{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105724"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105724","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Morphological and mechanical analysis of the porous structure of cortical bone","abstract":"Introduction: Bone is a complex hierarchical material that can be studied at many levels. For diseases like osteoporosis, characterized by bone loss, macro-level tests like DEXA scanning can predict an increased fracture risk, but cannot detect the driving mechanism.As a porous, anisotropic material, one of the only ways to truly predict bone mechanics is to model the underlying microstructure. The complexity of the porous structure of cortical bone presents a challenge when generating computational models requiring high resolution imaging, advanced mesh generation algorithms, and powerful computational resources for finite element analysis. Methods: Cortical bone samples were collected from the middle neck of a cadaver femur(71 year old female, no history of bone disease). The neck was separated into four quadrants:anterior, posterior, superior, and inferior then further sub-sectioned to 5 mm pieces. Micro-computed tomography scans were collected (4 μm/voxel), processed, and used to generate 3D models of the bone and of the porous network. Effective strain in each model was derived through finite element analysis using physiologic displacement boundary conditions and Young’s modulus estimation using density calibrations from hydroxyapatite phantoms.Two- and three-dimensional geometric measures were evaluated from the processed images. Results: For all quadrants, no significant relationship was found between the three-dimensional measures and the effective strain around pores in a two-dimensional cross section. Effective strain increased significantly with area, shape factor, and clustering, however,these relationships were not strong. Discussion: Studying the microstructure of cortical bone is useful for identifying the exact location of bone growth and repair based on mechanical stimulus. Relating microstrain and bone formation is important in developing a stronger understanding of how bone adapts.This knowledge could be used to develop training protocols for those susceptible to bone loss such as postmenopausal women and astronauts.","abstract_html":"Introduction: Bone is a complex hierarchical material that can be studied at many levels. For diseases like osteoporosis, characterized by bone loss, macro-level tests like DEXA scanning can predict an increased fracture risk, but cannot detect the driving mechanism.As a porous, anisotropic material, one of the only ways to truly predict bone mechanics is to model the underlying microstructure. The complexity of the porous structure of cortical bone presents a challenge when generating computational models requiring high resolution imaging, advanced mesh generation algorithms, and powerful computational resources for finite element analysis. Methods: Cortical bone samples were collected from the middle neck of a cadaver femur(71 year old female, no history of bone disease). The neck was separated into four quadrants:anterior, posterior, superior, and inferior then further sub-sectioned to 5 mm pieces. Micro-computed tomography scans were collected (4 μm/voxel), processed, and used to generate 3D models of the bone and of the porous network. Effective strain in each model was derived through finite element analysis using physiologic displacement boundary conditions and Young’s modulus estimation using density calibrations from hydroxyapatite phantoms.Two- and three-dimensional geometric measures were evaluated from the processed images. Results: For all quadrants, no significant relationship was found between the three-dimensional measures and the effective strain around pores in a two-dimensional cross section. Effective strain increased significantly with area, shape factor, and clustering, however,these relationships were not strong. Discussion: Studying the microstructure of cortical bone is useful for identifying the exact location of bone growth and repair based on mechanical stimulus. Relating microstrain and bone formation is important in developing a stronger understanding of how bone adapts.This knowledge could be used to develop training protocols for those susceptible to bone loss such as postmenopausal women and astronauts.","abstract_has_math":false,"creators":["Livingston, Elizabeth"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Kersh, Mariana E"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-11-26T20:35:17Z","date_published":"2019-11-26T20:35:17Z","updated_at":"2026-07-22T22:24:44Z","subjects":["cortical bone","porosity","microstructure","finite element analysis"],"languages":["en"],"rights":["Copyright 2019 Elizabeth Livingston"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105724","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kersh, Mariana E"]},{"key":"dc:creator","label":"Author","values":["Livingston, Elizabeth"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-11-26T20:35:17Z","2019-07-18","2019-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["cortical bone","porosity","microstructure","finite element analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Elizabeth Livingston"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105724"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Introduction: Bone is a complex hierarchical material that can be studied at many levels. For diseases like osteoporosis, characterized by bone loss, macro-level tests like DEXA scanning can predict an increased fracture risk, but cannot detect the driving mechanism.As a porous, anisotropic material, one of the only ways to truly predict bone mechanics is to model the underlying microstructure. The complexity of the porous structure of cortical bone presents a challenge when generating computational models requiring high resolution imaging, advanced mesh generation algorithms, and powerful computational resources for finite element analysis. Methods: Cortical bone samples were collected from the middle neck of a cadaver femur(71 year old female, no history of bone disease). The neck was separated into four quadrants:anterior, posterior, superior, and inferior then further sub-sectioned to 5 mm pieces. Micro-computed tomography scans were collected (4 μm/voxel), processed, and used to generate 3D models of the bone and of the porous network. Effective strain in each model was derived through finite element analysis using physiologic displacement boundary conditions and Young’s modulus estimation using density calibrations from hydroxyapatite phantoms.Two- and three-dimensional geometric measures were evaluated from the processed images. Results: For all quadrants, no significant relationship was found between the three-dimensional measures and the effective strain around pores in a two-dimensional cross section. Effective strain increased significantly with area, shape factor, and clustering, however,these relationships were not strong. Discussion: Studying the microstructure of cortical bone is useful for identifying the exact location of bone growth and repair based on mechanical stimulus. Relating microstrain and bone formation is important in developing a stronger understanding of how bone adapts.This knowledge could be used to develop training protocols for those susceptible to bone loss such as postmenopausal women and astronauts.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2019-11-26 without embargo terms","The student, Elizabeth Livingston, accepted the attached license on 2019-07-18 at 15:24.","The student, Elizabeth Livingston, submitted this Thesis for approval on 2019-07-18 at 15:30.","This Thesis was approved for publication on 2019-07-18 at 17:24.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14383 on 2019-11-26 at 12:54:25","Made available in DSpace on 2019-11-26T20:35:17Z (GMT). No. of bitstreams: 2 LIVINGSTON-THESIS-2019.pdf: 28903314 bytes, checksum: 43bd32a18b11b5412d9ca28b332cf328 (MD5) LICENSE.txt: 4217 bytes, checksum: e9a0e3acb95a134b0374ef919dbe697e (MD5) Previous issue date: 2019-07-18"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Morphological and mechanical analysis of the porous structure of cortical bone"]}]}],"canonical_facts":{"dc:contributor":["Kersh, Mariana E"],"dc:creator":["Livingston, Elizabeth"],"dc:date":["2019-11-26T20:35:17Z","2019-07-18","2019-08"],"dc:description":["Introduction: Bone is a complex hierarchical material that can be studied at many levels. For diseases like osteoporosis, characterized by bone loss, macro-level tests like DEXA scanning can predict an increased fracture risk, but cannot detect the driving mechanism.As a porous, anisotropic material, one of the only ways to truly predict bone mechanics is to model the underlying microstructure. The complexity of the porous structure of cortical bone presents a challenge when generating computational models requiring high resolution imaging, advanced mesh generation algorithms, and powerful computational resources for finite element analysis. Methods: Cortical bone samples were collected from the middle neck of a cadaver femur(71 year old female, no history of bone disease). The neck was separated into four quadrants:anterior, posterior, superior, and inferior then further sub-sectioned to 5 mm pieces. Micro-computed tomography scans were collected (4 μm/voxel), processed, and used to generate 3D models of the bone and of the porous network. Effective strain in each model was derived through finite element analysis using physiologic displacement boundary conditions and Young’s modulus estimation using density calibrations from hydroxyapatite phantoms.Two- and three-dimensional geometric measures were evaluated from the processed images. Results: For all quadrants, no significant relationship was found between the three-dimensional measures and the effective strain around pores in a two-dimensional cross section. Effective strain increased significantly with area, shape factor, and clustering, however,these relationships were not strong. Discussion: Studying the microstructure of cortical bone is useful for identifying the exact location of bone growth and repair based on mechanical stimulus. Relating microstrain and bone formation is important in developing a stronger understanding of how bone adapts.This knowledge could be used to develop training protocols for those susceptible to bone loss such as postmenopausal women and astronauts.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2019-11-26 without embargo terms","The student, Elizabeth Livingston, accepted the attached license on 2019-07-18 at 15:24.","The student, Elizabeth Livingston, submitted this Thesis for approval on 2019-07-18 at 15:30.","This Thesis was approved for publication on 2019-07-18 at 17:24.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14383 on 2019-11-26 at 12:54:25","Made available in DSpace on 2019-11-26T20:35:17Z (GMT). No. of bitstreams: 2 LIVINGSTON-THESIS-2019.pdf: 28903314 bytes, checksum: 43bd32a18b11b5412d9ca28b332cf328 (MD5) LICENSE.txt: 4217 bytes, checksum: e9a0e3acb95a134b0374ef919dbe697e (MD5) Previous issue date: 2019-07-18"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/105724"],"dc:language":["en"],"dc:rights":["Copyright 2019 Elizabeth Livingston"],"dc:subject":["cortical bone","porosity","microstructure","finite element analysis"],"dc:title":["Morphological and mechanical analysis of the porous structure of cortical bone"],"dc:type":["text"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:44Z"}