{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/150193"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/150193","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Late Complications in the Descending Aorta Following Valve-Sparing Root Replacement (VSRR) in Marfan Syndrome (MFS) Patients: A Computational Analysis","abstract":"Patients with Marfan Syndrome (MFS) experience an elevated risk of aortic dissection in the descending aorta (DA) following root surgery. Geometric factors related to either native anatomy or the root surgery may alter hemodynamic factors in the DA, potentially predisposing it to dissection. This study uses computational fluid dynamics (CFD) simulations alongside statistical shape modeling (SSM) to investigate the relationships between aortic geometry, hemodynamic indices, and post-surgical dissection risk. We retrospectively analyze CT imaging of a cohort of MFS patients who underwent root surgery, divided into a “dissection group” and a “non-dissection group.” Due to the absence of 4D MRI data, we conduct sensitivity analyses to evaluate the feasibility of using modified generic waveforms as inlet boundary conditions. After establishing a reliable CFD model, we assess near-wall hemodynamic parameters to explore potential links between flow characteristics and dissection likelihood. Our results show that the “dissection” group exhibits lower time-averaged wall shear stress (TAWSS) and higher oscillatory shear index (OSI) and relative residence time (RRT) in the DA. Additionally, we observe a localized increase in TAWSS near the subclavian artery post-surgery in the “dissection” group, which is not observed in the “no dissection” group. We then apply SSM, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), to identify key geometric features differentiating dissection-prone patients. These analyses highlight morphological factors, including average aortic diameter, descending aorta diameter, and ascending aortic bending angle, as significant discriminators. Virtual modifications of these geometric parameters, when feasible within clinical constraints, may influence hemodynamic patterns in the DA, presenting opportunities to enhance surgical planning from a hemodynamic perspective. Together, these findings suggest that both anatomical and surgically induced geometric features drive hemodynamic changes that may increase the risk of aortic dissection in the DA following aortic root surgery for patients with MFS. Ultimately, integrating CFD-based hemodynamic assessment with SSM provides a promising framework for improving risk stratification in patients with MFS and refining surgical strategies.","abstract_html":"Patients with Marfan Syndrome (MFS) experience an elevated risk of aortic dissection in the descending aorta (DA) following root surgery. Geometric factors related to either native anatomy or the root surgery may alter hemodynamic factors in the DA, potentially predisposing it to dissection. This study uses computational fluid dynamics (CFD) simulations alongside statistical shape modeling (SSM) to investigate the relationships between aortic geometry, hemodynamic indices, and post-surgical dissection risk. We retrospectively analyze CT imaging of a cohort of MFS patients who underwent root surgery, divided into a “dissection group” and a “non-dissection group.” Due to the absence of 4D MRI data, we conduct sensitivity analyses to evaluate the feasibility of using modified generic waveforms as inlet boundary conditions. After establishing a reliable CFD model, we assess near-wall hemodynamic parameters to explore potential links between flow characteristics and dissection likelihood. Our results show that the “dissection” group exhibits lower time-averaged wall shear stress (TAWSS) and higher oscillatory shear index (OSI) and relative residence time (RRT) in the DA. Additionally, we observe a localized increase in TAWSS near the subclavian artery post-surgery in the “dissection” group, which is not observed in the “no dissection” group. We then apply SSM, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), to identify key geometric features differentiating dissection-prone patients. These analyses highlight morphological factors, including average aortic diameter, descending aorta diameter, and ascending aortic bending angle, as significant discriminators. Virtual modifications of these geometric parameters, when feasible within clinical constraints, may influence hemodynamic patterns in the DA, presenting opportunities to enhance surgical planning from a hemodynamic perspective. Together, these findings suggest that both anatomical and surgically induced geometric features drive hemodynamic changes that may increase the risk of aortic dissection in the DA following aortic root surgery for patients with MFS. Ultimately, integrating CFD-based hemodynamic assessment with SSM provides a promising framework for improving risk stratification in patients with MFS and refining surgical strategies.","abstract_has_math":false,"creators":["Tajeddinisarvestani, Farshad"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Mechanical and Industrial Engineering","school":null,"contributors":[],"advisors":["Amon, Cristina H.","Chung, Jennifer C.Y."],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-10","date_published":"2025-10","updated_at":"2026-07-27T21:27:54Z","subjects":["Computational Fluid Dynamics","Marfan Syndrome","Principal Component Analysis","Statistical Shape Analysis","Type B Aortic Dissection","Valve Sparing Root Replacement"],"languages":[],"rights":["Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1807/150193","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Amon, Cristina H.","Chung, Jennifer C.Y."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical and Industrial Engineering"]},{"key":"dc:creator","label":"Author","values":["Tajeddinisarvestani, Farshad"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-10"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-11-28T17:38:44Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-10"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computational Fluid Dynamics","Marfan Syndrome","Principal Component Analysis","Statistical Shape Analysis","Type B Aortic Dissection","Valve Sparing Root Replacement"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1807/150193"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Patients with Marfan Syndrome (MFS) experience an elevated risk of aortic dissection in the descending aorta (DA) following root surgery. Geometric factors related to either native anatomy or the root surgery may alter hemodynamic factors in the DA, potentially predisposing it to dissection. This study uses computational fluid dynamics (CFD) simulations alongside statistical shape modeling (SSM) to investigate the relationships between aortic geometry, hemodynamic indices, and post-surgical dissection risk. We retrospectively analyze CT imaging of a cohort of MFS patients who underwent root surgery, divided into a “dissection group” and a “non-dissection group.” Due to the absence of 4D MRI data, we conduct sensitivity analyses to evaluate the feasibility of using modified generic waveforms as inlet boundary conditions. After establishing a reliable CFD model, we assess near-wall hemodynamic parameters to explore potential links between flow characteristics and dissection likelihood. Our results show that the “dissection” group exhibits lower time-averaged wall shear stress (TAWSS) and higher oscillatory shear index (OSI) and relative residence time (RRT) in the DA. Additionally, we observe a localized increase in TAWSS near the subclavian artery post-surgery in the “dissection” group, which is not observed in the “no dissection” group. We then apply SSM, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), to identify key geometric features differentiating dissection-prone patients. These analyses highlight morphological factors, including average aortic diameter, descending aorta diameter, and ascending aortic bending angle, as significant discriminators. Virtual modifications of these geometric parameters, when feasible within clinical constraints, may influence hemodynamic patterns in the DA, presenting opportunities to enhance surgical planning from a hemodynamic perspective. Together, these findings suggest that both anatomical and surgically induced geometric features drive hemodynamic changes that may increase the risk of aortic dissection in the DA following aortic root surgery for patients with MFS. Ultimately, integrating CFD-based hemodynamic assessment with SSM provides a promising framework for improving risk stratification in patients with MFS and refining surgical strategies."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Late Complications in the Descending Aorta Following Valve-Sparing Root Replacement (VSRR) in Marfan Syndrome (MFS) Patients: A Computational Analysis"]}]}],"canonical_facts":{"dc:contributor.advisor":["Amon, Cristina H.","Chung, Jennifer C.Y."],"dc:contributor.department":["Mechanical and Industrial Engineering"],"dc:creator":["Tajeddinisarvestani, Farshad"],"dc:date":["2025-10"],"dc:date.accessioned":["2025-11-28T17:38:44Z"],"dc:date.issued":["2025-10"],"dc:description.abstract":["Patients with Marfan Syndrome (MFS) experience an elevated risk of aortic dissection in the descending aorta (DA) following root surgery. Geometric factors related to either native anatomy or the root surgery may alter hemodynamic factors in the DA, potentially predisposing it to dissection. This study uses computational fluid dynamics (CFD) simulations alongside statistical shape modeling (SSM) to investigate the relationships between aortic geometry, hemodynamic indices, and post-surgical dissection risk. We retrospectively analyze CT imaging of a cohort of MFS patients who underwent root surgery, divided into a “dissection group” and a “non-dissection group.” Due to the absence of 4D MRI data, we conduct sensitivity analyses to evaluate the feasibility of using modified generic waveforms as inlet boundary conditions. After establishing a reliable CFD model, we assess near-wall hemodynamic parameters to explore potential links between flow characteristics and dissection likelihood. Our results show that the “dissection” group exhibits lower time-averaged wall shear stress (TAWSS) and higher oscillatory shear index (OSI) and relative residence time (RRT) in the DA. Additionally, we observe a localized increase in TAWSS near the subclavian artery post-surgery in the “dissection” group, which is not observed in the “no dissection” group. We then apply SSM, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), to identify key geometric features differentiating dissection-prone patients. These analyses highlight morphological factors, including average aortic diameter, descending aorta diameter, and ascending aortic bending angle, as significant discriminators. Virtual modifications of these geometric parameters, when feasible within clinical constraints, may influence hemodynamic patterns in the DA, presenting opportunities to enhance surgical planning from a hemodynamic perspective. Together, these findings suggest that both anatomical and surgically induced geometric features drive hemodynamic changes that may increase the risk of aortic dissection in the DA following aortic root surgery for patients with MFS. Ultimately, integrating CFD-based hemodynamic assessment with SSM provides a promising framework for improving risk stratification in patients with MFS and refining surgical strategies."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["https://hdl.handle.net/1807/150193"],"dc:rights":["Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:subject":["Computational Fluid Dynamics","Marfan Syndrome","Principal Component Analysis","Statistical Shape Analysis","Type B Aortic Dissection","Valve Sparing Root Replacement"],"dc:title":["Late Complications in the Descending Aorta Following Valve-Sparing Root Replacement (VSRR) in Marfan Syndrome (MFS) Patients: A Computational Analysis"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:27:54Z"}