Multiscale Structure-based Mechanical Modeling of the Human Spine Lumbar Facet Capsular Ligament

Abstract

Low back pain (LBP) is a major health issue affecting millions of Americans with annual health cost of nearly $100 million. Although LBP is generally associated with degenerative processes, since such processes are multifactorial, nearly 90% of patients are diagnosed with non-specific LBP which leads to poor treatments. The lumbar facet capsular ligament (FCL), located on the posterior protrusions of the spine, has been increasingly suggested to play a critical role in LBP. The lumbar FCL is richly innervated with mechanoreceptors (nociceptors) which could potentially undergo excessive deformation and subsequently trigger pain signals. As such, understanding the mechanical behavior of the nerves embedded in FCL remains critical in terms of understanding LBP mechanisms. The overarching goal of this dissertation is to develop a multiscale structure-based computational model which connects the physiological spine motions (~cm scale) to the heterogeneous deformation field on the FCL (~mm scale) and that to the mechanical response metrics of the underlying nerve fibers (~microm scale). First, imaging studies were performed to obtain the heterogeneous collagen fiber architecture in the lumbar FCL specimens. These structural data were then incorporated in a multiscale FE model to mimic the mechanical behavior of the specimens during biaxial tests. Next, a coupled fiber-nerve model was developed to quantify the mechanical response of the nerves embedded in the FCL's extracellular matrix which was modeled as a network of fibers with varying architectures subjected to various types of loading cases. Next, fiber mapping and geometry morphing techniques were implemented to construct multiscale FE models of the lumbar FCL on the facet joint undergoing various spinal motions. These models were used to obtain strain fields on the FCL, and finally, these strain results were used to estimate the mechanical response of the nerves. The multiscale FE model developed in this work provides us with a tool to explore the mechanical behavior of the underlying nerves in cases of different pathologies, which is an integral step in understanding the neural mechanisms leading to LBP.