A dual echo approach to removing motion artefacts in fMRI time series

In fMRI, subject motion can severely affect data quality. This is a particular problem when movement is correlated with the experimental paradigm as this potentially causes artefactual activation. A method is presented that uses linear regression, to utilise the time course of an image acquired at very short echo time (TE) as a voxel-wise regressor for a second image in the same echo train, that is acquired with high BOLD sensitivity. The value of this approach is demonstrated using task-locked motion combined with visual stimulation. Results obtained at both 1.5 and 3 T show improvements in functional activation maps for individual subjects. The method is straightforward to implement, does not require extra scan time and can easily be embedded in a multi-echo acquisition framework

Distortion-matched T1 maps and unbiased T1-weighted images as anatomical reference for high-resolution fMRI

The increasing availability of ultra-high field scanners has led to a growing number of submillimetre fMRI studies in humans, typically targeting the gray matter at different cortical depths. In most analyses, the definition of surfaces at different cortical depths is based on an anatomical image with different contrast and distortions than the functional images. Here, we introduce a novel sequence providing bias-field corrected T1-weighted images and T1-maps with distortions that match those of the fMRI data, with an image acquisition time significantly shorter than standard T1-weighted anatomical imaging. For 'T1-imaging with 2 3D-EPIs', or T123DEPI, 3D-EPI volumes are acquired centred at two inversion times. These 3D-EPIs are segmented into half, quarter or smaller blocks of k-space to allow for optimisation of the inversion times. T1-weighted images and T1-maps are then generated as for MP2RAGE acquisitions. A range of T123DEPI data acquired at 7 T is shown with resolutions ranging from 0.7 mm to 1.3 mm isotropic voxels. Co-registration quality to the mean EPI of matching fMRI timecourses shows markedly less local deviations compared to co-registration of a standard MP2RAGE to the same echo planar volume. Thus, the T123DEPI T1-weighted images and T1-maps can be used to provide cortical surfaces with matched distortions to the functional data or else to facilitate co-registration between functional and undistorted anatomical data

Examples of sub-millimeter, 7T, T-weighted EPI datasets acquired with the T23DEPI sequence.

These imaging data are examples of sub-millimeter resolution T1-weighted EPI (Echo Planar Imaging) acquired using the T123DEPI (T1-imaging with 2 3D-EPIs) sequence [1]; functional MRI data with matching resolution and distortion, and MP2RAGE (Magnetization Prepared 2 Rapid Acquisition Gradient Echoes) anatomical images [2], from the same subjects. Data from two protocols and subjects presented in the paper describing the sequence [1] are made available here: 1)0.8 mm protocol: whole brain, axial T123DEPI T1-weighted images; a 5-minute fMRI run with the same orientation and 27 mm coverage in the slice selection direction, covering the primary visual cortex. fMRI data were acquired while the volunteer viewed a flashing checkerboard stimulus; the unsmoothed GLM results of the fMRI and a 0.64 mm resolution MP2RAGE from the same subject. These data are from Experiment 3 in [1] 2)0.7 mm protocol: partial brain T123DEPI T1-weighted images with longer or shorter readouts; matching coronal echo planar images again acquired while viewing a flashing checkerboard stimulus and a 0.64 mm whole brain MP2RAGE from the same subject. These data are from Experiment 1 in [1]

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites

Background: The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose: To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods: An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brainwas disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linearmixed-effects models (denoted P-boot). Results: In total, 296 participants (mean age, 26 years +/- 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range,174-289), and low Cramer-Rao lower bounds ( .90), N-acetylaspartate and N-acetylaspartylglutamate (P-boot =.13), or glutamate and glutamine (P-boot =.11). Among the smaller resonances, no vendor effects were found for ascorbate (P-boot =.08), aspartate (P-boot >.90), glutathione (P-boot > .90), or lactate (P-boot =.28). Conclusion: Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. (C) RSNA, 202

Increased brain activation during motor imagery suggests central abnormality in Neonatal Brachial Plexus Palsy

Neonatal Brachial Plexus Palsy (NBPP) may lead to permanent impairment of arm function. As NBPP occurs when central motor programs develop, these may be ill-formed. We studied elbow flexion and motor imagery with fMRI to search for abnormal motor programming. We compared the cortical activity of adults with conservatively treated NBPP to that of healthy individuals stratified for hand dominance, using fMRI BOLD tasks of elbow flexion and motor imagery of flexion. Additionally, resting-state networks and regional gray matter volume were studied. Sixteen adult NBPP patients (seven men; median age 29 years) and sixteen healthy subjects (seven men, median age 27 years) participated. Cortical activation was significantly higher in patients during flexion imagery compared to healthy individuals and it increased with lesion extent and muscle weakness. The contralateral and ipsilateral premotor cortex, and the contralateral motor cortex showed stronger activity during imagined flexion in the right-handed NBPP subjects compared to healthy individuals. Activity patterns during actual flexion did not differ between groups. No differences in resting-state network connectivity or gray matter amount were found between the groups. NBPP affected imagined but not actual elbow flexion, suggesting an impairment of motor planning which would indicate abnormal motor programming in NBPP

Big GABA II:Water-referenced edited MR spectroscopy at 25 research sites

\u3cp\u3e Accurate and reliable quantification of brain metabolites measured in vivo using \u3csup\u3e1\u3c/sup\u3e H magnetic resonance spectroscopy (MRS) is a topic of continued interest. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, spectrally edited γ-aminobutyric acid (GABA) MRS data were analyzed and GABA levels were quantified relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using GABA+ (GABA + co-edited macromolecules (MM)) and MM-suppressed GABA editing. The unsuppressed water signal from the volume of interest was acquired for concentration referencing. Whole-brain T \u3csub\u3e1\u3c/sub\u3e -weighted structural images were acquired and segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17% for the GABA + data and 29% for the MM-suppressed GABA data. The mean within-site coefficient of variation was 10% for the GABA + data and 19% for the MM-suppressed GABA data. Vendor differences contributed 53% to the total variance in the GABA + data, while the remaining variance was attributed to site- (11%) and participant-level (36%) effects. For the MM-suppressed data, 54% of the variance was attributed to site differences, while the remaining 46% was attributed to participant differences. Results from an exploratory analysis suggested that the vendor differences were related to the unsuppressed water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA measurements exhibit similar levels of variance to creatine-referenced GABA measurements. It is concluded that quantification using internal tissue water referencing is a viable and reliable method for the quantification of in vivo GABA levels. \u3c/p\u3

Integrative Analysis of GABA-Edited MRS Data Acquired at 24 Research Sites

status: publishe

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites

Background: The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose: To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods: An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results: In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4–5.0 Hz), signal-to-noise ratio (range, 174–289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion: Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols

QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

Bolyen E, Rideout JR, Dillon MR, et al. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ. 2018