Matched-filter acquisition for BOLD fMRI.
We introduce matched-filter fMRI, which improves BOLD (blood oxygen level dependent) sensitivity by variable-density image acquisition tailored to subsequent image smoothing. Image smoothing is an established post-processing technique used in the vast majority of fMRI studies. Here we show that the signal-to-noise ratio of the resulting smoothed data can be substantially increased by acquisition weighting with a weighting function that matches the k-space filter imposed by the smoothing operation. We derive the theoretical SNR advantage of this strategy and propose a practical implementation of 2D echo-planar acquisition matched to common Gaussian smoothing. To reliably perform the involved variable-speed trajectories, concurrent magnetic field monitoring with NMR probes is used. Using this technique, phantom and in vivo measurements confirm reliable SNR improvement in the order of 30% in a "resting-state" condition and prove robust in different regimes of physiological noise. Furthermore, a preliminary task-based visual fMRI experiment equally suggests a consistent BOLD sensitivity increase in terms of statistical sensitivity (average t-value increase of about 35%). In summary, our study suggests that matched-filter acquisition is an effective means of improving BOLD SNR in studies that rely on image smoothing at the post-processing level.
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland; Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland. Electronic address: kasper@biomed.ee.ethz.ch.
Lars
L
Kasper
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
Maximilian
M
Haeberlin
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
Benjamin E
BE
Dietrich
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
Simon
S
Gross
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland; Skope Magnetic Resonance Technologies, Zurich, Switzerland.
Christoph
C
Barmet
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
Bertram J
BJ
Wilm
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
S Johanna
SJ
Vannesjo
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
David O
DO
Brunner
Laboratory for Social and Neural Systems Research (SNS), Department of Economics, University of Zurich, Switzerland.
Christian C
CC
Ruff
Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland; Laboratory for Social and Neural Systems Research (SNS), Department of Economics, University of Zurich, Switzerland; Wellcome Trust Center for Neuroimaging, Institute of Neurology, University College London, United Kingdom.
Klaas E
KE
Stephan
Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland.
Klaas P
KP
Pruessmann
D000328:Adult; D015350:Contrast Sensitivity / Q000502:physiology; D003627:Data Interpretation, Statistical; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D059629:Signal-To-Noise Ratio; D014793:Visual Cortex / Q000502:physiology
BOLD sensitivity; Density-weighted EPI; Image smoothing; Magnetic field monitoring; Matched-filter; fMRI