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Patient-specific lattice-Boltzmann simulations with inflow conditions from magnetic resonance velocimetry measurements for analyzing cerebral aneurysms

Rüttgers, Mario ; Waldmann, Moritz; Ito, Shota 1; Wüstenhagen, Carolin; Grundmann, Sven; Brede, Martin; Lintermann, Andreas
1 Institut für Mechanische Verfahrenstechnik und Mechanik (MVM), Karlsruher Institut für Technologie (KIT)

Abstract:

Magnetic resonance velocimetry (MRV) measurements were used as inflow conditions for lattice-Boltzmann (LB) simulations to analyze cerebral aneurysms. Unlike previous studies on larger vascular structures, aneurysm analysis involves smaller scales and higher pressure differences, making near-wall velocity measurements challenging with standard 3 Tesla scanners. To address this, the aneurysm geometry was scaled 5-fold for sufficient magnetic resonance velocimetry (MRV) resolution, with inflow measurements interpolated onto the simulation grid while ensuring dimensionless equivalence via the Reynolds number. Zero-velocity points were included near walls to enforce the no-slip condition if measurement points exceed the simulation domain. The proposed interpolation-based inflow method was compared to a nearest-neighbor approach and a parabolic velocity profile. It achieved the best agreement with MRV centerline velocity measurements (mean error: 3.12%), followed by the nearest-neighbor method (3.18%) and the parabolic profile (9.85%). The parabolic inflow led to centerline velocity overpredictions and total pressure underpredictions, while the nearest-neighbor approach underestimated the wall shear stress (WSS) and exhibited inconsistencies in wall normal stress (e.g., maximum WSS was 18.3% lower than with interpolation). ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000179614
Veröffentlicht am 28.02.2025
Originalveröffentlichung
DOI: 10.1016/j.compbiomed.2025.109794
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Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Mechanische Verfahrenstechnik und Mechanik (MVM)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 03.2025
Sprache Englisch
Identifikator ISSN: 0010-4825, 1879-0534
KITopen-ID: 1000179614
Erschienen in Computers in Biology and Medicine
Verlag Elsevier
Band 187
Seiten 109794
Nachgewiesen in OpenAlex
Scopus
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