Document Type

Article

Language

eng

Format of Original

9 p.

Publication Date

2-2014

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Source Publication

IEEE Transactions on Medical Imaging

Source ISSN

0278-0062

Original Item ID

doi: 10.1109/TMI.2013.2288521

Abstract

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.

Comments

Accepted version. IEEE Transactions on Medical Imaging, Vol. 33, No. 2 (February 2014): 495-503. DOI. © 2014 Institute of Electrical and Electronics Engineers (IEEE). Used with permission.

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