Integrating MRI-based geometry, composition and fiber architecture in a finite element model of the human intervertebral disc.

Intervertebral disc degeneration is a common disease that is often related to impaired mechanical function, herniations and chronic back pain. The degenerative process induces alterations of the disc's shape, composition and structure that can be visualized in vivo using magnetic resonance imaging (MRI). Numerical tools such as finite element analysis (FEA) have the potential to relate MRI-based information to the altered mechanical behavior of the disc. However, in terms of geometry, composition and fiber architecture, current FE models rely on observations made on healthy discs and might therefore not be well suited to study the degeneration process. To address the issue, we propose a new, more realistic FE methodology based on diffusion tensor imaging (DTI). For this study, a human disc joint was imaged in a high-field MR scanner with proton-density weighted (PD) and DTI sequences. The PD image was segmented and an anatomy-specific mesh was generated. Assuming accordance between local principal diffusion direction and local mean collagen fiber alignment, corresponding fiber angles were assigned to each element. Those element-wise fiber directions and PD intensities allowed the homogenized model to smoothly account for composition and fibrous structure of the disc. The disc's in vitro mechanical behavior was quantified under tension, compression, flexion, extension, lateral bending and rotation. The six resulting load-displacement curves could be replicated by the FE model, which supports our approach as a first proof of concept towards patient-specific disc modeling.

[1]  P. Zysset,et al.  Human intervertebral disc stiffness correlates better with the Otsu threshold computed from axial T2 map of its posterior annulus fibrosus than with clinical classifications. , 2014, Medical engineering & physics.

[2]  Stephen J Ferguson,et al.  Minimizing errors during in vitro testing of multisegmental spine specimens: considerations for component selection and kinematic measurement. , 2007, Journal of biomechanics.

[3]  Derek K. Jones,et al.  Diffusion‐tensor MRI: theory, experimental design and data analysis – a technical review , 2002 .

[4]  C. Pfirrmann,et al.  Magnetic Resonance Classification of Lumbar Intervertebral Disc Degeneration , 2001, Spine.

[5]  L. Setton,et al.  Mechanobiology of the intervertebral disc and relevance to disc degeneration. , 2006, The Journal of bone and joint surgery. American volume.

[6]  Tipu Z. Aziz,et al.  Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner , 2011, NeuroImage.

[7]  Takayuki Obata,et al.  Classification of intervertebral disk degeneration with axial T2 mapping. , 2007, AJR. American journal of roentgenology.

[8]  F. Marchand,et al.  Investigation of the Laminate Structure of Lumbar Disc Anulus Fibrosus , 1990, Spine.

[9]  Jutta Ellermann,et al.  Disc Degeneration Assessed by Quantitative T2* (T2 Star) Correlated With Functional Lumbar Mechanics , 2013, Spine.

[10]  Raúl San José Estépar,et al.  On Diffusion Tensor Estimation , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  G. Johnson,et al.  Magnetic Resonance Microscopy of the C57BL Mouse Brain , 2000, NeuroImage.

[12]  M. Adams,et al.  What is Intervertebral Disc Degeneration, and What Causes It? , 2006, Spine.

[13]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[14]  R. Hill Elastic properties of reinforced solids: some theoretical principles , 1963 .

[15]  E. Hsu,et al.  Diffusion tensor microscopy of the intervertebral disc anulus fibrosus , 1999, Magnetic resonance in medicine.

[16]  R. Ogden,et al.  A robust anisotropic hyperelastic formulation for the modelling of soft tissue. , 2014, Journal of the mechanical behavior of biomedical materials.

[17]  Ping Chung Leung,et al.  Modified Pfirrmann Grading System for Lumbar Intervertebral Disc Degeneration , 2007, Spine.

[18]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[19]  Gerhard A. Holzapfel,et al.  An Anisotropic Model for Annulus Tissue and Enhanced Finite Element Analyses of Intact Lumbar Disc Bodies , 2001 .

[20]  A. Rohlmann,et al.  What have we learned from finite element model studies of lumbar intervertebral discs in the past four decades? , 2013, Journal of biomechanics.

[21]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[22]  H. Brisby Pathology and possible mechanisms of nervous system response to disc degeneration. , 2006, The Journal of bone and joint surgery. American volume.

[23]  R. Ogden,et al.  A New Constitutive Framework for Arterial Wall Mechanics and a Comparative Study of Material Models , 2000 .

[24]  Wafa Skalli,et al.  Inter-lamellar shear resistance confers compressive stiffness in the intervertebral disc: An image-based modelling study on the bovine caudal disc. , 2015, Journal of biomechanics.

[25]  Michael M. Morlock,et al.  Compressive strength of elderly vertebrae is reduced by disc degeneration and additional flexion. , 2015, Journal of the mechanical behavior of biomedical materials.

[26]  B. D. Boss,et al.  Anisotropic Diffusion in Hydrated Vermiculite , 1965 .

[27]  Jianru Wang,et al.  Low back pain associated with lumbar disc herniation: role of moderately degenerative disc and annulus fibrous tears. , 2015, International journal of clinical and experimental medicine.