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Background: Several studies indicate that people who stutter show greater variability in speech movements than people who do not stutter, even when the speech produced is perceptually fluent. Speaking to the beat of a metronome reliably increases fluency in people who stutter, regardless of the severity of stuttering. Objectives: Here, we aimed to test whether metronome-timed speech reduces articulatory variability. Method: We analysed vocal tract MRI data from 24 people who stutter and 16 controls. Participants repeated sentences with and without a metronome. Midsagittal images of the vocal tract from lips to larynx were reconstructed at 33.3 frames per second. Any utterances containing dysfluencies or non-speech movements (e.g. swallowing) were excluded. For each participant, we measured the variability of movements (coefficient of variation) from the alveolar, palatal and velar regions of the vocal tract. Results: People who stutter had more variability than control speakers when speaking without a metronome, which was then reduced to the same level as controls when speaking with the metronome. The velar region contained more variability than the alveolar and palatal regions, which were similar. Conclusions: These results replicate previous findings of greater variability in the movements of people who stutter compared with controls during natural, fluent speaking (i.e. speaking without the metronome). Furthermore, these results extend previous knowledge to show that in addition to increasing fluency in people who stutter, metronome timed speech also reduces articulatory variability to the same level as that seen in control speakers.

Purpose To estimate dynamic off-resonance due to vigorous body motion in accelerated fMRI of awake behaving non-human primates (NHPs) using the standard EPI 3-line navigator, in order to attenuate the effects of time-varying off-resonance on the reconstruction. Methods In NHP fMRI the animal’s head is usually head-posted, and the dynamic off-resonance is mainly caused by motion in body parts that are distant from the brain and have low spatial frequency. Hence, off-resonance at each frame can be approximated as a spatially linear perturbation of the off-resonance at a reference frame, and is manifested as a relative linear shift in k-space. Using GRAPPA operators, we estimated these shifts by comparing the 3-line navigator at each time frame with that at the reference frame. Estimated shifts were then used to correct the data at each frame. The proposed method was evaluated in phantom scans, simulations, and in vivo data. Results The proposed method is shown to successfully estimate low-spatial order dynamic off-resonance perturbations, including induced linear off-resonance perturbations in phantoms, and is able to correct retrospectively corrupted data in simulations. Finally, it is shown to reduce ghosting artifacts and geometric distortions by up to 20% in simultaneous multi-slice in vivo acquisitions in awake-behaving NHPs. Conclusion A method is proposed that does not need any sequence modification or extra acquisitions and makes accelerated awake behaving NHP imaging more robust and reliable, reducing the gap between what is possible with NHP protocols and state-of-the-art human imaging.

Purpose: To evaluate an algorithm for calibrationless parallel imaging to reconstruct undersampled parallel transmit field maps for the body and brain. Methods: Using synthetic data, body, and brain measurements of relative transmit maps, three different approaches to a joint transmit-receive low-rank tensor completion algorithm are evaluated. These methods included: (i) virtual coils using the product of receive and transmit sensitivities, (ii) joint-receiver coils that enforces a low rank structure across receive coils of all transmit modes, and (iii) transmit low rank (TxLR) that uses a low rank structure for both receive and transmit modes simultaneously. The performance of each are investigated for different noise levels and different acceleration rates on an 8-channel parallel transmit 7T system. Results: The virtual coils method broke down with increasing noise levels or acceleration rates greater than two producing RMS error greater than 0.1. The joint receiver coils method worked well up to acceleration factors of four, beyond which the RMS error exceeded 0.1. While TxLR enabled an eight-fold acceleration with most RMS errors remaining below 0.1. Conclusion: This work demonstrates that under-sampling factors of up to eight-fold are feasible for transmit array mapping and can be reconstructed using calibrationless parallel imaging methods., 30 pages, 14 figures

Purpose Dynamic angiography using arterial spin labeling (ASL) can provide detailed hemodynamic information. However, the long time-resolved readouts require small flip angles to preserve ASL signal for later timepoints, limiting SNR. By using time-encoded ASL to generate temporal information, the readout can be shortened. Here, the SNR improvements from using larger flip angles, made possible by the shorter readout, are quantitatively investigated. Methods The SNR of a conventional protocol with nine Look-Locker readouts and a 4 3 time-encoded protocol with three Look-Locker readouts (giving nine matched timepoints) were compared using simulations and in vivo data. Both protocols were compared using readouts with constant flip angles (CFAs) and variable flip angles (VFAs), where the VFA scheme was designed to produce a consistent ASL signal across readouts. Optimization of the background suppression to minimize physiological noise across readouts was also explored. Results The time-encoded protocol increased in vivo SNR by 103% and 96% when using CFAs or VFAs, respectively. Use of VFAs improved SNR compared with CFAs by 25% and 21% for the conventional and time-encoded protocols, respectively. The VFA scheme also removed signal discontinuities in the time-encoded data. Preliminary data suggest that optimizing the background suppression could improve in vivo SNR by a further 16%. Conclusions Time encoding can be used to generate additional temporal information in ASL angiography. This enables the use of larger flip angles, which can double the SNR compared with a non-time-encoded protocol. The shortened time-encoded readout can also lead to improved background suppression, reducing physiological noise and further improving SNR.

BackgroundThe iron concentration increases during normal brain development and is identified as a risk factor for many neurodegenerative diseases, it is vital to monitor iron content in the brain non-invasively.PurposeThis study aimed to quantify in vivo brain iron concentration with a 3D rosette-based ultra-short echo time (UTE) magnetic resonance imaging (MRI) sequence.MethodsA cylindrical phantom containing nine vials of different iron concentrations (iron (II) chloride) from 0.5 millimoles to 50 millimoles and six healthy subjects were scanned using 3D high-resolution (0.94×0.94×0.94 mm3) rosette UTE sequence at an echo time (TE) of 20 μs.ResultsIron-related hyperintense signals (i.e., positive contrast) were detected based on the phantom scan, and were used to establish an association between iron concentration and signal intensity. The signal intensities from in vivo scans were then converted to iron concentrations based on the association. The deep brain structures, such as the substantia nigra, putamen, and globus pallidus, were highlighted after the conversion, which indicated potential iron accumulations.ConclusionThis study suggested that T1-weighted signal intensity could be used for brain iron mapping.

This study aimed to develop a new 3D dual-echo rosette k-space trajectory, specifically designed for UTE MRI applications. The imaging of the ultra-short transverse relaxation time (uTThe rosette trajectory was developed based on rotations of a "petal-like" pattern in the kThe 3D rosette dual-echo UTE sequence showed better performance than a 3D radial UTE acquisition. More significant signal intensity decay in white matter than gray matter was observed along with the TEs. The white matter regions had higher uTThe higher uT

PurposeTo extend and optimize a non-contrast MRI technique to obtain whole head 4D (time-resolved 3D) angiographic and perfusion images from a single scan.Methods4D combined angiography and perfusion using radial imaging and arterial spin labeling (CAPRIA) uses pseudocontinuous labeling with a 3D golden ratio (“koosh ball”) readout to continuously image the blood water as it travels through the arterial system and exchanges into the tissue. High spatial/temporal resolution angiograms and low spatial/temporal resolution perfusion images can be flexibly reconstructed from the same raw k-space data at any timepoint within the readout. A constant flip angle (CFA) and a quadratic variable flip angle (VFA) excitation schedule were optimized through simulations and tested in healthy volunteers. A conventional sensitivity encoding (SENSE) reconstruction was compared against a locally low rank (LLR) reconstruction, which leverages spatiotemporal correlations to improve reconstruction quality. Differences in image quality were assessed through split-scan repeatability.ResultsThe optimized VFA schedule (2-9°) reduced initial signal attenuation whilst boosting the signal at later timepoints, resulting in a significant (p < 0.001) improvement in image quality (up to 84%), particularly for the lower SNR perfusion images. The LLR reconstruction provided effective denoising without biasing the signal timecourses, significantly improving angiographic and perfusion imaging repeatability (up to 143%, p < 0.001) and enabling the clear depiction of small distal vessels and late tissue perfusion.Conclusion4D CAPRIA can be optimized using a VFA schedule and LLR reconstruction to yield whole head 4D angiograms and perfusion images from a single scan.

Purpose The human cerebellum plays an important role in the functional activity of the cerebrum, ranging from motor to cognitive systems given its relaying role between the spinal cord and cerebrum. The cerebellum poses many challenges to Magnetic Resonance Spectroscopic Imaging (MRSI) due to its caudal location, susceptibility to physiological artifacts, and partial volume artifacts resulting from its complex anatomical structure. Thus, in the present study, we propose a high-resolution MRSI acquisition scheme for the cerebellum. Methods A zoom or reduced field of view (rFOV) metabolite-cycled MRSI acquisition at 3 Tesla, with a grid of 48 × 48, was developed to achieve a nominal resolution of 62.5 μL. Single-slice rFOV MRSI data were acquired from the cerebellum of 5 healthy subjects with a nominal resolution of 2.5 × 2.5 × 10 mm3 in 9.6 min. Spectra were quantified using the LCModel package. A spatially unbiased atlas template of the cerebellum was used to analyze metabolite distributions in the cerebellum. Results The superior quality of the achieved spectra-enabled generation of high-resolution metabolic maps of total N-acetylaspartate, total Creatine (tCr), total Choline (tCho), glutamate+glutamine, and myo-inositol, with Cramér-Rao lower bounds below 50%. A template-based regions of interest (ROI) analysis resulted in spatially dependent metabolite distributions in 9 ROIs. The group-averaged high-resolution metabolite maps across subjects increased the contrast-to-noise ratio between cerebellum regions. Conclusion These findings indicate that very high-resolution metabolite probing of the cerebellum is feasible using rFOV or zoomed MRSI at 3 Tesla.

Purpose: We investigate the use of TURBINE, a 3D radial-Cartesian acquisition scheme in which EPI planes are rotated about the phase-encoding axis to acquire a cylindrical k-space, for high-fidelity ultra-high isotropic resolution fMRI at 7T with minimal distortion and blurring. Methods: An improved, completely self-navigated version of the TURBINE sampling scheme was designed for fMRI at 7T. To demonstrate the image quality and spatial specificity of the acquisition, thin-slab visual and motor BOLD fMRI at 0.67 mm isotropic resolution (16 mm slab, TRvol = 2.32 s) and 0.8x0.8x2.0 mm (whole-brain, TRvol = 2.4 s) data were acquired. To prioritize the high spatial fidelity, we employed a temporally regularized reconstruction to improve sensitivity without any spatial bias. Results: TURBINE images provide high structural fidelity with almost no distortion, dropout or T2* blurring for the thin-slab acquisitions compared to conventional 3D EPI, owing to the radial sampling in-plane and the short echo train used. This results in activation that can be localized to pre- and post-central gyri in a motor task, for example, with excellent correspondence to brain structure measured by a T1-MPRAGE. The benefits of TURBINE (low distortion, dropout, blurring) are reduced for the whole-brain acquisition due to the longer EPI train. We demonstrate robust BOLD activation at 0.67 mm isotropic resolution (thin-slab) and also anisotropic 0.8x0.8x2.0 mm (whole-brain) acquisitions. Conclusion: TURBINE is a promising acquisition approach for high-resolution, minimally distorted fMRI at 7T and could be particularly useful for fMRI in areas of high B0 inhomogeneity.

PurposeTo estimate dynamic off-resonance due to vigorous body motion in accelerated fMRI of awake behaving non-human primates (NHPs) using the standard EPI 3-line navigator, in order to attenuate the effects of time-varying off-resonance on the reconstruction.MethodsIn NHP fMRI the animal’s head is usually head-posted, and the dynamic off-resonance is mainly caused by motion in body parts that are distant from the brain and have low spatial frequency. Hence, off-resonance at each frame can be approximated as a spatially linear perturbation of the off-resonance at a reference frame, and is manifested as a relative linear shift in k-space. Using GRAPPA operators, we estimated these shifts by comparing the 3-line navigator at each time frame with that at the reference frame. Estimated shifts were then used to correct the data at each frame. The proposed method was evaluated in phantom scans, simulations, and in vivo data.ResultsThe proposed method is shown to successfully estimate low-spatial order dynamic off-resonance perturbations, including induced linear off-resonance perturbations in phantoms, and is able to correct retrospectively corrupted data in simulations. Finally, it is shown to reduce ghosting artifacts and geometric distortions by up to 20% in simultaneous multi-slice in vivo acquisitions in awake-behaving NHPs.ConclusionA method is proposed that does not need any sequence modification or extra acquisitions and makes accelerated awake behaving NHP imaging more robust and reliable, reducing the gap between what is possible with NHP protocols and state-of-the-art human imaging.

PurposeThis study aimed to develop a new 3D dual-echo rosette k-space trajectory, specifically for ultra-short echo time (UTE) magnetic resonance imaging (MRI) applications. The direct imaging of the myelin bilayer, which has ultra-short transverse relaxation time (uT2), was acquired to test the performance of the proposed UTE sequence.Theory and MethodsThe rosette trajectory was developed based on rotations of a ‘petal-like’ pattern in the kx-ky plane, with oscillated extensions in kz-direction for 3D coverage. Five healthy volunteers were recruited and underwent ten dual-echo 3D rosette UTE scans with various echo times (TEs). Dual-exponential complex model fitting was performed on the magnitude data to separate uT2 signals, with the output of uT2 fraction, uT2 value, and long T2 value.ResultsThe reconstructed images’ signal contrast between whiate matter (WM) and grey matter (GM) increased with longer TEs. The WM regions had higher uT2 fraction values than GM (10.9%±1.9% vs. 5.7%±2.4%). The uT2 value was approximately 0.15 milliseconds in WM.ConclusionThe higher uT2 fraction value in WM compared to GM demonstrated the ability of the proposed sequence to capture rapidly decaying signals.

Three-dimensional (3D) encoding methods are increasingly being explored as alternatives to multi-slice two-dimensional (2D) acquisitions in fMRI, particularly in cases where high isotropic resolution is needed. 3D multi-shot EPI is the most popular 3D fMRI acquisition method, but is susceptible to physiological fluctuations which can induce inter-shot phase variations, and thus reducing the achievable tSNR, negating some of the benefit of 3D encoding. This issue can be particularly problematic at ultra-high fields like 7T, which have more severe off-resonance effects. In this work, we aim to improve the temporal stability of 3D multi-shot EPI at 7T by improving its robustness to inter-shot phase variations. We presented a 3D segmented CAIPI sampling trajectory (“seg-CAIPI”) and an improved reconstruction method based on Hankel structured low-rank matrix recovery. Simulation and in-vivo results demonstrate that the combination of the seg-CAIPI sampling scheme and the proposed structured low-rank reconstruction is a promising way to effectively reduce the unwanted temporal variance induced by inter-shot physiological fluctuations, and thus improve the robustness of 3D multi-shot EPI for fMRI.HighlightsA 3D multi-shot EPI sampling trajectory using interleaved ordering along kz and a CAIPI blipping pattern improves robustness to inter-shot phase variationsReconstruction based on Hankel structured low-rank matrix completion can significantly improve the temporal stability of 3D multi-shot acquisitions at 7T1.5mm resolution brain fMRI data show that ~60% improvement in mean tSNR can be obtained using the proposed method compared to the conventional method1.8mm resolution brain fMRI data demonstrate that the proposed method allows for 4-fold acceleration without loss of tSNR compared to conventional 3D EPIPreliminary brainstem fMRI data show that ~40% improvement in mean tSNR can be obtained using the proposed sampling and reconstruction

Purpose People who stutter (PWS) have more unstable speech motor systems than people who are typically fluent (PWTF). Here, we used real-time magnetic resonance imaging (MRI) of the vocal tract to assess variability and duration of movements of different articulators in PWS and PWTF during fluent speech production. Method The vocal tracts of 28 adults with moderate to severe stuttering and 20 PWTF were scanned using MRI while repeating simple and complex pseudowords. Midsagittal images of the vocal tract from lips to larynx were reconstructed at 33.3 frames per second. For each participant, we measured the variability and duration of movements across multiple repetitions of the pseudowords in three selected articulators: the lips, tongue body, and velum. Results PWS showed significantly greater speech movement variability than PWTF during fluent repetitions of pseudowords. The group difference was most evident for measurements of lip aperture using these stimuli, as reported previously, but here, we report that movements of the tongue body and velum were also affected during the same utterances. Variability was not affected by phonological complexity. Speech movement variability was unrelated to stuttering severity within the PWS group. PWS also showed longer speech movement durations relative to PWTF for fluent repetitions of multisyllabic pseudowords, and this group difference was even more evident as complexity increased. Conclusions Using real-time MRI of the vocal tract, we found that PWS produced more variable movements than PWTF even during fluent productions of simple pseudowords. PWS also took longer to produce multisyllabic words relative to PWTF, particularly when words were more complex. This indicates general, trait-level differences in the control of the articulators between PWS and PWTF. Supplemental Material https://doi.org/10.23641/asha.14782092

PURPOSE:T2 -relaxation-under-spin-tagging (TRUST) is an MR technique for the non-invasive assessment of whole-brain cerebral oxygen extraction fraction (OEF), through measurement of the venous blood T2 relaxation time in the sagittal sinus. A key limitation of TRUST, however, is the lack of spatial specificity of the measurement. We sought to develop a modified TRUST sequence, selective localized TRUST (SL-TRUST), having sensitivity to venous blood T2 within a targeted brain region, and therefore achieving spatially localized measurements of cerebral tissue OEF, while still retaining acquisition in the sagittal sinus. METHODS:A method for selective localization of TRUST sequence was developed, and the reproducibility of the technique was evaluated in healthy participants. Regional measurements were achieved for a single hemisphere and for a 3D-localized 70 × 70 × 80 mm3 tissue region using SL-TRUST and compared to a global TRUST measure. An additional measure of venous blood T1 in the sagittal sinus was used to estimate subject-specific hematocrit. Six subjects were scanned over 4 sessions, including intra-session repeat measurements. RESULTS:The average T2 in the sagittal sinus was found to be 60.8 ± 8.9, 62.7 ± 7.9, 64.6 ± 8.4, and 66.3 ± 10.3 ms (mean ± SD) for conventional TRUST, global SL-TRUST, hemispheric SL-TRUST, and 3D-localized SL-TRUST, respectively. Intra-, inter-session, and inter-subject coefficients of variation for OEF using SL-TRUST were found to be comparable and in some cases superior to those obtained using TRUST. CONCLUSION:OEF comparison of 2 contralateral regions was achievable in under 5 min suggesting SL-TRUST offers potential for quantifying regional OEF differences in both healthy and clinical populations.

PurposeLow-rank denoising of MRSI data results in an apparent increase in spectral SNR. However, it is not clear if this translates to a lower uncertainty in metabolite concentrations after spectroscopic fitting. Estimation of the true uncertainty after denoising is desirable for downstream analysis in spectroscopy.In this work the uncertainty reduction from low-rank denoising methods based on spatio-temporal separability and linear predictability in MRSI are assessed. A new method for estimating metabolite concentration uncertainty after denoising is proposed. Finally, automatic rank threshold selection methods are assessed in simulated low SNR regimes.MethodsAssessment of denoising methods is conducted using Monte Carlo simulation of proton MRSI data, and by reproducibility of repeated in vivo acquisitions in five subjects.ResultsIn simulated and in vivo data, spatio-temporal based denoising is shown to reduce the concentration uncertainty, but linear prediction denoising increases uncertainty. Uncertainty estimates provided by fitting algorithms after denoising consistently under-estimate actual metabolite uncertainty. However, the proposed uncertainty estimation, based on an analytical expression for entry-wise variance after denoising, is more accurate. Finally, it is shown automated rank threshold selection using Marchenko-Pastur distribution can bias the data in low SNR conditions. An alternative soft-thresholding function is proposed.ConclusionLow-rank denoising methods based on spatio-temporal separability do reduce uncertainty in MRS(I) data. However, thorough assessment is needed as assessment by SNR measured from residual baseline noise is insufficient given the presence of non-uniform variance. It is also important to select the right rank thresholding method in low SNR cases.

Purpose: People who stutter (PWS) have more unstable speech motor systems than people who are typically fluent (PWTF). Here, we used real-time MRI of the vocal tract to assess variability and duration of movements of different articulators in PWS and PWTF during fluent speech production.Method: The vocal tracts of 28 adults with moderate to severe stuttering and 20 PWTF were scanned using MRI while repeating simple and complex pseudowords. Mid-sagittal images of the vocal tract from lips to larynx were reconstructed at 33.3 frames per second. For each participant, we measured the variability and duration of movements across multiple repetitions of the pseudowords in three selected articulators: the lips, tongue body, and velum. Results: PWS showed significantly greater speech movement variability than PWTF during fluent repetitions of pseudowords. The group difference was most evident for measurements of lip aperture, as reported previously, but here we report that movements of the tongue body and velum were also affected during the same utterances. Variability was highest in both PWS and PWTF for repetitions of the monosyllabic pseudowords and was not affected by phonological complexity. Speech movement variability was unrelated to stuttering severity with the PWS group. PWS also showed longer speech movement durations relative to PWTF for fluent repetitions of multisyllabic pseudowords and this group difference was even more evident when repeating the phonologically complex pseudowords. Conclusions: Using real-time MRI of the vocal tract, we found that PWS produced more variable movements than PWTF even during fluent productions of simple pseudowords. This indicates general, trait-level differences in the control of the articulators between PWS and PWTF.

PurposeTo present and assess a method for choosing a fixed increment between spokes in radially sampled MRI that results in higher SNR than other radial sampling increments.Theory and MethodsSampling uniformity contributes to image SNR when reconstructed using linear methods. Thus, for a radial trajectory, uniformly spaced sampling is ideal. However, uniform sampling lacks post-acquisition reconstruction flexibility, which is often needed in dynamic imaging. Golden ratio-based increments are often used for this purpose. The method presented here, Set Increment with Limited Views Encoding Ratio (SILVER), optimizes sampling uniformity when a limited number of temporal resolutions are required. With SILVER, an optimization algorithm finds the angular increment that provides the highest uniformity for a pre-defined set of reconstruction window sizes. SILVER was tested over multiple sets and assessed in terms of uniformity, noise amplification, and SNR both in simulations and in acquisitions of a phantom and healthy volunteers.ResultsThe proposed algorithm produced trajectories that, for the optimized window sizes, had higher uniformity and lower image noise than golden ratio sampling both in a simulated single-coil system and in a multi-coil system, assessed using simulation, phantom, and in vivo experiments. The noise in SILVER optimized trajectories was comparable to uniformly distributed spokes whilst retaining flexibility in reconstruction at multiple temporal resolutions. In a resting state fMRI experiment, tSNR increases at different spatial and temporal resolutions ranged from 21-72%.ConclusionSILVER is a simple addition to any sequence currently using golden ratio sampling and significantly increases sampling efficiency and SNR.

PurposeThe human cerebellum plays an important role in functional activity cerebrum which is ranging from motor to cognitive activities since due to its relaying role between spinal cord and cerebrum. The cerebellum poses many challenges to magnetic resonance spectroscopic imaging (MRSI) due to the caudal location, the susceptibility to physiological artifacts and partial volume artifact due to its complex anatomical structure. Thus, in present study, we propose a high-resolution MRSI acquisition scheme for the cerebellum.MethodsA zoomed or reduced-field of view (rFOV) metabolite-cycled full-intensity magnetic resonance spectroscopic imaging (MRSI) at 3T with a nominal resolution of 62.5 μL was developed. Single-slice rFOV MRSI data were acquired from the cerebellum of 5 healthy subjects with a nominal resolution of 2.5□×□2.5□mm2 in 9□minutes 36. Spectra were quantified with LCModel. A spatially unbiased atlas template of the cerebellum was used for analyzing metabolite distributions in the cerebellum.ResultsThe high quality of the achieved spectra enabled to generate a high-resolution metabolic map of total N-acetylaspartate, total creatine, total choline, glutamate+glutamine and myo-inositol with Cramér-Rao lower bounds below 50%. A spatially unbiased atlas template of the cerebellum-based region of interest (ROIs) analysis resulted in spatially dependent metabolite distributions in 9 ROIs. The group-averaging across subjects in the Montreal Neurological Institute-152 template space allowed to generate a very high-resolution metabolite maps in the cerebellum.ConclusionThese findings indicate that very high-resolution metabolite probing of cerebellum is feasible using rFOV or zoomed MRSI at 3T.

Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology.Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices.Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex.Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.

Acceleration methods in fMRI aim to reconstruct high fidelity images from undersampled k-space, allowing fMRI datasets to achieve higher temporal resolution, reduced physiological noise aliasing, and increased statistical degrees of freedom. While low levels of acceleration are typically part of standard fMRI protocols through parallel imaging, there exists the potential for approaches that allow much greater acceleration. One such existing approach is k-t FASTER, which exploits the inherent low-rank nature of fMRI. In this paper, we present a reformulated version of k-t FASTER which includes additional L2 constraints within a low-rank framework. We evaluated the effect of three different constraints against existing low-rank approaches to fMRI reconstruction: Tikhonov constraints, low-resolution priors, and temporal subspace smoothness. The different approaches are separately tested for robustness to undersampling and thermal noise levels, in both retrospectively and prospectively-undersampled finger-tapping task fMRI data. Reconstruction quality is evaluated by accurate reconstruction of low-rank subspaces and activation maps. The use of L2 constraints was found to achieve consistently improved results, producing high fidelity reconstructions of statistical parameter maps at higher acceleration factors and lower SNR values than existing methods, but at a cost of longer computation time. In particular, the Tikhonov constraint proved very robust across all tested datasets, and the temporal subspace smoothness constraint provided the best reconstruction scores in the prospectively-undersampled dataset. These results demonstrate that regularized low-rank reconstruction of fMRI data can recover functional information at high acceleration factors without the use of any model-based spatial constraints.

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 a has 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 PEAR’s 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 Lowrank+ 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.

Simultaneous multi-slice or multi-band parallel imaging is frequently used in fMRI to accelerate acquisition. In this study, we propose a new a non-water-suppressed multi-band MRSI using a density weighted concentric ring trajectory (DW-CRT) acquisition. The properties of multi-band acquisition scheme were compared against single-band acquisition in phantoms and in-vivo experiments. High-quality spectra were acquired for all simultaneously acquired three slices from a limited volume of interest with an in-plane resolution of 5 × 5 mm2 in 19.2 min. The achieved in vivo spectral quality of the multi-band method allowed the reliable metabolic mapping of four major metabolites with Cramér-Rao lower bounds below 50%, using a LCModel analysis. Metabolite maps and LCModel quality metrics were compared between multi-band and single-band acquisition schemes for both phantom and in-vivo measurements. Structural similarity (SSIM) index and conventional coefficient of variance analysis of both phantom and in-vivo measurements revealed a SSIM index higher than 0.83, corresponding to a coefficient of variance of less than 30%. These findings demonstrate that our multi-band DW-CRT MRSI demonstrate a multi-band acceleration, simultaneously acquired 3 slices, with no apparently loss in spectral quality, reducing scan time by a factor of 3 without any significant penalty.

Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology. Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices. Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex. Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.

A new technique called constrained source space imaging is introduced that holds promise for ultrafast acquisition of functional magnetic resonance imaging data. A sparse set of arbitrarily positioned, coarse voxels is first localized using radiofrequency selective excitation, from which magnetization signals are separated using only the spatial sensitivities of multichannel receiver coils, without the need for k-space encoding using imaging gradients. This method permits very fast acquisitions of targeted magnetization without complex or time-consuming image reconstruction techniques. Furthermore, because the data acquisition is performed without imaging gradients, T2* decays can be densely sampled and processed for contrast enhancement to improve functional magnetic resonance imaging data quality. Here, the constrained source space imaging technique is validated in proof-of-concept form, for a simple functional magnetic resonance imaging motor task using a prototype dual-band stimulated echo acquisition mode excitation to image four voxels at TR = 250 ms. Results demonstrate good voxel signal separation and good characterization of hemodynamic responses in primary motor cortices (M1) and supplementary motor areas through T2* fitting of the measured signals. With further refinement, the constrained source space imaging method has potential utility in a priori ROI-based functional magnetic resonance imaging experiments with TR values under 100 ms. Rapid, multivoxel measurements of other sources of MR signal contrast are also possible. Magn Reson Med, 70:1058–1069, 2013. © 2012 Wiley Periodicals, Inc.

Functional MRI neurofeedback (fMRI NF) is an emerging technique that trains subjects to regulate their brain activity while they manipulate sensory stimulus representations of fMRI signals in “real-time”. Here we report an fMRI NF study of brain activity associated with kinesthetic motor imagery (kMI), analyzed using partial least squares (PLS), a multivariate analysis technique. Thirteen healthy young adult subjects performed kMI involving each hand separately, with NF training targeting regions of interest (ROIs) in the left and right primary motor cortex (M1). Throughout, subjects attempted to maximize a laterality index (LI) of brain activity—the difference in activity between the contralateral ROI (relative to the hand involved in kMI) and the ipsilateral M1 ROI—while receiving real-time updates on a visual display. Six of 13 subjects were successful in increasing the LI value, whereas the other 7 were not successful and performed similarly to 5 control subjects who received sham NF training. Ability to suppress activity in the ipsilateral M1 ROI was the primary driver of successful NF performance. Multiple PLS analyses depicted activated networks of brain regions involved with imagery, self-awareness, and feedback processing, and additionally showed that activation of the task positive network was correlated with task performance. These results indicate that fMRI NF of kMI is capable of modulating brain activity in primary motor regions in a subset of the population. In the future, such methods may be useful in the development of NF training methods for enhancing motor rehabilitation following stroke.

Purpose 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. Methods The EPI “blades” of the 3D hybrid radial‐Cartesian EPI sequence, called TURBINE, are rotated about the phase‐encoding axis to fill out a cylinder in 3D k‐space. Angular blades are acquired over time using a golden‐angle rotation increment, allowing reconstruction at flexible temporal resolution. The self‐navigating properties of the sequence are used to determine motion parameters from a high temporal‐resolution navigator time series. The motion is corrected in k‐space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion. Results We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal‐to‐noise ratio and fMRI activation in the presence of both severe and subtle motion. Conclusion We show the potential for hybrid radial‐Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527–540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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. © 2012 Wiley Periodicals, Inc.

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.

Purpose: Functional magnetic resonance imaging (fMRI) is limited by sensitivity to millimetre-scale head motion. Adaptive correction is a strategy to adjust the imaging plane in response to measured head motion, thereby suppressing motion artifacts. This strategy should correct for motion in all six degrees of freedom and also holds promise for through-plane motion that creates “spin-history” artifact that cannot easily be removed by postprocessing methods. Improved quantitative understanding of the MRI signal behavior associated with spin-history artifact would be useful for implementing adaptive correction robustly. Methods: A numerical simulation was developed to predict MRI artifact signal amplitude in a single-slice for simple motions, implemented with and without adaptive correction, and compared with experiment by imaging a phantom at 3.0 T. Functional MRI was also performed of a human volunteer to illustrate adaptive correction in the presence of spin-history artifact. Results: Good agreement was achieved between simulation and experimental results. Although time-averaged artifact signal amplitude was observed to correlate linearly with motion speed, artifact time-courses were nonlinearly related to motion waveforms. In addition, experimental results demonstrated effective adaptive correction of spin-history artifact when the phantom underwent complex motions. Adaptive correction during human fMRI suppressed spin-history artifacts and spurious activations associated with task-correlated motion. Conclusions: Overall, this work suggests that adaptive correction, especially when implemented with minimal lag between motion measurement and scan plane update, may help to expand the populations for which fMRI can be performed robustly.

“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. © 2010 Wiley-Liss, Inc.

Purpose 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. Methods The multicoil rank‐constrained reconstruction used hard thresholding and shrinkage on matrix singular values of the space‐time data matrix, using sensitivity encoding and the nonuniform Fast Fourier Transform to enforce data consistency in the multicoil non‐Cartesian k‐t domain. Variable acceleration factors were made possible using a radial increment based on the golden ratio. Both retrospective and prospectively under‐sampled data were used to assess the fidelity of the enhancements to the k‐t FASTER technique in resting and task‐fMRI data. Results The improved k‐t FASTER is capable of tailoring acceleration factors for recovery of different signal components, achieving up to R = 12.5 acceleration in visual‐motor task data. The enhancements reduce data matrix reconstruction errors even at much higher acceleration factors when compared directly with the original k‐t FASTER approach. Conclusion We have shown that k‐t FASTER can be used to significantly accelerate fMRI data acquisition with little penalty to data quality. Magn Reson Med 76:1825–1836, 2016. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

PURPOSE: 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. THEORY AND METHODS: Using matrix completion, 4.27× retrospectively and prospectively under-sampled data were reconstructed (coil-independently) using an iterative nonlinear algorithm, and compared with several different reconstruction strategies. Matrix reconstruction error was evaluated; a dual regression analysis was performed to determine fidelity of recovered fMRI resting state networks (RSNs). RESULTS: The retrospective sampling data showed that k-t FASTER produced the lowest error, approximately 3-4%, and the highest quality RSNs. These results were validated in prospectively under-sampled experiments, with k-t FASTER producing better identification of RSNs than fully sampled acquisitions of the same duration. CONCLUSION: With k-t FASTER, incoherently under-sampled fMRI data can be robustly recovered using only rank constraints. This technique can be used to improve the speed of fMRI sampling, particularly for multivariate analyses such as temporal independent component analysis.

A new technique called constrained source space imaging is introduced that holds promise for ultrafast acquisition of functional magnetic resonance imaging data. A sparse set of arbitrarily positioned, coarse voxels is first localized using radiofrequency selective excitation, from which magnetization signals are separated using only the spatial sensitivities of multichannel receiver coils, without the need for k-space encoding using imaging gradients. This method permits very fast acquisitions of targeted magnetization without complex or time-consuming image reconstruction techniques. Furthermore, because the data acquisition is performed without imaging gradients, T2* decays can be densely sampled and processed for contrast enhancement to improve functional magnetic resonance imaging data quality. Here, the constrained source space imaging technique is validated in proof-of-concept form, for a simple functional magnetic resonance imaging motor task using a prototype dual-band stimulated echo acquisition mode excitation to image four voxels at TR = 250 ms. Results demonstrate good voxel signal separation and good characterization of hemodynamic responses in primary motor cortices (M1) and supplementary motor areas through T2* fitting of the measured signals. With further refinement, the constrained source space imaging method has potential utility in a priori ROI-based functional magnetic resonance imaging experiments with TR values under 100 ms. Rapid, multivoxel measurements of other sources of MR signal contrast are also possible.

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.

Functional magnetic resonance imaging (fMRI) is limited by sensitivity to millimetre-scale head motion. Adaptive correction is a strategy to adjust the imaging plane in response to measured head motion, thereby suppressing motion artifacts. This strategy should correct for motion in all six degrees of freedom and also holds promise for through-plane motion that creates "spin-history" artifact that cannot easily be removed by postprocessing methods. Improved quantitative understanding of the MRI signal behavior associated with spin-history artifact would be useful for implementing adaptive correction robustly.A numerical simulation was developed to predict MRI artifact signal amplitude in a single-slice for simple motions, implemented with and without adaptive correction, and compared with experiment by imaging a phantom at 3.0 T. Functional MRI was also performed of a human volunteer to illustrate adaptive correction in the presence of spin-history artifact.Good agreement was achieved between simulation and experimental results. Although time-averaged artifact signal amplitude was observed to correlate linearly with motion speed, artifact time-courses were nonlinearly related to motion waveforms. In addition, experimental results demonstrated effective adaptive correction of spin-history artifact when the phantom underwent complex motions. Adaptive correction during human fMRI suppressed spin-history artifacts and spurious activations associated with task-correlated motion.Overall, this work suggests that adaptive correction, especially when implemented with minimal lag between motion measurement and scan plane update, may help to expand the populations for which fMRI can be performed robustly.

"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.

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.