title: Optimizing RetroICor and RetroKCor corrections for multi-shot 3D FMRI acquisitions.
abstract: Physiological noise, if unaccounted for, can drastically reduce the statistical significance of detected activation in FMRI. In this paper, we systematically optimize physiological noise regressions for multi-shot 3D FMRI data. First, we investigate whether 3D FMRI data are best corrected in image space (RetroICor) or k-space (RetroKCor), in which each k-space segment can be assigned its unique physiological phase. In addition, the optimal regressor set is determined using the Bayesian Information Criterion (BIC) for a variety of 3D acquisitions corresponding to different image contrasts and k-space readouts. Our simulations and experiments indicate that: (a) k-space corrections are more robust when performed on real/imaginary than magnitude/phase data; (b) k-space corrections do not outperform image-space corrections, despite the ability to synchronize physiological phase to acquisition time more accurately; and (c) the optimal model varied considerably between the various acquisition techniques. These results suggest the use of a tailored set of volume-wide regressors, determined by BIC or other selection criteria, that achieves optimal balance between variance reduction and potential over-fitting.
authors.affiliation: FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: r.tijssen@umcutrecht.nl.
authors.forename: Rob H N
authors.initials: RH
authors.lastname: Tijssen
authors.forename: Mark
authors.initials: M
authors.lastname: Jenkinson
authors.forename: Jonathan C W
authors.initials: JC
authors.lastname: Brooks
authors.forename: Peter
authors.initials: P
authors.lastname: Jezzard
authors.forename: Karla L
authors.initials: KL
authors.lastname: Miller
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio
keywords: 3D EPI; Brainstem; Functional MRI; GRE; Physiological noise; SPGR; SSFP
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