Ces radiol. 2023, 77(3):150-155 | DOI: 10.55095/CesRadiol2023/018

Use of the lattice Boltzmann method to model flow in the aortic bifurcation: comparison with 4D Flow MRIOriginal article

Radek Galabov1, Jan Kovář2, Pavel Eichler2, Kateřina Škardová2, Radomír Chabiniok3, Tomáš Oberhuber2, Radek Fučík2, Petr Pauš2, Aleš Wodecki2, Jiří Novotný1, Jaroslav Tintěra1
1 Institut klinické a experimentální medicíny, Praha
2 Fakulta jaderná a fyzikálně inženýrská, České vysoké učení technické, Praha
3 UT Southwestern Medical Center, Dallas, USA

Aim: The aim of the article is to qualitatively assess the usability of amathematical flow model for visualizing the flow in aortic bifurcation treatedwith stents.

Methodology: Nine examinations of aortic bifurcations were conducted using a4D Flow sequence. Patients without stents, patients with a stent in one branch,and patients with stents in both branches of the aortic bifurcation wereexamined. 4D Flow data were used to prepare a visualization of the velocityfield. Flow simulations were performed based on the segmented bifurcation andmeasured flow data, including areas where flow measurements were affected byartifacts. Measured and simulated velocity fields were visually compared.

Results: For patients without stents, the simulated flow contributed toeliminating small inaccuracies in the measured field. In patients with stents,the simulated data were more consistent than the measured data and providedadditional insight into the situation within the stents.

Discussion: Simulated velocity fields must inherently adhere to the laws ofphysics, allowing for the correction of measured data in regions where measurements arecompromised. Depending on the accuracy of the segmentation, it may also offernew diagnostic information. However, the obtained results are solelyqualitative and will need quantitative validation.

Conclusion: The mathematical flow model can aid in quantitative assessment offlow in the vascular locations treated with stents where the direct MRmeasurement of blood flow fails.

Keywords: 4D Flow, lattice Boltzmann method, aortic bifurcation

Published: September 1, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Galabov R, Kovář J, Eichler P, Škardová K, Chabiniok R, Oberhuber T, et al.. Use of the lattice Boltzmann method to model flow in the aortic bifurcation: comparison with 4D Flow MRI. Ces radiol. 2023;77(3):150-155. doi: 10.55095/CesRadiol2023/018.
Download citation

References

  1. Lotz J, Meier C, Leppert A, Galanski M. Cardiovascular flow measurement with phase-contrast MR imaging: basic facts and implementation. RadioGraphics
  2. 22(3): 651-671.
  3. Dyverfeldt P, Bissell M, Barker AJ, et al. 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson Internet 2015; 17(1). Available from: http://dx.doi.org/10.1186/s12968-015-0174-5 Go to original source... Go to PubMed...
  4. Bunck A, Jüttner A, Kröger J, Burg, et al. 4D phase contrast flow imaging for in-stent flow visualization and assessment of stent patency in peripheral vascular stents - A phantom study. European Journal of Radiology 2012; 81: e929-937. Go to original source... Go to PubMed...
  5. Morris PD, Narracott A, von Tengg-Kobligk H, et al. Computational fluid dynamics modelling in cardiovascular medicine. Heart 2016; 102(1): 18-28. doi: 10.1136/heartjnl-2015-308044 [Epub 2015 Oct 28]. PMID: 26512019; PMCID: PMC4717410. Go to original source... Go to PubMed...
  6. Nourgaliev RR, Dinh TN, Theofanous TG, Joseph D. The lattice Boltzmann equation method: theoretical interpretation, numerics and implications. Int J Multiph Flow Internet 2003; 29(1): 117-169. Available from: https://www.sciencedirect.com/science/article/pii/S0301932202001088 Go to original source...
  7. Galabov R, Škardová K, Chabiniok R, et al. Zkušenosti s použitím a zpracováním dat z měření průtoků magnetickou rezonancí sekvencí 4D Flow. Ces Radiol 2022; 76(4): 249-255. Go to original source...
  8. Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magn Reson Imaging 2012; 30(9): 1323-1341. PMID: 22770690. PMCID: PMC3466397. Go to original source... Go to PubMed...

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.