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Patient-specific FEA requires detailed information on ATAA geometry, loading conditions, material properties, and wall thickness. Unfortunately, measuring aortic wall thickness and mechanical properties non-invasively poses a significant challenge, necessitating the use of non-patient-specific data in most FE simulations. This study aimed to assess the impact of employing non-patient-specific material properties and wall thickness on ATAA wall stress predictions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>FE simulations were performed on 13 ATAA geometries reconstructed from computed tomography angiography (CTA) images. Patient-specific material properties and wall thicknesses were made available from a previous study where uniaxial tensile testing was performed on tissue samples obtained from the same patients. The ATAA wall models were discretised with hexahedral elements and prestressed. For each ATAA model, FE simulations were conducted using patient-specific material properties and wall thicknesses, and group-mean values derived from all tissue samples included in the same experimental study. Literature-based material property and wall thickness were also obtained from the literature and applied to 4 representative cases. Additional FE simulations were performed on these 4 cases by employing group-mean and literature-based wall thicknesses.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>FE simulations using the group-mean material property produced peak wall stresses comparable to those obtained using patient-specific material properties, with a mean deviation of 7.8%. Peak wall stresses differed by 20.8% and 18.7% in patients with exceptionally stiff or compliant walls, respectively. Comparison to results using literature-based material properties revealed larger discrepancies, ranging from 5.4% to 28.0% (mean 20.1%). Bland-Altman analysis showed significant discrepancies in areas of high wall stress, where wall stress obtained using patient-specific and literature-based properties differed by up to 674\u00a0kPa, compared to 227\u00a0kPa between patient-specific and group-mean properties. Regarding wall thickness, using the literature-based value resulted in even larger discrepancies in predicted peak stress, ranging from 24.2% to 30.0% (mean 27.3%). Again, using the group-mean wall thickness offered better predictions with a difference less than 5% in three out of four cases. While peak wall stresses were most affected by the choice of mechanical properties or wall thickness, the overall distribution of wall stress hardly changed.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Our study demonstrated the importance of incorporating patient-specific material properties and wall thickness in FEA for risk prediction of aortic dissection or rupture. Our future efforts will focus on developing inverse methods for non-invasive determination of patient-specific wall material parameters and wall thickness.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s13239-024-00756-9","type":"journal-article","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T16:01:54Z","timestamp":1729872114000},"page":"52-65","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["The Influence of Material Properties and Wall Thickness on Predicted Wall Stress in Ascending Aortic Aneurysms: A Finite Element Study"],"prefix":"10.1007","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1714-0408","authenticated-orcid":false,"given":"Yu","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Selene","family":"Pirola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. 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