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Glover_retrocor - Image-Based Method for Retrospective...

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Image-Based Method for Retrospective Correction of Physiological Motion Effects in fMRI: RETROICOR G ARY H. G LOVER § , T IE -Q IANG L I § , D AVID R ESS Stanford University Department of Radiology § ; Department of Psychology Center for Advanced MR Technology at Stanford Stanford, California 94305-5488 Accepted, M AGNETIC R ESONANCE IN M EDICINE : MRM 99-4512 ABSTRACT Respiration effects and cardiac pulsatility can induce signal modulations in functional MR image time-series that increase noise and degrade the statistical significance of activation signals. A simple image-based correction method is described that does not have the limitations of k- space methods that preclude high spatial frequency correction. Low order Fourier series are fit to the image data based on time of each image acquisition relative to the phase of the cardiac and respiratory cycles, monitored using a photoplethysmograph and pneumatic belt, respectively. The RETROICOR method is demonstrated using resting-state experiments on three subjects and compared with the k-space method. The method is found to perform well for both respiration and cardiac induced noise without imposing spatial filtering on the correction. Keywords: Functional magnetic resonance imaging; physiological motion, retrospective motion correction INTRODUCTION Functional Magnetic Resonance Imaging (fMRI) is based on changes in the signal resulting from BOLD contrast (1, 2) or blood flow changes (2). Pulsatility of blood flow in the brain and respiration-induced magnetic field changes or motion can cause appreciable modulation of the signal (3, 4), and this in turn causes undesired perturbations in the images that include intensity fluctuations and other artifacts. In many cases the added noise induced by these physiological processes can be comparable to the desired signal, which degrades the statistical significance of activation signals or otherwise compromises event-related analyses. Dagli has found that the effects of cardiac function tend to be rather localized in the brain due to the vessel-dependent brain pulsatility (5). Respiration effects, which originate from thoracic modulation of the magnetic field in the head or from bulk motions of the head, are often more spatially global (3). However, we show here that respiration effects can also be localized. Several methods have been developed for reducing such physiological noise in fMRI time- series. Navigator methods correct k-space data using either an auxiliary echo (6) or the scan data itself (7, 8). While navigator methods can be effective, they sample either a projection of the brain or the entire slice and therefore lack specificity in localizing the source of motion. This in turn can cause incomplete correction or can introduce fluctuations in quiescent parts of the brain. Biswal introduced the use of notch filters to remove components of the time-series spectrum at the cardiac and respiratory frequencies (9).
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