Quantifying the statistical impact of GRAPPA in fcMRI data with a real-valued isomorphism.

Journal Article

The interpolation of missing spatial frequencies through the generalized auto-calibrating partially parallel acquisitions (GRAPPA) parallel magnetic resonance imaging (MRI) model implies a correlation is induced between the acquired and reconstructed frequency measurements. As the parallel image reconstruction algorithms in many medical MRI scanners are based on the GRAPPA model, this study aims to quantify the statistical implications that the GRAPPA model has in functional connectivity studies. The linear mathematical framework derived in the work of Rowe , 2007, is adapted to represent the complex-valued GRAPPA image reconstruction operation in terms of a real-valued isomorphism, and a statistical analysis is performed on the effects that the GRAPPA operation has on reconstructed voxel means and correlations. The interpolation of missing spatial frequencies with the GRAPPA model is shown to result in an artificial correlation induced between voxels in the reconstructed images, and these artificial correlations are shown to reside in the low temporal frequency spectrum commonly associated with functional connectivity. Through a real-valued isomorphism, such as the one outlined in this manuscript, the exact artificial correlations induced by the GRAPPA model are not simply estimated, as they would be with simulations, but are precisely quantified. If these correlations are unaccounted for, they can incur an increase in false positives in functional connectivity studies.

Full Text

Duke Authors

Cited Authors

  • Bruce, IP; Rowe, DB

Published Date

  • February 2014

Published In

Volume / Issue

  • 33 / 2

Start / End Page

  • 495 - 503

PubMed ID

  • 24235300

Pubmed Central ID

  • 24235300

Electronic International Standard Serial Number (EISSN)

  • 1558-254X

Digital Object Identifier (DOI)

  • 10.1109/TMI.2013.2288521


  • eng

Conference Location

  • United States