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DPD enables mesoscopic MRI simulation of slow flow

  • Mueed Azhar
  • Suleman Shakil
  • Andreas Greiner
  • David Kauzlarić
  • Jan G. Korvink
Research Paper
  • 132 Downloads

Abstract

We present a novel method to simulate magnetic resonance imaging (MRI) for the assessment of slow flow at Reynolds number \(Re \approx 0.02\). We couple Bloch equations with dissipative particle dynamics (DPD) to study the effect of flow dynamics at the mesoscopic level on acquired MR images. The Bloch equations are used to propagate the evolution of the magnetization of particles while their trajectories are being computed simultaneously based on DPD interaction forces. The magnetic resonance assessment of fluid velocities is performed using a phase-contrast MRI technique, implemented by a spin echo single-sided bipolar gradient sequence. The computational cost for simulating the fluid flow is successfully reduced by an efficient implementation of a vectorized isochromat algorithm. We demonstrate successful simulation of laminar flow, flow with diffusion effects, and flow around an obstacle. The method can be used to simulate convective and diffusive flow MRI experiments at the mesoscopic level.

Keywords

Phase-contrast magnetic resonance imaging Dissipative particle dynamics Isochromat summation method Spin echo single-sided bipolar gradient pulse sequence 

Notes

Acknowledgements

MA acknowledges funding from DAAD (Grant Number A0895301) for this research and also would like to thank Dr. Waltraud Buchenberg, Mr. Torsten Kirk, and Dr. Said Abdu for fruitful discussions. AG and DK acknowledges partial funding by the DFG (Grant Number GR 2622/6-1). DK also acknowledges partial funding by the DFG (Grant Number KA 3482/2). JGK acknowledges partial funding from the ERC Senior Grant Number 290586—NMCEL, and the excellence cluster Brain-Links-Brain-Tools EXC 1086. The authors acknowledge partial funding by the University of Freiburg through the German excellence initiative.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory for Simulation, Department of Microsystems Engineering (IMTEK)University of FreiburgFreiburgGermany
  2. 2.Department of Microstructure TechnologyKarlsruhe Institute of TechnologyEggenstein-LeopoldshafenGermany

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