Literature DB >> 27169665

The Potential of Computational Fluid Dynamics Simulation on Serial Monitoring of Hemodynamic Change in Type B Aortic Dissection.

Simon C H Yu1, Wen Liu2, Randolph H L Wong3, Malcolm Underwood3, Defeng Wang2.   

Abstract

PURPOSE: We aimed to assess the potential of computational fluid dynamics simulation (CFD) in detecting changes in pressure and flow velocity in response to morphological changes in type B aortic dissection.
MATERIALS AND METHODS: Pressure and velocity in four morphological models of type B aortic dissection before and after closure of the entry tear were calculated with CFD and analyzed for changes among the different scenarios. The control model (Model 1) was patient specific and built from the DICOM data of CTA, which bore one entry tear and three re-entry tears. Models 2-4 were modifications of Model 1, with two re-entry tears less in Model 2, one re-entry tear more in Model 3, and a larger entry tear in Model 4.
RESULTS: The pressure and velocity pertaining to each of the morphological models were unique. Changes in pressure and velocity findings were accountable by the changes in morphological features of the different models. There was no blood flow in the false lumen across the entry tear after its closure, the blood flow direction across the re-entry tears was reversed after closure of the entry tear.
CONCLUSION: CFD simulation is probably useful to detect hemodynamic changes in the true and false lumens of type B aortic dissection in response to morphological changes, it may potentially be developed into a non-invasive and patient-specific tool for serial monitoring of hemodynamic changes of type B aortic dissection before and after treatment.

Entities:  

Keywords:  Artificial intelligence; Great vessel disease; Non-invasive blood pressure assessment

Mesh:

Year:  2016        PMID: 27169665     DOI: 10.1007/s00270-016-1352-z

Source DB:  PubMed          Journal:  Cardiovasc Intervent Radiol        ISSN: 0174-1551            Impact factor:   2.740


  4 in total

1.  Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment.

Authors:  Vanessa Diaz-Zuccarini; Mirko Bonfanti; Gaia Franzetti; Stavroula Balabani
Journal:  Theranostics       Date:  2018-12-07       Impact factor: 11.556

2.  Vascular Remodelling Relates to an Elevated Oscillatory Shear Index and Relative Residence Time in Spontaneously Hypertensive Rats.

Authors:  Zhiyan Chen; Haiyi Yu; Yue Shi; Minjia Zhu; Yueshen Wang; Xi Hu; Youyi Zhang; Yu Chang; Ming Xu; Wei Gao
Journal:  Sci Rep       Date:  2017-05-17       Impact factor: 4.379

3.  Quantitative Study of Abdominal Blood Flow Patterns in Patients with Aortic Dissection by 4-Dimensional Flow MRI.

Authors:  Dongting Liu; Zhanming Fan; Yu Li; Nan Zhang; Zhonghua Sun; Jing An; Aurélien F Stalder; Andreas Greiser; Jiayi Liu
Journal:  Sci Rep       Date:  2018-06-14       Impact factor: 4.379

4.  Association of hemodynamic factors and progressive aortic dilatation following type A aortic dissection surgical repair.

Authors:  Yu Zhu; Saeed Mirsadraee; George Asimakopoulos; Alessia Gambaro; Ulrich Rosendahl; John Pepper; Xiao Yun Xu
Journal:  Sci Rep       Date:  2021-06-01       Impact factor: 4.379

  4 in total

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