{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/84036"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/84036","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Application of Computational Modeling Tools in Management of Intracranial Aneurysms","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Rajabzadeh-Oghaz, Hamidreza; 0000-0002-9138-9239"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Meng, Hui","Mechanical and Aerospace Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-06-21T15:47:16Z","date_published":"2022-06-21T15:47:16Z","updated_at":"2026-07-27T19:05:30Z","subjects":["artificial intelligence","biomedical engineering","fluid mechanics"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/84036","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Meng, Hui","Mechanical and Aerospace Engineering"]},{"key":"dc:creator","label":"Author","values":["Rajabzadeh-Oghaz, Hamidreza; 0000-0002-9138-9239"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-06-21T15:47:16Z","2020"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["artificial intelligence","biomedical engineering","fluid mechanics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/84036"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Image-based computational tools have been used to study detailed morphology and hemodynamics of intracranial aneurysms (IAs) for more than two decades. Despite years of research and development, the application of these tools and their associated findings have been limited only to the research sites and not yet adopted by clinicians. The main objective of this dissertation was to investigate the real-world application of these tools and their clinical utility in the management of IAs. First, we introduced and validated a computational workflow for detailed IA morphology evaluation and showed its superiority, in terms of accuracy and consistency, compared to traditional clinical practice. Then, we quantified the sensitivity of hemodynamic metrics derived from image-based computational fluid dynamics (CFD) to flow boundary conditions variations. We found CFD-simulated results are highly sensitive to inflow rate and outflow split boundary conditions. In the last two chapters of this dissertation, we applied these computational tools to study morphology and hemodynamics of IAs and developed and applied different data-driven models to address two clinical needs. First, we highlighted real-world application of a data driven model that provides a rupture resemblance score (RRS) for unruptured aneurysms in term of morphology and hemodynamics. We showed that when current clinical metrics are not adequate for making treatment decision for unruptured IAs, RRS can add additional information and stratify aneurysms based on their resemblance to ruptured IAs. Furthermore, we developed rupture identification models (RIMs) which incorporate aneurysmal morphology and hemodynamics to identify the ruptured IA in subarachnoid hemorrhage (SAH) patients with multiple aneurysms. RIMs outperformed existing aneurysmal metrics in identifying the ruptured aneurysm in SAH patients with multiple IAs.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Application of Computational Modeling Tools in Management of Intracranial Aneurysms"]}]}],"canonical_facts":{"dc:contributor":["Meng, Hui","Mechanical and Aerospace Engineering"],"dc:creator":["Rajabzadeh-Oghaz, Hamidreza; 0000-0002-9138-9239"],"dc:date":["2022-06-21T15:47:16Z","2020"],"dc:description":["Ph.D.","Image-based computational tools have been used to study detailed morphology and hemodynamics of intracranial aneurysms (IAs) for more than two decades. Despite years of research and development, the application of these tools and their associated findings have been limited only to the research sites and not yet adopted by clinicians. The main objective of this dissertation was to investigate the real-world application of these tools and their clinical utility in the management of IAs. First, we introduced and validated a computational workflow for detailed IA morphology evaluation and showed its superiority, in terms of accuracy and consistency, compared to traditional clinical practice. Then, we quantified the sensitivity of hemodynamic metrics derived from image-based computational fluid dynamics (CFD) to flow boundary conditions variations. We found CFD-simulated results are highly sensitive to inflow rate and outflow split boundary conditions. In the last two chapters of this dissertation, we applied these computational tools to study morphology and hemodynamics of IAs and developed and applied different data-driven models to address two clinical needs. First, we highlighted real-world application of a data driven model that provides a rupture resemblance score (RRS) for unruptured aneurysms in term of morphology and hemodynamics. We showed that when current clinical metrics are not adequate for making treatment decision for unruptured IAs, RRS can add additional information and stratify aneurysms based on their resemblance to ruptured IAs. Furthermore, we developed rupture identification models (RIMs) which incorporate aneurysmal morphology and hemodynamics to identify the ruptured IA in subarachnoid hemorrhage (SAH) patients with multiple aneurysms. RIMs outperformed existing aneurysmal metrics in identifying the ruptured aneurysm in SAH patients with multiple IAs.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/84036"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["artificial intelligence","biomedical engineering","fluid mechanics"],"dc:title":["Application of Computational Modeling Tools in Management of Intracranial Aneurysms"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:30Z"}