Neil E. Wilson

Application of compressed sensing to multidimensional spectroscopic imaging in human prostate.

The application of compressed sensing is demonstrated in a recently implemented four‐dimensional echo‐planar based J‐resolved spectroscopic imaging sequence combining two spatial and two spectral dimensions. The echo‐planar readout simultaneously acquires one spectral and one spatial dimension. Therefore, the compressed sensing undersampling is performed along the indirectly acquired spatial and spectral dimensions, and the reconstruction is performed using the split Bregman algorithm, an efficient TV‐minimization solver. The four‐dimensional echo‐planar‐based J‐resolved spectroscopic imaging data acquired in a prostate phantom containing metabolites at physiological concentrations are accurately reconstructed with as little as 20% of the original data. Experimental data acquired in six healthy prostates using the external body matrix “receive” coil on a 3T magnetic resonance imaging scanner are reconstructed with acquisitions using only 25% of the Nyquist–Shannon required amount of data, indicating the potential for a 4‐fold acceleration factor in vivo, bringing the required scan time for multidimensional magnetic resonance spectroscopic imaging within clinical feasibility. Magn Reson Med, 2012.

Accelerated five-dimensional echo planar J-resolved spectroscopic imaging: Implementation and pilot validation in human brain

To implement an accelerated five‐dimensional (5D) echo‐planar J‐resolved spectroscopic imaging sequence combining 3 spatial and 2 spectral encoding dimensions and to apply the sequence in human brain.

Spectroscopic imaging using concentrically circular echo-planar trajectories in vivo.

An alternative to the standard echo‐planar spectroscopic imaging technique is presented, spectroscopic imaging using concentrically circular echo‐planar trajectories (SI‐CONCEPT). In contrast to the conventional chemical shift imaging data, the sampled data from each set of concentric rings were regridded into Cartesian space. Usage of concentric k‐space trajectories has the advantage of requiring significantly reduced slew rates than echo‐planar spectroscopic imaging, allowing for the collection of higher spectral bandwidths and opening the door for high‐bandwidth echo‐planar styled spectroscopic imaging at higher magnetic fields. Before two‐dimensional spatial and one‐dimensional spectral encoding, the volume of interest was localized using the standard point‐resolved spectroscopy sequence. The feasibility of using concentric k‐space trajectories is demonstrated, and the spatial profiles and representative spectra are compared with the standard echo‐planar spectroscopic imaging technique in a gray matter phantom containing metabolites at physiological concentrations and healthy human brain in vivo. The symmetric nature of the concentric circles also reduces the number of required excitations for a given resolution by a factor of two. Possible artifacts and limitations are discussed. Magn Reson Med, 2011.

Group Sparse Reconstruction of Multi-Dimensional Spectroscopic Imaging in Human Brain in vivo

Four-dimensional (4D) Magnetic Resonance Spectroscopic Imaging (MRSI) data combining 2 spatial and 2 spectral dimensions provides valuable biochemical information in vivo; however, its 20–40 min acquisition time is too long to be used for a clinical protocol. Data acquisition can be accelerated by non-uniformly under-sampling (NUS) the ky− t1 plane, but this causes artifacts in the spatial-spectral domain that must be removed by non-linear, iterative reconstruction. Previous work has demonstrated the feasibility of accelerating 4D MRSI data acquisition through NUS and iterative reconstruction using Compressed Sensing (CS), Total Variation (TV), and Maximum Entropy (MaxEnt) reconstruction. Group Sparse (GS) reconstruction is a variant of CS that exploits the structural sparsity of transform coefficients to achieve higher acceleration factors than traditional CS. In this article, we derive a solution to the GS reconstruction problem within the Split Bregman iterative framework that uses arbitrary transform grouping patterns of overlapping or non-overlapping groups. The 4D Echo-Planar Correlated Spectroscopic Imaging (EP-COSI) gray matter brain phantom and in vivo brain data are retrospectively under-sampled 2×, 4×, 6×, 8×, and 10___ and reconstructed using CS, TV, MaxEnt, and GS with overlapping or non-overlapping groups. Results show that GS reconstruction with overlapping groups outperformed the other reconstruction methods at each NUS rate for both phantom and in vivo data. These results can potentially reduce the scan time of a 4D EP-COSI brain scan from 40 min to under 5 min in vivo.

Non-uniformly under-sampled multi-dimensional spectroscopic imaging in vivo: maximum entropy versus compressed sensing reconstruction

The four‐dimensional (4D) echo‐planar correlated spectroscopic imaging (EP‐COSI) sequence allows for the simultaneous acquisition of two spatial (ky, kx) and two spectral (t2, t1) dimensions in vivo in a single recording. However, its scan time is directly proportional to the number of increments in the ky and t1 dimensions, and a single scan can take 20–40 min using typical parameters, which is too long to be used for a routine clinical protocol. The present work describes efforts to accelerate EP‐COSI data acquisition by application of non‐uniform under‐sampling (NUS) to the ky–t1 plane of simulated and in vivo EP‐COSI datasets then reconstructing missing samples using maximum entropy (MaxEnt) and compressed sensing (CS). Both reconstruction problems were solved using the Cambridge algorithm, which offers many workflow improvements over other l1‐norm solvers. Reconstructions of retrospectively under‐sampled simulated data demonstrate that the MaxEnt and CS reconstructions successfully restore data fidelity at signal‐to‐noise ratios (SNRs) from 4 to 20 and 5× to 1.25× NUS. Retrospectively and prospectively 4× under‐sampled 4D EP‐COSI in vivo datasets show that both reconstruction methods successfully remove NUS artifacts; however, MaxEnt provides reconstructions equal to or better than CS. Our results show that NUS combined with iterative reconstruction can reduce 4D EP‐COSI scan times by 75% to a clinically viable 5 min in vivo, with MaxEnt being the preferred method. Copyright

3D spatially encoded and accelerated TE-averaged echo planar spectroscopic imaging in healthy human brain.

Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE‐averaged 1H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non‐uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE‐averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2–2.4 ppm spectral region contained 95% glutamate signal using the TE‐averaged method. Peak integration of this spectral range and home‐developed, prior‐knowledge‐based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non‐uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight‐fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior‐knowledge‐based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE‐averaged echo planar spectroscopic imaging (TEA‐EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright

Accelerated echo planar J-resolved spectroscopic imaging in prostate cancer: a pilot validation of non-linear reconstruction using total variation and maximum entropy

The overlap of metabolites is a major limitation in one‐dimensional (1D) spectral‐based single‐voxel MRS and multivoxel‐based MRSI. By combining echo planar spectroscopic imaging (EPSI) with a two‐dimensional (2D) J‐resolved spectroscopic (JPRESS) sequence, 2D spectra can be recorded in multiple locations in a single slice of prostate using four‐dimensional (4D) echo planar J‐resolved spectroscopic imaging (EP‐JRESI). The goal of the present work was to validate two different non‐linear reconstruction methods independently using compressed sensing‐based 4D EP‐JRESI in prostate cancer (PCa): maximum entropy (MaxEnt) and total variation (TV). Twenty‐two patients with PCa with a mean age of 63.8 years (range, 46–79 years) were investigated in this study. A 4D non‐uniformly undersampled (NUS) EP‐JRESI sequence was implemented on a Siemens 3‐T MRI scanner. The NUS data were reconstructed using two non‐linear reconstruction methods, namely MaxEnt and TV. Using both TV and MaxEnt reconstruction methods, the following observations were made in cancerous compared with non‐cancerous locations: (i) higher mean (choline + creatine)/citrate metabolite ratios; (ii) increased levels of (choline + creatine)/spermine and (choline + creatine)/myo‐inositol; and (iii) decreased levels of (choline + creatine)/(glutamine + glutamate). We have shown that it is possible to accelerate the 4D EP‐JRESI sequence by four times and that the data can be reliably reconstructed using the TV and MaxEnt methods. The total acquisition duration was less than 13 min and we were able to detect and quantify several metabolites. Copyright

Correlated spectroscopic imaging of calf muscle in three spatial dimensions using group sparse reconstruction of undersampled single and multichannel data

To implement a 5D (three spatial + two spectral) correlated spectroscopic imaging sequence for application to human calf.

Group Dynamics in Automatic Imitation.

Imitation–matching the configural body movements of another individual–plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach.

Muscle oxidative phosphorylation quantitation using creatine chemical exchange saturation transfer (CrCEST) MRI in mitochondrial disorders

Systemic mitochondrial energy deficiency is implicated in the pathophysiology of many age-related human diseases. Currently available tools to estimate mitochondrial oxidative phosphorylation (OXPHOS) capacity in skeletal muscle in vivo lack high anatomic resolution. Muscle groups vary with respect to their contractile and metabolic properties. Therefore, muscle group-specific estimates of OXPHOS would be advantageous. To address this need, a noninvasive creatine chemical exchange saturation transfer (CrCEST) MRI technique has recently been developed, which provides a measure of free creatine. After exercise, skeletal muscle can be imaged with CrCEST in order to make muscle group-specific measurements of OXPHOS capacity, reflected in the recovery rate (τCr) of free Cr. In this study, we found that individuals with genetic mitochondrial diseases had significantly (P = 0.026) prolonged postexercise τCr in the medial gastrocnemius muscle, suggestive of less OXPHOS capacity. Additionally, we observed that lower resting CrCEST was associated with prolonged τPCr, with a Pearsons correlation coefficient of -0.42 (P = 0.046), consistent with previous hypotheses predicting that resting creatine levels may correlate with 31P magnetic resonance spectroscopy-based estimates of OXPHOS capacity. We conclude that CrCEST can noninvasively detect changes in muscle creatine content and OXPHOS capacity, with high anatomic resolution, in individuals with mitochondrial disorders.