Osteoporosis is a bone disease associated with fracture risk. Accurate assessments of fracture risk, guidelines to initiate preventive intervention, and monitoring treatment response are of paramount importance in public health. Clinically, osteoporosis is defined by low bone mineral density, which explains 65-75% of the variance in bone stiffness. The remaining variability is due to the cumulative and synergistic effects of various factors, including trabecular bone micro-architecture. Osteoporostic imaging is critically important in identifying fracture risks for planning of therapeutic intervention and monitoring response to treatments. In this work, quantitative analysis of trabecular bone micro-architecture using volumetric imaging techniques and computational biomechanical simulation through finite element modeling (FEM) are applied on in vivo imaging for various human studies. The ability of imaging methods in characterizing trabecular bone micro-architecture was experimentally examined using MRI and multi-row detector CT. They were found suitable for cross-sectional and longitudinal studies in monitoring changes of trabecular micro-architectural quality in clinical research. A framework which consists of robust segmentation of in vivo images and quality mesh generator, was constructed for FEM analysis. The framework was experimentally demonstrated effcient and effective to predict bone strength under limited spatial resolution. The ability of distinguishing bone strengths of different groups were evaluated on various human studies. And the relation between FEM and image-based micro-architectural measures was explored. Quantitative analysis supports the hypothesis that trabecular bone have distinct structural properties in different anatomic sites and the osteoporosis related change of the micro-architecture also varies. It highlight the importance of standardizing the definition of bone scan locations and the segmentation of such well-defined regions. A shape modeling method was proposed to solve the problem and its application in human proximal femur using MRI were presented. The method was compared with manual segmentation and found highly accurate. Together with tools developed for quantitative analysis, this work facilitates future researches of trabecular bone micro-architecture in different anatomic sites.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-6843 |
| Date | 01 December 2016 |
| Creators | Chen, Cheng |
| Contributors | Saha, Punam K. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright © 2016 Cheng Chen |
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