Literature DB >> 25224077

Is MRI-based CFD able to improve clinical treatment of coarctations of aorta?

L Goubergrits1, E Riesenkampff, P Yevtushenko, J Schaller, U Kertzscher, F Berger, T Kuehne.   

Abstract

Pressure drop associated with coarctation of the aorta (CoA) can be successfully treated surgically or by stent placement. However, a decreased life expectancy associated with altered aortic hemodynamics was found in long-term studies. Image-based computational fluid dynamics (CFD) is intended to support particular diagnoses, to help in choosing between treatment options, and to improve performance of treatment procedures. This study aimed to prove the ability of CFD to improve aortic hemodynamics in CoA patients. In 13 patients (6 males, 7 females; mean age 25 ± 14 years), we compared pre- and post-treatment peak systole hemodynamics [pressure drops and wall shear stress (WSS)] vs. virtual treatment as proposed by biomedical engineers. Anatomy and flow data for CFD were based on MRI and angiography. Segmentation, geometry reconstruction and virtual treatment geometry were performed using the software ZIBAmira, whereas peak systole flow conditions were simulated with the software ANSYS(®) Fluent(®). Virtual treatment significantly reduced pressure drop compared to post-treatment values by a mean of 2.8 ± 3.15 mmHg, which significantly reduced mean WSS by 3.8 Pa. Thus, CFD has the potential to improve post-treatment hemodynamics associated with poor long-term prognosis of patients with coarctation of the aorta. MRI-based CFD has a huge potential to allow the slight reduction of post-treatment pressure drop, which causes significant improvement (reduction) of the WSS at the stenosis segment.

Entities:  

Mesh:

Year:  2014        PMID: 25224077     DOI: 10.1007/s10439-014-1116-3

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


  6 in total

1.  Avoidable costs of stenting for aortic coarctation in the United Kingdom: an economic model.

Authors:  Maximilian Salcher; Alistair Mcguire; Vivek Muthurangu; Marcus Kelm; Titus Kuehne; Huseyin Naci
Journal:  BMC Health Serv Res       Date:  2017-04-10       Impact factor: 2.655

2.  Reducing the impact of geometric errors in flow computations using velocity measurements.

Authors:  David Nolte; Cristóbal Bertoglio
Journal:  Int J Numer Method Biomed Eng       Date:  2019-04-16       Impact factor: 2.747

3.  Percutaneous Thrombin Injection Based on Computational Fluid Dynamics of Femoral Artery Pseudoaneurysms.

Authors:  Hyoung-Ho Kim; Kyung-Wuk Kim; Changje Lee; Young Ho Choi; Min Uk Kim; Yasutaka Baba
Journal:  Korean J Radiol       Date:  2021-07-26       Impact factor: 3.500

4.  Personalized Pre- and Post-Operative Hemodynamic Assessment of Aortic Coarctation from 3D Rotational Angiography.

Authors:  Cosmin-Ioan Nita; Andrei Puiu; Daniel Bunescu; Lucian Mihai Itu; Viorel Mihalef; Gouthami Chintalapani; Aimee Armstrong; Jeffrey Zampi; Lee Benson; Puneet Sharma; Saikiran Rapaka
Journal:  Cardiovasc Eng Technol       Date:  2021-06-18       Impact factor: 2.495

5.  Establishment and assessment of the hepatic venous pressure gradient using biofluid mechanics (HVPGBFM): protocol for a prospective, randomised, non-controlled, multicentre study.

Authors:  Jia-Yun Lin; Chi-Hao Zhang; Lei Zheng; Hui-Song Chen; Hong-Jie Li; Yi-Ming Zhu; Xiao Fan; Feng Li; Yan Xia; Ming-Zhe Huang; Sun-Hu Yang; Xiao-Liang Qi; Hai-Zhong Huo; Xiao-Lou Lou; Meng Luo
Journal:  BMJ Open       Date:  2019-12-03       Impact factor: 2.692

6.  Assessment of a biofluid mechanics-based model for calculating portal pressure in canines.

Authors:  Jia-Yun Lin; Chi-Hao Zhang; Lei Zheng; Chen-Lu Song; Wen-Sheng Deng; Yi-Ming Zhu; Li Zheng; Li-Zhong Wu; Long-Ci Sun; Meng Luo
Journal:  BMC Vet Res       Date:  2020-08-26       Impact factor: 2.741

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.