Matched-filter acquisition for BOLD fMRI

Proton-free induction decay MRSI at 7 T in the human brain using an egg-shaped modified rosette K-space trajectory

PURPOSE

Proton (1H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency because of their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time.

METHODS

Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in 6 min in a 2D slice in the brain. An elliptical phase-encoding sequence was measured in one volunteer in 22 min, and a 3D sequence was measured in one volunteer within 19 min. The SNR per-unit-time, linewidth, Cramer-Rao lower bounds (CRLBs), lipid contamination, and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory.

RESULTS

Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an SNR per-unit-time increase of up to 12% compared to rosette's and 23% compared to elliptical phase-encoding, dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in vivo, and phantom data. The CRLBs of γ-aminobutyric acid and N-acetylaspartylglutamate improved non-significantly for the modified rosette trajectory, whereas the linewidths and lipid contamination remained similar.

CONCLUSION

By optimizing the shape of the rosette trajectory, the modified rosette trajectories achieved higher SNR per-unit-time and enhanced data quality at the same scan time.

Giving the prostate the boost it needs: Spiral diffusion MRI using a high-performance whole-body gradient system for high b-values at short echo times

PURPOSE

To address key issues of low SNR and image distortions in prostate diffusion MRI (dMRI) by means of using strong gradients, single-shot spiral readouts and an expanded encoding model for image reconstruction.

METHODS

Diffusion-weighted spin echo imaging with EPI and spiral readouts is performed on a whole-body system equipped with strong gradients (up to 250 mT/m). An expanded encoding model including static off-resonance, coil sensitivities, and magnetic field dynamics is employed for image reconstruction. The acquisitions are performed on a phantom and in vivo (one healthy volunteer and one patient with prostate cancer). The resulting images are compared to conventional dMRI EPI with navigator-based image reconstruction and assessed in terms of their congruence, SNR, tissue contrast, and quantitative parameters.

RESULTS

Using the expanded encoding model, high-quality images of the prostate gland are obtained across all b-values (up to 3 ms/μm2), clearly outperforming the results obtained with conventional image reconstruction. Compared to EPI, spiral imaging provides an SNR gain up to 45% within the gland and even higher in the lesion. In addition, prostate dMRI with single-shot spirals at submillimeter in-plane resolution (0.85 mm) is accomplished.

CONCLUSION

The combination of strong gradients and an expanded encoding model enables imaging of the prostate with unprecedented image quality. Replacing the commonly used EPI with spirals provides the inherent benefit of shorter echo times and superior readout efficiency and results in higher SNR, which is in particular relevant for considered applications.

Proton Free Induction Decay MRSI at 7T in the Human Brain Using an Egg-Shaped Modified Rosette K-Space Trajectory

Purpose

1.1 Proton ( 1 H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency due to their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time.

Methods

1.2Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in six minutes in a 2D slice in the brain. A 3D sequence was measured in one volunteer within 19 minutes. The SNR, linewidth, CRLBs, lipid contamination and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory.

Results

1.3Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an increase of up to 12% in SNR compared to rosette's dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in-vivo and phantom data. The CRLBs improved slightly, but non-significantly for the modified rosette trajectories, while the linewidths and lipid contamination remained similar.

Conclusion

1.4By improving the rosette trajectory's shape, modified rosette trajectories achieved higher SNR at the same scan time and data quality.

Artifact suppression in readout-segmented consistent K-t space EPSI (RS-COKE) for fast 1 H spectroscopic imaging at 7 T

PURPOSE

Fast proton (¹ H) MRSI is an important diagnostic tool for clinical investigations, providing metabolic and spatial information. MRSI at 7 T benefits from increased SNR and improved separation of peaks but requires larger spectral widths. RS-COKE (Readout-Segmented Consistent K-t space Epsi) is an echo planar spectroscopic imaging (Epsi) variant capable to support the spectral width required for human brain metabolites spectra at 7 T. However, mismatches between readout segments lead to artifacts, particularly when subcutaneous lipid signals are not suppressed. In this study, these mismatches and their effects are analyzed and reduced.

METHODS

The following corrections to the data were performed: i) frequency-dependent phase corrections; ii) k-space trajectory corrections, derived from short reference scans; and iii) smoothing of data at segment transitions to mitigate the effect of residual mismatches. The improvement was evaluated by performing single-slice RS-COKE on a head-shaped phantom with a "lipid" layer and healthy subjects, using varying resolutions and durations ranging from 4.1 × 4.7 × 15 mm³ in 5:46 min to 3.1 × 3.3 × 15 mm³ in 13:07 min.

RESULTS

Artifacts arising from the readout-segmented acquisition were substantially reduced, thus providing high-quality spectroscopic imaging in phantom and human scans. LCModel fitting of the human data resulted in a relative Cramer-Rao lower bounds within 6% for NAA, Cr, and Cho images in the majority of the voxels.

CONCLUSION

Using the new reference scans and reconstruction steps, RS-COKE was able to deliver fast ¹ H MRSI at 7 T, overcoming the spectral width limitation of standard EPSI at this field strength.

Connectome spatial smoothing (CSS): Concepts, methods, and evaluation

Structural connectomes are increasingly mapped at high spatial resolutions comprising many hundreds-if not thousands-of network nodes. However, high-resolution connectomes are particularly susceptible to image registration misalignment, tractography artifacts, and noise, all of which can lead to reductions in connectome accuracy and test-retest reliability. We investigate a network analogue of image smoothing to address these key challenges. Connectome Spatial Smoothing (CSS) involves jointly applying a carefully chosen smoothing kernel to the two endpoints of each tractography streamline, yielding a spatially smoothed connectivity matrix. We develop computationally efficient methods to perform CSS using a matrix congruence transformation and evaluate a range of different smoothing kernel choices on CSS performance. We find that smoothing substantially improves the identifiability, sensitivity, and test-retest reliability of high-resolution connectivity maps, though at a cost of increasing storage burden. For atlas-based connectomes (i.e. low-resolution connectivity maps), we show that CSS marginally improves the statistical power to detect associations between connectivity and cognitive performance, particularly for connectomes mapped using probabilistic tractography. CSS was also found to enable more reliable statistical inference compared to connectomes without any smoothing. We provide recommendations for optimal smoothing kernel parameters for connectomes mapped using both deterministic and probabilistic tractography. We conclude that spatial smoothing is particularly important for the reliability of high-resolution connectomes, but can also provide benefits at lower parcellation resolutions. We hope that our work enables computationally efficient integration of spatial smoothing into established structural connectome mapping pipelines.

Feasibility of spiral fMRI based on an LTI gradient model

Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B0 inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible, we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step. GIRF-predicted reconstruction was tested for high-resolution (0.8 mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the nominal trajectory and concurrent field monitoring. The reconstructions using nominal spiral trajectories contain substantial artifacts and the activation maps contain misplaced activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction, and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction. The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality spiral fMRI in situations where concurrent trajectory monitoring is not available.

Advances in spiral fMRI: A high-resolution study with single-shot acquisition

Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from imperfections in both static and dynamic magnetic fields. Recently, these limitations have been overcome by the concerted application of an expanded signal model that accounts for such field imperfections, and its inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency. In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8 mm in-plane resolution. We demonstrate that high-resolution spiral fMRI at 7 T is not only feasible, but delivers both excellent image quality, BOLD sensitivity, and spatial specificity of the activation maps, with little artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination.

Mono-planar T-Hex: Speed and flexibility for high-resolution 3D imaging

Purpose

The aim of this work is the reconciliation of high spatial and temporal resolution for MRI. For this purpose, a novel sampling strategy for 3D encoding is proposed, which provides flexible k‐space segmentation along with uniform sampling density and benign filtering effects related to signal decay.

Methods

For time‐critical MRI applications such as functional MRI (fMRI), 3D k‐space is usually sampled by stacking together 2D trajectories such as echo planar imaging (EPI) or spiral readouts, where each shot covers one k‐space plane. For very high temporal and medium to low spatial resolution, tilted hexagonal sampling (T‐Hex) was recently proposed, which allows the acquisition of a larger k‐space volume per excitation than can be covered with a planar readout. Here, T‐Hex is described in a modified version where it instead acquires a smaller k‐space volume per shot for use with medium temporal and high spatial resolution.

Results

Mono‐planar T‐Hex sampling provides flexibility in the choice of speed, signal‐to‐noise ratio (SNR), and contrast for rapid MRI acquisitions. For use with a conventional gradient system, it offers the greatest benefit in a regime of high in‐plane resolution <1 mm. The sampling scheme is combined with spirals for high sampling speed as well as with more conventional EPI trajectories.

Conclusion

Mono‐planar T‐Hex sampling combines fast 3D encoding with SNR efficiency and favorable depiction characteristics regarding noise amplification and filtering effects from T2∗ decay, thereby providing flexibility in the choice of imaging parameters. It is attractive both for high‐resolution time series such as fMRI and for applications that require rapid anatomical imaging.

Revealing the mechanisms behind novel auditory stimuli discrimination: An evaluation of silent functional MRI using looping star

Looping Star is a near‐silent, multi‐echo, 3D functional magnetic resonance imaging (fMRI) technique. It reduces acoustic noise by at least 25dBA, with respect to gradient‐recalled echo echo‐planar imaging (GRE‐EPI)‐based fMRI. Looping Star has successfully demonstrated sensitivity to the cerebral blood‐oxygen‐level‐dependent (BOLD) response during block design paradigms but has not been applied to event‐related auditory perception tasks. Demonstrating Looping Star's sensitivity to such tasks could (a) provide new insights into auditory processing studies, (b) minimise the need for invasive ear protection, and (c) facilitate the translation of numerous fMRI studies to investigations in sound‐averse patients. We aimed to demonstrate, for the first time, that multi‐echo Looping Star has sufficient sensitivity to the BOLD response, compared to that of GRE‐EPI, during a well‐established event‐related auditory discrimination paradigm: the “oddball” task. We also present the first quantitative evaluation of Looping Star's test–retest reliability using the intra‐class correlation coefficient. Twelve participants were scanned using single‐echo GRE‐EPI and multi‐echo Looping Star fMRI in two sessions. Random‐effects analyses were performed, evaluating the overall response to tones and differential tone recognition, and intermodality analyses were computed. We found that multi‐echo Looping Star exhibited consistent sensitivity to auditory stimulation relative to GRE‐EPI. However, Looping Star demonstrated lower test–retest reliability in comparison with GRE‐EPI. This could reflect differences in functional sensitivity between the techniques, though further study is necessary with additional cognitive paradigms as varying cognitive strategies between sessions may arise from elimination of acoustic scanner noise.

On the signal-to-noise ratio benefit of spiral acquisition in diffusion MRI

PURPOSE

Spiral readouts combine several favorable properties that promise superior net sensitivity for diffusion imaging. The purpose of this study is to verify the signal-to-noise ratio (SNR) benefit of spiral acquisition in comparison with current echo-planar imaging (EPI) schemes.

METHODS

Diffusion-weighted in vivo brain data from three subjects were acquired with a single-shot spiral sequence and several variants of single-shot EPI, including full-Fourier and partial-Fourier readouts as well as different diffusion-encoding schemes. Image reconstruction was based on an expanded signal model including field dynamics obtained by concurrent field monitoring. The effective resolution of each sequence was matched to that of full-Fourier EPI with 1 mm nominal resolution. SNR maps were generated by determining the noise statistics of the raw data and analyzing the propagation of equivalent synthetic noise through image reconstruction. Using the same approach, maps of noise amplification due to parallel imaging (g-factor) were calculated for different acceleration factors.

RESULTS

Relative to full-Fourier EPI at b = 0 s/mm² , spiral acquisition yielded SNR gains of 42-88% and 40-89% in white and gray matter, respectively, depending on the diffusion-encoding scheme. Relative to partial-Fourier EPI, the gains were 36-44% and 34-42%. Spiral g-factor maps exhibited less spatial variation and lower maxima than their EPI counterparts.

CONCLUSION

Spiral readouts achieve significant SNR gains in the order of 40-80% over EPI in diffusion imaging at 3T. Combining systematic effects of shorter echo time, readout efficiency, and favorable g-factor behavior, similar benefits are expected across clinical and neurosciences uses of diffusion imaging.

T-Hex: Tilted hexagonal grids for rapid 3D imaging

PURPOSE

The purpose of this work is to devise and demonstrate an encoding strategy for 3D MRI that reconciles high speed with flexible segmentation, uniform k-space density, and benign T 2 ∗ effects.

METHODS

Fast sampling of a 3D k-space is typically accomplished by 2D readouts per shot using EPI trains or spiral readouts. Tilted hexagonal (T-Hex) sampling is a way of acquiring more k-space volume per excitation while maintaining uniform sampling density and a smooth T 2 ∗ filter. The k-space volume covered per shot is controlled by the tilting angle. Image reconstruction is performed with a 3D extension of the iterative SENSE approach, incorporating actual field dynamics and static off-resonance. T-Hex imaging is compared with established 3D schemes in terms of speed and noise performance.

RESULTS

Tilted hexagonal acquisition is found to achieve greater imaging speed than known alternatives, particularly in combination with spiral trajectories. The interplay of the proposed 3D trajectories, array detection, and off-resonance is successfully addressed by iterative inversion of the full signal model. Enhanced coverage per shot is of greatest utility for high speed in an intermediate resolution regime of 1 to 4 mm. T-Hex EPI combines the benefits of extended coverage per shot with increased robustness against off-resonance effects.

CONCLUSION

Sampling of tilted hexagonal grids is a feasible means of gaining 3D imaging speed with near-optimal SNR efficiency and benign depiction properties. It is a particularly promising technique for time-resolved applications such as fMRI.

Novel Ultrafast Spiral Head MR Angiography Compared to Standard MR and CT Angiography

BACKGROUND AND PURPOSE

Intracranial vessel imaging by time-of-flight MR angiography (TOF-MRA) is one of the most frequently performed investigations in clinical neuroradiology. Particularly in the acute setting, fast imaging is needed for diagnostics, with a sequence ideally depicting even small vessels. The purpose of this study was to compare image and diagnostic quality of a novel ultrashort TOF-MRA sequence accelerated by spiral imaging (TOF-Spiral-short) to a standard TOF-MRA sequence accelerated by compressed sensing (TOF-CS) and to CT angiography (CTA).

METHODS

Forty-one patients (36.6% showing vessel pathologies) who had undergone TOF-CS (acquisition duration: 4 minutes 8 seconds), TOF-Spiral-short (acquisition duration: 51 seconds; spiral imaging [accelerating factor 1.3], decreased field of view [accelerating factor 1.2], and increased voxel size [accelerating factor 3.3]), and CTA were retrospectively evaluated. Assessment of image quality, diagnostic confidence, and quantification of stenosis or aneurysm diameter were performed by two readers.

RESULTS

Image quality at the skull base was slightly reduced with TOF-Spiral-short compared to CTA and TOF-CS (P < .05). Delineation of small intracranial vessels was improved by TOF-Spiral-short compared to CTA (P < .0001). In TOF-Spiral-short, diagnostic confidence was not reduced compared to TOF-CS in patients with vessel pathologies. We observed no significant difference in quantitative pathology assessment between TOF-Spiral-short and the other two modalities. TOF-Spiral-short enabled the correct identification of all vessel pathologies.

CONCLUSIONS

Accelerating TOF-MRA of brain-feeding arteries by a novel ultrashort spiral imaging sequence shows adequate image quality and sufficient diagnostic performance. Thus, TOF-Spiral-short holds potential for fast and reliable diagnostics of vessel pathologies, particularly in the acute setting.

Chemical shift encoding using asymmetric readout waveforms

Purpose

To describe a new method for encoding chemical shift using asymmetric readout waveforms that enables more SNR‐efficient fat/water imaging.

Methods

Chemical shift was encoded using asymmetric readout waveforms, rather than conventional shifted trapezoid readouts. Two asymmetric waveforms are described: a triangle and a spline. The concept was applied to a fat/water separated RARE sequence to increase sampling efficiency. The benefits were investigated through comparisons to shifted trapezoid readouts. Using asymmetric readout waveforms, the scan time was either shortened or maintained to increase SNR. A matched in‐phase waveform is also described that aims to improve the SNR transfer function of the fat and water estimates. The sequence was demonstrated for cervical spine, musculoskeletal (MSK), and optic nerve applications at 3T and compared with conventional shifted readouts.

Results

By removing sequence dead times, scan times were shortened by 30% with maintained SNR. The shorter echo spacing also reduced T2 blurring. Maintaining the scan times and using asymmetric readout waveforms achieved an SNR improvement in agreement with the prolonged sampling duration.

Conclusions

Asymmetric readout waveforms offer an additional degree of freedom in pulse sequence designs where chemical shift encoding is desired. This can be used to significantly shorten scan times or to increase SNR with maintained scan time.

Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints

Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features.

The Diagnosis of Autism Spectrum Disorder Based on the Random Neural Network Cluster

As the autism spectrum disorder (ASD) is highly heritable, pervasive and prevalent, the clinical diagnosis of ASD is vital. In the existing literature, a single neural network (NN) is generally used to classify ASD patients from typical controls (TC) based on functional MRI data and the accuracy is not very high. Thus, the new method named as the random NN cluster, which consists of multiple NNs was proposed to classify ASD patients and TC in this article. Fifty ASD patients and 42 TC were selected from autism brain imaging data exchange (ABIDE) database. First, five different NNs were applied to build five types of random NN clusters. Second, the accuracies of the five types of random NN clusters were compared to select the highest one. The random Elman NN cluster had the highest accuracy, thus Elman NN was selected as the best base classifier. Then, we used the significant features between ASD patients and TC to find out abnormal brain regions which include the supplementary motor area, the median cingulate and paracingulate gyri, the fusiform gyrus (FG) and the insula (INS). The proposed method provides a new perspective to improve classification performance and it is meaningful for the diagnosis of ASD.

Density-weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T

PURPOSE

Full-slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k-space filtering, but this prolongs scan times and reduces the signal-to-noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR-efficiency further. In this study, we propose an SNR-efficient spatial-spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming-weighted k-space, thus termed density-weighted-CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR.

THEORY AND METHODS

Trajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single-slice, field-of-view 220 × 220 mm2 , matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density-weighted-CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e-CONCEPT), (b) elliptical phase-encoding, and (c) 5-fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding.

RESULTS

By intrinsically sampling a Hamming-weighted k-space, density-weighted-CONCEPT removed Gibbs-ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e-CONCEPT, elliptical phase-encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding (all P < 0.05), respectively, which lead to improved metabolic maps.

CONCLUSION

Density-weighted-CONCEPT provides clinically attractive full-slice high-resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874-2885, 2018. © 2017 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.

Density-weighted concentric rings k-space trajectory for 1 H magnetic resonance spectroscopic imaging at 7 T

It has been shown that density-weighted (DW) k-space sampling with spiral and conventional phase encoding trajectories reduces spatial side lobes in magnetic resonance spectroscopic imaging (MRSI). In this study, we propose a new concentric ring trajectory (CRT) for DW-MRSI that samples k-space with a density that is proportional to a spatial, isotropic Hanning window. The properties of two different DW-CRTs were compared against a radially equidistant (RE) CRT and an echo-planar spectroscopic imaging (EPSI) trajectory in simulations, phantoms and in vivo experiments. These experiments, conducted at 7 T with a fixed nominal voxel size and matched acquisition times, revealed that the two DW-CRT designs improved the shape of the spatial response function by suppressing side lobes, also resulting in improved signal-to-noise ratio (SNR). High-quality spectra were acquired for all trajectories from a specific region of interest in the motor cortex with an in-plane resolution of 7.5 × 7.5 mm2 in 8 min 3 s. Due to hardware limitations, high-spatial-resolution spectra with an in-plane resolution of 5 × 5 mm2 and an acquisition time of 12 min 48 s were acquired only for the RE and one of the DW-CRT trajectories and not for EPSI. For all phantom and in vivo experiments, DW-CRTs resulted in the highest SNR. The achieved in vivo spectral quality of the DW-CRT method allowed for reliable metabolic mapping of eight metabolites including N-acetylaspartylglutamate, γ-aminobutyric acid and glutathione with Cramér-Rao lower bounds below 50%, using an LCModel analysis. Finally, high-quality metabolic mapping of a whole brain slice using DW-CRT was achieved with a high in-plane resolution of 5 × 5 mm2 in a healthy subject. These findings demonstrate that our DW-CRT MRSI technique can perform robustly on MRI systems and within a clinically feasible acquisition time.

Effects of spatial fMRI resolution on the classification of naturalistic movies

Studies involving multivariate pattern analysis (MVPA) of BOLD fMRI data generally attribute the success of the information-theoretic approach to BOLD signal contrast on the fine spatial scale of millimeters facilitating the classification or decoding of perceptual stimuli. However, to date MVPA studies that have actually explored fMRI resolutions at less than 2 mm voxel size are rare and limited to small sets of unnatural stimuli (like visual gratings) as well as specific sub-regions of the brain, notably the primary somatosensory cortices. To investigate what spatial scale best supports high information extraction under more general conditions this study combined naturalistic movie stimuli with high-resolution fMRI at 7 T and linear discriminant analysis (LDA) of global and local BOLD signal patterns. Contrary to predictions, LDA and similar classifiers reached a maximum in classification accuracy (CA) at a smoothed resolution close to 3 mm, well above the 1.2 mm voxel size of the fMRI acquisition. Maximal CAs around 90% were contingent upon global fMRI signal patterns comprising 4 k-16 k of the most reactive voxels distributed sparsely throughout the occipital and ventro-temporal cortices. A Searchlight analysis of local fMRI patterns largely confirmed the global results, but also revealed a small subset of brain regions in early visual cortex showing limited increases in CA with higher resolution. Principal component analysis of the global and local fMRI signal patterns suggested that reproducible neuronal contributions were spatially auto-correlated and smooth, while other components of higher spatial frequency were likely related to physiological noise and responsible for the reduced CA at higher resolution. Systematic differences between experiments and subjects suggested that higher CA was significantly correlated with more consistent behavior revealed by eye tracking. Thus, the optimal resolution of fMRI data for MVPA was mainly limited by physiological noise of high spatial frequency as well as behavioral (in-)consistency.

Rapid anatomical brain imaging using spiral acquisition and an expanded signal model

We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B₀ dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute. A range of options is explored, including proton-density and T₂* contrast, acceleration by parallel imaging, different readout orientations, and the extraction of phase images. Results are shown to exhibit competitive image quality along with high geometric consistency.

Analysis and correction of field fluctuations in fMRI data using field monitoring

This work investigates the role of magnetic field fluctuations as a confound in fMRI. In standard fMRI experiments with single-shot EPI acquisition at 3 Tesla the uniform and gradient components of the magnetic field were recorded with NMR field sensors. By principal component analysis it is found that differences of field evolution between the EPI readouts are explainable by few components relating to slow and within-shot field dynamics of hardware and physiological origin. The impact of fluctuating field components is studied by selective data correction and assessment of its influence on image fluctuation and SFNR. Physiological field fluctuations, attributed to breathing, were found to be small relative to those of hardware origin. The dominant confounds were hardware-related and attributable to magnet drift and thermal changes. In raw image time series, field fluctuation caused significant SFNR loss, reflected by a 67% gain upon correction. Large part of this correction can be accomplished by traditional image realignment, which addresses slow and spatially uniform field changes. With realignment, explicit field correction increased the SFNR on the order of 6%. In conclusion, field fluctuations are a relevant confound in fMRI and can be addressed effectively by retrospective data correction. Based on the physics involved it is anticipated that the advantage of full field correction increases with field strength, with non-Cartesian readouts, and upon phase-sensitive BOLD analysis.

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.

Concurrent recording of RF pulses and gradient fields - comprehensive field monitoring for MRI

Reconstruction of MRI data is based on exact knowledge of all magnetic field dynamics, since the interplay of RF and gradient pulses generates the signal, defines the contrast and forms the basis of resolution in spatial and spectral dimensions. Deviations caused by various sources, such as system imperfections, delays, eddy currents, drifts or externally induced fields, can therefore critically limit the accuracy of MRI examinations. This is true especially at ultra-high fields, because many error terms scale with the main field strength, and higher available SNR renders even smaller errors relevant. Higher baseline field also often requires higher acquisition bandwidths and faster signal encoding, increasing hardware demands and the severity of many types of hardware imperfection. To address field imperfections comprehensively, in this work we propose to expand the concept of magnetic field monitoring to also encompass the recording of RF fields. In this way, all dynamic magnetic fields relevant for spin evolution are covered, including low- to audio-frequency magnetic fields as produced by main magnets, gradients and shim systems, as well as RF pulses generated with single- and multiple-channel transmission systems. The proposed approach permits field measurements concurrently with actual MRI procedures on a strict common time base. The combined measurement is achieved with an array of miniaturized field probes that measure low- to audio-frequency fields via (19) F NMR and simultaneously pick up RF pulses in the MRI system's (1) H transmit band. Field recordings can form the basis of system calibration, retrospective correction of imaging data or closed-loop feedback correction, all of which hold potential to render MRI more robust and relax hardware requirements. The proposed approach is demonstrated for a range of imaging methods performed on a 7 T human MRI system, including accelerated multiple-channel RF pulses. Copyright © 2015 John Wiley & Sons, Ltd.

High resolution CBV assessment with PEAK-EPI: k-t-undersampling and reconstruction in echo planar imaging

PURPOSE

Achieving higher spatial resolution and improved brain coverage while mitigating in-plane susceptibility artifacts in the assessment of perfusion parameters, such as cerebral blood volume, in echo planar imaging (EPI)-based dynamic susceptibility contrast weighted cerebral perfusion measurements.

METHODS

PEAK-EPI, an EPI sequence with interleaved readout trajectories and three different strategies for autocalibration-signal acquisition (inplace, dynamic extra and extra) is presented. Performance of each approach is analyzed in vivo based on flip angle variation induced dynamics, assessing temporal fidelity, temporal SNR and g-factors. All approaches are compared with conventional GRAPPA reconstructions. PEAK-EPI with inplace autocalibration-signal at R = 5 is then compared with the standard clinical EPI protocol in six patients, using two half-dose dynamic susceptibility contrast weighted cerebral perfusion measurements per subject.

RESULTS

PEAK-EPI acquisition facilitates a substantial increase of spatial resolution at a higher number of slices per TR and provides improved SNR compared to conventional GRAPPA. High dependency of the resulting reconstruction quality on the type of autocalibration-signal acquisition is observed. PEAK-EPI with inplace autocalibration-signal achieves high temporal fidelity and initial feasibility is shown.

CONCLUSION

The obtained high resolution cerebral blood volume maps reveal more detailed information than in corresponding standard EPI measurements and facilitate detailed delineation of tumorous tissue. Magn Reson Med 77:2153-2166, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Image reconstruction using a gradient impulse response model for trajectory prediction

PURPOSE

Gradient imperfections remain a challenge in MRI, especially for sequences relying on long imaging readouts. This work aims to explore image reconstruction based on k-space trajectories predicted by an impulse response model of the gradient system.

THEORY AND METHODS

Gradient characterization was performed twice with 3 years interval on a commercial 3 Tesla (T) system. The measured gradient impulse response functions were used to predict actual k-space trajectories for single-shot echo-planar imaging (EPI), spiral and variable-speed EPI sequences. Image reconstruction based on the predicted trajectories was performed for phantom and in vivo data. Resulting images were compared with reconstructions based on concurrent field monitoring, separate trajectory measurements, and nominal trajectories.

RESULTS

Image reconstruction using model-based trajectories yielded high-quality images, comparable to using separate trajectory measurements. Compared with using nominal trajectories, it strongly reduced ghosting, blurring, and geometric distortion. Equivalent image quality was obtained with the recent characterization and that performed 3 years prior.

CONCLUSION

Model-based trajectory prediction enables high-quality image reconstruction for technically challenging sequences such as single-shot EPI and spiral imaging. It thus holds great promise for fast structural imaging and advanced neuroimaging techniques, including functional MRI, diffusion tensor imaging, and arterial spin labeling. The method can be based on a one-time system characterization as demonstrated by successful use of 3-year-old calibration data. Magn Reson Med 76:45-58, 2016. © 2015 Wiley Periodicals, Inc.

Analysis of temperature dependence of background phase errors in phase-contrast cardiovascular magnetic resonance

BACKGROUND

The accuracy of phase-contrast cardiovascular magnetic resonance (PC-CMR) can be compromised by background phase errors. It is the objective of the present work to provide an analysis of the temperature dependence of background phase errors in PC-CMR by means of gradient mount temperature sensing and magnetic field monitoring.

METHODS

Background phase errors were measured for various temperatures of the gradient mount using magnetic field monitoring and validated in a static phantom. The effect of thermal changes during k-space acquisition was simulated and confirmed with measurements in a stationary phantom.

RESULTS

The temperature of the gradient mount was found to increase by 20-30 K during PC-CMR measurements of 6-12 min duration. Associated changes in background phase errors of up to 11% or 0.35 radian were measured at 10 cm from the magnet's iso-center as a result of first order offsets. Zeroth order phase errors exhibited little thermal dependence.

CONCLUSIONS

It is concluded that changes in gradient mount temperature significantly modify background phase errors during PC-CMR with high gradient duty cycle. Since temperature increases significantly during the first minutes of scanning the results presented are also of relevance for single-slice or multi-slice PC-CMR scans. The findings prompt for further studies to investigate advanced correction methods taking into account gradient temperature and/or the use of concurrent field-monitoring to map gradient-induced fields throughout the scan.

Real-time motion correction using gradient tones and head-mounted NMR field probes

PURPOSE

Sinusoidal gradient oscillations in the kilohertz range are proposed for position tracking of NMR probes and prospective motion correction for arbitrary imaging sequences without any alteration of sequence timing. The method is combined with concurrent field monitoring to robustly perform image reconstruction in the presence of potential dynamic field deviations.

METHODS

Benchmarking experiments were done to assess the accuracy and precision of the method and to compare it with theoretical predictions based on the field probe's time-dependent signal-to-noise ratio. An array of four field probes was used to perform real-time prospective motion correction in vivo. Images were reconstructed based on both predetermined and concurrently measured k-space trajectories.

RESULTS

For observation windows of 4.8 ms, the precision of probe position determination was found to be 35 to 62 µm, and the maximal measurement error was 595 µm root-mean-square on a single axis. Sequence update per repetition time on this basis yielded images free of conspicuous artifacts despite substantial head motion. Predetermined and concurrently observed k-space trajectories yielded equivalent image quality.

CONCLUSION

NMR field probes in conjunction with gradient tones permit the tracking and prospective correction of rigid-body motion. Relying on gradient oscillations in the kilohertz range, the method allows for concurrent motion detection and image encoding.