Magnetic resonance advection imaging of cerebrovascular pulse dynamics

J Cereb Blood Flow Metab. 2017 Apr;37(4):1223-1235. doi: 10.1177/0271678X16651449. Epub 2016 Jan 1.

Abstract

We analyze the pulsatile signal component of dynamic echo planar imaging data from the brain by modeling the dependence between local temporal and spatial signal variability. The resulting magnetic resonance advection imaging maps depict the location of major arteries. Color direction maps allow for visualization of the direction of blood vessels. The potential significance of magnetic resonance advection imaging maps is demonstrated on a functional magnetic resonance imaging data set of 19 healthy subjects. A comparison with the here introduced pulse coherence maps, in which the echo planar imaging signal is correlated with a cardiac pulse signal, shows that the magnetic resonance advection imaging approach results in a better spatial definition without the need for a pulse reference. In addition, it is shown that magnetic resonance advection imaging velocities can be estimates of pulse wave velocities if certain requirements are met, which are specified. Although for this application magnetic resonance advection imaging velocities are not quantitative estimates of pulse wave velocities, they clearly depict local pulsatile dynamics. Magnetic resonance advection imaging can be applied to existing dynamic echo planar imaging data sets with sufficient spatiotemporal resolution. It is discussed whether magnetic resonance advection imaging might have the potential to evolve into a biomarker for the health of the cerebrovascular system.

Keywords: Brain imaging; cerebral hemodynamics; magnetic resonance angiography; magnetic resonance imaging; mathematical modeling.

MeSH terms

  • Blood Flow Velocity / physiology*
  • Brain / blood supply*
  • Brain Mapping
  • Cerebral Arteries / anatomy & histology
  • Cerebrovascular Circulation / physiology*
  • Echo-Planar Imaging / methods*
  • Humans
  • Magnetic Resonance Angiography / methods*
  • Models, Biological*