during cadaveric testing of nine three-functional spinal unit (L3–S1) lumbar spine segments. Each specimen was tested from 8 Nm of applied flexion moment to 6 Nm of applied extension moment with an applied 400 N compressive follower preload. A nonlinear kinematic curve representing the spinal quality of motion (applied moment versus angular rotation) for the index finite element model was constructed and compared to the kinematic responses of the experimental specimens. The effect of spinal soft tissue structure mechanical behaviors on the fidelity of the model’s quality of motion to experimental data was assessed by iteratively modifying the material representations of annulus fibrosus, nucleus pulposus, and ligaments.

Findings

The present work demonstrated that for this model, the annulus fibrosus played a small role in the nonlinear quality of motion of the model, whereas changes in ligament representations had a large effect, as validated against the full kinematic range of motion. An anisotropic continuum representation of the annulus fibrosus was used, along with nonlinear fabric representations of the ligaments and a hyperelastic representation of the nucleus pulposus.

Interpretation

Our results suggest that improvements in current methodologies broadly used in numerical simulations of the lumbar spine are needed to fully describe the highly nonlinear motion 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.

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    Current address: Brigham Young University, Department of Mechanical Engineering, Provo, UT, USA.

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