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Predictions of Radius Bending Strength by Radius Stiffness, Mineral, and Ulna Mechanical Properties

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Predictions of Radius Bending Strength by Radius Stiffness, Mineral, and Ulna Mechanical Properties PREDICTIONS OF RADIUS BENDING STRENGTH BY RADIUS STIFFNESS, MINERAL, AND ULNA MECHANICAL PROPERTIES ___________________________________________ A Thesis Presented to The College of Arts and Sciences, Ohio University ___________________________________________ In Partial Fulfillment of the Requirements for Graduation with Honors from the College of Arts and Sciences with the degree of Bachelor of Science in Biological Sciences ___________________________________________ by McKenzie L. Nelson April 2017 2 Table of Contents Acknowledgements……………………………….……………………......3 Abstract…………………………….……………….…………………...…4 1. Introduction…………………………………………..............................5 1.1 Bone Structure, Development, and Maintenance..………....…….5 1.2 Osteoporosis Manifestation and Diagnosis…………..……….…..8 1.3 Bone Biomechanics...…………………...……………………….….13 1.4 Importance of the Radius…..……………………………..…….….23 1.5 Specific Aims.………………..……………………………………....26 1.6 Hypotheses.…………..………………………………………....……26 2. Methods………………………………..............………………….…....27 2.1 Specimens…………………………….....…………………….……..27 2.2 Experimental Design..………………………............……….…….32 2.3 Experimental Protocol………..……………………………….…...35 2.4 Data Analysis.………………………..……………………….……..48 2.5 Statistical Analysis.……………………..…………………….…….53 3. Results……………………………..…………………………….….….57 3.1 Data Exclusions……………..………………………………………57 3.2 Radius EI Corrections………..………………………….…………57 3.3 Univariate Analysis.…………...………………………….………...61 3.4 Bivariate Analysis in the Prediction of Radius Strength……….62 3.5 Bivariate Analysis in the Prediction of Radius EI………………69 4. Discussion…………………………………………………….….…......74 4.1 Main Findings………………………………………….…………….74 4.2 Significance in Context with Previous Research....……………..74 4.3 Strengths………………………….…………………………………..80 4.4 Weaknesses……………………………………………….……….….82 4.5 Future Research.……………………………………….………...….87 References………………………………………………..……….…….…89 3 Acknowledgments This project was made possible by funding from the Ohio Space Grant Consortium and Dr. Anne B. Loucks of the Department of Biological Sciences at Ohio University. I am grateful for Dr. Betty Sindelar of the Ohio University School of Rehabilitation and Communication Studies, Division of Physical Therapy for allowing me to use her QMT system, the human tissue banks, Science Care and AdvancedMed, for providing specimens for this project, and to the donors and their families for selflessly giving their bodies to science. I am also thankful for the guidance of Dr. Chris Griffin in completing this thesis. I would further like to recognize the extensive work done by previous students in the lab that provided predictors used in this project: Emily Ellerbrock and Jennifer Neumeyer for their analysis of MRTA data, Tyler Beck for his analysis of ulna QMT data, Gabrielle Hausfeld for her analysis of ulna bending strength predictors, and Maureen Dean for her analysis of radius UD compressive strength and radius DXA scans. Without their efforts, this project would not have been possible. The support of my family and friends has additionally been crucial in the completion of this thesis, and I would like to thank them for providing me with the network I needed. Finally, I have been very fortunate to work under Dr. Anne B. Loucks and Lyn Bowman. I am deeply appreciative of Lyn’s patience in educating me on everything from biomechanics and statistical analysis to life lessons, and for his assistance in helping to develop the study protocol. I am also deeply indebted to Dr. Loucks for allowing me to work in her lab for the past two years, mentoring me, and giving me every opportunity to succeed in my project and educational pursuits. The challenges and education I received in this experience are unparalleled by any other experience in my college career. 4 Abstract Osteoporosis is a systemic, skeletal disease characterized by decreased bone strength that predisposes individuals to an increased risk of fracture. Unfortunately, there is no clinical device able to measure bone strength. Instead, osteoporosis is diagnosed on the basis of bone mineral density (BMD) as measured by dual-energy X- ray absorptiometry (DXA). However, research has shown that BMD does not predict fractures well. Bone strength has been shown to be predicted accurately by bone stiffness (EI), but no clinical device measures bone stiffness either. Ohio University is developing Mechanical Response Tissue Analysis (MRTA) to measure EI of the human ulna in vivo. Accurate predictions of ulna bending strength are of limited clinical importance, however, unless the ulna is representative of other long bones. The radius is of further clinical importance because a fracture of the radius often precedes and could predict fractures at more serious sites such as the hip. This project used cadaveric radius specimens, of which the ipsilateral ulna was previously tested, to determine the accuracy with which radius bending strength was predicted by various predictors from both mechanical testing of the radius and ulna and DXA measurements of the radius. Mechanical testing methods included MRTA of the ulna in vivo and quasistatic mechanical testing (QMT) of the ulna and radius ex vivo. DXA measurements included scans of the standard UD and 1/3 sites of the radius. Linear regression analyses revealed that ulna EI measured by MRTA is a more accurate predictor of radius bending strength than BMD measurements, but is not the most accurate predictor. Radius EI and BMC at the 1/3 site were the most accurate predictors of radius bending strength, though not significantly different from each other. The most accurate predictor of radius EI was BMC at the 1/3 site. 5 1. Introduction 1.1 Bone Structure, Development, and Maintenance Bone is multifunctional. It offers mechanical support for locomotion, protection of vital organs in the body, storage of exchangeable minerals for homeostasis, and hematopoiesis (Burr and Allen, 2013). It therefore plays a crucial role in viability. Bone is comprised of mineral, collagen, non-collagenous proteins such as osteocalcin, cells, marrow tissue, and water (Burr and Allen, 2013). On a macroscopic scale, bone tissue is of two distinct types: cortical bone and trabecular bone. Cortical bone, or compact bone, is found in the shafts of long bones (the diaphyses) and as a cortex or shell at the ends of long bones (metaphyses), around vertebral bodies, and at the surface of the pelvis, skull, and other flat bones (Burr and Allen, 2013). It is very dense, comprising 80% of bone mass, formed from circumferential layers, or lamellae (Heller, 2004). Healthy cortical bone contains Haversian canals that create a porosity of 3-5% (Burr and Allen, 2013). These canals, each several millimeters long, are distributed throughout the length and thickness of cortical bone tissue carrying nerves and capillaries. Volkmann’s canals are also present, running transversely, connecting Haversian canals to each other and to the outside surface of the bone. (Figure 1) (Martin et al., 1998) 6 Figure 1: Composition of Cortical Bone Showing Lamellae, Haversian Canals, and Volkmann’s Canals (Cowin and Cardoso, 2015) Trabecular bone, also known as cancellous or spongy bone, makes up 80% of the bone surface area and is found inside cuboidal bones like the vertebrae, flat bones, and the ends of long bones (metaphyses). It is composed of interconnected rods and plates of bone, known as trabeculae, creating a porosity of 50-90% that is filled with marrow (Figure 2). The interconnected architecture offers strength while minimizing the mass of the bone, as the trabeculae distribute weight-bearing stress to the stronger cortical bone. (Burr and Allen, 2013; Martin et al., 1998) 7 Figure 2: Composition of Trabecular Bone Showing Rods (Purple Arrows) and Plates (Blue Arrows) (Burr and Allen, 2013) As bones grow and are maintained, bone turnover must occur. In order to be sculpted in various ways in response to how the skeleton is loaded, some bone must be removed in certain areas and added to others. In growing children, this process is continuous and known as modeling. In older bone, the process, known as remodeling, is characterized by removal of underutilized bone and by removal and replacement of old, damaged bone (Martin et al., 1998) In cortical bone, bone remodeling is accomplished through basic multicellular units (BMUs) which contain a few osteoclasts and many osteoblasts. When damage is present in cortical bone, osteoclasts are signaled to form and activate. As shown in Figure 3, they begin resorbing bone perpendicular to the surface of a Haversian canal then turn and proceed for several millimeters parallel to the canal until they have passed through the damaged site. This process takes about four weeks. The osteoblasts then follow behind the osteoclasts and refill the resulting tunnel with new bone, taking 8 about three months. (Martin et al., 1998) The narrow residual tunnel becomes a new Haversian canal, and as adults age, this remodeling repair process riddles the bone with additional porosity. Figure 3: Basic Multicellular Unit (BMU) with Osteoclasts (Red) and Osteoblasts (Blue) (Adapted from (Martin et al., 1998)) 1.2 Osteoporosis Manifestation and Diagnosis Osteoporosis is a systemic, skeletal disease characterized by decreased bone strength that predisposes individuals to an increased risk of fracture (NIH Consensus Development Panel on Osteoporosis Prevention, 2001). Recent studies estimate that 10.2 million people in the United States ages 50 or older already have osteoporosis
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