The future of ultra-high field MRI and fMRI for study of the human brain

500 MHz Inductive Birdcage RF Coil for Brain MRI: Design, Implementation and Validation

OBJECTIVE

We present a 500 MHz inductive birdcage RF resonator for imaging the human brain in an 11.7 T MRI scanner.

METHODS

A homogenous circularly polarized transmit field ($\text{B}_{1}^{+}$) was generated by transmitting power to the resonator through four couplers driven in differential mode and with an incremental 90-degree phase delay. A detailed mechanical and electrical model of the hardware, loaded with different phantoms, was generated and its performance simulated using a finite-difference time-domain method.

RESULTS

The head-size inductively coupled birdcage presented a fundamental mode at 500 MHz. MR thermometry maps were in good agreement with heating profiles estimated from simulated SAR maps Conclusion: The model of the hardware was validated through both bench and MRI measurements.

SIGNIFICANCE

This validation is important for future analysis of radiofrequency safety and performance at ultra-high field MRI through the prediction of SAR and $\text{B}_{1}^{+}$ profiles across different human brain models at various positions inside the coil.

Functional Ultrasound Imaging of Auditory Responses in Comatose Patients

Bedside monitoring of brain function in severely brain-injured patients remains a critical clinical challenge. We demonstrate the translational potential of functional ultrasound (fUS) imaging for this purpose. In 6 comatose patients (Glasgow coma scale ≤ 8) with cranial windows after decompressive craniectomy, we used a 7.8-MHz transducer optimized for cortical depths of 1.5 to 4 cm to perform real-time fUS during auditory stimulation. We observed task-related increases in regional cerebral blood flow (rCBF) in relevant brain regions (P < 0.001, t test), which correlated with subsequent neurological recovery at 9-month follow-up. These findings establish fUS as a sensitive and portable tool for bedside brain function assessment, offering potential for improved prognostication, treatment guidance, and development of targeted rehabilitative strategies.

Design simulation of high-homogeneity portable MRI magnet array using global optimization algorithm and equivalent currents model

BACKGROUND

High-field magnetic resonance imaging (MRI) systems offer high sensitivity and resolution but are costly and bulky, limiting their widespread use, particularly in remote areas. Conversely, portable MRI systems have emerged as a complementary technology, promising enhanced accessibility.

PURPOSE

This study introduces a novel optimization method combining an analytical model with a highly convergent global optimization algorithm to enhance the design of portable MRI permanent magnet arrays. The approach aims to significantly improve the efficiency of the magnet design process, thereby advancing the homogeneity of portable MRI magnet array.

METHODS

The proposed approach begins with the calculation of initial magnetic field distributions using current element principles. This is followed by the development of an advanced analytical model based on matrix algebra. The consistency between the calculated results of the analytical model and the results from finite element method (FEM) simulations is then evaluated to assess the reliability of the magnetic field calculations across various magnet array configurations. The integration of the analytical model with the improved grey wolf optimization (IGWO) algorithm enhances the optimization process, leading to magnet array configurations with improved homogeneity.

RESULTS

FEM simulations agree with the analytical model, revealing a computational error with an average root mean square error (RMSE) of 0.4% in the magnetic field map. The calculation speed of analytical model is at least 200 times higher than that using FEM-based software with uncompromised accuracy. The optimization process successfully yields a permanent magnet array with exceptional homogeneity (1080 ppm) and strong field strength (79.5 mT) across a 0.2 m diameter of spherical volume (DSV). Moreover, this is accomplished while maintaining a lightweight (129 kg) and compact design (interior diameter: 0.31 m). The IGWO model has been shown to outperform the benchmark genetic algorithm (GA) model, which is currently used for magnet design in MRI.

CONCLUSIONS

This study introduces a novel optimization method that significantly enhances the design of portable MRI permanent magnet arrays. By integrating an analytical model with the IGWO algorithm, this method enhances the efficiency of magnet design compared to traditional FEM. This method addresses the limitations of traditional magnet optimization techniques, which are often susceptible to local optima. The results indicate that this method can play a crucial role in developing MRI systems with high homogeneity.

Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies

Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer's disease, Parkinson's disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques-Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging-in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. Despite challenges such as technical variability, data privacy concerns, and regulatory barriers, the potential of AI-enhanced neuroimaging to revolutionize early diagnosis and personalized treatment in neurodegenerative and neuro-ophthalmic disorders is immense. This review underscores the importance of ongoing efforts to validate, standardize, and implement these technologies to maximize their clinical impact.

Phantom Safety Assessment of 3 Tesla Magnetic Resonance Imaging in Directional and Sensing Deep Brain Stimulation Devices

INTRODUCTION

Magnetic resonance imaging (MRI) is both a crucial clinical and research tool for patients with deep brain stimulation (DBS) devices. However, safety concerns predominantly related to device heating have limited such imaging. Rigorous safety testing has demonstrated that scanning outside of vendor guidelines may be both safe and feasible, unlocking unique opportunities for advanced imaging in this patient population. Currently, however, 3T MRI safety data including advanced MRI sequences in novel directional and sensing DBS devices is lacking.

METHODS

An anthropomorphic phantom replicating bilateral DBS system was used to assess the temperature rise at the electrode tips, implantable pulse generator, and cranial loop during acquisition of routine clinical sequences (three dimensional [3D] T1, GRE T2*, T2 FSE) and advanced imaging sequences including functional MRI (fMRI), arterial spin labelling (ASL), and diffusion weighted imaging (DWI). Measures of radiofrequency exposure (specific absorption rate [SAR] and root-mean square value of the MRI effective component of the radiofrequency transmission field [B1+rms]) were also recorded as an indirect measure of heating. Testing involved both a new directional and sensing DBS device (Medtronic: B30015 leads and Percept PC neurostimulator) and a previous-generation DBS device (Medtronic: 3,387 leads and Percept PC neurostimulator) in combination with a state-of-the-art (Siemens MAGNETOM Prisma) and a previous-generation (GE Signa HDxt) 3T MRI scanner.

RESULTS

On the state-of-the-art 3T MRI scanner, the new DBS device produced safe temperature rises with clinically used sequences and fMRI but not with other advanced sequences such as DWI and ASL, which also exceeded B1+rms vendor guidelines (i.e., ≤2 μT). When scanned on the previous MRI scanner, the recent DBS device produced overall lower and slower temperature rises compared to the previous DBS model. Among the sequences performed on this scanner, several (3D T1, DWI, T2 FSE, and ASL) exceeded the approved SAR vendor limit (<1 W/kg), but only ASL resulted in an unacceptable temperature rise during scanning of the previous DBS model.

CONCLUSION

These phantom safety data show that both clinically used MRI sequences and research sequences such as fMRI can be successfully acquired on 3T MRI scanners with a novel directional and sensing DBS model. As several of these sequences were obtained outside regulatory-approved vendor guidelines, preemptive safety testing should be done. As directional leads become increasingly common, improving MRI safety knowledge is crucial to expand clinical and research possibilities.

INTRODUCTION

Magnetic resonance imaging (MRI) is both a crucial clinical and research tool for patients with deep brain stimulation (DBS) devices. However, safety concerns predominantly related to device heating have limited such imaging. Rigorous safety testing has demonstrated that scanning outside of vendor guidelines may be both safe and feasible, unlocking unique opportunities for advanced imaging in this patient population. Currently, however, 3T MRI safety data including advanced MRI sequences in novel directional and sensing DBS devices is lacking.

METHODS

An anthropomorphic phantom replicating bilateral DBS system was used to assess the temperature rise at the electrode tips, implantable pulse generator, and cranial loop during acquisition of routine clinical sequences (three dimensional [3D] T1, GRE T2*, T2 FSE) and advanced imaging sequences including functional MRI (fMRI), arterial spin labelling (ASL), and diffusion weighted imaging (DWI). Measures of radiofrequency exposure (specific absorption rate [SAR] and root-mean square value of the MRI effective component of the radiofrequency transmission field [B1+rms]) were also recorded as an indirect measure of heating. Testing involved both a new directional and sensing DBS device (Medtronic: B30015 leads and Percept PC neurostimulator) and a previous-generation DBS device (Medtronic: 3,387 leads and Percept PC neurostimulator) in combination with a state-of-the-art (Siemens MAGNETOM Prisma) and a previous-generation (GE Signa HDxt) 3T MRI scanner.

RESULTS

On the state-of-the-art 3T MRI scanner, the new DBS device produced safe temperature rises with clinically used sequences and fMRI but not with other advanced sequences such as DWI and ASL, which also exceeded B1+rms vendor guidelines (i.e., ≤2 μT). When scanned on the previous MRI scanner, the recent DBS device produced overall lower and slower temperature rises compared to the previous DBS model. Among the sequences performed on this scanner, several (3D T1, DWI, T2 FSE, and ASL) exceeded the approved SAR vendor limit (<1 W/kg), but only ASL resulted in an unacceptable temperature rise during scanning of the previous DBS model.

CONCLUSION

These phantom safety data show that both clinically used MRI sequences and research sequences such as fMRI can be successfully acquired on 3T MRI scanners with a novel directional and sensing DBS model. As several of these sequences were obtained outside regulatory-approved vendor guidelines, preemptive safety testing should be done. As directional leads become increasingly common, improving MRI safety knowledge is crucial to expand clinical and research possibilities.

LRE-MMF: A novel multi-modal fusion algorithm for detecting neurodegeneration in Parkinson's disease among the geriatric population

Parkinson's disease (PD) is a prevalent neurological disorder characterized by progressive dopaminergic neuron loss, leading to both motor and non-motor symptoms. Early and accurate diagnosis is challenging due to the subtle and variable nature of early symptoms. This study aims to address these diagnostic challenges by proposing a novel method, Localized Region Extraction and Multi-Modal Fusion (LRE-MMF), designed to enhance diagnostic accuracy through the integration of structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) data. The LRE-MMF method utilizes the complementary strengths of sMRI and rs-fMRI: sMRI provides detailed anatomical information, while rs-fMRI captures functional connectivity patterns. We applied this approach to a dataset consisting of 20 PD patients and 20 healthy controls (HC), all scanned with a 3 T MRI. The primary objective was to determine whether the integration of sMRI and rs-fMRI through the LRE-MMF method improves the classification accuracy between PD and HC subjects. LRE-MMF involves the division of imaging data into localized regions, followed by feature extraction and dimensionality reduction using Principal Component Analysis (PCA). The resulting features were fused and processed through a neural network to learn high-level representations. The model achieved an accuracy of 75 %, with a precision of 0.8125, recall of 0.65, and an AUC of 0.8875. The validation accuracy curves indicated good generalization, with significant brain regions identified, including the caudate, putamen, thalamus, supplementary motor area, and precuneus, as per the AAL atlas. These results demonstrate the potential of the LRE-MMF method for improving early diagnosis and understanding of PD by effectively utilizing both sMRI and rs-fMRI data. This approach could contribute to the development of more accurate diagnostic tools.

Customization of neonatal functional magnetic resonance imaging: A preclinical phantom-based study

Over the past few decades, the use of functional magnetic resonance imaging (fMRI) on neonates and very young children has increased dramatically in research and clinical settings. However, the specific characteristics of this population and the MRI standards largely derived from adult studies, pose serious practical challenges. The current study aims to provide general methodological guidelines for customized neonatal fMRI by assessing the performance of various fMRI hardware and software applications. Specifically, this article focuses on MR equipment (head coils) and MR sequences (singleband vs. multiband). We computed and compared the signal-to-noise ratio (SNR) and the temporal SNR (tSNR) in different fMRI protocols using a small-size spherical phantom in three different commercial receiver-only head-neck coils. Our findings highlight the importance of coil selection and fMRI sequence planning in optimizing neonatal fMRI. For SNR, the prescan normalize filter resulted in significantly higher values overall, while in general there was no difference between the different sequences. In terms of head coil performance, the 20-channel head coil showed slightly but significantly higher values compared to the others. For tSNR, there was no difference in the usage of the prescan normalize filter, but the values were significantly higher in the singleband EPI sequences compared to the multiband. In contrast to the SNR, the pediatric head coil seems to have an advantage for tSNR. We provide five practical guidelines to assist researchers and clinicians in developing fMRI studies in neonates and young infants. These recommendations are especially relevant considering ethical constraints and exogenous challenges of neonatal fMRI.

Coupled stack-up volume RF coils for low-field open MR imaging

Background

Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities.

Purpose

In response to these challenges, we introduce the coupled stack-up volume coil, a novel RF coil design that addresses the shortcomings of conventional birdcage in the context of low-field open MRI.

Methods

The proposed coupled stack-up volume coil design utilizes a unique architecture that optimizes both transmit/receive efficiency and RF field homogeneity and offers the advantage of a simple design and construction, making it a practical and feasible solution for low-field MRI applications. This paper presents a comprehensive exploration of the theoretical framework, design considerations, and experimental validation of this innovative coil design.

Results

We demonstrate the superior performance of the coupled stack-up volume coil in achieving 47.7% higher transmit/receive efficiency and 68% more uniform magnetic field distribution compared to traditional birdcage coils in electromagnetic simulations. Bench tests results show that the B1 field efficiency of coupled stack-up volume coil is 57.3% higher compared with that of conventional birdcage coil.

Conclusions

The proposed coupled stack-up volume coil outperforms the conventional birdcage coil in terms of B1 efficiency, imaging coverage, and low-frequency operation capability. This design provides a robust and simple solution to low-field MR RF coil design.

How do we make progress in phenotyping patients with lower urinary tract such as overactive bladder and underactive detrusor, including using urine markers and microbiome data, to personalize therapy? ICI-RS 2023-Part 2

INTRODUCTION

Overactive bladder (OAB) and underactive bladder (UAB) could be associated with metabolic syndrome, affective disorders, sex hormone deficiency, changes in urinary microbiota, functional gastrointestinal disorders, or autonomic nervous system dysfunction.

OBJECTIVES

The aim of this Think Tank was to provide a guide on how to investigate OAB and/or detrusor underactivity (DU) patients to better clarify the underlying pathophysiology and possibly personalize the treatment.

METHODS

A compendium of discussion based on the current evidence related to phenotyping patients with OAB or DU using urodynamic tests, functional neuro-imaging, urinary markers, and microbiome.

RESULTS AND CONCLUSIONS

The article emphasizes the critical significance of adopting a comprehensive yet tailored approach to phenotyping patients with lower urinary tract (LUT) symptoms, such as OAB and UAB. The intricate interplay between the LUT and various factors, metabolic, neurological, psychological, and gastrointestinal can define unique LUT profiles, enabling personalized therapies to replace the one-size-fits-all approach.

Flexible metasurface for improving brain imaging at 7T

PURPOSE

Ultra-high field MRI offers unprecedented detail for noninvasive visualization of the human brain. However, brain imaging is challenging at 7T due to the B  1 + $$ {}_1^{+} $$ field inhomogeneity, which results in signal intensity drops in temporal lobes and a bright region in the brain center. This study aims to evaluate using a metasurface to improve brain imaging at 7T and simplify the investigative workflow.

METHODS

Two flexible metasurfaces comprising a periodic structure of copper strips and parallel-plate capacitive elements printed on an ultra-thin substrate were optimized for brain imaging and implemented via PCB. We considered two setups: (1) two metasurfaces located near the temporal lobes and (2) one metasurface placed near the occipital lobe. The effect of metasurface placement on the transmit efficiency and specific absorption rate was evaluated via electromagnetic simulation studies with voxelized models. In addition, their impact on signal-to-noise ratio (SNR) and diagnostic image quality was assessed in vivo for two male and one female volunteers.

RESULTS

Placement of metasurfaces near the regions of interest led to an increase in homogeneity of the transmit field by 5% and 10.5% in the right temporal lobe and occipital lobe for a male subject, respectively. SAR efficiency values changed insignificantly, dropping by less than 8% for all investigated setups. In vivo studies also confirmed the numerically predicted improvement in field distribution and receive sensitivity in the desired ROI.

CONCLUSION

Optimized metasurfaces enable homogenizing transmit field distribution in the brain at 7T. The proposed lightweight and flexible structure can potentially provide MR examination with higher diagnostic value images.

Developing new ways to assess neural control of pelvic organ function in spinal conditions: ICI-RS 2023

OBJECTIVES

Several central nervous system (CNS) centers affect muscle groups of the lower urinary tract (LUT) and anorectal tract (ART) via autonomic and somatic pathways, working in different modes (storage or expulsion). Hence spinal cord dysfunction can affect the LUT and ART by several possible mechanisms.

METHODS

This review reports the discussions of a workshop at the 2023 meeting of the International Consultation on Incontinence Research Society, which reviewed uncertainties and research priorities of spinal dysfunction.

RESULTS

Discussion focussed on the levator ani nerve, mechanisms underpinning sensory function and sensation, functional imaging, dyssynergia, and experimental models. The following key research questions were identified. (1) Clinically, how can we evaluate the levator ani muscle to support assessment and identify prognosis for effective treatment selection? (2) How can we reliably measure levator ani tone? (3) How can we evaluate sensory information and sensation for the LUT and the ART? (4) What is the role of functional CNS imaging in development of scientific insights and clinical evaluation? (5) What is the relationship of detrusor sphincter dyssynergia to renal failure?

CONCLUSIONS

Spinal cord dysfunction can fundamentally disrupt LUT and ART function, with considerable clinical impact. The evaluation needs to reflect the full scope of potential problems, and new clinical and diagnostic approaches are needed, for prognosis and treatment. The preclinical science evaluating spinal cord function in both LUT and ART storage and elimination remains a major priority, even though it is a challenging experimental context. Without this underpinning evidence, development of new clinical evidence may be held back.

Quality assessment of routine brain imaging at 0.55 T: initial experience in a clinical workflow

The purpose of this study was to assess the quality of clinical brain imaging in healthy subjects and patients on an FDA-approved commercial 0.55 T MRI scanner, and to provide information about the feasibility of using this scanner in a clinical workflow. In this IRB-approved study, brain examinations on the scanner were prospectively performed in 10 healthy subjects (February-April 2022) and retrospectively derived from 44 patients (February-July 2022). Images collected using the following pulse sequences were available for assessment: axial DWI (diffusion-weighted imaging), apparent diffusion coefficient maps, 2D axial fluid-attenuated inversion recovery images, axial susceptibility-weighted images (both magnitude and phase), sagittal T1-weighted (T1w) Sampling Perfection with Application Optimized Contrast images, sagittal T1w MPRAGE (magnetization prepared rapid gradient echo) with contrast enhancement, axial T1w turbo spin echo (TSE) with and without contrast enhancement, and axial T2-weighted TSE. Two readers retrospectively and independently evaluated image quality and specific anatomical features in a blinded fashion on a four-point Likert scale, with a score of 1 being unacceptable and 4 being excellent, and determined the ability to answer the clinical question in patients. For each category of image sequences, the mean, standard deviation, and percentage of unacceptable quality images (<2) were calculated. Acceptable (rating ≥ 2) image quality was achieved at 0.55 T in all sequences for patients and 85% of the sequences for healthy subjects. Radiologists were able to answer the clinical question in all patients scanned. In total, 50% of the sequences used in patients and about 60% of the sequences used in healthy subjects exhibited good (rating ≥ 3) image quality. Based on these findings, we conclude that diagnostic quality clinical brain images can be successfully collected on this commercial 0.55 T scanner, indicating that the routine brain imaging protocol may be deployed on this system in the clinical workflow.

Research on the Migration and Adsorption Mechanism Applied to Microplastics in Porous Media: A Review

In recent years, microplastics (MPs) have emerged as a significant environmental pollutant, garnering substantial attention for their migration and transformation behaviors in natural environments. MPs frequently infiltrate natural porous media such as soil, sediment, and rock through various pathways, posing potential threats to ecological systems and human health. Consequently, the migration and adsorption mechanisms applied to MPs in porous media have been extensively studied. This paper aims to elucidate the migration mechanisms of MPs in porous media and their influencing factors through a systematic review. The review encompasses the characteristics of MPs, the physical properties of porous media, and hydrodynamic factors. Additionally, the paper further clarifies the adsorption mechanisms of MPs in porous media to provide theoretical support for understanding their environmental behavior and fate. Furthermore, the current mainstream detection techniques for MPs are reviewed, with an analysis of the advantages, disadvantages, and applications of each technique. Finally, the paper identifies the limitations and shortcomings of current research and envisions future research directions.

Multimodal surface coils for low field MR imaging

Low field MRI is safer and more cost effective than the high field MRI. One of the inherent problems of low field MRI is its low signal-to-noise ratio or sensitivity. In this work, we introduce a multimodal surface coil technique for signal excitation and reception to improve the RF magnetic field (B 1 ) efficiency and potentially improve MR sensitivity. The proposed multimodal surface coil consists of multiple identical resonators that are electromagnetically coupled to form a multimodal resonator. The field distribution of its lowest frequency mode is suitable for MR imaging applications. The prototype multimodal surface coils are built, and the performance is investigated and validated through numerical simulation, standard RF measurements and tests, and comparison with the conventional surface coil at low fields. Our results show that the B 1 efficiency of the multimodal surface coil outperforms that of the conventional surface coil which is known to offer the highest B 1 efficiency among all coil categories, i.e., volume coil, half-volume coil and surface coil. In addition, in low-field MRI, the required low-frequency coils often use large value capacitance to achieve the low resonant frequency which makes frequency tuning difficult. The proposed multimodal surface coil can be conveniently tuned to the required low frequency for low-field MRI with significantly reduced capacitance value, demonstrating excellent low-frequency operation capability over the conventional surface coil.

Performance reserves in brain-imaging-based phenotype prediction

This study examines the impact of sample size on predicting cognitive and mental health phenotypes from brain imaging via machine learning. Our analysis shows a 3- to 9-fold improvement in prediction performance when sample size increases from 1,000 to 1 M participants. However, despite this increase, the data suggest that prediction accuracy remains worryingly low and far from fully exploiting the predictive potential of brain imaging data. Additionally, we find that integrating multiple imaging modalities boosts prediction accuracy, often equivalent to doubling the sample size. Interestingly, the most informative imaging modality often varied with increasing sample size, emphasizing the need to consider multiple modalities. Despite significant performance reserves for phenotype prediction, achieving substantial improvements may necessitate prohibitively large sample sizes, thus casting doubt on the practical or clinical utility of machine learning in some areas of neuroimaging.

Seven Tesla MRI in Alzheimer's disease research: State of the art and future directions: A narrative review

Seven tesla magnetic resonance imaging (7T MRI) is known to offer a superior spatial resolution and a signal-to-noise ratio relative to any other non-invasive imaging technique and provides the possibility for neuroimaging researchers to observe disease-related structural changes, which were previously only apparent on post-mortem tissue analyses. Alzheimer's disease is a natural and widely used subject for this technology since the 7T MRI allows for the anticipation of disease progression, the evaluation of secondary prevention measures thought to modify the disease trajectory, and the identification of surrogate markers for treatment outcome. In this editorial, we discuss the various neuroimaging biomarkers for Alzheimer's disease that have been studied using 7T MRI, which include morphological alterations, molecular characterization of cerebral T2*-weighted hypointensities, the evaluation of cerebral microbleeds and microinfarcts, biochemical changes studied with MR spectroscopy, as well as some other approaches. Finally, we discuss the limitations of the 7T MRI regarding imaging Alzheimer's disease and we provide our outlook for the future.

Enhancing the brain MRI at ultra-high field systems using a meta-array structure

BACKGROUND

The main advantage of ultra-high field (UHF) magnetic resonance neuroimaging is theincreased signal-to-noise ratio (SNR) compared with lower field strength imaging. However, the wavelength effect associated with UHF MRI results in radiofrequency (RF) inhomogeneity, compromising whole brain coverage for many commercial coils. Approaches to resolving this issue of transmit field inhomogeneity include the design of parallel transmit systems (PTx), RF pulse design, and applying passive RF shimming such as high dielectric materials. However, these methods have some drawbacks such as unstable material parameters of dielectric pads, high-cost, and complexity of PTx systems. Metasurfaces are artificial structures with a unique platform that can control the propagation of the electromagnetic (EM) waves, and they are very promising for engineering EM device. Implementation of meta-arrays enhancing MRI has been explored previously in several studies.

PURPOSE

The aim of this study was to assess the effect of new meta-array technology on enhancing the brain MRI at 7T. A meta-array based on a hybrid structure consisting of an array of broadside-coupled split-ring resonators and high-permittivity materials was designed to work at the Larmor frequency of a 7 Tesla (7T) MRI scanner. When placed behind the head and neck, this construct improves the SNR in the region of the cerebellum,brainstem and the inferior aspect of the temporal lobes.

METHODS

Numerical electromagnetic simulations were performed to optimize the meta-array design parameters and determine the RF circuit configuration. The resultant transmit-efficiency and signal sensitivity improvements were experimentally analyzed in phantoms followed by healthy volunteers using a 7T whole-body MRI scanner equipped with a standard one-channel transmit, 32-channel receive head coil. Efficacy was evaluated through acquisition with and without the meta-array using two basic sequences: gradient-recalled-echo (GRE) and turbo-spin-echo (TSE).

RESULTS

Experimental phantom analysis confirmed two-fold improvement in the transmit efficiency and 1.4-fold improvement in the signal sensitivity in the target region. In vivo GRE and TSE images with the meta-array in place showed enhanced visualization in inferior regions of the brain, especially of the cerebellum, brainstem, and cervical spinal cord.

CONCLUSION

Addition of the meta-array to commonly used MRI coils can enhance SNR to extend the anatomical coverage of the coil and improve overall MRI coil performance. This enhancement in SNR can be leveraged to obtain a higher resolution image over the same time slot or faster acquisition can be achieved with same resolution. Using this technique could improve the performance of existing commercial coils at 7T for whole brain and other applications.

Neuropragmatics: A scientometric review

Neuropragmatics investigates brain functions and neural activities responsible for pragmatic language abilities, often impaired in disorders such as hemisphere damage, autism, schizophrenia, and neurodegenerative disorders. This study examined the development of neuropragmatics and existing neuroimaging evidence using bibliometric and scientometric indicators, analyzing 4,247 documents published between 1967 and 2022 with CiteSpace and VOSviewer. Our cluster analysis revealed key themes. 1) Language comprehension loss due to brain injury: Studies exploring the impact of brain injuries on language comprehension and underlying neural mechanisms. 2) Right hemisphere damage and pragmatic language skills: Research focusing on the relationship between right hemisphere damage and pragmatic language abilities, investigating impairments in social language use and potential neural correlates. 3) Traumatic brain injury and social communication assessment: Research on traumatic brain injury effects on social communication skills, using various assessment tools to evaluate communication effectiveness in social situations. These clusters provide valuable insights into the neuropragmatics field and serve as a framework for future investigations. By building upon existing knowledge, researchers can improve our understanding of brain functions, language behavior, and enhance rehabilitation for individuals with pragmatic language impairments.

Hyperoxic BOLD-MRI-Based Characterization of Breast Cancer Molecular Subtypes Is Independent of the Supplied Amount of Oxygen: A Preclinical Study

Hyperoxic BOLD-MRI targeting tumor hypoxia may provide imaging biomarkers that represent breast cancer molecular subtypes without the use of injected contrast agents. However, the diagnostic performance of hyperoxic BOLD-MRI using different levels of oxygen remains unclear. We hypothesized that molecular subtype characterization with hyperoxic BOLD-MRI is feasible independently of the amount of oxygen. Twenty-three nude mice that were inoculated into the flank with luminal A (n = 9), Her2+ (n = 5), and triple-negative (n = 9) human breast cancer cells were imaged using a 9.4 T Bruker BioSpin system. During BOLD-MRI, anesthesia was supplemented with four different levels of oxygen (normoxic: 21%; hyperoxic: 41%, 71%, 100%). The change in the spin-spin relaxation rate in relation to the normoxic state, ΔR2*, dependent on the amount of erythrocyte-bound oxygen, was calculated using in-house MATLAB code. ΔR2* was significantly different between luminal A and Her2+ as well as between luminal A and triple-negative breast cancer, reflective of the less aggressive luminal A breast cancer's ability to better deliver oxygen-rich hemoglobin to its tissue. Differences in ΔR2* between subtypes were independent of the amount of oxygen, with robust distinction already achieved with 41% oxygen. In conclusion, hyperoxic BOLD-MRI may be used as a biomarker for luminal A breast cancer identification without the use of exogenous contrast agents.

Resting-state functional connectivity is modulated by cognitive reserve in early Parkinson's disease

Background

Fronto-striatal disconnection is thought to be at the basis of dysexecutive symptoms in patients with Parkinson's disease (PD). Multiple reserve-related processes may offer resilience against functional decline. Among these, cognitive reserve (CR) refers to the adaptability of cognitive processes.

Objective

To test the hypothesis that functional connectivity of pathways associated with executive dysfunction in PD is modulated by CR.

Methods

Twenty-six PD patients and 24 controls underwent resting-state functional magnetic resonance imaging. Functional connectivity was explored with independent component analysis and seed-based approaches. The following networks were selected from the outcome of the independent component analysis: default-mode (DMN), left and right fronto-parietal (l/rFPN), salience (SalN), sensorimotor (SMN), and occipital visual (OVN). Seed regions were selected in the substantia nigra and in the dorsolateral and ventromedial prefrontal cortex for the assessment of seed-based functional connectivity maps. Educational and occupational attainments were used as CR proxies.

Results

Compared with their counterparts with high CR, PD individuals with low CR had reduced posterior DMN functional connectivity in the anterior cingulate and basal ganglia, and bilaterally reduced connectivity in fronto-parietal regions within the networks defined by the dorsolateral and ventrolateral prefrontal seeds. Hyper-connectivity was detected within medial prefrontal regions when comparing low-CR PD with low-CR controls.

Conclusion

CR may exert a modulatory effect on functional connectivity in basal ganglia and executive-attentional fronto-parietal networks. In PD patients with low CR, attentional control networks seem to be downregulated, whereas higher recruitment of medial frontal regions suggests compensation via an upregulation mechanism. This upregulation might contribute to maintaining efficient cognitive functioning when posterior cortical function is progressively reduced.

Cell specificity of Manganese-enhanced MRI signal in the cerebellum

Magnetic Resonance Imaging (MRI) resolution continues to improve, making it important to understand the cellular basis for different MRI contrast mechanisms. Manganese-enhanced MRI (MEMRI) produces layer-specific contrast throughout the brain enabling in vivo visualization of cellular cytoarchitecture, particularly in the cerebellum. Due to the unique geometry of the cerebellum, especially near the midline, 2D MEMRI images can be acquired from a relatively thick slice by averaging through areas of uniform morphology and cytoarchitecture to produce very high-resolution visualization of sagittal planes. In such images, MEMRI hyperintensity is uniform in thickness throughout the anterior-posterior axis of sagittal sections and is centrally located in the cerebellar cortex. These signal features suggested that the Purkinje cell layer, which houses the cell bodies of the Purkinje cells and the Bergmann glia, is the source of hyperintensity. Despite this circumstantial evidence, the cellular source of MRI contrast has been difficult to define. In this study, we quantified the effects of selective ablation of Purkinje cells or Bergmann glia on cerebellar MEMRI signal to determine whether signal could be assigned to one cell type. We found that the Purkinje cells, not the Bergmann glia, are the primary of source of the enhancement in the Purkinje cell layer. This cell-ablation strategy should be useful for determining the cell specificity of other MRI contrast mechanisms.

Hybrid PET/MRI in Cerebral Glioma: Current Status and Perspectives

Advanced MRI methods and PET using radiolabelled amino acids provide valuable information, in addition to conventional MR imaging, for brain tumour diagnostics. These methods are particularly helpful in challenging situations such as the differentiation of malignant processes from benign lesions, the identification of non-enhancing glioma subregions, the differentiation of tumour progression from treatment-related changes, and the early assessment of responses to anticancer therapy. The debate over which of the methods is preferable in which situation is ongoing, and has been addressed in numerous studies. Currently, most radiology and nuclear medicine departments perform these examinations independently of each other, leading to multiple examinations for the patient. The advent of hybrid PET/MRI allowed a convergence of the methods, but to date simultaneous imaging has reached little relevance in clinical neuro-oncology. This is partly due to the limited availability of hybrid PET/MRI scanners, but is also due to the fact that PET is a second-line examination in brain tumours. PET is only required in equivocal situations, and the spatial co-registration of PET examinations of the brain to previous MRI is possible without disadvantage. A key factor for the benefit of PET/MRI in neuro-oncology is a multimodal approach that provides decisive improvements in the diagnostics of brain tumours compared with a single modality. This review focuses on studies investigating the diagnostic value of combined amino acid PET and 'advanced' MRI in patients with cerebral gliomas. Available studies suggest that the combination of amino acid PET and advanced MRI improves grading and the histomolecular characterisation of newly diagnosed tumours. Few data are available concerning the delineation of tumour extent. A clear additive diagnostic value of amino acid PET and advanced MRI can be achieved regarding the differentiation of tumour recurrence from treatment-related changes. Here, the PET-guided evaluation of advanced MR methods seems to be helpful. In summary, there is growing evidence that a multimodal approach can achieve decisive improvements in the diagnostics of cerebral gliomas, for which hybrid PET/MRI offers optimal conditions.

BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development

The benefits, opportunities and growing availability of ultra-high field magnetic resonance imaging (MRI) for humans have prompted an expansion in research and development efforts towards increasingly more advanced high-resolution imaging techniques. To maximize their effectiveness, these efforts need to be supported by powerful computational simulation platforms that can adequately reproduce the biophysical characteristics of MRI, with high spatial resolution. In this work, we have sought to address this need by developing a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI properties that affect image generation. This phantom, termed BigBrain-MR, was generated from the publicly available BigBrain histological dataset and lower-resolution in-vivo 7T-MRI data, using a newly-developed image processing framework that allows mapping the general properties of the latter into the fine anatomical scale of the former. Overall, the mapping framework was found to be effective and robust, yielding a diverse range of realistic "in-vivo-like" MRI contrasts and maps at 100-µm resolution. BigBrain-MR was then tested in three imaging applications (motion effects and interpolation, super-resolution imaging, and parallel imaging reconstruction) to investigate its properties, value and validity as a simulation platform. The results consistently showed that BigBrain-MR can closely approximate the behavior of real in-vivo data, more realistically and with more extensive features than a more classic option such as the Shepp-Logan phantom. Its flexibility in simulating different contrast mechanisms and artifacts may also prove valuable for educational applications. BigBrain-MR is therefore deemed a favorable choice to support methodological development and demonstration in brain MRI, and has been made freely available to the community.

Improving the validity of neuroimaging decoding tests of invariant and configural neural representation

Many research questions in sensory neuroscience involve determining whether the neural representation of a stimulus property is invariant or specific to a particular stimulus context (e.g., Is object representation invariant to translation? Is the representation of a face feature specific to the context of other face features?). Between these two extremes, representations may also be context-tolerant or context-sensitive. Most neuroimaging studies have used operational tests in which a target property is inferred from a significant test against the null hypothesis of the opposite property. For example, the popular cross-classification test concludes that representations are invariant or tolerant when the null hypothesis of specificity is rejected. A recently developed neurocomputational theory suggests two insights regarding such tests. First, tests against the null of context-specificity, and for the alternative of context-invariance, are prone to false positives due to the way in which the underlying neural representations are transformed into indirect measurements in neuroimaging studies. Second, jointly performing tests against the nulls of invariance and specificity allows one to reach more precise and valid conclusions about the underlying representations, particularly when the null of invariance is tested using the fine-grained information from classifier decision variables rather than only accuracies (i.e., using the decoding separability test). Here, we provide empirical and computational evidence supporting both of these theoretical insights. In our empirical study, we use encoding of orientation and spatial position in primary visual cortex as a case study, as previous research has established that these properties are encoded in a context-sensitive way. Using fMRI decoding, we show that the cross-classification test produces false-positive conclusions of invariance, but that more valid conclusions can be reached by jointly performing tests against the null of invariance. The results of two simulations further support both of these conclusions. We conclude that more valid inferences about invariance or specificity of neural representations can be reached by jointly testing against both hypotheses, and using neurocomputational theory to guide the interpretation of results.

A Hybrid Volume-Surface Integral Equation Method for Rapid Electromagnetic Simulations in MRI

OBJECTIVE

We developed a hybrid volume surface integral equation (VSIE) method based on domain decomposition to perform fast and accurate magnetic resonance imaging (MRI) simulations that include both remote and local conductive elements.

METHODS

We separated the conductive surfaces present in MRI setups into two domains and optimized electromagnetic (EM) modeling for each case. Specifically, interactions between the body and EM waves originating from local radiofrequency (RF) coils were modeled with the precorrected fast Fourier transform, whereas the interactions with remote conductive surfaces (RF shield, scanner bore) were modeled with a novel cross tensor train-based algorithm. We compared the hybrid-VSIE with other VSIE methods for realistic MRI simulation setups.

RESULTS

The hybrid-VSIE was the only practical method for simulation using 1 mm voxel isotropic resolution (VIR). For 2 mm VIR, our method could be solved at least 23 times faster and required 760 times lower memory than traditional VSIE methods.

CONCLUSION

The hybrid-VSIE demonstrated a marked improvement in terms of convergence times of the numerical EM simulation compared to traditional approaches in multiple realistic MRI scenarios.

SIGNIFICANCE

The efficiency of the novel hybrid-VSIE method could enable rapid simulations of complex and comprehensive MRI setups.

Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution

Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.

The design and evaluation of single-channel loopole coils at 7T MRI

Objective. Improving the local uniformity of B 1 + field for awake monkey brain magnetic resonance imaging (MRI) at ultra-high fields while facilitating convenient placement and fixation of MRI-compatible multimodal devices for neuroscience study, can eventually advance our understanding of the primate’s brain organization. Approach. A group of single-channel RF coils including conventional loop coils and loopole coils sharing the same size and shape were designed for comparison; their performance as the transmit coil was quantitatively evaluated through a series of numerical electromagnetic (EM) simulations, and further verified by using 7T MRI over a saline phantom and a monkey in vivo. Main results. Compared to conventional loop coils, the optimized loopole coil brought up to 23.5% B 1 + uniformity improvement for monkey brain imaging in EM simulations, and this performance was further verified over monkey brain imaging at 7T in vivo. Importantly, we have systematically explored the underlying mechanism regarding the relationship between loopole coils’ current density distribution and B 1 + uniformity, observing that it can be approximated as a sinusoidal curve. Significance. The proposed loopole coil design can improve the imaging quality in awake and behaving monkeys, thus benefiting advanced brain research at UHF.

Outstanding MRI contrast with dysprosium phosphate nanoparticles of tuneable size

The use of high-field magnets for magnetic resonance imaging (MRI) is expected to experience the fastest growth rate during the present decade. Although several CAs for MRI scanners using high magnetic fields have been reported, they are mostly based on fluoride matrices, which are known for their low chemical stability in aqueous suspensions. Chemically stable MRI CAs for high-field magnets are therefore needed to enable the advances in MRI technique. Herein, we synthesized uniform DyPO₄ nanoparticles (NPs) with tuneable sizes between 23 and 57 nm using homogeneous precipitation in butanol. The NPs were successfully functionalized with polyacrylic acid (PAA) and showed good colloidal stability in aqueous suspensions. Chemical stability was also assessed in PBS, showing negligible solubility. The effect of particle size on the transversal relaxivity value (r₂) was further explored at 9.4 T, finding a clear increase in r₂ with particle size. The r₂ value found for the largest NPs was 516 mM^-1 s^-1, which is, to the best of our knowledge, the highest r₂ value ever reported at 9.4 T for any Dy-based nanometric particles in the literature. Finally, the latter NPs were submitted to biosafety studies after polyethylene glycol (PEG) functionalization. Cell morphology, induction of necrotic/late apoptotic cells, and mitochondrial activity were thoroughly analyzed. The results clearly indicated negligible toxicity effects under the assayed conditions. Short- and long-term in vivo pharmacokinetics of the intravenously injected NPs were assessed by dynamic T₂-weighted MRI and quantitative T₂ mapping, revealing faster liver than spleen uptake, while no accumulation was observed in the kidneys. Finally, no histopathological changes were observed in any of the studied organs, including the liver, kidney, spleen, and lung, which provide further evidence of the biocompatibility of DyPO₄ NPs and, therefore, their suitability as bioimaging probes.

Early detection of increased marrow adiposity with age in rats using Z-spectral MRI at ultra-high field (7 T)

BACKGROUND

Nowadays, the drive towards high-field MRI is fueled by the pursuit of higher signal-to-noise ratio, spatial resolution, and imaging speed. However, high field strength is associated with field inhomogeneity, acceleration of T₂ * decay, and increased chemical shift, which may pose challenges to conventional MRI for fat quantification in complex tissues such as bone marrow. With proton MRI spectroscopy (¹ H-MRS), on the other hand, it is difficult to produce high resolution. As a novel alternative fat quantification method, high-resolution Z-spectral MRI (ZS-MRI) can achieve fat quantification by acquiring direct saturated images of both fat and water under the same T_E , which may be less affected by T₂ * decay and field inhomogeneity.

PURPOSE

To demonstrate ZS-MRI for marrow adipose tissue (MAT) quantification in rat's lumbar spine and the early detection of MAT changes with age.

METHODS

The accuracy of ZS-MRI for fat quantification at ultra-high-field MRI (7 T) was verified with MRS and conventional Dixon MRI in water-oil mixed phantoms with varying fat fraction (FF). Dixon MRI data were processed with iterative decomposition of water and fat with echo asymmetry and least-squares estimation. ZS-MRI was then used to longitudinally monitor the adiposity in the lumbar spine of young healthy rats at 13, 17, and 21 weeks to detect the early changes of FF with age in MAT. Hematoxylin-eosin staining of lumbar spines from separated rat groups was performed for verification.

RESULTS

In ex vivo phantom experiments, both Dixon MRI and ZS-MRI were well correlated with ¹ H-MRS for the quantification of FF at 7 T (R > 0.99). Compared with Dixon MRI, ZS-MRI showed reduced image artifacts due to field inhomogeneity and presented better agreement with ¹ H-MRS for the early detection of increased MAT due to age at 7 T (ZS-MRI R = 0.78 versus Dixon MRI R = 0.34). The increased MAT FF due to age was confirmed by histology.

CONCLUSION

ZS-MRI proves itself as an alternative fat quantification method for bone marrow in rats at 7 T.

7T ultra-high-field neuroimaging for mental health: an emerging tool for precision psychiatry?

Given the huge symptom diversity and complexity of mental disorders, an individual approach is the most promising avenue for clinical transfer and the establishment of personalized psychiatry. However, due to technical limitations, knowledge about the neurobiological basis of mental illnesses has, to date, mainly been based on findings resulting from evaluations of average data from certain diagnostic groups. We postulate that this could change substantially through the use of the emerging ultra-high-field MRI (UHF-MRI) technology. The main advantages of UHF-MRI include high signal-to-noise ratio, resulting in higher spatial resolution and contrast and enabling individual examinations of single subjects. Thus, we used this technology to assess changes in the properties of resting-state networks over the course of therapy in a naturalistic study of two depressed patients. Significant changes in several network property measures were found in regions corresponding to prior knowledge from group-level studies. Moreover, relevant parameters were already significantly divergent in both patients at baseline. In summary, we demonstrate the feasibility of UHF-MRI for capturing individual neurobiological correlates of mental diseases. These could serve as a tool for therapy monitoring and pave the way for a truly individualized and predictive clinical approach in psychiatric care.

Neurite density imaging in amygdala nuclei reveals interindividual differences in neuroticism

Neuroticism is known to have significant health implications. While previous research revealed that interindividual differences in the amygdala function are associated with interindividual differences in neuroticism, the impact of the amygdala’s structure and especially microstructure on variations in neuroticism remains unclear. Here, we present the first study using NODDI to examine the association between the in vivo microstructural architecture of the amygdala and neuroticism at the level of neurites. We, therefore, acquired brain images from 221 healthy participants using advanced multi‐shell diffusion‐weighted imaging. Because the amygdala comprises several nuclei, we, moreover, used a high‐resolution T1 image to automatically segment the amygdala into eight different nuclei. Neuroticism and its facets have been assessed using the NEO‐PI‐R. Finally, we associated neuroticism and its facets with the volume and microstructure of the amygdala nuclei. Statistical analysis revealed that lower neurite density in the lateral amygdala nucleus (La) was significantly associated with higher scores in depression, one of the six neuroticism facets. The La is the sensory relay of the amygdala, filtering incoming information based on previous experiences. Reduced neurite density and related changes in the dendritic structure of the La could impair its filtering function. This again might cause harmless sensory information to be misevaluated as threatening and lead to the altered amygdala responsivity as reported in previous studies investigating the functional correlates of neuroticism and neuroticism‐related disorders like depression.

Longitudinal and transverse NMR relaxivities of Ln(III)-DOTA complexes: A comprehensive investigation

Longitudinal and transverse ¹H nuclear magnetic resonance relaxivities of Ln(III)-DOTA complexes (with Ln = Gd, Tb, Dy, Er; DOTA = 1,4,7,10-tetraazacyclododecane-N,N',N^″,N‴-tetraacetic acid) and Mn(II) aqueous solutions were measured in a wide range of frequencies, 10 kHz to 700 MHz. The experimental data were interpreted by means of models derived from the Solomon-Bloembergen-Morgan theory. The data analysis was performed assuming the orbital angular momentum L = 0 for Gd-DOTA and the aqua ion [Mn(H₂O)₆]²⁺ and L ≠ 0 for Dy-, Tb-, and Er-DOTA. A refined estimation of the zero-field-splitting barrier Δ and of the modulation correlation time τ_v was obtained for [Mn(H₂O)₆]²⁺ by extending the fitting of nuclear magnetic relaxation dispersion profiles to the low-field regime. The Gd-DOTA fitting parameters resulted in good agreement with the literature, and the fit of transverse relaxivity data confirmed the negligibility of the scalar interaction in the nuclear relaxation mechanism. Larger transverse relaxivities of Dy-DOTA and Tb-DOTA (∼10 mM^-1 s^-1) with respect to Er-DOTA (∼1 mM^-1 s^-1) were observed at 16 T. Such higher values are suggested to be due to a shorter residence time τ_m that is possibly linked to the fluctuations of the hyperfine interaction and the different shape of the magnetic anisotropy. The possible employment of Dy-DOTA, Tb-DOTA, and Er-DOTA as negative magnetic resonance imaging contrast agents for high-field applications was envisaged by collecting spin-echo images at 7 T. Particularly in Dy- and Tb-derivatives, the transverse relaxivity at 16 T is of the order of the Gd-one at 1.5 T.

CEREBRUM-7T: Fast and Fully Volumetric Brain Segmentation of 7 Tesla MR Volumes

Ultra-high-field magnetic resonance imaging (MRI) enables sub-millimetre resolution imaging of the human brain, allowing the study of functional circuits of cortical layers at the meso-scale. An essential step in many functional and structural neuroimaging studies is segmentation, the operation of partitioning the MR images in anatomical structures. Despite recent efforts in brain imaging analysis, the literature lacks in accurate and fast methods for segmenting 7-tesla (7T) brain MRI. We here present CEREBRUM-7T, an optimised end-to-end convolutional neural network, which allows fully automatic segmentation of a whole 7T T1_w MRI brain volume at once, without partitioning the volume, pre-processing, nor aligning it to an atlas. The trained model is able to produce accurate multi-structure segmentation masks on six different classes plus background in only a few seconds. The experimental part, a combination of objective numerical evaluations and subjective analysis, confirms that the proposed solution outperforms the training labels it was trained on and is suitable for neuroimaging studies, such as layer functional MRI studies. Taking advantage of a fine-tuning operation on a reduced set of volumes, we also show how it is possible to effectively apply CEREBRUM-7T to different sites data. Furthermore, we release the code, 7T data, and other materials, including the training labels and the Turing test.

Improvement of magnetic resonance imaging using a wireless radiofrequency resonator array

In recent years, new human magnetic resonance imaging systems operating at static magnetic fields strengths of 7 Tesla or higher have become available, providing better signal sensitivity compared with lower field strengths. However, imaging human-sized objects at such high field strength and associated precession frequencies is limited due to the technical challenges associated with the wavelength effect, which substantially disturb the transmit field uniformity over the human body when conventional coils are used. Here we report a novel passive inductively-coupled radiofrequency resonator array design with a simple structure that works in conjunction with conventional coils and requires only to be tuned to the scanner's operating frequency. We show that inductive-coupling between the resonator array and the coil improves the transmit efficiency and signal sensitivity in the targeted region. The simple structure, flexibility, and cost-efficiency make the proposed array design an attractive approach for altering the transmit field distribution specially at high field systems, where the wavelength is comparable with the tissue size.

A line through the brain: implementation of human line-scanning at 7T for ultra-high spatiotemporal resolution fMRI

Functional magnetic resonance imaging (fMRI) is a widely used tool in neuroscience to detect neurally evoked responses, e.g. the blood oxygenation level-dependent (BOLD) signal. Typically, BOLD fMRI has millimeter spatial resolution and temporal resolution of one to few seconds. To study the sub-millimeter structures and activity of the cortical gray matter, the field needs an fMRI method with high spatial and temporal resolution. Line-scanning fMRI achieves very high spatial resolution and high sampling rate, at the cost of a sacrifice in volume coverage. Here, we present a human line-scanning implementation on a 7T MRI system. First, we investigate the quality of the saturation pulses that suppress MR signal outside the line. Second, we established the best coil combination for reconstruction. Finally, we applied the line-scanning method in the occipital lobe during a visual stimulation task, showing BOLD responses along cortical depth, every 250 µm with a 200 ms repetition time (TR). We found a good correspondence of t-statistics values with 2D gradient-echo echo planar imaging (GE-EPI) BOLD fMRI data with the same temporal resolution and voxel volume (R = 0.6 ± 0.2). In summary, we demonstrate the feasibility of line-scanning in humans and this opens line-scanning fMRI for applications in cognitive and clinical neuroscience.

7 Tesla and Beyond: Advanced Methods and Clinical Applications in Magnetic Resonance Imaging

ABSTRACT

Ultrahigh magnetic fields offer significantly higher signal-to-noise ratio, and several magnetic resonance applications additionally benefit from a higher contrast-to-noise ratio, with static magnetic field strengths of B0 ≥ 7 T currently being referred to as ultrahigh fields (UHFs). The advantages of UHF can be used to resolve structures more precisely or to visualize physiological/pathophysiological effects that would be difficult or even impossible to detect at lower field strengths. However, with these advantages also come challenges, such as inhomogeneities applying standard radiofrequency excitation techniques, higher energy deposition in the human body, and enhanced B0 field inhomogeneities. The advantages but also the challenges of UHF as well as promising advanced methodological developments and clinical applications that particularly benefit from UHF are discussed in this review article.

Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies

Diffusion magnetic resonance imaging (dMRI) provides indirect measures of white matter microstructure that can be used to make inferences about structural connectivity within the brain. Over the last decade, a growing literature of cross-sectional and longitudinal studies have documented relationships between dMRI indices and cognitive development. In this review, we provide a brief overview of dMRI methods and how they can be used to study white matter and connectivity and review the extant literature examining the links between dMRI indices and executive functions during development. We explore the links between white matter microstructure and specific executive functions: inhibition, working memory and cognitive shifting, as well as performance on complex executive function tasks. Concordance in findings across studies are highlighted, and potential explanations for discrepancies between results, together with challenges with using dMRI in child and adolescent populations, are discussed. Finally, we explore future directions that are necessary to better understand the links between child and adolescent development of structural connectivity of the brain and executive functions.

MXene-infused bioelectronic interfaces for multiscale electrophysiology and stimulation

Soft bioelectronic interfaces for mapping and modulating excitable networks at high resolution and at large scale can enable paradigm-shifting diagnostics, monitoring, and treatment strategies. Yet, current technologies largely rely on materials and fabrication schemes that are expensive, do not scale, and critically limit the maximum attainable resolution and coverage. Solution processing is a cost-effective manufacturing alternative, but biocompatible conductive inks matching the performance of conventional metals are lacking. Here, we introduce MXtrodes, a class of soft, high-resolution, large-scale bioelectronic interfaces enabled by Ti3C2 MXene (a two-dimensional transition metal carbide nanomaterial) and scalable solution processing. We show that the electrochemical properties of MXtrodes exceed those of conventional materials and do not require conductive gels when used in epidermal electronics. Furthermore, we validate MXtrodes in applications ranging from mapping large-scale neuromuscular networks in humans to cortical neural recording and microstimulation in swine and rodent models. Last, we demonstrate that MXtrodes are compatible with standard clinical neuroimaging modalities.

Neuroimaging at 3T vs 7T: Is It Really Worth It?

Food and Drug Administration approval of 7T MR imaging allows ultrahigh-field neuroimaging to extend from the research realm into the clinical realm. Increased signal is clinically advantageous for smaller voxels and thereby high spatial resolution imaging, with additional advantages of increased tissue contrast. Susceptibility, time-of-flight signal, and blood oxygen level-dependent signal also have favorable clinical benefit from 7T. This article provides a survey of clinical cases showcasing some advantages of 7T.

Cortical and white matter correlates of language-learning aptitudes

People learn new languages with varying degrees of success but what are the neuroanatomical correlates of the difference in language‐learning aptitude? In this study, we set out to investigate how differences in cortical morphology and white matter microstructure correlate with aptitudes for vocabulary learning, phonetic memory, and grammatical inferencing as measured by the first‐language neutral LLAMA test battery. We used ultra‐high field (7T) magnetic resonance imaging to estimate the cortical thickness and surface area from sub‐millimeter resolved image volumes. Further, diffusion kurtosis imaging was used to map diffusion properties related to the tissue microstructure from known language‐related white matter tracts. We found a correlation between cortical surface area in the left posterior‐inferior precuneus and vocabulary learning aptitude, possibly indicating a greater predisposition for storing word‐figure associations. Moreover, we report negative correlations between scores for phonetic memory and axial kurtosis in left arcuate fasciculus as well as mean kurtosis, axial kurtosis, and radial kurtosis of the left superior longitudinal fasciculus III, which are tracts connecting cortical areas important for phonological working memory.

Common neurobiological correlates of resilience and personality traits within the triple resting-state brain networks assessed by 7-Tesla ultra-high field MRI

Despite numerous studies investigating resilience and personality trials, a paucity of information regarding their neurobiological commonalities at the level of the large resting-state networks (rsNWs) remains. Here we address this topic using the advantages of ultra-high-field (UHF) 7T-MRI, characterized by higher signal-to-noise ratio and increased sensitivity. The association between resilience, personality traits and three fMRI measures (fractional amplitude of low-frequency fluctuations (fALFF), degree centrality (DC) and regional homogeneity (ReHo)) determined for three core rsNWs (default mode (DMN), salience (SN), and central executive network (CEN)) were examined in 32 healthy volunteers. The investigation revealed a significant role of SN in both resilience and personality traits and a tight association of the DMN with resilience. DC in CEN emerged as a significant moderator for the correlations of resilience with the personality traits of neuroticism and extraversion. Our results indicate that the common neurobiological basis of resilience and the Big Five personality traits may be reflected at the level of the core rsNWs.

3D MRI Reconstruction Based on 2D Generative Adversarial Network Super-Resolution

The diagnosis of brain pathologies usually involves imaging to analyze the condition of the brain. Magnetic resonance imaging (MRI) technology is widely used in brain disorder diagnosis. The image quality of MRI depends on the magnetostatic field strength and scanning time. Scanners with lower field strengths have the disadvantages of a low resolution and high imaging cost, and scanning takes a long time. The traditional super-resolution reconstruction method based on MRI generally states an optimization problem in terms of prior information. It solves the problem using an iterative approach with a large time cost. Many methods based on deep learning have emerged to replace traditional methods. MRI super-resolution technology based on deep learning can effectively improve MRI resolution through a three-dimensional convolutional neural network; however, the training costs are relatively high. In this paper, we propose the use of two-dimensional super-resolution technology for the super-resolution reconstruction of MRI images. In the first reconstruction, we choose a scale factor of 2 and simulate half the volume of MRI slices as input. We utilize a receiving field block enhanced super-resolution generative adversarial network (RFB-ESRGAN), which is superior to other super-resolution technologies in terms of texture and frequency information. We then rebuild the super-resolution reconstructed slices in the MRI. In the second reconstruction, the image after the first reconstruction is composed of only half of the slices, and there are still missing values. In our previous work, we adopted the traditional interpolation method, and there was still a gap in the visual effect of the reconstructed images. Therefore, we propose a noise-based super-resolution network (nESRGAN). The noise addition to the network can provide additional texture restoration possibilities. We use nESRGAN to further restore MRI resolution and high-frequency information. Finally, we achieve the 3D reconstruction of brain MRI images through two super-resolution reconstructions. Our proposed method is superior to 3D super-resolution technology based on deep learning in terms of perception range and image quality evaluation standards.

Altered Effective Connectivity within the Fronto-Limbic Circuitry in Response to Negative Emotional Task in Female Patients with Major Depressive Disorder

Background: Major depressive disorder (MDD) is a mood disorder associated with disruptions in emotional control. Previous studies have investigated abnormal regional activity and connectivity within the fronto-limbic circuit. However, condition-specific connectivity changes and their association with the pathophysiology of MDD remain unexplored. This study investigated effective connectivity in the fronto-limbic circuit induced by negative emotional processing from patients with MDD. Methods: Thirty-four unmedicated female patients with MDD and 28 healthy participants underwent event-related functional magnetic resonance imaging at 7T while viewing emotionally negative and neutral images. Brain regions whose dynamics are driven by experimental conditions were identified by using statistical parametric mapping. Effective connectivity among regions of interest was then estimated by using dynamic causal modeling. Results: Patients with MDD had lower activation of the orbitofrontal cortex (OFC) and higher activation of the parahippocampal gyrus (PHG) than healthy controls (HC). In association with these regional changes, we found that patients with MDD did not have significant modulatory connections from the primary visual cortex (V1) to OFC, whereas those connections of HC were significantly positively modulated during negative emotional processing. Regarding the PHG activity, patients with MDD had greater modulatory connection from the V1, but reduced negative modulatory connection from the OFC, compared with healthy participants. Conclusions: These results imply that disrupted effective connectivity among regions of the OFC, PHG, and V1 may be closely associated with the impaired regulation of negative emotional processing in the female patients with MDD.

FMRI based on transition-band balanced SSFP in comparison with EPI on a high-performance 0.55 T scanner

PURPOSE

Low-field (<1 tesla) MRI scanners allow more widespread diagnostic use for a range of cardiac, musculoskeletal, and neurological applications. However, the feasibility of performing robust fMRI at low field has yet to be fully demonstrated. To address this gap, we investigated task-based fMRI using a highly sensitive transition-band balanced steady-state free precession approach and standard EPI on a 0.55 tesla scanner equipped with modern high-performance gradient coils and a receive array.

METHODS

TR and flip-angle of transition-band steady-state free precession were optimized for 0.55 tesla by simulations. Static shimming was employed to compensate for concomitant field effects. Visual task-based fMRI data were acquired from 8 healthy volunteers. For comparison, standard EPI data were also acquired with TE = T 2 ∗ . Retrospective image-based correction for physiological effects (RETROICOR) was used to quantify physiological noise effects.

RESULTS

Activation was robustly detected using both methods in a 4-min scan time. Transition-band steady-state free precession was found to be sensitive to interference from subtle spatial and temporal (field drift, respiration) variations in the magnetic field, counteracting potential advantages of the reduced magnetic susceptibility effects compared to its utilization at high field. These adverse effects could be partially remedied with static shimming and postprocessing approaches. Standard EPI proved more robust against the sources of interference.

CONCLUSION

BOLD contrast is sufficiently large at 0.55 tesla for robust detection of brain activation and may be employed to broaden the spectrum of applications of low-field MRI. Standard EPI outperforms transition-band steady-state free precession in terms of signal stability.

A fieldmap-driven few-channel shim coil design for MRI of the human brain

We exploit the inter-subject similarity of inhomogeneous static magnetic field patterns arising in the human brain under MRI examination to design a small set of shim coils providing performance equivalent to numerous coils based on high-order Spherical Harmonics corrections. A hundred brain B ₀-maps were first collected at 3 T. Ideal subject-specific electric current density stream functions are then computed with low power constraints, on a cylindrical surface. This step is repeated over tens of brain maps so that a Principal Component Analysis can be applied to the stream functions; the main components result in the small set of coils. Both 50-subject hold-out and 10-fold cross-validation are employed to evaluate consistency of the proposed system performance over a posteriori subjects. Simulations show that only three cylindrical coils manage to capture the principal magnetic field profiles in the human brain, thus providing a better static field inhomogeneity mitigation than that obtained from 16 unlimited-power high-order Spherical Harmonics coils, with inhomogeneity greatly reduced in the pre-frontal cortex compared to 2nd-order shimmed baseline field acquisitions. The approach provides a very reduced channel count system for mitigating complex B ₀-inhomogeneity patterns. Thus, a compact, cost-effective system could be conceived and driven by relatively low-budget electronics. The method should therefore have a strong impact in both ultra-high and portable low-field MRI/MRS. Moreover, this technique can be applied to the design of shim coils addressing anatomies other than the brain.

Functional Neuroimaging of Adult-to-Adult Romantic Attachment Separation, Rejection, and Loss: A Systematic Review

Romantic attachment rejection (RAR) is a highly prevalent phenomenon among young adults. Rejection by a romantic attachment figure can be a painful and incapacitating experience with lasting negative mental health sequelae, yet the underlying neurobiology of RAR is not well characterized. We systematically reviewed functional neuroimaging studies of adult RAR. Four functional magnetic resonance imaging (fMRI) studies that measured participants' responses to real or imagined RAR and met inclusion criteria were evaluated. These included studies were published between 2004 and 2018. Brain activity in adult participants with an RAR appears to be influenced by the stimulus used to elicit a reaction as well as by attachment styles. Brain regions that show a significant change in activation following a rejection stimulus include cortical regions (cingulate, insular, orbitofrontal, and prefrontal), and subcortical regions (angular gyrus, hippocampus, striatum, tegmental area, and temporal pole) and correspond to (i) pain, distress, and memory retrieval; (ii) reward, romantic love, and dopaminergic circuits; and (iii) emotion regulation and behavioural adaptation. Further neuroimaging studies of adult RAR, as moderated by stimulus and attachment style, are needed to better understand the underlying neurobiology of RAR.

Hardware Considerations for Preclinical Magnetic Resonance of the Kidney

Magnetic resonance imaging (MRI) is a noninvasive imaging technology that offers unparalleled anatomical and functional detail, along with diagnostic sensitivity. MRI is suitable for longitudinal studies due to the lack of exposure to ionizing radiation. Before undertaking preclinical MRI investigations of the kidney, the appropriate MRI hardware should be carefully chosen to balance the competing demands of image quality, spatial resolution, and imaging speed, tailored to the specific scientific objectives of the investigation. Here we describe the equipment needed to perform renal MRI in rodents, with the aim to guide the appropriate hardware selection to meet the needs of renal MRI applications.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This chapter on hardware considerations for renal MRI in small animals is complemented by two separate publications describing the experimental procedure and data analysis.

Inversion Recovery Susceptibility Weighted Imaging With Enhanced T2 Weighting at 3 T Improves Visualization of Subpial Cortical Multiple Sclerosis Lesions

OBJECTIVES

Cortical demyelination is common in multiple sclerosis (MS) and can be extensive. Cortical lesions contribute to disability independently from white matter lesions and may form via a distinct mechanism. However, current magnetic resonance imaging methods at 3 T are insensitive to cortical, and especially subpial cortical, lesions. Subpial lesions are well seen on T2*-weighted imaging at 7 T, but T2*-weighted methods on 3 T scanners are limited by poor lesion-to-cortex and cerebrospinal fluid-to-lesion contrast. We aimed to develop and evaluate a cerebrospinal fluid-suppressed, T2*-weighted sequence optimized for subpial cortical lesion visualization.

MATERIALS AND METHODS

We developed a new magnetic resonance imaging sequence, inversion recovery susceptibility weighted imaging with enhanced T2 weighting (IR-SWIET; 0.8 mm × 0.8 mm in plane, 0.64 mm slice thickness with whole brain coverage, acquisition time ~5 minutes). We compared cortical lesion visualization independently on IR-SWIET (median signal from 4 acquisitions), magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE), double inversion recovery (DIR), T2*-weighted segmented echo-planar imaging, and phase-sensitive inversion recovery images for 10 adults with MS. We also identified cortical lesions with a multicontrast reading of IR-SWIET (median of 2 acquisitions), MP2RAGE, and fluid-attenuated inversion recovery (FLAIR) images for each case. Lesions identified on 3 T images were verified on "gold standard" 7 T T2* and MP2RAGE images.

RESULTS

Cortical, and particularly subpial, lesions appeared much more conspicuous on IR-SWIET compared with other 3 T methods. A total of 101 true-positive subpial lesions were identified on IR-SWIET (average per-participant sensitivity vs 7 T, 29% ± 8%) versus 36 on MP2RAGE (5% ± 2%; comparison to IR-SWIET sensitivity, P = 0.07), 17 on FLAIR (2% ± 1%; P < 0.05), 28 on DIR (6% ± 2%; P < 0.05), 42 on T2*-weighted segmented echo-planar imaging (11% ± 5%; P < 0.05), and 13 on phase-sensitive inversion recovery (4% ± 2%; P < 0.05). When a combination of IR-SWIET, MP2RAGE, and FLAIR images was used, a total of 147 subpial lesions (30% ± 5%) were identified versus 83 (16% ± 3%, P < 0.01) on a combination of DIR, MP2RAGE, and FLAIR. More cases had at least 1 subpial lesion on IR-SWIET, and IR-SWIET improved cortical lesion subtyping accuracy and correlation with 7 T subpial lesion number.

CONCLUSIONS

Subpial lesions are better visualized on IR-SWIET compared with other 3 T methods. A 3 T protocol combining IR-SWIET with MP2RAGE, in which leukocortical lesions are well seen, improves cortical lesion visualization over existing approaches. Therefore, IR-SWIET may enable improved MS diagnostic specificity and a better understanding of the clinical implications of cortical demyelination.

Cortical thickness and surface area of left anterior temporal areas affects processing of phonological cues to morphosyntax

Lack of methods to experimentally assess the perceptual processing of sound features and allow one to measure differences in phonological proficiency has been a limitation for speech processing studies in native speakers. Tonal features associated with Swedish word-stems, word accents, which cue grammatical suffixes, constitute, however, such sound features that can be exploited to generate measures of reliance on morphosyntactically relevant phonological information during word processing. Specifically, there is a natural variance between native speakers in response time (RT) difference between phonologically valid and invalid word accent-suffix combinations that can be used to quantify perceptual phonological proficiency. This study uses ultra-high field magnetic resonance imaging (MRI) to investigate word accents as phonological cues to morphosyntactic meaning. The study adds to the understanding of the neural basis for both morphosyntactically relevant phonological cues by reporting correlations between differences in listeners' RT for validly and invalidly cued suffixes and cortical thickness in left anterior and middle temporal gyrus, and the left anterior superior temporal sulcus as well as cortical surface area in the left middle and inferior temporal gyri. The cortical areas studied are known constituents of the ventral speech processing stream, necessary for word and phrase recognition.

High spatiotemporal vessel-specific hemodynamic mapping with multi-echo single-vessel fMRI

High-resolution fMRI enables noninvasive mapping of the hemodynamic responses from individual penetrating vessels in animal brains. Here, a 2D multi-echo single-vessel fMRI (MESV-fMRI) method has been developed to map the fMRI signal from arterioles and venules with a 100 ms sampling rate at multiple echo times (TE, 3-30 ms) and short acquisition windows (<1 ms). The T₂*-weighted signal shows the increased extravascular effect on venule voxels as a function of TE. In contrast, the arteriole voxels show an increased fMRI signal with earlier onset than venules voxels at the short TE (3 ms) with increased blood inflow and volume effects. MESV-fMRI enables vessel-specific T2* mapping and presents T2*-based fMRI time courses with higher contrast-to-noise ratios (CNRs) than the T2*-weighted fMRI signal at a given TE. The vessel-specific T2* mapping also allows semi-quantitative estimation of the oxygen saturation levels (Y) and their changes (ΔY) at a given blood volume fraction upon neuronal activation. The MESV-fMRI method enables vessel-specific T2* measurements with high spatiotemporal resolution for better modeling of the fMRI signal based on the hemodynamic parameters.