A protocol for physiological mechanical testing of cortical bone using digital volume correlation

Rogalski, Michael

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https://hdl.handle.net/2142/113929 Copy

Description

Title

A protocol for physiological mechanical testing of cortical bone using digital volume correlation

Author(s)

Rogalski, Michael

Issue Date

2021-12-10

Director of Research (if dissertation) or Advisor (if thesis)

Kersh, Mariana E

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

Keyword(s)

• Cortical bone
• digital volume correlation
• femur
• mechanical testing
• finite element analysis
• muscle forces
• osteoporosis

Abstract

As we age, an imbalance and uncoupling in the remodeling process deteriorates the intracortical network and subsequently weakens our bones. Impaired mechanical strength, structural degradation, and deficient material composition point to a loss of bone quality that leads to osteoporosis. As bone quality and strength decrease, patients become at high risk for osteoporotic fractures during a fall or other atypical loading conditions. Among these fractures, femoral neck fractures (or cervical hip fractures) lead to high mortality rates and societal costs. Dual-energy x-ray absorptiometry (DEXA) is the current gold standard for measuring apparent bone mineral density for diagnosing osteoporosis, but it continues to be an imperfect predictor of osteoporotic fracture risk. Thus, high resolution imaging techniques paired with mechanical testing and simulations are needed to better understand how the cortical pore network distributes load and which microstructural properties are the best indicators of fracture risk. Additionally, exercise is known to improve overall bone health, but targeted exercise interventions in the femoral neck have been less successful. The overall objectives of this thesis were twofold. First, we aimed to quantify the physiological level of strain in the proximal femur during regular activity and characterize the resulting mechanical environment. Second, we aimed to perform a digital volume correlation (DVC) error analysis on cortical bone and perform mechanical testing to develop a protocol for loading bone and measuring local strains using DVC. To investigate the normal level of strain in the femoral neck, we used 3D subject-specific finite element (FE) models to compare principal strains and their orientations for three loading configurations: [1] hip joint force, gluteus medius, gluteus maximus, gluteus minimus, vasti, iliopsoas, and several other smaller hip spanning muscles, [2] hip joint, gluteus medius, gluteus minimus, and the iliopsoas, and [3] hip joint force only. The principal strains and their orientations were compared in four quadrants of 8 regions during walking. Our findings indicate that including muscle forces result in more physiologically accurate FE models, and they support the hypothesis that FE models used to calculate femoral neck strains during walking should not neglect the contribution of muscle forces. These results help establish a baseline for the normal level of strain in the femoral neck which will help create new exercise interventions that cause bone adaptation and subsequent strengthening of the femoral neck. For the DVC analysis, a pair of consecutive micro-CT scans was acquired of specimens from the superior neck, inferior neck and middle diaphysis with no motion between the scans. The effect of three DVC input parameters on strain error was assessed via a Design of Experiments (DOE). Although the femoral neck specimens had large in-plane strain errors, the ezz component was 1,330 microstrain, which indicates that uniaxial compression/tension testing of these specimens via DVC is feasible. Loaded DVC of femoral neck specimen may help elucidate the relationship between intracortical pore morphology and local strain, which may one day lead to new insights into (re)modelling mechanisms and femoral neck fragility.

Graduation Semester

2021-12

Type of Resource

Thesis

Permalink

http://hdl.handle.net/2142/113929

Copyright and License Information

Copyright 2021 Michael Rogalski

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