Sensitivity‐encoded single‐shot spiral imaging for reduced susceptibility artifacts in BOLD fMRI

Abstract

Sensitivity encoding (SENSE) with iterative image reconstruction was used to shorten the readout duration in single-shot spiral imaging by a factor of 2. This enabled susceptibilityrelated blurring and signal loss artifacts to be reduced and spatial resolution to be improved. As a beneficial side effect, the gradient duty cycle was also reduced. The spiral SENSE technique was applied to functional MRI (fMRI) with blood oxygen level-dependent (BOLD) contrast and compared to a conventional spiral acquisition. Stimulation experiments were performed in seven volunteers using motor, visual, and taste paradigms. The signal-to-noise ratio (SNR) and signal-to-fluctuation-noise ratio (SFNR) of the SENSE acquisitions were reduced by 20% and 13%, respectively, with respect to the longer readout. The overall activation detected was comparable to that of the conventional spiral acquisition, even though difficulties in reproducing the stimulation response hampered the evaluation. In some cases, the application of SENSE enabled recovery of acti- Key words: single-shot spiral imaging; sensitivity encoding; SENSE; susceptibility artifacts; BOLD fMRI Spiral readout techniques (1) are frequently used in functional MRI (fMRI) of the brain based on blood oxygen level-dependent (BOLD) contrast (2) because of their superior motion and flow properties as compared with Cartesian trajectories (3,4). Usually, complete images are acquired in a single shot after spin excitation to provide high time efficiency and to avoid sensitivity to intershot motion. However, depending on the required spatial resolution and the available gradient system, this leads to relatively long acquisition windows (in the range of 20 -100 ms). During this period of time, off-resonance phase errors evolve due to susceptibility gradients or chemical shift differences, causing a degradation of the point-spread function (PSF) (5). Additional blurring results from signal loss caused by transverse (T * 2 ) relaxation during the readout period (6).The conjugate phase reconstruction (CPR) method (7,8) partly enables correction of off-resonance errors, even in the case of non-Cartesian trajectories. However, CPR assumes a certain smoothness of the spatial off-resonance distribution and fails in cases where strong susceptibility gradients are present. Furthermore, it cannot account for signal loss due to through-plane dephasing or T * 2 decay. One way to address both types of dephasing is to shorten the acquisition window using multiple spiral interleaves. However, motion sensitivity has to be dealt with by using some kind of navigation (9), and more excitations are needed to complete an image, leading to reduced temporal resolution.As a means of improving time efficiency in MRI, parallel acquisition techniques using receiver coil arrays can shorten readout trains in Cartesian single-shot imaging, thereby reducing artifacts (10 -12) and improving spatial resolution (13). For sensitivity encoding (SENSE) (14), an efficient algorithm for iterative reconstruction of data from ...

Event-related single-shot volumetric functional magnetic resonance inverse imaging of visual processing

“…For example, to mitigate these artifacts, we can use field mapping to investigate the spatial distribution of the off-resonance effects and then use this information to reduce the susceptibility artifacts (Chen et al, 2006;Chen and Wyrwicz, 1999;Zeng and Constable, 2002). It is also possible to use parallel imaging techniques with EPI acquisitions to limit geometric distortion (Weiger et al, 2002), by systematically skipping multiple integer lines in the continuous sampling of different phaseencoding lines and then reconstructing the skipped phase encoding lines using spatial information embedded inside different array channels. Thus the effective bandwidth in the reconstructed image will be wider and will thereby reduce the distortion.…”

“…Prior information can be incorporated by combining EPI with parallel MR imaging (Golay et al, 2000;Preibisch et al, 2003;Schmidt et al, 2005;Weiger et al, 2002), resulting in fMRI detection sensitivity improvements with sensitivity encoded parallel MRI techniques (Lin et al, 2005b). Prior-informed parallel MRI has been explored using a fixed regularization parameter with empirical singular value decomposition truncation (King, 2001;Sodickson, 2000).…”

High‐resolution fMRI with higher‐order generalized series imaging and parallel imaging techniques (HGS‐parallel)

“…In this optimization, the l 1 regularization was used to effectively reconstruct the sharp edges (in contrast to the l 2 regularization) (27) and to produce sparse solutions (28). Equation [7] was solved by using the iterative Quasi-Newton algorithm. In this case, the LaGrange multiplier was selected experimentally, which was 2 HGS ϭ 1 in the article.…”

“…In the HGS reconstruction step, the series coefficients, c n,l (x), are computed with the aid of Eq. [7] for each receiver channel, l ϭ 1,2,…L, based on the reference data, d (ref) l (x,k n ), and the acquired dynamic data, d l (x,k m ). The HGS-reconstructed images, I (HGS) l (x,y), for each receiver channel, l ϭ 1,2,…L, can then be obtained with Eq.…”

SNR and functional sensitivity of BOLD and perfusion-based fMRI using arterial spin labeling with spiral SENSE at 3 T

“…For blood oxygenation level dependent (BOLD) functional MRI (fMRI) studies, parallel imaging methods have been used to decrease the readout times of single-shot echoplanar imaging (EPI) (2) and spiral acquisitions (3). This reduction in the readout time was shown to increase the detection power of BOLD fMRI studies in brain regions where magnetic susceptibility inhomogeneities can lead to significant image distortions and signal loss when long readout windows are used.…”