Frontiers in Neuroscience (Mar 2015)

An evaluation of Prospective Motion Correction (PMC) for high resolution quantitative MRI

  • Martina F Callaghan,
  • Oliver eJosephs,
  • Michael eHerbst,
  • Michael eHerbst,
  • Maxim eZaitsev,
  • Nick eTodd,
  • Nikolaus eWeiskopf

DOI
https://doi.org/10.3389/fnins.2015.00097
Journal volume & issue
Vol. 9

Abstract

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Quantitative imaging aims to provide in vivo neuroimaging biomarkers with high research and diagnostic value that are sensitive to underlying tissue microstructure. In order to use these data to examine intra-cortical differences or to define boundaries between different myelo-architectural areas, high resolution data are required. The quality of such measurements is degraded in the presence of motion hindering insight into brain microstructure. Correction schemes are therefore vital for high resolution, whole brain coverage approaches that have long acquisition times and greater sensitivity to motion. Here we evaluate the use of prospective motion correction (PMC) via an optical tracking system to counter intra-scan motion in a high resolution (800µm isotropic) multi-parameter mapping (MPM) protocol. Data were acquired on six volunteers using a 2x2 factorial design permuting the following conditions: PMC on/off and motion/no motion. In the presence of head motion, PMC-based motion correction considerably improved the quality of the maps as reflected by fewer visible artefacts and improved consistency. The precision of the maps, parameterised by the coefficient of variation in cortical sub-regions, showed improvements of 11-24% in the presence of deliberate head motion. Importantly, in the absence of motion the PMC system did not introduce extraneous artefacts into the quantitative maps. The PMC system based on optical tracking offers a robust approach to minimising motion artefacts in quantitative anatomical imaging without extending scan times. Such a robust motion correction scheme is crucial in order to achieve the ultra-high resolution required of quantitative imaging for cutting edge in vivo histology applications.

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