Ultra-high Field Magnetic Resonance Imaging Research Articles

Segmentation and quantification of venous structures and perivascular spaces in the thalamus in epilepsy using 7 Tesla MRI

Background and purposeEpilepsy is a complex neurological disorder affecting 50 million people worldwide. Persistent seizures may correlate with neural network, microstructural, and vascular changes within the thalamus. These thalamic changes may result from seizure activity or broader alterations involving neuronal vasculature and neuroinflammatory processes linked to glymphatic drainage. Improved resolution with Ultra-high field (UHF) magnetic resonance imaging (MRI) may be useful in identifying possible thalamic vascular abnormalities not otherwise detectable at lower field strengths. Materials and methodsWe outline a novel method which leverages UHF neuroimaging for detection and quantification of vessels and perivascular spaces (PVS) within the thalamus in 25 epilepsy patients and 16 controls, to uncover possible underlying imaging biomarkers of epilepsy. In our analysis, we optimize a MATLAB-based Frangi-based detection tool called Perivascular Space Semi-Automated Segmentation (PVSSAS) to detect thalamic PVSs, and additionally use a second Frangi-based segmentation tool method to automate detection of vascular structures in the thalamus. The resulting PVS and vessel masks were used to quantify differences in the number of vessels, PVS, overlaps, and number of PVS overlaps per vessel detected between groups, using a Hessian detection filter linked on an 18-connected network. ResultsWe found significantly more thalamic PVS (p = 0.0307) and a significant increase in the number of thalamic vessels (p = 0.038) in patients compared to controls. ConclusionHere we have developed a novel process which leverages UHF MRI to quantify and detect thalamic vessels and PVS that may provide a potential neuroimaging biomarker of epilepsy. Statement of SignificanceWe use 7T, ultra-high field MRI and employed an innovative combination of semi-automated perivascular space segmentation and automated vessel segmentation to visualize and quantify vessels and perivascular spaces (PVS) within the thalamus, a highly cited region of interest in epilepsy. To our knowledge, this is the first study to semi-automatically visualize and segment PVS in the thalamus and automatically detect thalamic vessels. We uncovered detectable differences in thalamic vasculature and PVS. These findings suggests that increases in the number of thalamic PVS and vessels may be a potential neuroimaging biomarker in epilepsy. This tool may be useful in the detection of subtle vascular changes in other regions of the brain related to epilepsy or can be employed in other neurological conditions.

Toward hippocampal volume measures on ultra-high field magnetic resonance imaging: a comprehensive comparison study between deep learning and conventional approaches.

The hippocampus is a complex brain structure that plays an important role in various cognitive aspects such as memory, intelligence, executive function, and path integration. The volume of this highly plastic structure is identified as one of the most important biomarkers of specific neuropsychiatric and neurodegenerative diseases. It has also been extensively investigated in numerous aging studies. However, recent studies on aging show that the performance of conventional approaches in measuring the hippocampal volume is still far from satisfactory, especially in terms of delivering longitudinal measures from ultra-high field magnetic resonance images (MRIs), which can visualize more boundary details. The advancement of deep learning provides an alternative solution to measuring the hippocampal volume. In this work, we comprehensively compared a deep learning pipeline based on nnU-Net with several conventional approaches including Freesurfer, FSL and DARTEL, for automatically delivering hippocampal volumes: (1) Firstly, we evaluated the segmentation accuracy and precision on a public dataset through cross-validation. Results showed that the deep learning pipeline had the lowest mean (L = 1.5%, R = 1.7%) and the lowest standard deviation (L = 5.2%, R = 6.2%) in terms of volume percentage error. (2) Secondly, sub-millimeter MRIs of a group of healthy adults with test-retest 3T and 7T sessions were used to extensively assess the test-retest reliability. Results showed that the deep learning pipeline achieved very high intraclass correlation coefficients (L = 0.990, R = 0.986 for 7T; L = 0.985, R = 0.983 for 3T) and very small volume percentage differences (L = 1.2%, R = 0.9% for 7T; L = 1.3%, R = 1.3% for 3T). (3) Thirdly, a Bayesian linear mixed effect model was constructed with respect to the hippocampal volumes of two healthy adult datasets with longitudinal 7T scans and one disease-related longitudinal dataset. It was found that the deep learning pipeline detected both the subtle and disease-related changes over time with high sensitivity as well as the mild differences across subjects. Comparison results from the aforementioned three aspects showed that the deep learning pipeline significantly outperformed the conventional approaches by large margins. Results also showed that the deep learning pipeline can better accommodate longitudinal analysis purposes.

Disparities in Research Participation within a Multi‐Racial SARS‐CoV‐2 Cohort for Evaluation of Ultrahigh Field (7T) MRI and Clinical Precursors of Alzheimer’s Disease and Related Dementias

AbstractBackgroundThe COVID‐19 pandemic has disproportionately affected ethno‐racial minority populations and people with greater social deprivation. It is unknown whether such disparities influence research participation for investigations of long‐term neuro‐cognitive effects of SARS‐CoV‐2 infection.MethodAcross 3 US and 1 UK sites, we are enrolling a multi‐racial cohort of SARS‐CoV‐2 infected individuals and age, sex, race‐matched non‐infected controls. Utilizing harmonized protocols for cognitive assessments and 7‐Tesla MRI, we aim to provide ultra‐high‐field data on natural history of COVID‐19 driven microstructural and microvascular cerebral changes and associated cognitive trajectories. We will also compare the imaging markers to those observed in an existing cohort of early onset Alzheimer’s Disease and Related Dementias (ADRD). We analyzed screening and enrollment data to determine potential age, sex, race, ethnicity, and social deprivation disparities in research participation. We derived address‐based Area Deprivation Index (ADI) (scale 1 ‐10), with higher ADI indicating greater deprivation. Logistic regression models were fit to evaluate associates of non‐response and refusal. Odds Ratios (OR) and 95% confidence intervals (CI) are reported.ResultOver a 11‐month period, at a single US site, a total of 1,046 SARS‐CoV‐2 infected people and their controls were contacted, and 379 (36.2%) responded. In univariable analyses, non‐response was associated with younger age, male sex, non‐White race, and higher ADI (Table 1). In the fully adjusted model, non‐White race was independently associated with higher likelihood of non‐response [OR (CI) for Black vs. White: 1.49 (1.04, 2.12) and for Asian vs. White: 1.88 (1.28, 2.76)]., Independent of race, higher ADI was also associated with likelihood of non‐response (Table 2 and Figure 1). Among the responders, 228 (60.2%) refused. Although, no socio‐demographic factors were significantly associated with likelihood of refusal, the point estimates in the fully adjusted model suggest potential racial disparities in providing consent (Tables 1 and 2). Aggregated data from all sites will be presented.ConclusionIt is imperative to recognize and mitigate persistent disparities in the COVID‐19 pandemic, particularly pertaining to participation in long‐COVID research. Mechanisms of such persistent disparities need to be studied in context of cultures, beliefs, access, and clinical factors.

Evaluation of coaxial dipole antennas as transceiver elements of human head array for ultra-high field MRI at 9.4T.

The aim of this work is to evaluate a new eight-channel transceiver (TxRx) coaxial dipole array for imaging of the human head at 9.4T developed to improve specific absorption rate (SAR) performance, and provide for a more compact and robust alternative to the state-of-the art dipole arrays. First, the geometry of a single coaxial element was optimized to minimize peak SAR and sensitivity to the load variation. Next, a multi-tissue voxel model was used to numerically simulate a TxRx array coil that consisted of eight coaxial dipoles with the optimal configuration. Finally, we compared the developed array to other human head dipole arrays. Results of numerical simulations were verified on a bench and in the scanner including in vivo measurements on a healthy volunteer. The developed eight-element coaxial dipole TxRx array coil showed up to 1.1times higher SAR-efficiency than a similar in geometry folded-end and fractionated dipole array while maintaining whole brain coverage and low sensitivity of the resonance frequency to variation in the head size. As a proof of concept, we developed and constructed a prototype of a 9.4T (400 MHz) human head array consisting of eight TxRx coaxial dipoles. The developed array improved SAR-efficiency and provided for a more compact and robust alternative to the folded-end dipole design. To the best of our knowledge, this is the first example of using coaxial dipoles for human head MRI at ultra-high field.

Brainstem anatomy with 7-T MRI: in vivo assessment and ex vivo comparison

Background The brainstem contains grey matter nuclei and white matter tracts to be identified in clinical practice. The small size and the low contrast among them make their in vivo visualisation challenging using conventional magnetic resonance imaging (MRI) sequences at high magnetic field strengths. Combining higher spatial resolution, signal- and contrast-to-noise ratio and sensitivity to magnetic susceptibility (χ), susceptibility-weighted 7-T imaging could improve the assessment of brainstem anatomy.MethodsWe acquired high-resolution 7-T MRI of the brainstem in a 46-year-old female healthy volunteer (using a three-dimensional multi-echo gradient-recalled-echo sequence; spatial resolution 0.3 × 0.3 × 1.2 mm3) and in a brainstem sample from a 48-year-old female body donor that was sectioned and stained. Images were visually assessed; nuclei and tracts were labelled and named according to the official nomenclature.ResultsThis in vivo imaging revealed structures usually evaluated through light microscopy, such as the accessory olivary nuclei, oculomotor nucleus and the medial longitudinal fasciculus. Some fibre tracts, such as the medial lemniscus, were visible for most of their course. Overall, in in vivo acquisitions, χ and frequency maps performed better than T2*-weighted imaging and allowed for the evaluation of a greater number of anatomical structures. All the structures identified in vivo were confirmed by the ex vivo imaging and histology.ConclusionsThe use of multi-echo GRE sequences at 7 T allowed the visualisation of brainstem structures that are not visible in detail at conventional magnetic field and opens new perspectives in the diagnostic and therapeutical approach to brain disorders.Relevance statementIn vivo MR imaging at UHF provides detailed anatomy of CNS substructures comparable to that obtained with histology. Anatomical details are fundamentals for diagnostic purposes but also to plan a direct targeting for a minimally invasive brain stimulation or ablation.Key points• The in vivo brainstem anatomy was explored with ultrahigh field MRI (7 T).• In vivo T2*-weighted magnitude, χ, and frequency images revealed many brainstem structures.• Ex vivo imaging and histology confirmed all the structures identified in vivo.• χ and frequency imaging revealed more brainstem structures than magnitude imaging.Graphical

A hybrid 2D-FDTD/3D-MoM method used for the analysis of MRI RF coils

The design of radiofrequency (RF) coils is crucial for ultra-high field (UHF) magnetic resonance imaging (MRI) systems. To analyze RF coils, various numerical methods, such as finite-difference time-domain (FDTD) and method of moments (MoM), are usually adopted. In this paper, we present a novel hybrid approach that combines a two-dimensional (2D) FDTD with a three-dimensional (3D) MoM to analyze MRI RF problems. In our algorithm, the MoM is utilized for calculating the coil current, and FDTD is assigned for solving the electromagnetic (EM) fields in the imaging region. The hybrid method achieves superior efficiency and acceptable accuracy than using either method individually. To validate the hybrid method, we analyze an ellipse coil loaded with a uniform phantom and a realistic human head model, with the objective of tailoring the magnetic field intensity by adding a multilayer dielectric pad (DP). The results show an improvement in the magnetic field after optimizing the DP configuration. These simulation studies indicate the potential of the new numerical method for the design and analysis of RF systems for ultra-high field applications.

34 Verbal Memory as a Language Function: Phonological Processing Contributes to Word List Recall in Persons with Multiple Sclerosis

Objective:Verbal memory deficits are present in multiple sclerosis (MS), but neither inflammatory T2 lesion volume nor cerebral atrophy (generalized or localized hippocampal atrophy) fully explain disease-related verbal memory changes. Importantly, the hippocampus does not function in a vacuum; memory encoding and retrieval requires interactions between the hippocampus and cortical areas where information is processed and represented. Indeed, we have previously shown that lexical access speed (a language function assessed by rapid automatized naming) independently predicted delayed recall of verbal information (word list) for persons with MS, even when controlling for total learning. Informed by this work and recent ultra high field (7.0 Tesla) MRI research reporting high cortical lesion count in regions associated with phonological processing (e.g., plenum temporale, superior temporal gyrus), we assessed whether phonological processing independently explains verbal memory deficits in persons with MS.Participants and Methods:Analyses were performed on a clinical sample of persons with MS aged 18 to 59 years (n=60: 49 relapsing, 11 progressive). Word-list memory was assessed by the Hopkins Verbal Learning Test, Revised (HVLT-R), which yielded scores for Total Learning (TL) and Delayed Recall (DR). Phonological processing was assessed with WIAT-4 Phonemic Proficiency. WIAT-4 Sentence Repetition was utilized as a non-phonological language control task, and WIAT-4 Word Reading was administered to control for premorbid verbal ability. CANTAB Paired Associate Learning served as a nonverbal memory comparison. Performance on tasks was standardized using published age-adjusted norms. Primary analyses used partial correlations to assess relationships between Phonemic Proficiency and (a) HVLT-R TL and DR controlling for WIAT-4 Word Reading, and (b) HVLT-R DR controlling for WIAT-4 Word Reading and HVLT-R TL. To assess specificity to phonological processing, the same partial correlations assessed relationships between Sentence Repetition and HVLT-R variables, and between Phonemic Proficiency and nonverbal memory (CANTAB PAL).Results:When controlling for premorbid verbal ability, Phonemic Proficiency performance accounted for 7.8% of the variance in HVLT-R TL (rpartial=0.28, p=0.031) and 16% of the variance in HVLT-R DR (rpartial=0.40, p=0.002). Moreover, when additionally controlling for HVLT-R TL, Phonemic Proficiency still accounted for 10% of the variance in HVLT-R DR (r partial— 0.32, p=0.016). Showing specificity to phonological processing ability, performance on Sentence Repetition was not significantly related to HVLT-R DR when controlling for premorbid verbal ability (WIAT-4 Word Reading) and HVLT-R TL (rpartial=0.09, p=0.510). Showing specificity to verbal memory, neither Phonemic Proficiency nor Sentence Repetition performance were reliably related to CANTAB PAL for any variance in performance in nonverbal memory (Ps>0.9).Conclusions:Results suggest that language ability, specifically phonological processing, contributes to delayed recall of word lists independent of premorbid verbal ability and initial total learning scores in persons with MS. These findings demonstrate contributions of language ability to verbal memory and highlight the need for further research into language ability changes in persons with MS. This may have implications for verbal memory rehabilitation in MS.

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

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. 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. 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). 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. 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.

Effects of ultra-high field MRI environment on cognitive performance in healthy participants

IntroductionUltra-high field MRI (UHF MRI) is rapidly becoming an essential part of our toolbox within health care and research studies; therefore, we need to get a deeper understanding of the physiological effects of ultra-high field. This study aims to investigate the cognitive performance of healthy participants in a 7 T (T) MRI environment in connection with subjectively experienced effects. MethodsWe measured cognitive performance before and after a 1-h 7T MRI scanning session using a Digit Symbol Substitution Test (DSST) in 42 subjects. Furthermore, a computer-based survey regarding the subjectively experienced effects in connection with the MRI examination was distributed. Similarly, two DSSTs were also performed by a control group of 40 participants. ResultsEven though dizziness was the strongest sensory perception in connection to the MRI scanning, we did not find any correlation between dizziness and cognitive performance. Whilst the control group improved (p=<0.001) on their second DSST the MRI group showed no significant difference (p=0.741) in the DSST before and after MRI scanning. ConclusionTransient effect on cognition after undergoing MRI scanning can't be ruled out as the expected learning effect on the DSST was not observed. Implications for practiceIncreasing understanding of the possible adverse effects may guide operators in performing UHF MRI in a safe way and with person-centered care. Furthermore, it can guide researchers in setting up research protocols to minimize confounding factors in their fMRI studies due to the transient adverse effects of the UHF environment.

Early functional and morphological changes of calf muscles in delayed onset muscle soreness (DOMS) assessed with 7T MRI

BackgroundTo assess morphological and functional alterations of the skeletal muscle in exercise-induced delayed onset muscle soreness (DOMS) using 7 Tesla (T) magnetic resonance imaging (MRI). MethodsDOMS was induced in 16 volunteers performing an eccentric exercise protocol of the calf muscles of one randomized leg. 7 T MRI including T1w- (0.18×0.18×1mm3), T2w-images (0.2×0.2×2mm3), T2-maps (0.5×0.5×5mm3), and susceptibility weighted imaging (SWI, 0.7×0.7×0.7 mm3) were acquired at baseline, directly (t1) and 60 hours (t2) after the exercise. T2 signal intensity (SI), T2 values [ms], T1 SI and SWI were assessed in the medial (MG) and lateral gastrocnemius muscle (LG) and in the soleus muscle (SM). In addition, the serum creatine kinase (CK) activity, range of motion (ROM) of the ankle, calf circumference, and muscle soreness were assessed at each time point. ResultsDirectly after exercise (t1), T2 SI (p=0.04) and T2 values (p=0.03) increased significantly in the LG. No changes of SI and T2 values for MG and SM were present at t1. At t2, T2 SI and T2 values of LG (p=0.001, p=0.02) and MG (p=0.04, p=0.03) increased significantly compared to baseline. T1 SI did not change in any muscle at any time point. In SWI, no signs of intramuscular signal drop could be detected. Clinical parameters confirmed the induction of DOMS, with a significant increase of CK (p=0.03), muscle soreness (p<0.001), calf circumference (p=0.001), and respective a decrease of ROM (p=0.04). Conclusions7 T MRI has the potential to visualize microstructural muscle damage immediately after an exercise that induces DOMS. No changes in susceptibility which could, for example, reflect micro-hemorrhage, could be detected with SWI immediately after exercise or in DOMS. Ultra-high field MRI may potentially be used in sports medicine to monitor intramuscular structural changes, allowing for modification of training intensity or to implement appropriate therapeutic strategies.

Holmium (III)-doped multifunctional nanotheranostic agent for ultra-high-field magnetic resonance imaging-guided chemo-photothermal tumor therapy

Ultra-high-field (UHF) MRI has shown great advantages over low-field magnetic resonance imaging (MRI). Despite being the most commonly used MRI contrast agents, gadolinium chelates perform poorly in high magnetic fields, which significantly weakens their T1 intensity. In comparison, the rare element Holmium (Ho)-based nanoparticles (NPs) have demonstrated great potential as T2-weighted MRI contrast agents in UHF MRI due to their extremely short electron relaxation times (∼ 10−13s). In this study, a multifunctional nanotherapeutic probe was designed for UHF MRI-guided chemotherapy and photothermal therapy. The Ho (III)-doped mesoporous polydopamine (Ho-MPDA, HM) nanosphere was loaded with the chemotherapeutic drug mitoxantrone (MTO) and then coated with 4T1 cell membranes to enhance active targeting delivery to breast cancer. The prepared nanotherapeutic probe MTO@HMM@4T1 (HMM@T) exhibited good biocompatibility, high drug-loading capability and great potential as Ho (III)-based UHF MRI contrast agents. Moreover, the biodegradation of HMM@T in response to the intratumor pH and glutathione (GSH) promotes MTO release. Near-infrared (NIR) light irradiation of HM induced photothermal therapy and further enhanced drug release. Consequently, HMM@T effectively acted as an MRI-guided tumor-targeting chemo-photothermal therapy against 4T1 breast cancer. Statement of significanceUltra-high-field (UHF) MRI has shown great advantages over low-field magnetic resonance imaging (MRI). Although gadolinium chelates are the most commonly used MRI contrast agents in clinical practice, they exhibit a significantly decreased T1 relaxivity at UHF. Holmium exhibits outstanding UHF magnetic resonance capabilities in comparison with gadolinium chelates currently used in clinic. Herein, a theranostic nanodrug (HMM@T) was designed for UHF MRI-guided chemo-photothermal therapy. The nanodrug possessed remarkable UHF T2 MRI properties (r2 = 152.13 mM−1s−1) and high drug loading capability of 18.4 %. The biodegradation of HMM@T NPs under triple stimulations of pH, GSH, and NIR led to an efficient release of MTO in tumor microenvironment. Our results revealed the potential of a novel UHF MRI-guided multifunctional nanosystem in cancer treatment.

Safety and function of programmable ventriculo-peritoneal shunt valves: An in vitro 7 Tesla magnetic resonance imaging study.

The quantity of ultra-high field MRI neuroimaging studies has rapidly increased. This study tests function, safety, and image artifacts of two frequently implanted programmable ventriculo-peritoneal (VP) shunt valves in a 7T MRI system. All tests were performed using a whole-body 7T MRI system. Three proGAV 2.0 and 3 CODMAN CERTAS® Plus programmable VP-shunt valves were tested in three steps. 1) Deflection angle tests close to the bore opening at the location of a static magnetic field gradient of 3-5 T/m. 2) Valves were fixed on a spherical phantom in 3 positions (a. lateral, b. cranial, c. cranial with 22.5° tilt anteriorly) and assessed for keeping the programmed pressure setting and reprogrammability. 3) Valves were fixed on the phantom and positioned lateral in a radiofrequency head coil. MRI scans were performed for both models, including MPRAGE, GRE and SE sequences. Deflection angles were moderate (13°, 14°, 13°) for the proGAV valves and close to critical (43°, 43°, 41°) for the CODMAN valves at the test location. Taking a scaling factor of 2-3 for the maximum spatial magnetic field gradient accessible to a patient within the magnet bore into account renders both valves MR unsafe regarding ferromagnetic attraction. The proGAV valves kept the pressure settings in all positions and were reprogrammable in positions a. and b. In position c., reprogrammability was lost. The CODMAN valves changed their pressure setting and reprogrammability was lost in all positions. MR image signal homogeneity was unaltered in the phantom center, artifacts limit the assessability of structures in close vicinity to the valves. Both tested programmable VP-shunt valves are MR unsafe for 7T systems. Novel programming mechanisms using permanent magnets with sufficient magnetic coercivity or magnet-free mechanisms may allow the development of programmable VP-shunt valves that are conditional for 7T MR systems.

Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.

Different roles of response covariability and its attentional modulation in the sensory cortex and posterior parietal cortex

The covariability of neural responses in the neuron population is highly relevant to the information encoding. Cognitive processes, such as attention, are found to modulate the covariability in the visual cortex to improve information encoding, suggesting the computational advantage of covariability modulation in the neural system. However, is the covariability modulation a general mechanism for enhanced information encoding throughout the information processing pathway, or only adopted in certain processing stages, depending on the property of neural representation? Here, with ultrahigh-field MRI, we examined the covariability, which was estimated by noise correlation, in different attention states in the early visual cortex and posterior parietal cortex (PPC) of the human brain, and its relationship to the quality of information encoding. Our results showed that while attention decreased the covariability to improve the stimulus encoding in the early visual cortex, covariability modulation was not observed in the PPC, where covariability had little impact on information encoding. Further, attention promoted the information flow between the early visual cortex and PPC, with an apparent emphasis on a flow from high- to low-dimensional representations, suggesting the existence of a reduction in the dimensionality of neural representation from the early visual cortex to PPC. Finally, the neural response patterns in the PPC could predict the amplitudes of covariability change in the early visual cortex, indicating a top-down control from the PPC to early visual cortex. Our findings reveal the specific roles of the sensory cortex and PPC during attentional modulation of covariability, determined by the complexity and fidelity of the neural representation in each cortical region.

Manual segmentation of the paraventricular nucleus of the hypothalamus and the dorsal and ventral bed nucleus of stria terminalis using multimodal 7 Tesla structural MRI: probabilistic atlases for a stress-control triad

The paraventricular nucleus of the hypothalamus (PVN) is uniquely capable of proximal control over autonomic and neuroendocrine stress responses, and the bed nucleus of the stria terminalis (BNST) directly modulates PVN function, as well as playing an important role in stress control itself. The dorsal BNST (dBNST) is predominantly preautonomic, while the ventral BNST (vBNST) is predominantly viscerosensory, receiving dense noradrenergic signaling. Distinguishing the dBNST and vBNST, along with the PVN, may facilitate our understanding of dynamic interactions among these regions. T1-weighted MPRAGE and high resolution gradient echo (GRE) modalities were acquired at 7T. GRE was coregistered to MPRAGE and segmentations were performed in MRIcroGL based on their Atlas of the Human Brain depictions. The dBNST, vBNST and PVN were manually segmented in 25 participants; 10 images were rated by 2 raters. These segmentations were normalized and probabilistic atlases for each region were generated in MNI space, now available as resources for future research. We found moderate–high inter-rater reliability [n = 10; Mean Dice (SD); PVN = 0.69 (0.04); dBNST = 0.77 (0.04); vBNST = 0.62 (0.04)]. Probabilistic atlases were reverse normalized into native space for six additional participants that were segmented but not included in the original 25. We also found moderate to moderate–high reliability between the probabilistic atlases and manual segmentations [n = 6; Mean Dice (SD); PVN = 0.55 (0.12); dBNST = 0.60 (0.10); vBNST = 0.47 (0.12 SD)]. By isolating these hypothalamic and BNST subregions using ultra-high field MRI modalities, more specific delineations of these regions can facilitate greater understanding of mechanisms underlying stress-related function and psychopathology.

BAFF blockade in experimental autoimmune encephalomyelitis reduces inflammation in the meninges and synaptic and neuronal loss in adjacent brain regions

Multiple sclerosis (MS) has traditionally been viewed as a chronic inflammatory disease affecting the white matter of the central nervous system. However, over the past two decades, increasing evidence has highlighted the role of gray matter pathology in MS-related disability. Numerous studies have linked the presence of leptomeningeal inflammation to a more severe disease course, underscoring its potential importance as a driver of gray matter pathology in MS. The major components of leptomeningeal inflammation include T cells, B cells, macrophages, follicular dendritic cells, and plasma cells. Since BAFF [B cell-activating factor of the tumor necrosis factor (TNF) family] promotes B cell survival and maturation and is a co-stimulator of T cells, we used anti-BAFF antibody 10F4 as a BAFF antagonist to study its effect on meningeal inflammation and adjacent brain regions in a relapsing–remitting PLP-EAE (rr-EAE) model of multiple sclerosis in SJL/J mice. rr-EAE mice were treated either with anti-BAFF antibody 10F4 or with IgG control antibody. We performed ultra-high field (11.7 T) MRI to identify areas of meningeal inflammation and track them over time in both treatment groups. We also performed histopathological analysis in brain sections of these mice to study the effects of the BAFF antagonist on leptomeningeal inflammation, and hippocampal and cortical neurons and synapses. We observed that BAFF antagonist treatment reduced B cells, T cells, and myeloid cells in regions of meningeal inflammation. Additionally, we noted that BAFF treatment protected against EAE-induced synaptic and neuronal loss in the adjacent cortex and in the CA1, CA3, and dentate gyrus regions of the hippocampus likely due to its effects on meningeal inflammation.

Computational methods for the estimation of ideal current patterns in realistic human models.

To introduce a method for the estimation of the ideal current patterns (ICP) that yield optimal signal-to-noise ratio (SNR) for realistic heterogeneous tissue models in MRI. The ICP were calculated for different surfaces that resembled typical radiofrequency (RF) coil formers. We constructed numerical electromagnetic (EM) bases to accurately represent EM fields generated by RF current sources located on the current-bearing surfaces. Using these fields as excitations, we solved the volume integral equation and computed the EM fields in the sample. The fields were appropriately weighted to calculate the optimal SNR and the corresponding ICP. We demonstrated how to qualitatively use ICP to guide the design of a coil array to maximize SNR inside a head model. In agreement with previous analytic work, ICP formed large distributed loops for voxels in the middle of the sample and alternated between a single loop and a figure-eight shape for a voxel 3-cm deep in the sample's cortex. For the latter voxel, a surface quadrature loop array inspired by the shape of the ICP reached of the optimal SNR at 3T, whereas a single loop placed above the voxel reached only of the optimal SNR. At 7T, the performance of the two designs decreased to and , respectively, suggesting that loops could be suboptimal at ultra-high field MRI. ICP can be calculated for human tissue models, potentially guiding the design of application-specific RF coil arrays.

Capillary Flow-MRI: Quantifying Micron-Scale Cooperativity in Complex Dispersions.

Strongly confined flow of particulate fluids is encountered in applications ranging from three-dimensional (3D) printing to the spreading of foods and cosmetics into thin layers. When flowing in constrictions with gap sizes, w, within 102 times the mean size of particles or aggregates, d, structured fluids experience enhanced bulk velocities and inhomogeneous viscosities, as a result of so-called cooperative, or nonlocal, particle interactions. Correctly predicting cooperative flow for a wide range of complex fluids requires high-resolution flow imaging modalities applicable in situ to even optically opaque fluids. To this goal, we here developed a pressure-driven high-field magnetic resonance imaging (MRI) velocimetry platform, comprising a pressure controller connected to a capillary. Wall properties and diameter could be modified respectively as hydrophobic/hydrophilic, or within w ∼ 100-540 μm. By achieving a high spatial resolution of 9 μm, flow cooperativity length scales, ξ, down to 15 μm in Carbopol with d ∼ 2 μm could be quantified by means of established physical models with an accuracy of 13%. The same approach was adopted for a heterogeneous fat crystal dispersion (FCD) with d and ξ values up to an order of magnitude higher than those for Carbopol. We found that for strongly confined flow of Carbopol in the 100 μm capillary, ξ is independent of flow conditions. For the FCD, ξ increases with gap size and applied pressures over 0.25-1 bar. In both samples, nonlocal interactions span domains up to about 5-8 particles but, at the highest confinement degree explored, ∼8% for FCD, domains of only ∼2 particles contribute to cooperative flow. The developed flow-MRI platform is easily scalable to ultrahigh field MRI conditions for chemically resolved velocimetric measurements of, e.g., complex fluids with anisotropic particles undergoing alignment. Future potential applications of the platform encompass imaging extrusion under confinement during the 3D printing of complex dispersions or in in vitro vascular and perfusion studies.

Syn_SegNet: A Joint Deep Neural Network for Ultrahigh-Field 7T MRI Synthesis and Hippocampal Subfield Segmentation in Routine 3T MRI.

Precise delineation of hippocampus subfields is crucial for the identification and management of various neurological and psychiatric disorders. However, segmenting these subfields automatically in routine 3T MRI is challenging due to their complex morphology and small size, as well as the limited signal contrast and resolution of the 3T images. This research proposes Syn_SegNet, an end-to-end, multitask joint deep neural network that leverages ultrahigh-field 7T MRI synthesis to improve hippocampal subfield segmentation in 3T MRI. Our approach involves two key components. First, we employ a modified Pix2PixGAN as the synthesis model, incorporating self-attention modules, image and feature matching loss, and ROI loss to generate high-quality 7T-like MRI around the hippocampal region. Second, we utilize a variant of 3D-U-Net with multiscale deep supervision as the segmentation subnetwork, incorporating an anatomic weighted cross-entropy loss that capitalizes on prior anatomical knowledge. We evaluate our method on hippocampal subfield segmentation in paired 3T MRI and 7T MRI with seven different anatomical structures. The experimental findings demonstrate that Syn_SegNet's segmentation performance benefits from integrating synthetic 7T data in an online manner and is superior to competing methods. Furthermore, we assess the generalizability of the proposed approach using a publicly accessible 3T MRI dataset. The developed method would be an efficient tool for segmenting hippocampal subfields in routine clinical 3T MRI.

Brain MRI Biomarkers in Isolated Rapid Eye Movement Sleep Behavior Disorder: Where Are We? A Systematic Review.

The increasing number of MRI studies focused on prodromal Parkinson's Disease (PD) demonstrates a strong interest in identifying early biomarkers capable of monitoring neurodegeneration. In this systematic review, we present the latest information regarding the most promising MRI markers of neurodegeneration in relation to the most specific prodromal symptoms of PD, namely isolated rapid eye movement (REM) sleep behavior disorder (iRBD). We reviewed structural, diffusion, functional, iron-sensitive, neuro-melanin-sensitive MRI, and proton magnetic resonance spectroscopy studies conducted between 2000 and 2023, which yielded a total of 77 relevant papers. Among these markers, iron and neuromelanin emerged as the most robust and promising indicators for early neurodegenerative processes in iRBD. Atrophy was observed in several regions, including the frontal and temporal cortices, limbic cortices, and basal ganglia, suggesting that neurodegenerative processes had been underway for some time. Diffusion and functional MRI produced heterogeneous yet intriguing results. Additionally, reduced glymphatic clearance function was reported. Technological advancements, such as the development of ultra-high field MRI, have enabled the exploration of minute anatomical structures and the detection of previously undetectable anomalies. The race to achieve early detection of neurodegeneration is well underway.