Document Type

Thesis

Date of Degree

Spring 2017

Access Restrictions

Access restricted until 07/13/2018

Degree Name

MS (Master of Science)

Degree In

Biomedical Engineering

First Advisor

Jessica E. Goetz

Second Advisor

Nicole M. Grosland

Abstract

Osteoarthritis is a chronic, deleterious disease of the joints. It currently affects nearly 25 million Americans. Clinically, osteoarthritis presents as joint pain and verified by radiographic evidence of joint space narrowing. Unfortunately, symptomatic osteoarthritis describes the later stages of disease, at which point irreversible cartilage and bone damage has occurred. Cross-sectional imaging modalities offer the promise of visualizing early features of disease, enabling the development and evaluation of interventions to forestall or prevent degenerative change. Modalities of clinical interest include magnetic resonance imaging (MRI) and multi-detector computed tomography (MDCT).

The following work describes the efficacy of MRI-derived measures for the identification and accurate quantification of local and whole joint changes in articular cartilage thickness changes in vivo. This was performed as part of a study investigating the diagnostic potential of clinical morphometric and compositional MRI to identify early features of osteoarthritis in a large animal model of traumatic knee joint injury. Surgically induced trauma consisted of a partial medial meniscectomy and blunt impact of either 0 J, 0.6 J, or 1.2 J to the weight-bearing cartilage of the medial femur. The study was six months in duration. To evaluate the accuracy of MRI-derived measures of cartilage thickness, imaging acquired at time of euthanasia was compared to high-resolution contrast-enhanced micro-computed tomography (micro CT). 3-dimensional multimodal analysis demonstrated that morphometric MRI imaging is sensitive to sub-voxel changes in cartilage thickness. Therefore, MRI is a clinically relevant modality to quantify subtle cartilage damage, thereby presenting an opportunity to identify patients earlier in the disease process.

Keywords

biomechanics, imaging, knee, orthopedics, osteoarthritis

Pages

xv, 79 pages

Bibliography

Includes bibliographical references (pages 67-76).

Copyright

Copyright © 2017 David James Heckelsmiller

Available for download on Friday, July 13, 2018

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