Image-Driven Subject-Specific Spine Models: Developing a Novel Tool to Measure In-Vivo Loading

Description

This presentation by David Williams provides an overview of a collaborative project with the University of Exeter, aimed at understanding spinal disorders through innovative assessment methods. The project addresses the significant prevalence of back pain, affecting over 7 million people in the UK, and seeks to develop finite element models to provide subject-specific insights into spinal forces. By utilizing advanced imaging techniques such as MRI, the research aims to derive specific material properties for spinal tissues and evaluate them against physiological measures during various movements.



The presentation outlines three main components of the research: in vitro, in silico, and in vivo studies. It details how MRI is employed to capture both anatomical structures and tissue properties, contributing to more accurate modeling of spinal biomechanics. The ongoing work includes the implementation of testing protocols involving various test specimens to establish a comprehensive database of mechanical properties.



Williams highlights efforts in developing a self-learning finite element model based on in vitro testing data, connected to real-time physiological data acquired through advanced imaging techniques. He also discusses the complexities and challenges of conducting in vivo assessments, including the use of a biplane X-ray system to verify model accuracy under various movements, notably during activities like flexion and lifting.



The initial pilot data collected from human participants is discussed, with a focus on the results from electromagnetic capture experiments that will ultimately feed into musculoskeletal models aimed at improving understanding of spinal disorders and potential treatments. The future of the project will include further data collection from more participants to enhance model validation and provide clearer insights into the dynamics of back pain and treatment efficacy.

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