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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.03660 |
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| _version_ | 1866908904111210496 |
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| author | Katsoudas, Spyridon C. Kyriakoudi, Konstantina C. Chrimatopoulos, Grigorios T. Linardopoulos, Panagiotis D. Chrimatopoulos, Christoforos T. Raptis, Anastasios A. Moulakakis, Konstantinos G. Kakisis, John D. Manopoulos, Christos G. Xenos, Michail A. Tzirtzilakis, Efstratios E. |
| author_facet | Katsoudas, Spyridon C. Kyriakoudi, Konstantina C. Chrimatopoulos, Grigorios T. Linardopoulos, Panagiotis D. Chrimatopoulos, Christoforos T. Raptis, Anastasios A. Moulakakis, Konstantinos G. Kakisis, John D. Manopoulos, Christos G. Xenos, Michail A. Tzirtzilakis, Efstratios E. |
| contents | The development and progression of abdominal aortic aneurysms (AAA) are related to complex flow patterns and wall-shear-driven mechanobiological stimuli, yet the quantitative relationship between aneurysmal geometry and hemodynamics remains poorly defined. In this study, we conducted a comprehensive hemodynamic analysis of 74 patient-specific abdominal aortas, representing one of the largest Computational Fluid Dynamics (CFD) cohorts reported to date. A multiscale framework coupling 0D-1D systemic circulation models with 3D stabilized finite-element simulations is used to generate physiologically consistent boundary conditions and high-fidelity flow fields. From each model, we extract Time Averaged Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), Relative Residence Time (RRT) and Local Normalized Helicity (LNH) indicators alongside an extended set of geometric descriptors characterizing diameter, curvature and torsion. This study provides a clear and comprehensive view of how aneurysm shape influences blood-flow behavior, supported by one of the largest systematically analyzed CFD datasets of AAAs to date. Our results show that specific geometric features reliably shape shear-stress patterns, suggesting that these geometry-driven flow signatures could serve as valuable biomarkers for patient-specific risk assessment. Together, these insights highlight the potential of incorporating detailed geometric descriptors into future models that aim to predict AAA growth and rupture. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_03660 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Linking Aneurysmal Geometry and Hemodynamics Using Computational Fluid Dynamics Katsoudas, Spyridon C. Kyriakoudi, Konstantina C. Chrimatopoulos, Grigorios T. Linardopoulos, Panagiotis D. Chrimatopoulos, Christoforos T. Raptis, Anastasios A. Moulakakis, Konstantinos G. Kakisis, John D. Manopoulos, Christos G. Xenos, Michail A. Tzirtzilakis, Efstratios E. Fluid Dynamics Mathematical Physics 35Q30, 76D05, 65M22 The development and progression of abdominal aortic aneurysms (AAA) are related to complex flow patterns and wall-shear-driven mechanobiological stimuli, yet the quantitative relationship between aneurysmal geometry and hemodynamics remains poorly defined. In this study, we conducted a comprehensive hemodynamic analysis of 74 patient-specific abdominal aortas, representing one of the largest Computational Fluid Dynamics (CFD) cohorts reported to date. A multiscale framework coupling 0D-1D systemic circulation models with 3D stabilized finite-element simulations is used to generate physiologically consistent boundary conditions and high-fidelity flow fields. From each model, we extract Time Averaged Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), Relative Residence Time (RRT) and Local Normalized Helicity (LNH) indicators alongside an extended set of geometric descriptors characterizing diameter, curvature and torsion. This study provides a clear and comprehensive view of how aneurysm shape influences blood-flow behavior, supported by one of the largest systematically analyzed CFD datasets of AAAs to date. Our results show that specific geometric features reliably shape shear-stress patterns, suggesting that these geometry-driven flow signatures could serve as valuable biomarkers for patient-specific risk assessment. Together, these insights highlight the potential of incorporating detailed geometric descriptors into future models that aim to predict AAA growth and rupture. |
| title | Linking Aneurysmal Geometry and Hemodynamics Using Computational Fluid Dynamics |
| topic | Fluid Dynamics Mathematical Physics 35Q30, 76D05, 65M22 |
| url | https://arxiv.org/abs/2512.03660 |