University of Illinois Urbana-Champaign

Predicting peak load of the femoral neck using structural parameters

Currier, Eric J

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CURRIER-THESIS-2016.pdf

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https://hdl.handle.net/2142/92669

Description

Title
Predicting peak load of the femoral neck using structural parameters
Author(s)
Currier, Eric J
Issue Date
2016-07-21
Director of Research (if dissertation) or Advisor (if thesis)
Kersh, Mariana
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2016-11-10T17:49:12Z
Keyword(s)
  • Osteoporosis
  • Femoral Neck
  • Cortical Bone
  • microCT
  • Bone Quality
Abstract
The current clinical standard for diagnosing osteoporosis uses measurements of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA). This measurement only partially explains the strength of bones and fails to incorporate other factors that alter bone quality. The aim of this study was to investigate how micro and macro cortical bone structures along the length of the femoral neck relate to the peak load of the proximal femur. Structural measurements were taken from microCT images of ten murine right femurs at ten locations along the femoral neck. These specimens were then tested to failure. The major diameter, minor diameter, cortical thickness, cross sectional area, cortical area, and cortical fraction were measured and correlated to the peak compressive load. The highest significant correlation was found using major diameter (R2 = 0.6) or cross sectional area (R2 = 0.59). Significant correlations for the major diameter were found between 40% - 60% along the femoral neck, while cross sectional area had significant correlations between 40% - 80% of the femoral neck. By combining major diameter and cortical area in a multivariable regression, R2 improved to 0.66. Understanding the contribution of cortical structure to peak load will allow for improved characterization of bone properties in both healthy and diseased bone, and provide indices for targeted imaging to better diagnosis osteoporosis.
Graduation Semester
2016-08
Type of Resource
text
Permalink
http://hdl.handle.net/2142/92669
Copyright and License Information
Copyright 2016 Eric Currier

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