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Parallel imaging has been demonstrated to reduce the encoding time of MR spectroscopic imaging (MRSI). Here we investigate up to 5-fold acceleration of 2D proton echo planar spectroscopic imaging (PEPSI) at 3T using generalized autocalibrating partial parallel acquisition (GRAPPA) with a 32-channel coil array, 1.5 cm 3 voxel size, TR/TE of 15/2000 ms, and 2.1 Hz spectral resolution. Compared to an 8-channel array, the smaller RF coil elements in this 32-channel array provided a 3.1-fold and 2.8-fold increase in signal-to-noise ratio (SNR) in the peripheral region and the central region, respectively, and more spatial modulated information. Comparison of sensitivityencoding (SENSE) and GRAPPA reconstruction using an 8-channel array showed that both methods yielded similar quantitative metabolite measures (P > 0.1). Concentration values of N-acetyl-aspartate (NAA), total creatine (tCr), choline (Cho), myo-inositol (mI), and the sum of glutamate and glutamine (Glx) for both methods were consistent with previous studies. Using the 32-channel array coil the mean Cramer-Rao lower bounds (CRLB) were less than 8% for NAA, tCr, and Cho and less than 15% for mI and Glx at 2-fold acceleration. At 4-fold acceleration the mean CRLB for NAA, tCr, and Cho was less than 11%. In conclusion, the use of a 32-channel coil array and GRAPPA reconstruction can significantly reduce the measurement time for mapping brain metabolites. Key words: proton echo planar spectroscopic imaging; PEPSI; MR spectroscopic imaging; parallel MRI; 32-channel phase array; GRAPPA MR spectroscopic imaging (MRSI) plays important roles in both clinical diagnosis and biomedical research. One of the main challenges of the conventional MRSI techniques is the lengthy data acquisition time, a result of the many phase-encoding steps required for complete spatial encoding. Several methods have been proposed to reduce scanning time using reduced or weighted k-space acquisition (1). Other methods acquire multiple (typically two to four) individually phase-encoded spin echoes within a single RF excitation to reduce encoding time (2). However, because the acquisition of multiple echoes requires shortened echo spacing, such a method is characterized by a limited spectral resolution. Alternatively, it is possible to acquire all the spatial information in a single shot using fast imaging readout modules, and to encode the spectral information by incrementing the spectral evolution time in separate RF excitations (3-6). In this way, spatial resolution is independent of scanning time, thus high spatial resolution can be achieved. However, the disadvantage of such approaches is the time-consuming spectral encoding process required to achieve high spectral resolution and bandwidth. Proton echo planar spectroscopic imaging (PEPSI) (7-9) uses an oscillating readout gradient to simultaneously acquire spatial and spectral information in a single RF excitation. PEPSI yields spectral resolution that approximates that of conventional MRSI and enables a reduction in the encoding tim...

In this article we introduce the DRIFTER algorithm, which is a new model based Bayesian method for retrospective elimination of physiological noise from functional magnetic resonance imaging (fMRI) data. In the method, we first estimate the frequency trajectories of the physiological signals with the interacting multiple models (IMM) filter algorithm. The frequency trajectories can be estimated from external reference signals, or if the temporal resolution is high enough, from the fMRI data. The estimated frequency trajectories are then used in a state space model in combination of a Kalman filter (KF) and Rauch-Tung-Striebel (RTS) smoother, which separates the signal into an activation related cleaned signal, physiological noise, and white measurement noise components. Using experimental data, we show that the method outperforms the RETROICOR algorithm if the shape and amplitude of the physiological signals change over time.

This paper addresses the problem of radar target detection in severely heterogeneous clutter environments. Speciÿcally, we present the performance of the normalized matched ÿlter test in a background of disturbance consisting of clutter having a covariance matrix with known structure and unknown scaling plus background white Gaussian noise. It is shown that when the clutter covariance matrix is low rank, the (LRNMF) test retains invariance with respect to the unknown scaling as well as the background noise level and has an approximately constant false alarm rate (CFAR). Performance of the test depends only upon the number of elements, the number of pulses processed in a coherent processing interval, and the rank of the clutter covariance matrix. Analytical expressions for calculating the false alarm and detection probabilities are presented. Performance of the method is shown to degrade with increasing clutter rank especially for low false alarm rates. An adaptive version of the test (LRNAMF) is developed and its performance is studied with simulated data from the KASSPER program. Results pertaining to sample support for subspace estimation, CFAR, and detection performance are presented. Target contamination of training data has a deleterious impact on the performance of the test. Therefore, a technique known as self-censoring reiterative fast maximum likelihood/adaptive power residue (SCRFML/APR) is developed to treat this problem and its performance is discussed. The SCRFML/APR method is used to estimate the unknown covariance matrix in the presence of outliers. This covariance matrix estimate can then be used in the LRNAMF or any other eigen-based adaptive processing technique. ?

Abstract-A detector of a spatially distributed target in white Gaussian noise is developed. A reasonable distribution for the a priori target scatterer density is assumed, and a detector that incorporates this a priori knowledge is given. A simple detector form results, whose detection performance is robust over different scattering densities.

Metabolite T 2 is necessary for accurate quantification of the absolute concentration of metabolites using long-echo-time (TE) acquisition schemes. However, lengthy data acquisition times pose a major challenge to mapping metabolite T 2 . In this study we used proton echo-planar spectroscopic imaging (PEPSI) at 3T to obtain fast T 2 maps of three major cerebral metabolites: N-acetyl-aspartate (NAA), creatine (Cre), and choline (Cho). We showed that PEPSI spectra matched T 2 values obtained using single-voxel spectroscopy (SVS). Data acquisition for 2D metabolite maps with a voxel volume of 0.95 ml (32 ؋ 32 image matrix) can be completed in 25 min using five TEs and eight averages. A sufficient spectral signal-to-noise ratio (SNR) for T 2 estimation was validated by high Pearson's correlation coefficients between logarithmic MR signals and TEs (R 2 ‫؍‬ 0.98, 0.97, and 0.95 for NAA, Cre, and Cho, respectively). In agreement with previous studies, we found that the T 2 values of NAA, but not Cre and Cho, were significantly different between gray matter (GM) and white matter (WM; P < 0.001). The difference between the T 2 estimates of the PEPSI and SVS scans was less than 9%. Consistent spatial distributions of T 2 were found in six healthy subjects, and disagreement among subjects was less than 10%. In summary, the PEPSI technique is a robust method to obtain fast mapping of metabolite Key words: proton echo-planar spectroscopic imaging; singlevoxel spectroscopy; T 2 relaxation time; cerebral metabolites; gray/white matter difference Estimation of the relaxation times of metabolites is necessary for accurate quantification of metabolite concentrations using long-echo-time (TE) acquisition schemes (1-3). Given the T2 relaxation time, metabolite signals acquired at different TEs can be extrapolated to obtain the signal at TE ϭ 0 and thus estimate the concentration of the metabolite (4). Differences in T2 decay are negligible only for short-TE methods (with TE below 10 ms). In several pathological conditions, such as edema and ischemic stroke (5-8), interactions between cerebral metabolites and macromolecules and proteins are known to modify the biochemical environments of the metabolites, which in turn alters the motion-sensitive T2 relaxation time. Accurate estimation of metabolite T2 is therefore especially important in clinical applications of magnetic resonance spectroscopy (MRS) to ascertain whether changes in metabolite MR signals are derived from fluctuations in the metabolite concentration or from changes in the metabolite relaxation time (2,9). In addition to providing information about metabolite concentration, T2 values may give complementary information about metabolite behavior, as has been suggested by studies of brain tumor (9), ischemic stroke (5-7,10), virus infection (11), drug abuse (12), and other neurological disorders (13-15).The T2 relaxation times of metabolites can be measured by collecting multiple spectra over a range of TEs and then fitting the MR signals as a function of TE (1-3,5,10). Se...

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An anaerobic, Gram-stain-positive, rod-shaped, motile and spore-forming bacterium, designated strain LBM18003T, was isolated from pit clay used for making Chinese strong aroma-type liquor. Growth occurred at 20–40 °C (optimum, 30–37 °C), pH 4.5–9.5 (optimum, pH 6.5–7.0) and in the presence of 0.0–1.0 % (w/v) sodium chloride (optimum, 0 %). The predominant fatty acids were C16:0, C14:0, C14:0 DMA and C16:0 3-OH, and the major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, two unidentified phospholipids and nine unidentified glycolipids. Phylogenetic analysis revealed that strain LBM18003T is a novel member of the family Oscillospiraceae . The 16S rRNA gene sequence similarities of strain LBM18003T to its two most closely related species were less than 94.5 % for distinguishing genera, i.e. closely related to Caproiciproducens galactitolivorans JCM 30532T (94.1 %) and Caproicibacter fermentans DSM 107079T (93.2 %). The genome size of strain LBM18003T was 2 996 201 bp and its DNA G+C content was 48.48 mol%. Strain LBM18003T exhibited 67.8 and 68.1% pairwise-determined whole-genome average nucleotide identity values to Caproiciproducens galactitolivorans JCM 30532T and Caproicibacter fermentans DSM 107079T, respectively; and showed 62.2 and 61.0 % the average amino acid identity values to Caproiciproducens galactitolivorans JCM 30532T and Caproicibacter fermentans DSM 107079T, respectively; and demonstrated 46.1 and 41.5 % conserved genes to Caproiciproducens galactitolivorans JCM 30532T and Caproicibacter fermentans DSM 107079T, respectively. The comparisons of 16S rRNA gene and genome sequences confirmed that strain LBM18003T represented a novel genus of the family Oscillospiraceae . Based on morphological, physiological, biochemical, chemotaxonomic, genotypic and phylogenetic results, strain LBM18003T represents a novel species of a novel genus of the family Oscillospiraceae , for which the name Caproicibacterium amylolyticum gen. nov., sp. nov. is proposed. The type strain is LBM18003T (=GDMCC 1.1626T=JCM 33783T).