Literature DB >> 21203844

A rapid and computationally inexpensive method to virtually implant current and next-generation stents into subject-specific computational fluid dynamics models.

Timothy J Gundert1, Shawn C Shadden, Andrew R Williams, Bon-Kwon Koo, Jeffrey A Feinstein, John F Ladisa.   

Abstract

Computational modeling is often used to quantify hemodynamic alterations induced by stenting, but frequently uses simplified device or vascular representations. Based on a series of Boolean operations, we developed an efficient and robust method for assessing the influence of current and next-generation stents on local hemodynamics and vascular biomechanics quantified by computational fluid dynamics. Stent designs were parameterized to allow easy control over design features including the number, width and circumferential or longitudinal spacing of struts, as well as the implantation diameter and overall length. The approach allowed stents to be automatically regenerated for rapid analysis of the contribution of design features to resulting hemodynamic alterations. The applicability of the method was demonstrated with patient-specific models of a stented coronary artery bifurcation and basilar trunk aneurysm constructed from medical imaging data. In the coronary bifurcation, we analyzed the hemodynamic difference between closed-cell and open-cell stent geometries. We investigated the impact of decreased strut size in stents with a constant porosity for increasing flow stasis within the stented basilar aneurysm model. These examples demonstrate the current method can be used to investigate differences in stent performance in complex vascular beds for a variety of stenting procedures and clinical scenarios.

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Year:  2011        PMID: 21203844     DOI: 10.1007/s10439-010-0238-5

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  11 in total

1.  Immersive visualization for enhanced computational fluid dynamics analysis.

Authors:  David J Quam; Timothy J Gundert; Laura Ellwein; Christopher E Larkee; Paul Hayden; Raymond Q Migrino; Hiromasa Otake; John F LaDisa
Journal:  J Biomech Eng       Date:  2015-01-29       Impact factor: 2.097

2.  Interactive virtual stent planning for the treatment of coarctation of the aorta.

Authors:  Mathias Neugebauer; Martin Glöckler; Leonid Goubergrits; Marcus Kelm; Titus Kuehne; Anja Hennemuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-05-16       Impact factor: 2.924

3.  Computational fluid dynamic simulations of image-based stented coronary bifurcation models.

Authors:  Claudio Chiastra; Stefano Morlacchi; Diego Gallo; Umberto Morbiducci; Rubén Cárdenes; Ignacio Larrabide; Francesco Migliavacca
Journal:  J R Soc Interface       Date:  2013-05-15       Impact factor: 4.118

4.  The Impact of Cardiac Motion on Aortic Valve Flow Used in Computational Simulations of the Thoracic Aorta.

Authors:  David C Wendell; Margaret M Samyn; Joseph R Cava; Mary M Krolikowski; John F LaDisa
Journal:  J Biomech Eng       Date:  2016-09-01       Impact factor: 2.097

5.  Quantification of local hemodynamic alterations caused by virtual implantation of three commercially available stents for the treatment of aortic coarctation.

Authors:  Sung Kwon; Jeffrey A Feinstein; Ronak J Dholakia; John F Ladisa
Journal:  Pediatr Cardiol       Date:  2013-11-21       Impact factor: 1.655

6.  A Pilot Study Characterizing Flow Patterns in the Thoracic Aorta of Patients With Connective Tissue Disease: Comparison to Age- and Gender-Matched Controls via Fluid Structure Interaction.

Authors:  Joseph A Camarda; Ronak J Dholakia; Hongfeng Wang; Margaret M Samyn; Joseph R Cava; John F LaDisa
Journal:  Front Pediatr       Date:  2022-05-04       Impact factor: 3.569

7.  Including aortic valve morphology in computational fluid dynamics simulations: initial findings and application to aortic coarctation.

Authors:  David C Wendell; Margaret M Samyn; Joseph R Cava; Laura M Ellwein; Mary M Krolikowski; Kimberly L Gandy; Andrew N Pelech; Shawn C Shadden; John F LaDisa
Journal:  Med Eng Phys       Date:  2012-08-20       Impact factor: 2.242

Review 8.  Lagrangian postprocessing of computational hemodynamics.

Authors:  Shawn C Shadden; Amirhossein Arzani
Journal:  Ann Biomed Eng       Date:  2014-07-25       Impact factor: 3.934

9.  A non-discrete method for computation of residence time in fluid mechanics simulations.

Authors:  Mahdi Esmaily-Moghadam; Tain-Yen Hsia; Alison L Marsden
Journal:  Phys Fluids (1994)       Date:  2013-08-23       Impact factor: 3.521

10.  Compound ex vivo and in silico method for hemodynamic analysis of stented arteries.

Authors:  Farhad Rikhtegar; Fernando Pacheco; Christophe Wyss; Kathryn S Stok; Heng Ge; Ryan J Choo; Aldo Ferrari; Dimos Poulikakos; Ralph Müller; Vartan Kurtcuoglu
Journal:  PLoS One       Date:  2013-03-13       Impact factor: 3.240

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