Literature DB >> 31993829

Fluid-structure interaction simulations of patient-specific aortic dissection.

Kathrin Bäumler1, Vijay Vedula2, Anna M Sailer3, Jongmin Seo2, Peter Chiu4, Gabriel Mistelbauer5, Frandics P Chan3, Michael P Fischbein4, Alison L Marsden6, Dominik Fleischmann3.   

Abstract

Credible computational fluid dynamic (CFD) simulations of aortic dissection are challenging, because the defining parallel flow channels-the true and the false lumen-are separated from each other by a more or less mobile dissection membrane, which is made up of a delaminated portion of the elastic aortic wall. We present a comprehensive numerical framework for CFD simulations of aortic dissection, which captures the complex interplay between physiologic deformation, flow, pressures, and time-averaged wall shear stress (TAWSS) in a patient-specific model. Our numerical model includes (1) two-way fluid-structure interaction (FSI) to describe the dynamic deformation of the vessel wall and dissection flap; (2) prestress and (3) external tissue support of the structural domain to avoid unphysiologic dilation of the aortic wall and stretching of the dissection flap; (4) tethering of the aorta by intercostal and lumbar arteries to restrict translatory motion of the aorta; and a (5) independently defined elastic modulus for the dissection flap and the outer vessel wall to account for their different material properties. The patient-specific aortic geometry is derived from computed tomography angiography (CTA). Three-dimensional phase contrast magnetic resonance imaging (4D flow MRI) and the patient's blood pressure are used to inform physiologically realistic, patient-specific boundary conditions. Our simulations closely capture the cyclical deformation of the dissection membrane, with flow simulations in good agreement with 4D flow MRI. We demonstrate that decreasing flap stiffness from [Formula: see text] to [Formula: see text] kPa (a) increases the displacement of the dissection flap from 1.4 to 13.4 mm, (b) decreases the surface area of TAWSS by a factor of 2.3, (c) decreases the mean pressure difference between true lumen and false lumen by a factor of 0.63, and (d) decreases the true lumen flow rate by up to 20% in the abdominal aorta. We conclude that the mobility of the dissection flap substantially influences local hemodynamics and therefore needs to be accounted for in patient-specific simulations of aortic dissection. Further research to accurately measure flap stiffness and its local variations could help advance future CFD applications.

Entities:  

Keywords:  4D flow MRI; Aortic dissection; Computational hemodynamics; Fluid–structure interaction; Prestress; Tissue support

Mesh:

Year:  2020        PMID: 31993829     DOI: 10.1007/s10237-020-01294-8

Source DB:  PubMed          Journal:  Biomech Model Mechanobiol        ISSN: 1617-7940


  17 in total

1.  Entry Tear Dominance at CT Angiography Predicts Long-term Clinical Outcomes in Aortic Dissection: Another Piece of the Puzzle.

Authors:  Dominik Fleischmann; Nicholas Burris
Journal:  Radiol Cardiothorac Imaging       Date:  2021-11-18

2.  Colocalization of Coronary Plaque with Wall Shear Stress in Myocardial Bridge Patients.

Authors:  Muhammad Owais Khan; Takeshi Nishi; Shinji Imura; Jongmin Seo; Hanjay Wang; Yasuhiro Honda; Koen Nieman; Ian S Rogers; Jennifer A Tremmel; Jack Boyd; Ingela Schnittger; Alison Marsden
Journal:  Cardiovasc Eng Technol       Date:  2022-03-16       Impact factor: 2.305

3.  The effects of clinically-derived parametric data uncertainty in patient-specific coronary simulations with deformable walls.

Authors:  Jongmin Seo; Daniele E Schiavazzi; Andrew M Kahn; Alison L Marsden
Journal:  Int J Numer Method Biomed Eng       Date:  2020-06-25       Impact factor: 2.747

4.  On the Periodicity of Cardiovascular Fluid Dynamics Simulations.

Authors:  Martin R Pfaller; Jonathan Pham; Nathan M Wilson; David W Parker; Alison L Marsden
Journal:  Ann Biomed Eng       Date:  2021-06-24       Impact factor: 3.934

5.  Critical Pressure of Intramural Delamination in Aortic Dissection.

Authors:  Ehsan Ban; Cristina Cavinato; Jay D Humphrey
Journal:  Ann Biomed Eng       Date:  2022-01-19       Impact factor: 3.934

6.  Experimental and Mouse-Specific Computational Models of the Fbln4SMKO Mouse to Identify Potential Biomarkers for Ascending Thoracic Aortic Aneurysm.

Authors:  Marisa S Bazzi; Ramin Balouchzadeh; Shawn N Pavey; James D Quirk; Hiromi Yanagisawa; Vijay Vedula; Jessica E Wagenseil; Victor H Barocas
Journal:  Cardiovasc Eng Technol       Date:  2022-01-22       Impact factor: 2.305

7.  A nonlinear rotation-free shell formulation with prestressing for vascular biomechanics.

Authors:  Nitesh Nama; Miquel Aguirre; Jay D Humphrey; C Alberto Figueroa
Journal:  Sci Rep       Date:  2020-10-16       Impact factor: 4.379

8.  The influence of inlet velocity profile on predicted flow in type B aortic dissection.

Authors:  Chlöe Harriet Armour; Baolei Guo; Selene Pirola; Simone Saitta; Yifan Liu; Zhihui Dong; Xiao Yun Xu
Journal:  Biomech Model Mechanobiol       Date:  2020-10-17

9.  Patient-Specific Computational Fluid Dynamics Reveal Localized Flow Patterns Predictive of Post-Left Ventricular Assist Device Aortic Incompetence.

Authors:  Rohan Shad; Alexander D Kaiser; Sandra Kong; Robyn Fong; Nicolas Quach; Cayley Bowles; Patpilai Kasinpila; Yasuhiro Shudo; Jeffrey Teuteberg; Y Joseph Woo; Alison L Marsden; William Hiesinger
Journal:  Circ Heart Fail       Date:  2021-06-18       Impact factor: 10.447

10.  A Combined In Vivo, In Vitro, In Silico Approach for Patient-Specific Haemodynamic Studies of Aortic Dissection.

Authors:  Mirko Bonfanti; Gaia Franzetti; Shervanthi Homer-Vanniasinkam; Vanessa Díaz-Zuccarini; Stavroula Balabani
Journal:  Ann Biomed Eng       Date:  2020-09-14       Impact factor: 3.934

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