Abstract #4007

Correcting respiratory-related noise in brainstem fMRI using regressors derived from phase data

David Bancelin¹, Pedro Lima Cardoso¹, Beata Bachrata^1,2, Andreas Ehrmann¹, Siegfried Trattnig^1,2, and Simon D. Robinson^1,3,4

¹High-Field MR Centre, Medical University of Vienna, Vienna, Austria, ²Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria, ³Department of Neurology, Medical University of Graz, Graz, Austria, ⁴Centre for Advanced Imaging, University of Queensland, Queensland, Australia

Respiratory and cardiac data are generally used to properly account for the presence of physiological noise in fMRI data. Pneumatic belts can be unreliable, but we show that EPI phase data can be used to generate a reliable respiratory time series from which regressors are used in a GLM procedure to correct magnitude data. The efficacy of our method is compared with respect to (i) uncorrected magnitude data and (ii) magnitude data corrected using respiratory belt-derived regressors.

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