Literature DB >> 17714975

Computational representation and hemodynamic characterization of in vivo acquired severe stenotic renal artery geometries using turbulence modeling.

George C Kagadis1, Eugene D Skouras, George C Bourantas, Christakis A Paraskeva, Konstantinos Katsanos, Dimitris Karnabatidis, George C Nikiforidis.   

Abstract

The present study reports on computational fluid dynamics in the case of severe renal artery stenosis (RAS). An anatomically realistic model of a renal artery was reconstructed from CT scans, and used to conduct CFD simulations of blood flow across RAS. The recently developed shear stress transport (SST) turbulence model was pivotally applied in the simulation of blood flow in the region of interest. Blood flow was studied in vivo under the presence of RAS and subsequently in simulated cases before the development of RAS, and after endovascular stent implantation. The pressure gradients in the RAS case were many orders of magnitude larger than in the healthy case. The presence of RAS increased flow resistance, which led to considerably lower blood flow rates. A simulated stent in place of the RAS decreased the flow resistance at levels proportional to, and even lower than, the simulated healthy case without the RAS. The wall shear stresses, differential pressure profiles, and net forces exerted on the surface of the atherosclerotic plaque at peak pulse were shown to be of relevant high distinctiveness, so as to be considered potential indicators of hemodynamically significant RAS.

Entities:  

Mesh:

Year:  2007        PMID: 17714975     DOI: 10.1016/j.medengphy.2007.07.005

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  8 in total

1.  Patient-specific 3D hemodynamics modelling of left coronary artery under hyperemic conditions.

Authors:  Sarfaraz Kamangar; Irfan Anjum Badruddin; Kalimuthu Govindaraju; N Nik-Ghazali; A Badarudin; Girish N Viswanathan; N J Salman Ahmed; T M Yunus Khan
Journal:  Med Biol Eng Comput       Date:  2016-12-21       Impact factor: 2.602

Review 2.  Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases.

Authors:  Yong He; Hannah Northrup; Ha Le; Alfred K Cheung; Scott A Berceli; Yan Tin Shiu
Journal:  Front Bioeng Biotechnol       Date:  2022-04-27

Review 3.  Mechanotransduction in the endothelium: role of membrane proteins and reactive oxygen species in sensing, transduction, and transmission of the signal with altered blood flow.

Authors:  Shampa Chatterjee; Aron B Fisher
Journal:  Antioxid Redox Signal       Date:  2014-01-22       Impact factor: 8.401

4.  Numerical investigation of the effect of stenosis geometry on the coronary diagnostic parameters.

Authors:  Sarfaraz Kamangar; Govindaraju Kalimuthu; Irfan Anjum Badruddin; A Badarudin; N J Salman Ahmed; T M Yunus Khan
Journal:  ScientificWorldJournal       Date:  2014-09-01

5.  Numerical investigation of angulation effects in stenosed renal arteries.

Authors:  Z Mortazavinia; S Arabi; A R Mehdizadeh
Journal:  J Biomed Phys Eng       Date:  2014-03-08

6.  Hemodynamics in Transplant Renal Artery Stenosis and its Alteration after Stent Implantation Based on a Patient-specific Computational Fluid Dynamics Model.

Authors:  Hong-Yang Wang; Long-Shan Liu; Hai-Ming Cao; Jun Li; Rong-Hai Deng; Qian Fu; Huan-Xi Zhang; Ji-Guang Fei; Chang-Xi Wang
Journal:  Chin Med J (Engl)       Date:  2017 5th Jan 2017       Impact factor: 2.628

7.  Non-invasive diagnostics of blockage growth in the descending aorta-computational approach.

Authors:  Mohammad Al-Rawi; Ahmed M Al-Jumaily; Djelloul Belkacemi
Journal:  Med Biol Eng Comput       Date:  2022-09-27       Impact factor: 3.079

Review 8.  Understanding the Causes and Implications of Endothelial Metabolic Variation in Cardiovascular Disease through Genome-Scale Metabolic Modeling.

Authors:  Sarah McGarrity; Haraldur Halldórsson; Sirus Palsson; Pär I Johansson; Óttar Rolfsson
Journal:  Front Cardiovasc Med       Date:  2016-04-18
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.