Mark Chiew

k-t FASTER: Acceleration of functional MRI data acquisition using low rank constraints.

In functional MRI (fMRI), faster sampling of data can provide richer temporal information and increase temporal degrees of freedom. However, acceleration is generally performed on a volume‐by‐volume basis, without consideration of the intrinsic spatio‐temporal data structure. We present a novel method for accelerating fMRI data acquisition, k‐t FASTER (FMRI Accelerated in Space‐time via Truncation of Effective Rank), which exploits the low‐rank structure of fMRI data.

k-t FASTER: a novel method for accelerating FMRI data acquisition using low rank constraints

In functional MRI (fMRI), faster sampling of data can provide richer temporal information and increase temporal degrees of freedom. However, acceleration is generally performed on a volume‐by‐volume basis, without consideration of the intrinsic spatio‐temporal data structure. We present a novel method for accelerating fMRI data acquisition, k‐t FASTER (FMRI Accelerated in Space‐time via Truncation of Effective Rank), which exploits the low‐rank structure of fMRI data.

The relationship between delay period eye movements and visuospatial memory.

We investigated whether overt shifts of attention were associated with visuospatial memory performance. Participants were required to study the locations of a set of visual objects and subsequently detect changes to the spatial location of one of the objects following a brief delay period. Relational information regarding the locations among all of the objects could be used to support performance on the task (Experiment 1) or relational information was removed during test and location manipulation judgments had to be made for a singly presented target item (Experiment 2). We computed the similarity of the fixation patterns in space during the study phase to the fixations made during the delay period. Greater fixation pattern similarity across participants was associated with higher accuracy when relational information was available at test (Experiment 1); however, this association was not observed when the target item was presented in isolation during the test display (Experiment 2). Similarly, increased fixation pattern similarity on a given trial (within participants) was associated with successful task performance when the relations among studied items could be used for comparison (Experiment 1), but not when memory for absolute spatial location was assessed (Experiment 2). This pattern of behavior and performance on the two tasks suggested that eye movements facilitated memory for the relationships among objects. Shifts of attention through eye movements may provide a mechanism for the maintenance of relational visuospatial memory.

Real‐time correction by optical tracking with integrated geometric distortion correction for reducing motion artifacts in functional MRI

Head motion artifacts are a major problem in functional MRI that limit its use in neuroscience research and clinical settings. Real‐time scan‐plane correction by optical tracking has been shown to correct slice misalignment and nonlinear spin‐history artifacts; however, residual artifacts due to dynamic magnetic field nonuniformity may remain in the data. A recently developed correction technique, Phase Labeling for Additional Coordinate Encoding, can correct for absolute geometric distortion using only the complex image data from two echo planar images with slightly shifted k‐space trajectories. An approach is presented that integrates Phase Labeling for Additional Coordinate Encoding into a real‐time scan‐plane update system by optical tracking, applied to a tissue‐equivalent phantom undergoing complex motion and an functional MRI finger tapping experiment with overt head motion to induce dynamic field nonuniformity. Experiments suggest that such integrated volume‐by‐volume corrections are very effective at artifact suppression, with potential to expand functional MRI applications. Magn Reson Med, 2013.

Accelerating functional MRI using fixed-rank approximations and radial-cartesian sampling

Recently, k‐t FASTER (fMRI Accelerated in Space‐time by means of Truncation of Effective Rank) was introduced for rank‐constrained acceleration of fMRI data acquisition. Here we demonstrate improvements achieved through a hybrid three‐dimensional radial‐Cartesian sampling approach that allows posthoc selection of acceleration factors, as well as incorporation of coil sensitivity encoding in the reconstruction.

Motion correction for functional MRI with three-dimensional hybrid radial-Cartesian EPI.

Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three‐dimensional (3D EPI). We present a hybrid radial‐Cartesian 3D EPI trajectory enabling motion correction in k‐space for functional MRI.

Multiecho coarse voxel acquisition for neurofeedback fMRI.

“Real‐time” functional magnetic resonance imaging is starting to be used in neurofeedback applications, enabling individuals to regulate their brain activity for therapeutic purposes. These applications use two‐dimensional multislice echo planar or spiral readouts to image the entire brain volume, often with a much smaller region of interest within the brain monitored for feedback purposes. Given that such brain activity should be sampled rapidly, it is worthwhile considering alternative functional magnetic resonance imaging pulse sequences that trade spatial resolution for temporal resolution. We developed a prototype sequence localizing a column of magnetization by outer volume saturation, from which densely sampled transverse relaxation time decays are obtained at coarse voxel locations using an asymmetric gradient echo train. For 5 × 20 × 20 mm3 voxels, 256 echoes are sampled at ∼1 msec and then combined in weighted summation to increase functional magnetic resonance imaging signal contrast. This multiecho coarse voxel pulse sequence is shown experimentally at 1.5 T to provide the same signal contrast to noise ratio as obtained by spiral imaging for a primary motor cortex region of interest, but with potential for enhanced temporal resolution. A neurofeedback experiment also illustrates measurement and calculation of functional magnetic resonance imaging signals within 1 sec, emphasizing the future potential of the approach. Magn Reson Med, 2011.

BOLD Contrast and Noise Characteristics of Densely Sampled Multi-Echo fMRI Data

Blood oxygenation level dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) can be enhanced using multi-echo imaging and postprocessing techniques that combine the echoes in weighted summation. Here, existing echo-weighting methods are reassessed in the context of an explicit physiological noise model, and a new method is introduced: weights that scale linearly with echo time. Additionally, a method using data-driven weights defined using principal component analysis (PCA) is included for comparison. Differences in BOLD contrast enhancement between methods were compared analytically where possible, and using Monte Carlo simulations for different noise conditions and different combinations of acquisition parameters. The comparisons were also validated through densely sampled (256-echo) multi-echo fMRI experimental data acquired at 1.5T and 3.0T. Results indicated that the contrast-to-noise ratio (CNR) of the studied weighting methods have a strong dependence on the physiological noise, echo spacing and the width of the sampling window. With low noise correlations between echoes, contrast gain for all weighting methods was shown to have a square root dependence on the echo sampling density, and in typical experimental noise conditions, increasing the sampling window beyond 3·T2* produced marginal additional benefit. Simulations and experiments also emphasized that noise correlations between echoes are likely the main factor limiting the potential CNR gains achievable by densely sampled multi-echo fMRI.

Non-water-suppressed short-echo-time magnetic resonance spectroscopic imaging using a concentric ring k-space trajectory.

Water‐suppressed MRS acquisition techniques have been the standard MRS approach used in research and for clinical scanning to date. The acquisition of a non‐water‐suppressed MRS spectrum is used for artefact correction, reconstruction of phased‐array coil data and metabolite quantification. Here, a two‐scan metabolite‐cycling magnetic resonance spectroscopic imaging (MRSI) scheme that does not use water suppression is demonstrated and evaluated. Specifically, the feasibility of acquiring and quantifying short‐echo (TE = 14 ms), two‐dimensional stimulated echo acquisition mode (STEAM) MRSI spectra in the motor cortex is demonstrated on a 3 T MRI system. The increase in measurement time from the metabolite‐cycling is counterbalanced by a time‐efficient concentric ring k‐space trajectory. To validate the technique, water‐suppressed MRSI acquisitions were also performed for comparison. The proposed non‐water‐suppressed metabolite‐cycling MRSI technique was tested for detection and correction of resonance frequency drifts due to subject motion and/or hardware instability, and the feasibility of high‐resolution metabolic mapping over a whole brain slice was assessed. Our results show that the metabolite spectra and estimated concentrations are in agreement between non‐water‐suppressed and water‐suppressed techniques. The achieved spectral quality, signal‐to‐noise ratio (SNR) > 20 and linewidth <7 Hz allowed reliable metabolic mapping of five major brain metabolites in the motor cortex with an in‐plane resolution of 10 × 10 mm2 in 8 min and with a Cramér‐Rao lower bound of less than 20% using LCModel analysis. In addition, the high SNR of the water peak of the non‐water‐suppressed technique enabled voxel‐wise single‐scan frequency, phase and eddy current correction. These findings demonstrate that our non‐water‐suppressed metabolite‐cycling MRSI technique can perform robustly on 3 T MRI systems and within a clinically feasible acquisition time.

PEAR: PEriodic And fixed Rank separation for fast fMRI

Purpose: In functional MRI (fMRI), faster acquisition via undersampling of data can improve the spatial‐temporal resolution trade‐off and increase statistical robustness through increased degrees‐of‐freedom. High‐quality reconstruction of fMRI data from undersampled measurements requires proper modeling of the data. We present an fMRI reconstruction approach based on modeling the fMRI signal as a sum of periodic and fixed rank components, for improved reconstruction from undersampled measurements. Methods: The proposed approach decomposes the fMRI signal into a component which has a fixed rank and a component consisting of a sum of periodic signals which is sparse in the temporal Fourier domain. Data reconstruction is performed by solving a constrained problem that enforces a fixed, moderate rank on one of the components, and a limited number of temporal frequencies on the other. Our approach is coined PEAR ‐ PEriodic And fixed Rank separation for fast fMRI. Results: Experimental results include purely synthetic simulation, a simulation with real timecourses and retrospective undersampling of a real fMRI dataset. Evaluation was performed both quantitatively and visually versus ground truth, comparing PEAR to two additional recent methods for fMRI reconstruction from undersampled measurements. Results demonstrate PEARs improvement in estimating the timecourses and activation maps versus the methods compared against at acceleration ratios of R = 8,10.66 (for simulated data) and R = 6.66,10 (for real data). Conclusions: This paper presents PEAR, an undersampled fMRI reconstruction approach based on decomposing the fMRI signal to periodic and fixed rank components. PEAR results in reconstruction with higher fidelity than when using a fixed‐rank based model or a conventional Low‐rank + Sparse algorithm. We have shown that splitting the functional information between the components leads to better modeling of fMRI, over state‐of‐the‐art methods.