A method for the dynamic correction of B0-related distortions in single-echo EPI at 7T

Multiband accelerated 2D EPI for multi-echo brain QSM at 3 T

PURPOSE

Data for QSM are typically acquired using multi-echo 3D gradient echo (GRE), but EPI can be used to accelerate QSM and provide shorter acquisition times. So far, EPI-QSM has been limited to single-echo acquisitions, which, for 3D GRE, are known to be less accurate than multi-echo sequences. Therefore, we compared single-echo and multi-echo EPI-QSM reconstructions across a range of parallel imaging and multiband acceleration factors.

METHODS

Using 2D single-shot EPI in the brain, we compared QSM from single-echo and multi-echo acquisitions across combined parallel-imaging and multiband acceleration factors ranging from 2 to 16, with volume pulse TRs from 21.7 to 3.2 s, respectively. For single-echo versus multi-echo reconstructions, we investigated the effect of acceleration factors on regional susceptibility values, temporal noise, and image quality. We introduce a novel masking method based on thresholding the magnitude of the local field gradients to improve brain masking in challenging regions.

RESULTS

At 1.6-mm isotropic resolution, high-quality QSM was achieved using multi-echo 2D EPI with a combined acceleration factor of 16 and a TR of 3.2 s, which enables functional applications. With these high acceleration factors, single-echo reconstructions are inaccurate and artefacted, rendering them unusable. Multi-echo acquisitions greatly improve QSM quality, particularly at higher acceleration factors, provide more consistent regional susceptibility values across acceleration factors, and decrease temporal noise compared with single-echo QSM reconstructions.

CONCLUSION

Multi-echo acquisition is more robust for EPI-QSM across parallel imaging and multiband acceleration factors than single-echo acquisition. Multi-echo EPI can be used for highly accelerated acquisition while preserving QSM accuracy and quality relative to gold-standard 3D-GRE QSM.

Dixon-based B0 self-navigation in radial stack-of-stars multi-echo gradient echo imaging

PURPOSE

To develop a Dixon-basedB 0 $$ {\mathrm{B}}_0 $$ self-navigation approach to estimate and correct temporalB 0 $$ {\mathrm{B}}_0 $$ variations in radial stack-of-stars gradient echo imaging for quantitative body MRI.

METHODS

The proposed method estimates temporalB 0 $$ {\mathrm{B}}_0 $$ variations using aB 0 $$ {\mathrm{B}}_0 $$ self-navigator estimated by a graph-cut-based water-fat separation algorithm on the oversampled k-space center. TheB 0 $$ {\mathrm{B}}_0 $$ self-navigator was employed to correct for phase differences between radial spokes (one-dimensional [1D] correction) and to perform a motion-resolved reconstruction to correct spatiotemporal pseudo-periodicB 0 $$ {\mathrm{B}}_0 $$ variations (three-dimensional [3D] correction). Numerical simulations, phantom experiments and in vivo neck scans were performed to evaluate the effects of temporalB 0 $$ {\mathrm{B}}_0 $$ variations on the field-map, proton density fat fraction (PDFF) andT 2 ∗ $$ {\mathrm{T}}_2^{\ast } $$ map, and to validate the proposed method.

RESULTS

TemporalB 0 $$ {\mathrm{B}}_0 $$ variations were found to cause signal loss and phase shifts on the multi-echo images that lead to an underestimation ofT 2 ∗ $$ {\mathrm{T}}_2^{\ast } $$ , while PDFF mapping was less affected. TheB 0 $$ {\mathrm{B}}_0 $$ self-navigator captured slowly varying temporalB 0 $$ {\mathrm{B}}_0 $$ drifts and temporal variations caused by respiratory motion. While the 1D correction effectively correctedB 0 $$ {\mathrm{B}}_0 $$ drifts in phantom studies, it was insufficient in vivo due to 3D spatially varying temporalB 0 $$ {\mathrm{B}}_0 $$ variations with amplitudes of up to 25 Hz at 3 T near the lungs. The proposed 3D correction locally improved the correction of field-map andT 2 ∗ $$ {\mathrm{T}}_2^{\ast } $$ and reduced image artifacts.

CONCLUSION

TemporalB 0 $$ {\mathrm{B}}_0 $$ variations particularly affectT 2 ∗ $$ {\mathrm{T}}_2^{\ast } $$ mapping in radial stack-of-stars imaging. The self-navigation approach can be applied without modifying the MR acquisition to correct forB 0 $$ {\mathrm{B}}_0 $$ drift and physiological motion-inducedB 0 $$ {\mathrm{B}}_0 $$ variations, especially in the presence of fat.

Dynamic field mapping and distortion correction using single-shot blip-rewound EPI and joint multi-echo reconstruction

PURPOSE

To develop a method for dynamic∆ B 0 $$ \Delta {B}_0 $$ mapping and distortion correction.

METHODS

A blip-rewound EPI trajectory was developed to acquire multiple 2D EPI images in a single readout with an interleaved order, which allows a short TE difference. A joint multi-echo reconstruction was utilized to exploit the shared information between EPI images. The reconstructed images from each readout are combined to produce a final magnitude image. A∆ B 0 $$ \Delta {B}_0 $$ map is calculated from the phase of these images for distortion correction. The efficacy of the proposed method is assessed with phantom and in vivo experiments. The performance of the proposed method in the presence of subject motion is also investigated.

RESULTS

Compared to conventional multi-echo EPI, the proposed method allows dynamic∆ B 0 $$ \Delta {B}_0 $$ mapping at matched resolution with a much shorter TR. Phantom and in vivo results show that the proposed method can provide a comparable magnitude image as conventional single-shot EPI. The∆ B 0 $$ \Delta {B}_0 $$ maps calculated from the proposed method are consistent with conventional multi-echo EPI in the phantom experiment. For in vivo experiments, the proposed method provides a more accurate estimation of∆ B 0 $$ \Delta {B}_0 $$ than conventional multi-echo EPI, which is prone to phase wrapping problems due to the long TE difference. In-vivo scan with subject motion shows the proposed dynamic field mapping method can improve the temporal stability of EPI time series compared to gradient echo (GRE) based static field mapping.

CONCLUSION

The proposed method allows accurate dynamic∆ B 0 $$ \Delta {B}_0 $$ mapping for robust distortion correction without compromising spatial or temporal resolution.

HAITCH: A Framework for Distortion and Motion Correction in Fetal Multi-Shell Diffusion-Weighted MRI

Diffusion magnetic resonance imaging (dMRI) is pivotal for probing the microstructure of the rapidly-developing fetal brain. However, fetal motion during scans and its interaction with magnetic field inhomogeneities result in artifacts and data scattering across spatial and angular domains. The effects of those artifacts are more pronounced in high-angular resolution fetal dMRI, where signal-to-noise ratio is very low. Those effects lead to biased estimates and compromise the consistency and reliability of dMRI analysis. This work presents HAITCH, the first and the only publicly available tool to correct and reconstruct multi-shell high-angular resolution fetal dMRI data. HAITCH offers several technical advances that include a blip-reversed dual-echo acquisition for dynamic distortion correction, advanced motion correction for model-free and robust reconstruction, optimized multi-shell design for enhanced information capture and increased tolerance to motion, and outlier detection for improved reconstruction fidelity. The framework is open-source, flexible, and can be used to process any type of fetal dMRI data including single-echo or single-shell acquisitions, but is most effective when used with multi-shell multi-echo fetal dMRI data that cannot be processed with any of the existing tools. Validation experiments on real fetal dMRI scans demonstrate significant improvements and accurate correction across diverse fetal ages and motion levels. HAITCH successfully removes artifacts and reconstructs high-fidelity fetal dMRI data suitable for advanced diffusion modeling, including fiber orientation distribution function estimation. These advancements pave the way for more reliable analysis of the fetal brain microstructure and tractography under challenging imaging conditions.

Predicting dynamic, motion-related changes in B0 field in the brain at a 7T MRI using a subject-specific fine-trained U-net

PURPOSE

Subject movement during the MR examination is inevitable and causes not only image artifacts but also deteriorates the homogeneity of the main magnetic field (B0 ), which is a prerequisite for high quality data. Thus, characterization of changes to B0 , for example induced by patient movement, is important for MR applications that are prone to B0 inhomogeneities.

METHODS

We propose a deep learning based method to predict such changes within the brain from the change of the head position to facilitate retrospective or even real-time correction. A 3D U-net was trained on in vivo gradient-echo brain 7T MRI data. The input consisted of B0 maps and anatomical images at an initial position, and anatomical images at a different head position (obtained by applying a rigid-body transformation on the initial anatomical image). The output consisted of B0 maps at the new head positions. We further fine-trained the network weights to each subject by measuring a limited number of head positions of the given subject, and trained the U-net with these data.

RESULTS

Our approach was compared to established dynamic B0 field mapping via interleaved navigators, which suffer from limited spatial resolution and the need for undesirable sequence modifications. Qualitative and quantitative comparison showed similar performance between an interleaved navigator-equivalent method and proposed method.

CONCLUSION

It is feasible to predict B0 maps from rigid subject movement and, when combined with external tracking hardware, this information could be used to improve the quality of MR acquisitions without the use of navigators.

Impact of B 0 $$ {\mathrm{B}}_0 $$ field imperfections correction on BOLD sensitivity in 3D-SPARKLING fMRI data

PURPOSE

Static and dynamicB 0 $$ {\mathrm{B}}_0 $$ field imperfections are detrimental to functional MRI (fMRI) applications, especially at ultra-high magnetic fields (UHF). In this work, a field camera is used to assess the benefits of retrospectively correctingB 0 $$ {\mathrm{B}}_0 $$ field perturbations on Blood Oxygen Level Dependent (BOLD) sensitivity in non-Cartesian three-dimensional (3D)-SPARKLING fMRI acquisitions.

METHODS

fMRI data were acquired at 1 mm3 $$ {}^3 $$ and for a 2.4s-TR while concurrently monitoring in real-time field perturbations using a Skope Clip-on field camera in a novel experimental setting involving a shorter TR than the required minimal TR of the field probes. Measurements of the dynamic field deviations were used along with a staticΔ B 0 $$ \Delta {\mathrm{B}}_0 $$ map to retrospectively correct static and dynamic field imperfections, respectively. In order to evaluate the impact of such a correction on fMRI volumes, a comparative study was conducted on healthy volunteers.

RESULTS

Correction ofB 0 $$ {\mathrm{B}}_0 $$ deviations improved image quality and yielded between 20% and 30% increase in median temporal signal-to-noise ratio (tSNR).Using fMRI data collected during a retinotopic mapping experiment, we demonstrated a significant increase in sensitivity to the BOLD contrast and improved accuracy of the BOLD phase maps: 44% (resp., 159%) more activated voxels were retrieved when using a significance control level based on a p-value of 0.001 without correcting for multiple comparisons (resp., 0.05 with a false discovery rate correction).

CONCLUSION

3D-SPARKLING fMRI hugely benefits from static and dynamicB 0 $$ {\mathrm{B}}_0 $$ imperfections correction. However, the proposed experimental protocol is flexible enough to be deployed on a large spectrum of encoding schemes, including arbitrary non-Cartesian readouts.

Super-resolution QSM in little or no additional time for imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes

Quantitative Susceptibility Mapping has the potential to provide additional insights into neurological diseases but is typically based on a quite long (5-10 min) 3D gradient-echo scan which is highly sensitive to motion. We propose an ultra-fast acquisition based on three orthogonal (sagittal, coronal and axial) 2D simultaneous multi-slice EPI scans with 1 mm in-plane resolution and 3 mm thick slices. Images in each orientation are corrected for susceptibility-related distortions and co-registered with an iterative non-linear Minimum Deformation Averaging (Volgenmodel) approach to generate a high SNR, super-resolution data set with an isotropic resolution of close to 1 mm. The net acquisition time is 3 times the volume acquisition time of EPI or about 12 s, but the three volumes could also replace "dummy scans" in fMRI, making it feasible to acquire QSM in little or No Additional Time for Imaging (NATIve). NATIve QSM values agreed well with reference 3D GRE QSM in the basal ganglia in healthy subjects. In patients with multiple sclerosis, there was also a good agreement between the susceptibility values within lesions and control ROIs and all lesions which could be seen on 3D GRE QSMs could also be visualized on NATIve QSMs. The approach is faster than conventional 3D GRE by a factor of 25-50 and faster than 3D EPI by a factor of 3-5. As a 2D technique, NATIve QSM was shown to be much more robust to motion than the 3D GRE and 3D EPI, opening up the possibility of studying neurological diseases involving iron accumulation and demyelination in patients who find it difficult to lie still for long enough to acquire QSM data with conventional methods.

Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL)

The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.

Prediction of motion induced magnetic fields for human brain MRI at 3 T

OBJECTIVE

Maps of B0 field inhomogeneities are often used to improve MRI image quality, even in a retrospective fashion. These field inhomogeneities depend on the exact head position within the static field but acquiring field maps (FM) at every position is time consuming. Here we propose a forward simulation strategy to obtain B0 predictions at different head-positions.

METHODS

FM were predicted by combining (1) a multi-class tissue model for estimation of tissue-induced fields, (2) a linear k-space model for capturing gradient imperfections, (3) a dipole estimation for quantifying lower-body perturbing fields (4) and a position-dependent tissue mask to model FM alterations caused by large motion effects. The performance of the combined simulation strategy was compared with an approach based on a rigid body transformation of the FM measured in the reference position to the new position.

RESULTS

The transformed FM provided inconsistent results for large head movements (> 5° rotation, approximately), while the simulation strategy had a superior prediction accuracy for all positions. The simulated FM was used to optimize B0 shims with up to 22.2% improvement with respect to the transformed FM approach.

CONCLUSION

The proposed simulation strategy is able to predict movement-induced B0 field inhomogeneities yielding more precise estimates of the ground truth field homogeneity than the transformed FM.

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.

Impact of susceptibility-induced distortion correction on perfusion imaging by pCASL with a segmented 3D GRASE readout

PURPOSE

The consensus for the clinical implementation of arterial spin labeling (ASL) perfusion imaging recommends a segmented 3D Gradient and Spin-Echo (GRASE) readout for optimal signal-to-noise-ratio(SNR). The correction of the associated susceptibility-induced geometric distortions has been shown to improve diagnostic precision, but its impact on ASL data has not been systematically assessed and it is not consistently part of pre-processing pipelines. Here, we investigate the effects of susceptibility-induced distortion correction on perfusion imaging by pseudo-continuous ASL (pCASL) with a segmented 3D GRASE readout.

METHODS

Data acquired from 28 women using pCASL with 3D GRASE at 3T was analyzed using three pre-processing options: without distortion correction, with distortion correction, and with spatial smoothing (without distortion correction) matched to control for blurring effects induced by distortion correction. Maps of temporal SNR (tSNR) and relative perfusion were analyzed in eight regions-of-interest (ROIs) across the brain.

RESULTS

Distortion correction significantly affected tSNR and relative perfusion across the brain. Increases in tSNR were like those produced by matched spatial smoothing in most ROIs, indicating that they were likely due to blurring effects. However, that was not the case in the frontal and temporal lobes, where we also found increased relative perfusion with distortion correction even compared with matched spatial smoothing. These effects were found in both controls and patients, with no interactions with the participant group.

CONCLUSION

Correction of Susceptibility-induced distortions significantly impacts ASL perfusion imaging using a segmented 3D GRASE readout, and this step should therefore be considered in ASL pre-processing pipelines. This is of special importance in clinical studies, reporting perfusion across ROIs defined on relatively undistorted images and when conducting group analyses requiring the alignment of images across different subjects.

The psychosis human connectome project: Design and rationale for studies of visual neurophysiology

Visual perception is abnormal in psychotic disorders such as schizophrenia. In addition to hallucinations, laboratory tests show differences in fundamental visual processes including contrast sensitivity, center-surround interactions, and perceptual organization. A number of hypotheses have been proposed to explain visual dysfunction in psychotic disorders, including an imbalance between excitation and inhibition. However, the precise neural basis of abnormal visual perception in people with psychotic psychopathology (PwPP) remains unknown. Here, we describe the behavioral and 7 tesla MRI methods we used to interrogate visual neurophysiology in PwPP as part of the Psychosis Human Connectome Project (HCP). In addition to PwPP (n = 66) and healthy controls (n = 43), we also recruited first-degree biological relatives (n = 44) in order to examine the role of genetic liability for psychosis in visual perception. Our visual tasks were designed to assess fundamental visual processes in PwPP, whereas MR spectroscopy enabled us to examine neurochemistry, including excitatory and inhibitory markers. We show that it is feasible to collect high-quality data across multiple psychophysical, functional MRI, and MR spectroscopy experiments with a sizable number of participants at a single research site. These data, in addition to those from our previously described 3 tesla experiments, will be made publicly available in order to facilitate further investigations by other research groups. By combining visual neuroscience techniques and HCP brain imaging methods, our experiments offer new opportunities to investigate the neural basis of abnormal visual perception in PwPP.

Off-resonance artifact correction for MRI: A review

In magnetic resonance imaging (MRI), inhomogeneity in the main magnetic field used for imaging, referred to as off-resonance, can lead to image artifacts ranging from mild to severe depending on the application. Off-resonance artifacts, such as signal loss, geometric distortions, and blurring, can compromise the clinical and scientific utility of MR images. In this review, we describe sources of off-resonance in MRI, how off-resonance affects images, and strategies to prevent and correct for off-resonance. Given recent advances and the great potential of low-field and/or portable MRI, we also highlight the advantages and challenges of imaging at low field with respect to off-resonance.

7 T Musculoskeletal MRI: Fundamentals and Clinical Implementation

ABSTRACT

This review summarizes the current state-of-the-art of musculoskeletal 7 T magnetic resonance imaging (MRI), the associated technological challenges, and gives an overview of current and future clinical applications of 1 H-based 7 T MRI. The higher signal-to-noise ratio at 7 T is predominantly used for increased spatial resolution and thus the visualization of anatomical details or subtle lesions rather than to accelerate the sequences. For musculoskeletal MRI, turbo spin echo pulse sequences are particularly useful, but with altered relaxation times, B1 inhomogeneity, and increased artifacts at 7 T; specific absorption rate limitation issues quickly arise for turbo spin echo pulse sequences. The development of dedicated pulse sequence techniques in the last 2 decades and the increasing availability of specialized coils now facilitate several clinical musculoskeletal applications. 7 T MRI is performed in vivo in a wide range of applications for the knee joint and other anatomical areas, such as ultra-high-resolution nerve imaging or bone trabecular microarchitecture imaging. So far, however, it has not been shown systematically whether the higher field strength compared with the established 3 T MRI systems translates into clinical advantages, such as an early-stage identification of tissue damage allowing for preventive therapy or an influence on treatment decisions and patient outcome. At the moment, results tend to suggest that 7 T MRI will be reserved for answering specific, targeted musculoskeletal questions rather than for a broad application, as is the case for 3 T MRI. Future data regarding the implementation of clinical use cases are expected to clarify if 7 T musculoskeletal MRI applications with higher diagnostic accuracy result in patient benefits compared with MRI at lower field strengths.

Unsupervised physiological noise correction of functional magnetic resonance imaging data using phase and magnitude information (PREPAIR)

Of the sources of noise affecting blood oxygen level-dependent functional magnetic resonance imaging (fMRI), respiration and cardiac fluctuations are responsible for the largest part of the variance, particularly at high and ultrahigh field. Existing approaches to removing physiological noise either use external recordings, which can be unwieldy and unreliable, or attempt to identify physiological noise from the magnitude fMRI data. Data-driven approaches are limited by sensitivity, temporal aliasing, and the need for user interaction. In the light of the sensitivity of the phase of the MR signal to local changes in the field stemming from physiological processes, we have developed an unsupervised physiological noise correction method using the information carried in the phase and the magnitude of echo-planar imaging data. Our technique, Physiological Regressor Estimation from Phase and mAgnItude, sub-tR (PREPAIR) derives time series signals sampled at the slice TR from both phase and magnitude images. It allows physiological noise to be captured without aliasing, and efficiently removes other sources of signal fluctuations not related to physiology, prior to regressor estimation. We demonstrate that the physiological signal time courses identified with PREPAIR agree well with those from external devices and retrieve challenging cardiac dynamics. The removal of physiological noise was as effective as that achieved with the most used approach based on external recordings, RETROICOR. In comparison with widely used recording-free physiological noise correction tools-PESTICA and FIX, both performed in unsupervised mode-PREPAIR removed significantly more respiratory and cardiac noise than PESTICA, and achieved a larger increase in temporal signal-to-noise-ratio at both 3 and 7 T.

Iterative static field map estimation for off-resonance correction in non-Cartesian susceptibility weighted imaging

Purpose

Patient‐induced inhomogeneities in the magnetic field cause distortions and blurring during acquisitions with long readouts such as in susceptibility‐weighted imaging (SWI). Most correction methods require collecting an additional ΔB0 field map to remove these artifacts.

Theory

The static ΔB0 field map can be approximated with an acceptable error directly from a single echo acquisition in SWI. The main component of the observed phase is linearly related to ΔB0 and the echo time (TE), and the relative impact of non‐ ΔB0 terms becomes insignificant with TE >20 ms at 3 T for a well‐tuned system.

Methods

The main step is to combine and unfold the multi‐channel phase maps wrapped many times, and several competing algorithms are compared for this purpose. Four in vivo brain data sets collected using the recently proposed 3D spreading projection algorithm for rapid k‐space sampling (SPARKLING) readouts are used to assess the proposed method.

Results

The estimated 3D field maps generated with a 0.6 mm isotropic spatial resolution provide overall similar off‐resonance corrections compared to reference corrections based on an external ΔB0 acquisitions, and even improved for 2 of 4 individuals. Although a small estimation error is expected, no aftermath was observed in the proposed corrections, whereas degradations were observed in the references.

Conclusion

A static ΔB0 field map estimation method was proposed to take advantage of acquisitions with long echo times, and outperformed the reference technique based on an external field map. The difference can be attributed to an inherent robustness to mismatches between volumes and external ΔB0 maps, and diverse other sources investigated.

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Model-based dynamic off-resonance correction for improved accelerated fMRI in awake behaving nonhuman primates

Purpose

To estimate dynamic off‐resonance due to vigorous body motion in accelerated fMRI of awake behaving nonhuman primates (NHPs) using the echo‐planar imaging reference 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 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 spatially low‐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 multislice in vivo acquisitions in awake‐behaving NHPs.

Conclusion

A method is proposed that does not need 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.

Assessing methods for geometric distortion compensation in 7 T gradient echo functional MRI data

Echo planar imaging (EPI) is widely used in functional and diffusion‐weighted MRI, but suffers from significant geometric distortions in the phase encoding direction caused by inhomogeneities in the static magnetic field (B₀). This is a particular challenge for EPI at very high field (≥7 T), as distortion increases with higher field strength. A number of techniques for distortion correction exist, including those based on B₀ field mapping and acquiring EPI scans with opposite phase encoding directions. However, few quantitative comparisons of distortion compensation methods have been performed using human EPI data, especially at very high field. Here, we compared distortion compensation using B₀ field maps and opposite phase encoding scans in two different software packages (FSL and AFNI) applied to 7 T gradient echo (GE) EPI data from 31 human participants. We assessed distortion compensation quality by quantifying alignment to anatomical reference scans using Dice coefficients and mutual information. Performance between FSL and AFNI was equivalent. In our whole‐brain analyses, we found superior distortion compensation using GE scans with opposite phase encoding directions, versus B₀ field maps or spin echo (SE) opposite phase encoding scans. However, SE performed better when analyses were limited to ventromedial prefrontal cortex, a region with substantial dropout. Matching the type of opposite phase encoding scans to the EPI data being corrected (e.g., SE‐to‐SE) also yielded better distortion correction. While the ideal distortion compensation approach likely varies depending on methodological differences across experiments, this study provides a framework for quantitative comparison of different distortion compensation methods.

TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry

Psychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients. This has motivated the genesis of two closely intertwined fields: (i) Translational Neuromodeling (TN), which develops "computational assays" for inferring patient-specific disease processes from neuroimaging, electrophysiological, and behavioral data; and (ii) Computational Psychiatry (CP), with the goal of incorporating computational assays into clinical decision making in everyday practice. In order to serve as objective and reliable tools for clinical routine, computational assays require end-to-end pipelines from raw data (input) to clinically useful information (output). While these are yet to be established in clinical practice, individual components of this general end-to-end pipeline are being developed and made openly available for community use. In this paper, we present the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) software package, an open-source collection of building blocks for computational assays in psychiatry. Collectively, the tools in TAPAS presently cover several important aspects of the desired end-to-end pipeline, including: (i) tailored experimental designs and optimization of measurement strategy prior to data acquisition, (ii) quality control during data acquisition, and (iii) artifact correction, statistical inference, and clinical application after data acquisition. Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized pipelines for predictions about individual patients. We hope that the openly available tools in TAPAS will contribute to the further development of TN/CP and facilitate the translation of advances in computational neuroscience into clinically relevant computational assays.

Real-time motion and retrospective coil sensitivity correction for CEST using volumetric navigators (vNavs) at 7T

PURPOSE

To explore the impact of temporal motion-induced coil sensitivity changes on CEST-MRI at 7T and its correction using interleaved volumetric EPI navigators, which are applied for real-time motion correction.

METHODS

Five healthy volunteers were scanned via CEST. A 4-fold correction pipeline allowed the mitigation of (1) motion, (2) motion-induced coil sensitivity variations, ΔB1- , (3) motion-induced static magnetic field inhomogeneities, ΔB₀ , and (4) spatially varying transmit RF field fluctuations, ΔB1+ . Four CEST measurements were performed per session. For the first 2, motion correction was turned OFF and then ON in absence of voluntary motion, whereas in the other 2 controlled head rotations were performed. During post-processing ΔB1- was removed additionally for the motion-corrected cases, resulting in a total of 6 scenarios to be compared. In all cases, retrospective ∆B₀ and - ΔB1+ corrections were performed to compute artifact-free magnetization transfer ratio maps with asymmetric analysis (MTR_asym ).

RESULTS

Dynamic ΔB1- correction successfully mitigated signal deviations caused by head motion. In 2 frontal lobe regions of volunteer 4, induced relative signal errors of 10.9% and 3.9% were reduced to 1.1% and 1.0% after correction. In the right frontal lobe, the motion-corrected MTR_asym contrast deviated 0.92%, 1.21%, and 2.97% relative to the static case for Δω = 1, 2, 3 ± 0.25 ppm. The additional application of ΔB1- correction reduced these deviations to 0.10%, 0.14%, and 0.42%. The fully corrected MTR_asym values were highly consistent between measurements with and without intended head rotations.

CONCLUSION

Temporal ΔB1- cause significant CEST quantification bias. The presented correction pipeline including the proposed retrospective ΔB1- correction significantly reduced motion-related artifacts on CEST-MRI.

Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO)

PURPOSE

To develop a rapid and accurate MRI phase-unwrapping technique for challenging phase topographies encountered at high magnetic fields, around metal implants, or postoperative cavities, which is sufficiently fast to be applied to large-group studies including Quantitative Susceptibility Mapping and functional MRI (with phase-based distortion correction).

METHODS

The proposed path-following phase-unwrapping algorithm, ROMEO, estimates the coherence of the signal both in space-using MRI magnitude and phase information-and over time, assuming approximately linear temporal phase evolution. This information is combined to form a quality map that guides the unwrapping along a 3D path through the object using a computationally efficient minimum spanning tree algorithm. ROMEO was tested against the two most commonly used exact phase-unwrapping methods, PRELUDE and BEST PATH, in simulated topographies and at several field strengths: in 3T and 7T in vivo human head images and 9.4T ex vivo rat head images.

RESULTS

ROMEO was more reliable than PRELUDE and BEST PATH, yielding unwrapping results with excellent temporal stability for multi-echo or multi-time-point data. It does not require image masking and delivers results within seconds, even in large, highly wrapped multi-echo data sets (eg, 9 seconds for a 7T head data set with 31 echoes and a 208 × 208 × 96 matrix size).

CONCLUSION

Overall, ROMEO was both faster and more accurate than PRELUDE and BEST PATH, delivering exact results within seconds, which is well below typical image acquisition times, enabling potential on-console application.

Attenuation of motion artifacts in fMRI using discrete reconstruction of irregular fMRI trajectories (DRIFT)

PURPOSE

Numerous studies report motion as the most detrimental source of noise and artifacts in fMRI. Current motion correction methods fail to completely address the motion problem. Retrospective techniques such as spatial realignment can correct for between-volume misalignment but fail to address within volume contamination and spin-history artifacts. Prospective motion correction can prevent spin-history artifacts but currently cannot update the gradients fast enough to remove k-space filling artifacts, calling for a hybrid approach to fully address these problems.

THEORY AND METHODS

Motion can be mathematically formulated into the MR signal equation to describe the motion artifacts at their origin in k-space. From these equations, it is demonstrated that different motions have different effects on the signal. A novel motion correction algorithm is designed from these equations to remove motion-induced artifacts directly in k-space, discrete reconstruction of irregular fMRI trajectory (DRIFT). This method is evaluated rigorously using fMRI simulations and data from a rotating phantom inside the scanner.

RESULTS

The results indicate that although some motion types have negligible effects on the MR signal, others produce catastrophic and lasting artifacts even after motion cessation. In simulation, DRIFT is able to remove motion artifacts in the absence of spin history. In a phantom scan, DRIFT significantly attenuates the motion artifacts in the fMRI data.

CONCLUSION

Neither prospective nor retrospective motion correction methods could completely remove the motion artifacts from the fMRI data. However, DRIFT, as a retrospective technique, when combined with prospective motion correction, can eliminate a significant portion of motion artifacts.

High-resolution fMRI at 7 Tesla: challenges, promises and recent developments for individual-focused fMRI studies

Limited detection power has been a bottleneck for subject-specific functional MRI (fMRI) studies, however the higher signal-to-noise ratio afforded by ultra-high magnetic fields (≥ 7 Tesla) provides levels of sensitivity and resolution needed to study individual subjects. What may be surprising is that higher imaging resolution may provide both higher specificity and sensitivity due to reductions in partial volume effects and reduced physiological noise. However, challenges remain to ensure high data quality and to reduce variability in ultra-high field fMRI. We discuss session-specific biases including those caused by factors related to instrumentation, anatomy, and physiology-which can translate into variability across sessions-and how to minimize these to help ultra-high field fMRI reach its full potential for individual-focused studies.

Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses

Functional magnetic resonance imaging (fMRI) data is typically collected with gradient-echo echo-planar imaging (GE-EPI) sequences, which are particularly prone to the susceptibility artifact as a result of B₀ field inhomogeneity. The component derived from in-plane spin dephasing induces pixel intensity variations and, more critically, geometric distortions. Despite the physical mechanisms underlying the susceptibility artifact being well established, a systematic investigation on the impact of the associated geometric distortions, and the direct comparison of different approaches to tackle them, on fMRI data analyses is missing. Here, we compared two different distortion correction approaches, by acquiring additional: (1) EPI data with reversed phase encoding direction (TOPUP), and (2) standard (and undistorted) GE data at two different echo times (GRE). We first characterized the geometric distortions and the correction approaches based on the estimated ΔB₀ field offset and voxel shift maps, and then conducted three types of analyses on the distorted and corrected fMRI data: (1) registration into structural data, (2) identification of resting-state networks (RSNs), and (3) mapping of task-related brain regions of interest. GRE estimated the largest voxel shifts and more positively impacted the quality of the analyses, in terms of the (significantly lower) cost function of the registration, the (higher) spatial overlap between the RSNs and appropriate templates, and the (significantly higher) sensitivity of the task-related mapping based on the Z-score values of the associated activation maps, although also evident when considering TOPUP. fMRI data should thus be corrected for geometric distortions, with the choice of the approach having a modest, albeit positive, impact on the fMRI analyses.

Image distortion correction for MRI in low field permanent magnet systems with strong B0 inhomogeneity and gradient field nonlinearities

Objective

To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${B}_{0}$$\end{document}B0 inhomogeneity and gradient field nonlinearities.

Materials and methods

Conventional image distortion correction algorithms require accurate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Delta B}_{0}$$\end{document}ΔB0 maps which are not possible to acquire directly when the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${B}_{0}$$\end{document}B0 inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${B}_{0}$$\end{document}B0 field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {B}_{0}$$\end{document}ΔB0 maps and images were reconstructed in an iterative manner. In each iteration, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {B}_{0}$$\end{document}ΔB0 maps were reconstructed from the phase difference using Tikhonov regularization, while images were reconstructed using either conjugate phase reconstruction (CPR) or model-based (MB) image reconstruction, taking the reconstructed field map into account. MB reconstructions were, furthermore, combined with compressed sensing (CS) to show the flexibility of this approach towards undersampling. These methods were compared to the standard fast Fourier transform (FFT) image reconstruction approach in simulations and measurements. Distortions due to gradient nonlinearities were corrected in CPR and MB using simulated gradient maps.

Results

Simulation results show that for moderate field inhomogeneities and gradient nonlinearities, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {B}_{0}$$\end{document}ΔB0 maps and images reconstructed using iterative CPR result in comparable quality to that for iterative MB reconstructions. However, for stronger inhomogeneities, iterative MB reconstruction outperforms iterative CPR in terms of signal intensity correction. Combining MB with CS, similar image and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {B}_{0}$$\end{document}ΔB0 map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results.

Discussion

In case of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${B}_{0}$$\end{document}B0 inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {B}_{0}$$\end{document}ΔB0 map estimation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10334-021-00907-2.

Deconvolution-based distortion correction of EPI using analytic single-voxel point-spread functions

PURPOSE

To develop a postprocessing algorithm that corrects geometric distortions due to spatial variations of the static magnetic field amplitude, B₀ , and effects from relaxation during signal acquisition in EPI.

THEORY AND METHODS

An analytic, complex point-spread function is deduced for k-space trajectories of EPI variants and applied to corresponding acquisitions in a resolution phantom and in human volunteers at 3 T. With the analytic point-spread function and experimental maps of B₀ (and, optionally, the effective transverse relaxation time, T 2 * ) as input, a point-spread function matrix operator is devised for distortion correction by a Thikonov-regularized deconvolution in image space. The point-spread function operator provides additional information for an appropriate correction of the signal intensity distribution. A previous image combination algorithm for acquisitions with opposite phase blip polarities is adapted to the proposed method to recover destructively interfering signal contributions.

RESULTS

Applications of the proposed deconvolution-based distortion correction ("DecoDisCo") algorithm demonstrate excellent distortion corrections and superior performance regarding the recovery of an undistorted intensity distribution in comparison to a multifrequency reconstruction. Examples include full and partial Fourier standard EPI scans as well as double-shot center-out trajectories. Compared with other distortion-correction approaches, DecoDisCo permits additional deblurring to obtain sharper images in cases of significant T 2 * effects.

CONCLUSION

Robust distortion corrections in EPI acquisitions are feasible with high quality by regularized deconvolution with an analytic point-spread function. The general algorithm, which is publicly released on GitHub, can be straightforwardly adapted for specific EPI variants or other acquisition schemes.

Dynamic distortion correction for functional MRI using FID navigators

PURPOSE

To develop a method for slice-wise dynamic distortion correction for EPI using rapid spatiotemporal B₀ field measurements from FID navigators (FIDnavs) and to evaluate the efficacy of this new approach relative to an established data-driven technique.

METHODS

A low-resolution reference image was used to create a forward model of FIDnav signal changes to enable estimation of spatiotemporal B₀ inhomogeneity variations up to second order from measured FIDnavs. Five volunteers were scanned at 3 T using a 64-channel coil with FID-navigated EPI. The accuracy of voxel shift measurements and geometric distortion correction was assessed for experimentally induced magnetic field perturbations. The temporal SNR was evaluated in EPI time-series acquired at rest and with a continuous nose-touching action, before and after image realignment.

RESULTS

Field inhomogeneity coefficients and voxel shift maps measured using FIDnavs were in excellent agreement with multi-echo EPI measurements. The FID-navigated distortion correction accurately corrected image geometry in the presence of induced magnetic field perturbations, outperforming the data-driven approach in regions with large field offsets. In functional MRI scans with nose touching, FIDnav-based correction yielded temporal SNR gains of 30% in gray matter. Following image realignment, which accounted for global image shifts, temporal SNR gains of 3% were achieved.

CONCLUSIONS

Our proposed application of FIDnavs enables slice-wise dynamic distortion correction with high temporal efficiency. We achieved improved signal stability by leveraging the encoding information from multichannel coils. This approach can be easily adapted to other EPI-based sequences to improve temporal SNR for a variety of clinical and research applications.

Investigating the accuracy and precision of TE-dependent versus multi-echo QSM using Laplacian-based methods at 3 T

PURPOSE

Multi-echo gradient-recalled echo acquisitions for QSM enable optimizing the SNR for several tissue types through multi-echo (TE) combination or investigating temporal variations in the susceptibility (potentially reflecting tissue microstructure) by calculating one QSM image at each TE (TE-dependent QSM). In contrast with multi-echo QSM, applying Laplacian-based methods (LBMs) for phase unwrapping and background field removal to single TEs could introduce nonlinear temporal variations (independent of tissue microstructure) into the measured susceptibility. Here, we aimed to compare the effect of LBMs on the QSM susceptibilities in TE-dependent versus multi-echo QSM.

METHODS

TE-dependent recalled echo data simulated in a numerical head phantom and gradient-recalled echo images acquired at 3 T in 10 healthy volunteers. Several QSM pipelines were tested, including four distinct LBMs: sophisticated harmonic artifact reduction for phase data (SHARP), variable-radius sophisticated harmonic artifact reduction for phase data (V-SHARP), Laplacian boundary value background field removal (LBV), and one-step total generalized variation (TGV). Results from distinct pipelines were compared using visual inspection, summary statistics of susceptibility in deep gray matter/white matter/venous regions of interest, and, in the healthy volunteers, regional susceptibility bias analysis and nonparametric tests.

RESULTS

Multi-echo versus TE-dependent QSM had higher regional accuracy, especially in high-susceptibility regions and at shorter TEs. Everywhere except in the veins, a processing pipeline incorporating TGV provided the most temporally stable TE-dependent QSM results with an accuracy similar to multi-echo QSM.

CONCLUSIONS

For TE-dependent QSM, carefully choosing LBMs can minimize the introduction of LBM-related nonlinear temporal susceptibility variations.

Higher Order Spherical Harmonics Reconstruction of Fetal Diffusion MRI With Intensity Correction

We present a novel method for higher order reconstruction of fetal diffusion MRI signal that enables detection of fiber crossings. We combine data-driven motion and intensity correction with super-resolution reconstruction and spherical harmonic parametrisation to reconstruct data scattered in both spatial and angular domains into consistent fetal dMRI signal suitable for further diffusion analysis. We show that intensity correction is essential for good performance of the method and identify anatomically plausible fiber crossings. The proposed methodology has potential to facilitate detailed investigation of developing brain connectivity and microstructure in-utero.

A 16-channel AC/DC array coil for anesthetized monkey whole-brain imaging at 7T

Functional magnetic resonance imaging (fMRI) in monkeys is important for bridging the gap between invasive animal brain studies and non-invasive human brain studies. To resolve the finer functional structure of the monkey brain, ultra-high-field (UHF) MR is essential, and high-performance, close-fitting RF receive coils are typically desired to fully leverage the intrinsic gains provided by UHF MRI. Moreover, static field (B0) inhomogeneity arising from the tissue susceptibility interface is more severe at UHF, presenting an obstacle to achieving high-resolution fMRI. B0 shim of the monkey head is challenging due to its smaller size and more complex sources of B0 offsets in multi-modal imaging tasks. In the present work, we have customized an array coil for lightly-anesthetized monkey fMRI in the 7T human scanner that combines RF and multi-coil (MC) B0 shim functionality (also referred to as AC/DC coils) to provide high imaging SNR and high-spatial-order, rapidly switchable B0-shim capability. Additional space was retained on the coil to render it compatible with monkey multi-modal imaging studies. Both MC global (whole-volume) and dynamic (slice-optimized) shim methods were tested and evaluated, and the benefits of MC shim for fMRI experiments was also studied. A minor reduction in RF coil performance was found after introducing additional B0 shim circuitry. However, the proposed RF coil provided higher image SNR and more uniform contrast compared to a commercially available coil for human knee imaging. Compared with static 2nd-order shim, the B0 inhomogeneity was reduced by 56.8%, and 95-percentile B0 offset was reduced to within 28.2 Hz through MC shim, versus 68.7 Hz with 2nd-order static shim. As a result, functional image quality could be improved, and brain activation can be better detected using the proposed AC/DC monkey coil.

In Utero Diffusion MRI: Challenges, Advances, and Applications

In utero diffusion magnetic resonance imaging (MRI) provides unique opportunities to noninvasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as the growth of white matter tracts in the brain, the maturation of placental villous trees, or the fibers in the fetal heart remain to be studied and understood in detail. Advances in fetal interventions and surgery furthermore increase the need for ever more precise antenatal diagnosis from fetal MRI. However, the specific properties of the in utero environment, such as fetal and maternal motion, increased field-of-view, tissue interfaces and safety considerations, are significant challenges for most MRI techniques, and particularly for diffusion. Recent years have seen major improvements, driven by the development of bespoke techniques adapted to these specific challenges in both acquisition and processing. Fetal diffusion MRI, an emerging research tool, is now adding valuable novel information for both research and clinical questions. This paper will highlight specific challenges, outline strategies to target them, and discuss two main applications: fetal brain connectomics and placental maturation.

Improved cortical boundary registration for locally distorted fMRI scans

With continuing advances in MRI techniques and the emergence of higher static field strengths, submillimetre spatial resolution is now possible in human functional imaging experiments. This has opened up the way for more specific types of analysis, for example investigation of the cortical layers of the brain. With this increased specificity, it is important to correct for the geometrical distortions that are inherent to echo planar imaging (EPI). Inconveniently, higher field strength also increases these distortions. The resulting displacements can easily amount to several millimetres and as such pose a serious problem for laminar analysis. We here present a method, Recursive Boundary Registration (RBR), that corrects distortions between an anatomical and an EPI volume. By recursively applying Boundary Based Registration (BBR) on progressively smaller subregions of the brain we generate an accurate whole-brain registration, based on the grey-white matter contrast. Explicit care is taken that the deformation does not break the topology of the cortical surface, which is an important requirement for several of the most common subsequent steps in laminar analysis. We show that RBR obtains submillimetre accuracy with respect to a manually distorted gold standard, and apply it to a set of human in vivo scans to show a clear increase in spacial specificity. RBR further automates the process of non-linear distortion correction. This is an important step towards routine human laminar fMRI for large field of view acquisitions. We provide the code for the RBR algorithm, as well as a variety of functions to better investigate registration performance in a public GitHub repository, https://github.com/TimVanMourik/OpenFmriAnalysis, under the GPL 3.0 license.

Intra-session and inter-subject variability of 3D-FID-MRSI using single-echo volumetric EPI navigators at 3T

Purpose

In this study, we demonstrate the first combination of 3D FID proton MRSI and spatial encoding via concentric‐ring trajectories (CRTs) at 3T. FID‐MRSI has many benefits including high detection sensitivity, in particular for J‐coupled metabolites (e.g., glutamate/glutamine). This makes it highly attractive, not only for clinical, but also for, potentially, functional MRSI. However, this requires excellent reliability and temporal stability. We have, therefore, augmented this 3D‐FID‐MRSI sequence with single‐echo, imaging‐based volumetric navigators (se‐vNavs) for real‐time motion/shim‐correction (SHMOCO), which is 2× quicker than the original double‐echo navigators (de‐vNavs), hence allowing more efficient integration also in short‐TR sequences.

Methods

The tracking accuracy (position and B₀‐field) of our proposed se‐vNavs was compared to the original de‐vNavs in phantoms (rest and translation) and in vivo (voluntary head rotation). Finally, the intra‐session stability of a 5:40 min 3D‐FID‐MRSI scan was evaluated with SHMOCO and no correction (NOCO) in 5 resting subjects. Intra/inter‐subject coefficients of variation (CV) and intra‐class correlations (ICC) over the whole 3D volume and in selected regions of interest ROI were assessed.

Results

Phantom and in vivo scans showed highly consistent tracking performance for se‐vNavs compared to the original de‐vNavs, but lower frequency drift. Up to ~30% better intra‐subject CVs were obtained for SHMOCO (P < 0.05), with values of 9.3/6.9/6.5/7.8% over the full VOI for Glx/tNAA/tCho/m‐Ins ratios to tCr. ICCs were good‐to‐high (91% for Glx/tCr in motor cortex), whereas the inter‐subject variability was ~11–19%.

Conclusion

Real‐time motion/shim corrected 3D‐FID‐MRSI with time‐efficient CRT‐sampling at 3T allows reliable, high‐resolution metabolic imaging that is fast enough for clinical use and even, potentially, for functional MRSI.

Improving sensitivity, specificity, and reproducibility of individual brainstem activation

Functional imaging of the brainstem may open new avenues for clinical diagnostics. However, for reliable assessments of brainstem activation, further efforts improving signal quality are needed. Six healthy subjects performed four repeated functional magnetic resonance imaging (fMRI) sessions on different days with jaw clenching as a motor task to elicit activation in the trigeminal motor nucleus. Functional images were acquired with a 7 T MR scanner using an optimized multiband EPI sequence. Activation measures in the trigeminal nucleus and a control region were assessed using different physiological noise correction methods (aCompCor and RETROICOR-based approaches with variable numbers of regressors) combined with cerebrospinal fluid or brainstem masking. Receiver-operating characteristic analyses accounting for sensitivity and specificity, activation overlap analyses to estimate the reproducibility between sessions, and intraclass correlation analyses (ICC) for testing reliability between subjects and sessions were used to systematically compare the physiological noise correction approaches. Masking the brainstem led to increased activation in the target ROI and resulted in higher values for the area under the curve (AUC) as a combined measure for sensitivity and specificity. With the highest values for AUC, activation overlap, and ICC, the most favorable physiological noise correction method was to control for the cerebrospinal fluid time series (aCompCor with one regressor). Brainstem motor nuclei activation can be reliably identified using high-field fMRI with optimized acquisition and processing strategies-even on single-subject level. Applying specific physiological noise correction methods improves reproducibility and reliability of brainstem activation encouraging future clinical applications.

A comparison of static and dynamic ∆B0 mapping methods for correction of CEST MRI in the presence of temporal B0 field variations

PURPOSE

To assess the performance, in the presence of scanner instabilities, of three dynamic correction methods which integrate ∆B₀ mapping into the chemical exchange saturation transfer (CEST) measurement and three established static ∆B₀ -correction approaches.

METHODS

A homogeneous phantom and five healthy volunteers were scanned with a CEST sequence at 7 T. The in vivo measurements were performed twice: first with unaltered system frequency and again applying frequency shifts during the CEST acquisition. In all cases, retrospective voxel-wise ∆B₀ -correction was performed using one intrinsic and two extrinsic [prescans with dual-echo gradient-echo and water saturation shift referencing (WASSR)] static approaches. These were compared with two intrinsic [using phase data directly generated by single-echo or double-echo GRE (gradient-echo) CEST readout (CEST-GRE-2TE)] and one extrinsic [phase from interleaved dual-echo EPI (echo planar imaging) navigator (NAV-EPI-2TE)] dynamic ∆B₀ -correction approaches [allowing correction of each Z-spectral point before magnetization transfer ratio asymmetry (MTR_asym) analysis].

RESULTS

All three dynamic methods successfully mapped the induced drift. The intrinsic approaches were affected by the CEST labeling near water (∆ω < |0.3| ppm). The MTR_asym contrast was distorted by the frequency drift in the brain by up to 0.21%/Hz when static ∆B₀ -corrections were applied, whereas the dynamic ∆B₀ corrections reduced this to <0.01%/Hz without the need of external scans. The CEST-GRE-2TE and NAV-EPI-2TE resulted in highly consistent MTR_asym values with/without drift for all subjects.

CONCLUSION

Reliable correction of scanner instabilities is essential to establish clinical CEST MRI. The three dynamic approaches presented improved the ∆B₀ -correction performance significantly in the presence of frequency drift compared to established static methods. Among them, the self-corrected CEST-GRE-2TE was the most accurate and straightforward to implement.

The Impact of Echo Time Shifts and Temporal Signal Fluctuations on BOLD Sensitivity in Presurgical Planning at 7 T

OBJECTIVES

Gradients in the static magnetic field caused by tissues with differing magnetic susceptibilities lead to regional variations in the effective echo time, which modifies both image signal and BOLD sensitivity. Local echo time changes are not considered in the most commonly used metric for BOLD sensitivity, temporal signal-to-noise ratio (tSNR), but may be significant, particularly at ultrahigh field close to air cavities (such as the sinuses and ear canals) and near gross brain pathologies and postoperative sites.

MATERIALS AND METHODS

We have studied the effect of local variations in echo time and tSNR on BOLD sensitivity in 3 healthy volunteers and 11 patients with tumors, postoperative cavities, and venous malformations at 7 T. Temporal signal-to-noise ratio was estimated from a 5-minute run of resting state echo planar imaging with a nominal echo time of 22 milliseconds. Maps of local echo time were derived from the phase of a multiecho GE scan. One healthy volunteer performed 10 runs of a breath-hold task. The t-map from this experiment served as a criterion standard BOLD sensitivity measure. Two runs of a less demanding breath-hold paradigm were used for patients.

RESULTS

In all subjects, a strong reduction in the echo time (from 22 milliseconds to around 11 milliseconds) was found close to the ear canals and sinuses. These regions were characterized by high tSNR but low t-values in breath-hold t-maps. In some patients, regions of particular interest in presurgical planning were affected by reductions in the echo time to approximately 13-15 milliseconds. These included the primary motor cortex, Broca's area, and auditory cortex. These regions were characterized by high tSNR values (70 and above). Breath-hold results were corrupted by strong motion artifacts in all patients.

CONCLUSIONS

Criterion standard BOLD sensitivity estimation using hypercapnic experiments is challenging, especially in patient populations. Taking into consideration the tSNR, commonly used for BOLD sensitivity estimation, but ignoring local reductions in the echo time (eg, from 22 to 11 milliseconds), would erroneously suggest functional sensitivity sufficient to map BOLD signal changes. It is therefore important to consider both local variations in the echo time and temporal variations in signal, using the product metric of these two indices for instance. This should ensure a reliable estimation of BOLD sensitivity and to facilitate the identification of potential false-negative results. This is particularly true at high fields, such as 7 T and in patients with large pathologies and postoperative cavities.

Influence of respiration-induced B0 variations in real-time phase-contrast echo planar imaging of the cervical cerebrospinal fluid

PURPOSE

Respiration induces temporal variations of the main magnetic field B₀ along the spinal cord. These variations are typically not compensated for in velocity quantifications using phase-contrast MRI. The goal of this study was to analyze errors caused by respiration-induced B₀ variations in real-time phase-contrast echo planar imaging (PCEPI) of cervical cerebrospinal fluid (CSF) velocity measurements and to evaluate this effect for various sequence parameters using numerical simulations.

METHODS

Real-time B₀ measurements with double gradient echo sequence and PCEPI measurements were acquired in the cervical CSF of 10 healthy subjects. Dynamic phase offsets attributed to respiration-induced B₀ variations were analyzed by quantifying amplitudes and comparing the temporal behavior with respiratory signals. In experiments and simulations, the influence of the echo time (TE) and the delay between PCEPI images (Δt) with respect to respiration on the dynamic phase offsets were investigated.

RESULTS

A good agreement was found between phase offsets extracted from both acquisition types. Furthermore, respiratory signals qualitatively matched the temporal behavior of the measured phase offsets showing a dependency on subject-dependent local B₀ distribution and respiration physiology. Simulations revealed residual background phases in PCEPI velocity quantification varying with TE and Δt.

CONCLUSION

Respiration-induced B₀ variations result in dynamic background phases in real-time PCEPI velocity quantifications of the CSF in the cervical spine. The current work underlines that these background phases need to be corrected to avoid confounding effects.

A critical assessment of data quality and venous effects in sub-millimeter fMRI

Advances in hardware, pulse sequences, and reconstruction techniques have made it possible to perform functional magnetic resonance imaging (fMRI) at sub-millimeter resolution while maintaining high spatial coverage and acceptable signal-to-noise ratio. Here, we examine whether sub-millimeter fMRI can be used as a routine method for obtaining accurate measurements of fine-scale local neural activity. We conducted fMRI in human visual cortex during a simple event-related visual experiment (7 T, gradient-echo EPI, 0.8-mm isotropic voxels, 2.2-s sampling rate, 84 slices), and developed analysis and visualization tools to assess the quality of the data. Our results fall along three lines of inquiry. First, we find that the acquired fMRI images, combined with appropriate surface-based processing, provide reliable and accurate measurements of fine-scale blood oxygenation level dependent (BOLD) activity patterns. Second, we show that the highly folded structure of cortex causes substantial biases on spatial resolution and data visualization. Third, we examine the well-recognized issue of venous contributions to fMRI signals. In a systematic assessment of large sections of cortex measured at a fine scale, we show that time-averaged T2*-weighted EPI intensity is a simple, robust marker of venous effects. These venous effects are unevenly distributed across cortex, are more pronounced in gyri and outer cortical depths, and are, to a certain degree, in consistent locations across subjects relative to cortical folding. Furthermore, we show that these venous effects are strongly correlated with BOLD responses evoked by the experiment. We conclude that sub-millimeter fMRI can provide robust information about fine-scale BOLD activity patterns, but special care must be exercised in visualizing and interpreting these patterns, especially with regards to the confounding influence of the brain's vasculature. To help translate these methodological findings to neuroscience research, we provide practical suggestions for both high-resolution and standard-resolution fMRI studies.

Simultaneous and inherent correction of B0 and eddy-current induced distortions in high-resolution diffusion MRI using reversed polarity gradients and multiplexed sensitivity encoding (RPG-MUSE)

In diffusion MRI (dMRI), static magnetic field (B0) inhomogeneity and time varying gradient eddy currents induce spatial distortions in reconstructed images. These distortions are exacerbated when high spatial resolutions are used, and many field-mapping based correction techniques often only acquire maps of static B0 distortion, which are not adequate for correcting eddy current induced image distortions. This report presents a novel technique, termed RPG-MUSE, for achieving distortion-free high-resolution diffusion MRI by integrating reversed polarity gradients (RPG) into the multi-shot echo planar imaging acquisition scheme used in multiplexed sensitivity encoding (MUSE). By alternating the phase encoding direction between shots in both baseline and diffusion-weighted acquisitions, maps of both static B0 and eddy current induced field inhomogeneities can be inherently derived, without the need for additional data acquisition. Through both 2D and 3D encoded dMRI acquisitions, it is shown that an RPG-MUSE reconstruction can simultaneously achieve high spatial resolution, high spatial fidelity, and subsequently, high accuracy in diffusion metrics.

Key clinical benefits of neuroimaging at 7T

The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.

Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data

Because of their low bandwidth in the phase-encode (PE) direction, the susceptibility-induced off-resonance field causes distortions in echo planar imaging (EPI) images. It is therefore crucial to correct for susceptibility-induced distortions when performing diffusion studies using EPI. The susceptibility-induced field is caused by the object (head) disrupting the field and it is typically assumed that it remains constant within a framework defined by the object, (i.e. it follows the object as it moves in the scanner).

However, this is only approximately true. When a non-spherical object rotates around an axis other than that parallel with the magnetic flux (the z-axis) it changes the way it disrupts the field, leading to different distortions. Hence, if using a single field to correct for distortions there will be residual distortions in the volumes where the object orientation is substantially different to that when the field was measured.

In this paper we present a post-processing method for estimating the field as it changes with motion during the course of an experiment. It only requires a single measured field and knowledge of the orientation of the subject when that field was acquired. The volume-to-volume changes of the field as a consequence of subject movement are estimated directly from the diffusion data without the need for any additional or special acquisitions. It uses a generative model that predicts how each volume would look predicated on field change and inverts that model to yield an estimate of the field changes. It has been validated on both simulations and experimental data. The results show that we are able to track the field with high accuracy and that we are able to correct the data for the adverse effects of the changing field.

Methods for cleaning the BOLD fMRI signal

Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.

Extended hybrid-space SENSE for EPI: Off-resonance and eddy current corrected joint interleaved blip-up/down reconstruction

INTRODUCTION

Geometric distortions along the phase encode direction caused by off-resonant spins are still a major issue in EPI based functional and diffusion imaging. If the off-resonance map is known it is possible to correct for distortions. Most correction methods operate as a post-processing step on the reconstructed magnitude images.

THEORY AND METHODS

Here, we present an algebraic reconstruction method (hybrid-space SENSE) that incorporates a physics based model of off-resonances, phase inconsistencies between k-space segments, and T2*-decay during the acquisition. The method can be used to perform a joint reconstruction of interleaved acquisitions with normal (blip-up) and inverted (blip-down) phase encode direction which results in reduced g-factor penalty.

RESULTS

A joint blip-up/down simultaneous multi slice (SMS) reconstruction for SMS-factor 4 in combination with twofold in-plane acceleration leads to a factor of two decrease in maximum g-factor penalty while providing off-resonance and eddy-current corrected images.

CONCLUSION

We provide an algebraic framework for reconstructing diffusion weighted EPI data that in addition to the general applicability of hybrid-space SENSE to 2D-EPI, SMS-EPI and 3D-EPI with arbitrary k-space coverage along z, allows for a modeling of arbitrary spatio-temporal effects during the acquisition period like off-resonances, phase inconsistencies and T2*-decay. The most immediate benefit is a reduction in g-factor penalty if an interleaved blip-up/down acquisition strategy is chosen which facilitates eddy current estimation and ensures no loss in k-space encoding in regions with strong off-resonance gradients.

The clinical relevance of distortion correction in presurgical fMRI at 7T

Presurgical planning with fMRI benefits from increased reliability and the possibility to reduce measurement time introduced by using ultra-high field. Echo-planar imaging suffers, however, from geometric distortions which scale with field strength and potentially give rise to clinically significant displacement of functional activation. We evaluate the effectiveness of a dynamic distortion correction (DDC) method based on unmodified single-echo EPI in the context of simulated presurgical planning fMRI at 7T and compare it with static distortion correction (SDC). The extent of distortion in EPI and activation shifts are investigated in a group of eleven patients with a range of neuropathologies who performed a motor task. The consequences of neglecting to correct images for susceptibility-induced distortions are assessed in a clinical context. It was possible to generate time series of EPI-based field maps which were free of artifacts in the eloquent brain areas relevant to presurgical fMRI, despite the presence of signal dropouts caused by pathologies and post-operative sites. Distortions of up to 5.1mm were observed in the primary motor cortex in raw EPI. These were accurately corrected with DDC and slightly less accurately with SDC. The dynamic nature of distortions in UHF clinical fMRI was demonstrated via investigation of temporal variation in voxel shift maps, confirming the potential inadequacy of SDC based on a single reference field map, particularly in the vicinity of pathologies or in the presence of motion. In two patients, the distortion correction was potentially clinically significant in that it might have affected the localization or interpretation of activation and could thereby have influenced the treatment plan. Distortion correction is shown to be effective and clinically relevant in presurgical planning at 7T.