{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/101335"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/101335","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Magnetic resonance elastography and nonlinear inversion problem in the aging brain","abstract":"The history of medical imaging has centered on finding correlations between contrast in an image and diagnosis of a disease, but there is a shift in medical imaging from contrast towards quantitative measurements as disease biomarkers. Magnetic resonance elastography (MRE) is a non-invasive imaging technique created, and being developed, based on modeling of mechanical properties of biological tissue. For example, the combination of state-of-the-art MR imaging and finite element based nonlinear inversion (NLI) for estimation of viscoelastic material properties have shown NLI-MRE's impressive ability to capture subtle correlations between memory performance and stiffness in grey matter regions. These discoveries are made possible by the rapid and extensive development of the underlying methods for the MR displacement imaging and the mechanical property estimation within the last few years. Within the MRE field, there are a number of open questions about the true in vivo material property values and how inaccurate current MRE methods are from actual values. The work in this dissertation attempts to address these fundamental questions through a comprehensive study of estimation parameters for NLI, optimizing for un-biased parameters, and proposing quality metrics for evaluating the confidence of final estimates. Additionally, the issue of model-data-mismatch for the isotropic material model assumption when reconstructing anisotropic tissue was investigated by subjecting the in vivo tissue to distinctly different excitation patterns, which elucidated the necessity of incorporating an anisotropic material model into NLI. Finally, the improvements in inversion techniques and new multi-excitation experiments were implemented in an in vivo study of aged human subjects to investigate how age affects anisotropic properties of the brain. MRE shows promise for being more sensitive to the normal effects of aging than the more widely utilized MR imaging techniques, specifically diffusion tensor imaging (DTI). Since DTI models the diffusion of free water in the tissue and MRE models material properties, MRE and DTI will likely be incorporated for a more comprehensive description than either alone. Thorough characterization of the MRE processes and improvements in methods will benefit future opportunities for applying MRE in the new frontier of quantitative imaging.","abstract_html":"The history of medical imaging has centered on finding correlations between contrast in an image and diagnosis of a disease, but there is a shift in medical imaging from contrast towards quantitative measurements as disease biomarkers. Magnetic resonance elastography (MRE) is a non-invasive imaging technique created, and being developed, based on modeling of mechanical properties of biological tissue. For example, the combination of state-of-the-art MR imaging and finite element based nonlinear inversion (NLI) for estimation of viscoelastic material properties have shown NLI-MRE's impressive ability to capture subtle correlations between memory performance and stiffness in grey matter regions. These discoveries are made possible by the rapid and extensive development of the underlying methods for the MR displacement imaging and the mechanical property estimation within the last few years. Within the MRE field, there are a number of open questions about the true in vivo material property values and how inaccurate current MRE methods are from actual values. The work in this dissertation attempts to address these fundamental questions through a comprehensive study of estimation parameters for NLI, optimizing for un-biased parameters, and proposing quality metrics for evaluating the confidence of final estimates. Additionally, the issue of model-data-mismatch for the isotropic material model assumption when reconstructing anisotropic tissue was investigated by subjecting the in vivo tissue to distinctly different excitation patterns, which elucidated the necessity of incorporating an anisotropic material model into NLI. Finally, the improvements in inversion techniques and new multi-excitation experiments were implemented in an in vivo study of aged human subjects to investigate how age affects anisotropic properties of the brain. MRE shows promise for being more sensitive to the normal effects of aging than the more widely utilized MR imaging techniques, specifically diffusion tensor imaging (DTI). Since DTI models the diffusion of free water in the tissue and MRE models material properties, MRE and DTI will likely be incorporated for a more comprehensive description than either alone. Thorough characterization of the MRE processes and improvements in methods will benefit future opportunities for applying MRE in the new frontier of quantitative imaging.","abstract_has_math":false,"creators":["Anderson, Aaron Thomas"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Theoretical & Applied Mechans","degree_department":null,"school":null,"contributors":["Georgiadis, John G.","Van Houten, Elijah EW","Saif, M. Taher A.","Insana, Michael"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-09-04T20:47:19Z","date_published":"2018-09-04T20:47:19Z","updated_at":"2026-07-22T22:24:38Z","subjects":["magnetic resonance imaging","elastography","human brain","nonlinear inversion","tissue properties","material estimation","aging"],"languages":["en"],"rights":["Copyright 2018 by Aaron Thomas Anderson. All rights reserved."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/101335","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Georgiadis, John G.","Van Houten, Elijah EW","Saif, M. 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These discoveries are made possible by the rapid and extensive development of the underlying methods for the MR displacement imaging and the mechanical property estimation within the last few years. Within the MRE field, there are a number of open questions about the true in vivo material property values and how inaccurate current MRE methods are from actual values. The work in this dissertation attempts to address these fundamental questions through a comprehensive study of estimation parameters for NLI, optimizing for un-biased parameters, and proposing quality metrics for evaluating the confidence of final estimates. Additionally, the issue of model-data-mismatch for the isotropic material model assumption when reconstructing anisotropic tissue was investigated by subjecting the in vivo tissue to distinctly different excitation patterns, which elucidated the necessity of incorporating an anisotropic material model into NLI. Finally, the improvements in inversion techniques and new multi-excitation experiments were implemented in an in vivo study of aged human subjects to investigate how age affects anisotropic properties of the brain. MRE shows promise for being more sensitive to the normal effects of aging than the more widely utilized MR imaging techniques, specifically diffusion tensor imaging (DTI). Since DTI models the diffusion of free water in the tissue and MRE models material properties, MRE and DTI will likely be incorporated for a more comprehensive description than either alone. Thorough characterization of the MRE processes and improvements in methods will benefit future opportunities for applying MRE in the new frontier of quantitative imaging.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Aaron Anderson, accepted the attached license on 2018-04-17 at 14:03.","The student, Aaron Anderson, submitted this Dissertation for approval on 2018-04-17 at 14:20.","This Dissertation was approved for publication on 2018-04-18 at 10:33.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12311 on 2018-08-31 at 17:29:29","Made available in DSpace on 2018-09-04T20:47:19Z (GMT). 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These discoveries are made possible by the rapid and extensive development of the underlying methods for the MR displacement imaging and the mechanical property estimation within the last few years. Within the MRE field, there are a number of open questions about the true in vivo material property values and how inaccurate current MRE methods are from actual values. The work in this dissertation attempts to address these fundamental questions through a comprehensive study of estimation parameters for NLI, optimizing for un-biased parameters, and proposing quality metrics for evaluating the confidence of final estimates. Additionally, the issue of model-data-mismatch for the isotropic material model assumption when reconstructing anisotropic tissue was investigated by subjecting the in vivo tissue to distinctly different excitation patterns, which elucidated the necessity of incorporating an anisotropic material model into NLI. Finally, the improvements in inversion techniques and new multi-excitation experiments were implemented in an in vivo study of aged human subjects to investigate how age affects anisotropic properties of the brain. MRE shows promise for being more sensitive to the normal effects of aging than the more widely utilized MR imaging techniques, specifically diffusion tensor imaging (DTI). Since DTI models the diffusion of free water in the tissue and MRE models material properties, MRE and DTI will likely be incorporated for a more comprehensive description than either alone. Thorough characterization of the MRE processes and improvements in methods will benefit future opportunities for applying MRE in the new frontier of quantitative imaging.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Aaron Anderson, accepted the attached license on 2018-04-17 at 14:03.","The student, Aaron Anderson, submitted this Dissertation for approval on 2018-04-17 at 14:20.","This Dissertation was approved for publication on 2018-04-18 at 10:33.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12311 on 2018-08-31 at 17:29:29","Made available in DSpace on 2018-09-04T20:47:19Z (GMT). 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All rights reserved."],"dc:subject":["magnetic resonance imaging","elastography","human brain","nonlinear inversion","tissue properties","material estimation","aging"],"dc:title":["Magnetic resonance elastography and nonlinear inversion problem in the aging brain"],"dc:type":["text"],"thesis:degree_discipline":["Theoretical & Applied Mechans"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:38Z"}