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MRI-based computational hemodynamics in patients with aortic coarctation using the lattice Boltzmann methods: Clinical validation study

 
: Mirzaee, H.; Henn, T.; Krause, M.J.; Goubergrits, L.; Schumann, C.; Neugebauer, M.; Kuehne, T.; Preusser, T.; Hennemuth, A.

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Journal of magnetic resonance imaging 45 (2017), Nr.1, S.139-146
ISSN: 1053-1807
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer MEVIS ()

Abstract
Purpose
To introduce a scheme based on a recent technique in computational hemodynamics, known as the lattice Boltzmann methods (LBM), to noninvasively measure pressure gradients in patients with a coarctation of the aorta (CoA). To provide evidence on the accuracy of the proposed scheme, the computed pressure drop values are compared against those obtained using the reference standard method of catheterization.
Materials and Methods
Pre- and posttreatment LBM-based pressure gradients for 12 patients with CoA were simulated for the time point of peak systole using the open source library OpenLB. Four-dimensional (4D) flow-sensitive phase-contrast MRI at 1.5 Tesla was used to acquire flow and to setup the simulation. The vascular geometry was reconstructed using 3D whole-heart MRI. Patients underwent pre- and postinterventional pressure catheterization as a reference standard.
Results
There is a significant linear correlation between the pretreatment catheter pressure drops and those computed based on the LBM simulation, , . The bias was -0.58 ± 4.1 mmHg and was not significant ( with a 95% confidence interval (CI) of -3.22 to 2.06. For the posttreatment results, the bias was larger and at -2.54 ± 3.53 mmHg with a 95% CI of -0.17 to -4.91 mmHg.
Conclusion
The results indicate a reasonable agreement between the simulation results and the catheter measurements. LBM-based computational hemodynamics can be considered as an alternative to more traditional computational fluid dynamics schemes for noninvasive pressure calculations and can assist in diagnosis and therapy planning. J. Magn. Reson. Imaging 2016.

: http://publica.fraunhofer.de/dokumente/N-417505.html