Human Connectome Project-style resting-state functional MRI at 7 Tesla using radiofrequency parallel transmission

Artificial intelligence for neuro MRI acquisition: a review

OBJECT

To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts.

MATERIALS AND METHODS

A comprehensive analysis was conducted on recent AI-based methods in neuro MRI acquisition. The study focused on key technological advances, their impact on clinical practice, and potential risks associated with these methods.

RESULTS

The findings indicate that AI-based algorithms have a substantial positive impact on the MRI acquisition process, improving both efficiency and throughput. Specific algorithms were identified as particularly effective in optimizing acquisition steps, with reported improvements in workflow efficiency.

DISCUSSION

The review highlights the transformative potential of AI in neuro MRI acquisition, emphasizing the technological advances and clinical benefits. However, it also discusses potential risks and challenges, suggesting areas for future research to mitigate these concerns and further enhance AI integration in MRI acquisition.

Local SAR management strategies to use two-channel RF shimming for fetal MRI at 3 T

PURPOSE

This study evaluates the imaging performance of two-channel RF-shimming for fetal MRI at 3 T using four different local specific absorption rate (SAR) management strategies.

METHODS

Due to the ambiguity of safe local SAR levels for fetal MRI, local SAR limits for RF shimming were determined based on either each individual's own SAR levels in standard imaging mode (CP mode) or the maximum SAR level observed across seven pregnant body models in CP mode. Local SAR was constrained either indirectly by further constraining the whole-body SAR (wbSAR) or directly by using subject-specific local SAR models. Each strategy was evaluated by the improvement of the transmit field efficiency (average |B1 + |) and nonuniformity (|B1 + | variation) inside the fetus compared with CP mode for the same wbSAR.

RESULTS

Constraining wbSAR when using RF shimming decreases B1 + efficiency inside the fetus compared with CP mode (by 12%-30% on average), making it inefficient for SAR management. Using subject-specific models with SAR limits based on each individual's own CP mode SAR value, B1 + efficiency and nonuniformity are improved on average by 6% and 13% across seven pregnant models. In contrast, using SAR limits based on maximum CP mode SAR values across seven models, B1 + efficiency and nonuniformity are improved by 13% and 25%, compared with the best achievable improvement without SAR constraints: 15% and 26%.

CONCLUSION

Two-channel RF-shimming can safely and significantly improve the transmit field inside the fetus when subject-specific models are used with local SAR limits based on maximum CP mode SAR levels in the pregnant population.

Reconstruction for 7T high-resolution whole-brain diffusion MRI using two-stage N/2 ghost correction and L1-SPIRiT without single-band reference

PURPOSE

To combine a new two-stage N/2 ghost correction and an adapted L1-SPIRiT method for reconstruction of 7T highly accelerated whole-brain diffusion MRI (dMRI) using only autocalibration scans (ACS) without the need of additional single-band reference (SBref) scans.

METHODS

The proposed ghost correction consisted of a 3-line reference approach in stage 1 and the reference-free entropy method in stage 2. The adapted L1-SPIRiT method was formulated within the 3D k-space framework. Its efficacy was examined by acquiring two dMRI data sets at 1.05-mm isotropic resolutions with a total acceleration of 6 or 9 (i.e., 2-fold or 3-fold slice and 3-fold in-plane acceleration). Diffusion analysis was performed to derive DTI metrics and estimate fiber orientation distribution functions (fODFs). The results were compared with those of 3D k-space GRAPPA using only ACS, all in reference to 3D k-space GRAPPA using both ACS and SBref (serving as a reference).

RESULTS

The proposed ghost correction eliminated artifacts more robustly than conventional approaches. Our adapted L1-SPIRiT method outperformed 3D k-space GRAPPA when using only ACS, improving image quality to what was achievable with 3D k-space GRAPPA using both ACS and SBref scans. The improvement in image quality further resulted in an improvement in estimation performances for DTI and fODFs.

CONCLUSION

The combination of our new ghost correction and adapted L1-SPIRiT method can reliably reconstruct 7T highly accelerated whole-brain dMRI without the need of SBref scans, increasing acquisition efficiency and reducing motion sensitivity.

Parallel transmit (pTx) with online pulse design for task-based fMRI at 7 T

PURPOSE

Parallel transmission (pTx) is an approach to improve image uniformity for ultra-high field imaging. In this study, we modified an echo planar imaging (EPI) sequence to design subject-specific pTx pulses online. We compared its performance against EPI with conventional circularly polarised (CP) pulses.

METHODS

We compared the pTx-EPI and CP-EPI sequences in a short EPI acquisition protocol and for two different functional paradigms in six healthy volunteers (2 female, aged 23-36 years, mean age 29.2 years). We chose two paradigms that are typically affected by signal dropout at 7 T: a visual objects localiser to determine face/scene selective brain regions and a semantic-processing task.

RESULTS

Across all subjects, pTx-EPI improved whole-brain mean temporal signal-to-noise ratio (tSNR) by 11.0% compared to CP-EPI. We also compared the ability of pTx-EPI and CP-EPI to detect functional activation for three contrasts over the two paradigms: face > object and scene > object for the visual objects localiser and semantic association > pattern matching for the semantic-processing paradigm. Across all three contrasts, pTx-EPI showed higher median z-scores and detected more active voxels in relevant areas, as determined from previous 3 T studies.

CONCLUSION

We have demonstrated a workflow for EPI acquisitions with online per-subject pulse calculations. We saw improved performance in both tSNR and functional acquisitions from pTx-EPI. Thus, we believe that online calculation pTx-EPI is robust enough for future fMRI studies, especially where activation is expected in brain areas liable to significant signal dropout.

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.

Mitigating transmit‐B 1 artifacts by predicting parallel transmission images with deep learning: A feasibility study using high‐resolution whole‐brain diffusion at 7 Tesla

Purpose

To propose a novel deep learning (DL) approach to transmit‐B₁ (B₁⁺)‐artifact mitigation without direct use of parallel transmission (pTx), by predicting pTx images from single‐channel transmission (sTx) images.

Methods

A deep encoder–decoder convolutional neural network was constructed and trained to learn the mapping from sTx to pTx images. The feasibility was demonstrated using 7 T Human‐Connectome Project (HCP)‐style diffusion MRI. The training dataset comprised images acquired on 5 healthy subjects using commercial Nova RF coils. Relevant hyperparameters were tuned with a nested cross‐validation, and the generalization performance evaluated using a regular cross‐validation.

Results

Our DL method effectively improved the image quality for sTx images by restoring the signal dropout, with quality measures (including normalized root‐mean‐square error, peak SNR, and structural similarity index measure) improved in most brain regions. The improved image quality was translated into improved performances for diffusion tensor imaging analysis; our method improved accuracy for fractional anisotropy and mean diffusivity estimations, reduced the angular errors of principal eigenvectors, and improved the fiber orientation delineation relative to sTx images. Moreover, the final DL model trained on data of all 5 subjects was successfully used to predict pTx images for unseen new subjects (randomly selected from the 7 T HCP database), effectively recovering the signal dropout and improving color‐coded fractional anisotropy maps with largely reduced noise levels.

Conclusion

The proposed DL method has potential to provide images with reduced B1⁺ artifacts in healthy subjects even when pTx resources are inaccessible on the user side.

Big contributions of the little brain for precision psychiatry

Our previous work using 3T functional Magnetic Resonance Imaging (fMRI) parcellated the human dentate nuclei (DN), the primary output of the cerebellum, to three distinct functional zones each contributing uniquely to default-mode, salience-motor, and visual brain networks. In this perspective piece, we highlight the possibility to target specific functional territories within the cerebellum using non-invasive brain stimulation, potentially leading to the refinement of cerebellar-based therapeutics for precision psychiatry. Significant knowledge gap exists in our functional understanding of cerebellar systems. Intervening early, gauging severity of illness, developing intervention strategies and assessing treatment response, are all dependent on our understanding of the cerebello-cerebral networks underlying the pathology of psychotic disorders. A promising yet under-examined avenue for biomarker discovery is disruptions in cerebellar output circuitry. This is primarily because most 3T MRI studies in the past had to exclude cerebellum from the field of view due to limitations in spatiotemporal resolutions. Using recent technological advances in 7T MRI (e.g., parallel transmit head coils) to identify functional territories of the DN, with a focus on dentato-cerebello-thalamo-cortical (CTC) circuitry can lead to better characterization of brain-behavioral correlations and assessments of co-morbidities. Such an improved mechanistic understanding of psychiatric illnesses can reveal aspects of CTC circuitry that can aid in neuroprognosis, identification of subtypes, and generate testable hypothesis for future studies.

The Human Connectome Project: A retrospective

The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.

Evaluation of the whole auditory pathway using high-resolution and functional MRI at 7T parallel-transmit

Purpose

The aim of the present study is to show a MR procedure for the evaluation of simultaneous left and right auditory functions with functional MRI, and high-resolution acquisition of anatomical auditory pathway using parallel-transmit (pTx) methods at 7T.

Methods

The time-efficient MR acquisition included two steps: RF weights were optimized for the regions-of-interest and high-resolution MR images of the inner-ear were acquired for the first 30 min (400 μm-iso resolution) followed by functional MRI acquisitions along the whole auditory pathway during the next 20 minutes. Data was processed with a linear cross-correlation analysis to define frequency preferences for each voxel in the auditory relays.

Results

Tonotopic maps revealed ordered bilateral frequency gradients in the auditory relays whereas at the level of the cochlear nuclei and superior olivary complexes the frequency gradients were less evident. A 21% increase in transmit-field efficiency was achieved over the left/right inner-ear regions and thus its main structures were clearly discernible using the pTx methods, compared to a single transmit RF coil.

Conclusion

Using 7T pTx allows a fast (less than 60 min in total) and qualitative evaluation of the simultaneous left and right auditory response along the entire auditory pathway, together with high-resolution anatomical images of the inner-ear. This could be further used for patient examination at 7T.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI

Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.

Robust RF shimming and small-tip-angle multispoke pulse design with finite-difference regularization

PURPOSE

A new regularizer is proposed for the magnitude least-squares optimization algorithm, to ensure robust parallel transmit RF shimming and small-tip-angle multispoke pulse designs for ultrahigh-field MRI.

METHODS

A finite-difference regularization term is activated as an additional regularizer in the iterative magnitude-least-squares based pulse design algorithm when an unwanted flip angle null distribution is detected. Both simulated and experimental B 1 + maps from different transmit arrays and different human subjects at 7 T were used to evaluate the proposed algorithm. The algorithm was further demonstrated in experiment with dynamic multislice RF shimming for a single-shot gradient-echo EPI for human functional MRI at 7 T.

RESULTS

The proposed finite-difference regularizer effectively prevented excitation null to be formed for RF shimming and small-tip-angle multispoke pulses, and improved the latter with a monotonic trade-off relationship between flip angle error and RF power. The proposed algorithm was demonstrated to be effective with several head-array geometries by simulation and with a commercial head array with 12 healthy human subjects by experiment. During a functional MRI scan at 7 T with dynamic RF shimming, the proposed algorithm ensured high image SNR throughout the human brain, compared with near-complete local signal loss by the conventional magnitude-least-squares algorithm.

CONCLUSION

Using finite-difference regularization to avoid unwanted solutions, the robustness of RF shimming and small-tip-angle multispoke pulse design algorithms are improved, with better flip angle homogeneity and a monotonic trade-off relationship between flip angle error and RF power.

Optimization of adiabatic pulses for pulsed arterial spin labeling at 7 tesla: Comparison with pseudo-continuous arterial spin labeling

PURPOSE

To optimize and evaluate adiabatic pulses for pulsed arterial spin labeling at ultrahigh field 7 tesla.

METHODS

Four common adiabatic inversion pulses, including hyperbolic secant, wideband uniform rate smooth truncation, frequency offset corrected inversion, and time-resampled frequency offset corrected inversion pulses, were optimized based on a custom-defined loss function that included labeling efficiency and inversion band uniformity. The optimized pulses were implemented in flow-sensitive alternating inversion recovery sequences and tested on phantom and 11 healthy volunteers with 2 constraints: 1) specific absorption rate normalized; and 2) equal peak RF amplitude, respectively. A pseudo-continuous arterial spin labeling sequence was implemented for comparison. Quantitative metrics such as perfusion and relative labeling efficiency versus residual tissue signal were calculated.

RESULTS

Among the 4 pulses, the wideband uniform rate smooth truncation pulse yielded the lowest loss in simulation and achieved a good balance between labeling efficiency and residual tissue signal from both phantom and in vivo experiments. Wideband uniform rate smooth truncation-pulsed arterial spin labeling showed significantly higher relative labeling efficiency compared to the other sequences (P < .01), whereas the perfusion signal was increased by 40% when the highest B 1 + amplitude was used. The 4 pulsed arterial spin labeling sequences yielded comparable perfusion signals compared to pseudo-continuous arterial spin labeling but with less than half the specific absorption rate.

CONCLUSION

Optimized wideband uniform rate smooth truncation pulse with the highest B 1 + amplitude allowed was recommended for 7 tesla pulsed arterial spin labeling.

New acquisition techniques and their prospects for the achievable resolution of fMRI

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

BRAIN Initiative: Cutting-Edge Tools and Resources for the Community

The overarching goal of the NIH BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative is to advance the understanding of healthy and diseased brain circuit function through technological innovation. Core principles for this goal include the validation and dissemination of the myriad innovative technologies, tools, methods, and resources emerging from BRAIN-funded research. Innovators, BRAIN funding agencies, and non-Federal partners are working together to develop strategies for making these products usable, available, and accessible to the scientific community. Here, we describe several early strategies for supporting the dissemination of BRAIN technologies. We aim to invigorate a dialogue with the neuroscience research and funding community, interdisciplinary collaborators, and trainees about the existing and future opportunities for cultivating groundbreaking research products into mature, integrated, and adaptable research systems. Along with the accompanying Society for Neuroscience 2019 Mini-Symposium, "BRAIN Initiative: Cutting-Edge Tools and Resources for the Community," we spotlight the work of several BRAIN investigator teams who are making progress toward providing tools, technologies, and services for the neuroscience community. These tools access neural circuits at multiple levels of analysis, from subcellular composition to brain-wide network connectivity, including the following: integrated systems for EM- and florescence-based connectomics, advances in immunolabeling capabilities, and resources for recording and analyzing functional connectivity. Investigators describe how the resources they provide to the community will contribute to achieving the goals of the NIH BRAIN Initiative. Finally, in addition to celebrating the contributions of these BRAIN-funded investigators, the Mini-Symposium will illustrate the broader diversity of BRAIN Initiative investments in cutting-edge technologies and resources.

Denoise magnitude diffusion magnetic resonance images via variance-stabilizing transformation and optimal singular-value manipulation

Although shown to have a great utility for a wide range of neuroscientific and clinical applications, diffusion-weighted magnetic resonance imaging (dMRI) faces a major challenge of low signal-to-noise ratio (SNR), especially when pushing the spatial resolution for improved delineation of brain's fine structure or increasing the diffusion weighting for increased angular contrast or both. Here, we introduce a comprehensive denoising framework for denoising magnitude dMRI. The framework synergistically combines the variance stabilizing transform (VST) with optimal singular value manipulation. The purpose of VST is to transform the Rician data to Gaussian-like data so that an asymptotically optimal singular value manipulation strategy tailored for Gaussian data can be used. The output of the framework is the estimated underlying diffusion signal for each voxel in the image domain. The usefulness of the proposed framework for denoising magnitude dMRI is demonstrated using both simulation and real-data experiments. Our results show that the proposed denoising framework can significantly improve SNR across the entire brain, leading to substantially enhanced performances for estimating diffusion tensor related indices and for resolving crossing fibers when compared to another competing method. More encouragingly, the proposed method when used to denoise a single average of 7 ​Tesla Human Connectome Project-style diffusion acquisition provided comparable performances relative to those achievable with ten averages for resolving multiple fiber populations across the brain. As such, the proposed denoising method is expected to have a great utility for high-quality, high-resolution whole-brain dMRI, desirable for many neuroscientific and clinical applications.

A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2nd spatial order in human-connectome-project-style multiband diffusion MRI experiment at 7T: A pilot study

Over the recent years, significant advances in Spin-Echo (SE) Echo-Planar (EP) Diffusion MRI (dMRI) have enabled improved fiber tracking conspicuity in the human brain. At the same time, pushing the spatial resolution and using higher b-values inherently expose the acquired images to further eddy-current-induced distortion and blurring. Recently developed data-driven correction techniques, capable of significantly mitigating these defects, are included in the reconstruction pipelines developed for the Human Connectome Project (HCP) driven by the NIH BRAIN initiative. In this case, however, corrections are derived from the original diffusion-weighted (DW) magnitude images affected by distortion and blurring. Considering the complexity of k-space deviations in the presence of time varying high spatial order eddy currents, distortion and blurring may not be fully reversed when relying on magnitude DW images only. An alternative approach, consisting of iteratively reconstructing DW images based on the actual magnetic field spatiotemporal evolution measured with a magnetic field monitoring camera, has been successfully implemented at 3T in single band dMRI (Wilm et al., 2017, 2015). In this study, we aim to demonstrate the efficacy of this eddy current correction method in the challenging context of HCP-style multiband (MB ​= ​2) dMRI protocol. The magnetic field evolution was measured during the EP-dMRI readout echo train with a field monitoring camera equipped with 16 ¹⁹F NMR probes. The time variation of 0^th, 1^st and 2^nd order spherical field harmonics were used to reconstruct DW images. Individual DW images reconstructed with and without field correction were compared. The impact of eddy current correction was evaluated by comparing the corresponding direction-averaged DW images and fractional anisotropy (FA) maps. ¹⁹F field monitoring data confirmed the existence of significant field deviations induced by the diffusion-encoding gradients, with variations depending on diffusion gradient amplitude and direction. In DW images reconstructed with the field correction, residual aliasing artifacts were reduced or eliminated, and when high b-values were applied, better gray/white matter delineation and sharper gyri contours were observed, indicating reduced signal blurring. The improvement in image quality further contributed to sharper contours and better gray/white matter delineation in mean DW images and FA maps. In conclusion, we demonstrate that up-to-2^nd-order-eddy-current-induced field perturbation in multiband, in-plane accelerated HCP-style dMRI acquisition at 7T can be corrected by integrating the measured field evolution in image reconstruction.

Comparison of SMS-EPI and 3D-EPI at 7T in an fMRI localizer study with matched spatiotemporal resolution and homogenized excitation profiles

The simultaneous multi-slice EPI (SMS-EPI, a.k.a. MB-EPI) sequence has met immense popularity recently in functional neuroimaging. A still less common alternative is the use of 3D-EPI, which offers similar acceleration capabilities. The aim of this work was to compare the SMS-EPI and the 3D-EPI sequences in terms of sampling strategies for the detection of task-evoked activations at 7T using detection theory. To this end, the spatial and temporal resolutions of the sequences were matched (1.6 mm isotropic resolution, TR = 1200 ms) and their excitation profiles were homogenized by means of calibration-free parallel-transmission (Universal Pulses). We used a fast-event “localizer” paradigm of 5:20 min in order to probe sensorimotor functions (visual, auditory and motor tasks) as well as higher level functions (language comprehension, mental calculation), where results from a previous large-scale study at 3T (N = 81) served as ground-truth reference for the brain areas implicated in each cognitive function. In the current study, ten subjects were scanned while their activation maps were generated for each cognitive function with the GLM analysis. The SMS-EPI and 3D-EPI sequences were compared in terms of raw tSNR, t-score testing for the mean signal, activation strength and accuracy of the robust sensorimotor functions. To this end, the sensitivity and specificity of these contrasts were computed by comparing their activation maps to the reference brain areas obtained in the 3T study. Estimated flip angle distributions in the brain reported a normalized root mean square deviation from the target value below 10% for both sequences. The analysis of the t-score testing for the mean signal revealed temporal noise correlations, suggesting the use of this metric instead of the traditional tSNR for testing fMRI sequences. The SMS-EPI and 3D-EPI thereby yielded similar performance from a detection theory perspective.

Designing parallel transmit head coil arrays based on radiofrequency pulse performance

PURPOSE

A new approach to design parallel transmit (pTx) head arrays is proposed that integrates transmit radiofrequency pulse designs with electromagnetic modeling of array coil elements.

THEORY AND METHODS

An approach to design pTx head arrays is proposed that finds optimal groupings of a large number of coils into a small number of channels. An algorithm is proposed to extend array-compressed parallel transmit pulse design by adding the ability to optimally select and prune coil elements, in addition to optimizing compression weights. The performance of the method is demonstrated in simulations of dynamic multislice shimming of the human brain in axial, coronal, and sagittal directions, and of reduced field-of-view excitation targeting the human occipital lobe, with simulated electromagnetic field maps from a group of 5 human head models at 7T.

RESULTS

For both dynamic multislice shimming and reduced field-of-view excitation, the method successfully designed pTx arrays that simultaneously achieved in general 15% lower mean excitation errors with 20% lower SDs, along with 20% lower mean global averaged specific absorption rate and 50% lower SD than previously reported pTx head array designs.

CONCLUSION

With the proposed optimal coil element selection algorithm, the array-compressed parallel transmit pulse design can be extended to design pTx transmit head arrays with joint consideration of the fields within the sample and the radiofrequency pulse. The pTx arrays from such an approach achieved higher transmit excitation accuracy, lower radiofrequency heating in subjects, and more robust performance across subjects compared with previously reported pTx head arrays with the same number of channels.

Parallel Transmission for Ultrahigh Field MRI

Magnetic resonance imaging (MRI) has been driven toward ultrahigh magnetic fields (UHF) in order to benefit from correspondingly higher signal-to-noise ratio and spectral resolution. Technological challenges associated with UHF, such as increased radiofrequency (RF) energy deposition and RF excitation inhomogeneity, limit realization of the full potential of these benefits. Parallel RF transmission (pTx) enables decreases in the inhomogeneity of RF excitations and in RF energy deposition by using multiple-transmit RF coils driven independently and operating simultaneously. pTx plays a fundamental role in UHF MRI by bringing the potential applications of UHF into reality. In this review article, we review the recent developments in pTx pulse design and RF safety in pTx. Simultaneous multislice imaging and inner volume imaging using pTx are reviewed with a focus on UHF applications. Emerging pTx design approaches using improved pTx design frameworks and calibrations are reviewed together with calibration-free approaches that remove the necessity of time-consuming calibrations necessary for successful pTx. Lastly, we focus on the safety of pTx that is improved by using intersubject variability analysis, proactively managing pTx and temperature-based pTx approaches.