Date of Award

Winter 12-15-2019

Author's School

McKelvey School of Engineering

Author's Department

Biomedical Engineering

Degree Name

Doctor of Philosophy (PhD)

Degree Type



Low back pain (LBP) is a devastating musculoskeletal ailment that impacts majority of the global population. Up to 95% of cases are considered nonspecific where the origin is unclear. Although there is a diagnosis with these cases, there lacks specificity that would help individuals with treatment and pain management. Imaging techniques such as magnetic resonance imaging (MRI) are primarily utilized in the diagnosis of LBP as it illuminates internal structures of the spine. One important structure clearly identified with MRI is the intervertebral disc (IVD) that is susceptible to injury and disease. Further, diagnostic imaging is performed lying down where the spine and IVD are under reduced mechanical loads. It may be more informative to image individuals standing up as the loads are up to five times greater than lying down The importance of standing is expounded with many people experiencing pain while in this posture. Additionally, there are relevant populations that exhibit inducible LBP symptoms during prolonged standing. Accordingly in this population these participants are termed pain developers (PDs) and non-pain developers (NPDs). Previous studies have offered insight into global anatomical and physiological mechanisms of the PDs and NPDs, however, there are few studies that examine internal joint mechanics of the spine especially within the IVD.Therefore this dissertation attempts to identify structural and tissue-level adaptations that occur in standing that may inform on LBP diagnostic criteria. Additionally, pinpoint factors that may demonstrate the magnitude of the pain development. These questions were investigated through three separate aims. The first aim explores the importance of standing and sets out to prove that a positional MRI is valid in detecting geometric IVD changes. This was completed by imaging individuals in a positional MRI in supine and standing, and obtaining measurements related to the spinal structure such as the Cobb angle, segmental Cobb angle, anterior-to-posterior (A/P) height ratio, and IVD width. The second aim combines the technique developed in aim one with a population with inducible LBP symptoms. Participants were imaged in a positional MRI for 105 minutes while obtaining self-reported pain scores every 15 minutes. Statistical analyses were utilized to investigate if separation of and NPDs was possible and then if the measurements were associated to the PDs pain rating. The third and final aim combines the imaging data with finite element models and artificial neural network techniques for further exploration of the rich dataset. The finite element model was run on a single lumbar IVD for all participants to evaluate differences in intradiscal strains between PDs and NPDs. The neural network explored the data obtained from structural measurements, pain parameters, and important strains to examine relationships that may have been missed with individual approaches.This work will aid in understanding factors associated with LBP development in standing through the combination of imaging, mechanical and statistical models, and hopefully provide new insights into clinical diagnosis, treatment and therapeutics.


English (en)


Simon Y. Tang

Committee Members

Philip V. Bayly, Michael D. Harris, Lori A. Setton, Matthew J. Silva,


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