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IntroductionLinking olfactory epithelium to the central nervous system are cranial nerve 1, the olfactory nerve, and cranial nerve “0,” and the nervus terminalis (NT). Since there is minimal expression of angiotensin-converting enzyme-2 (ACE-2) in the olfactory nerve, it is unclear how SARS-CoV-2 causes anosmia (loss of smell) and hypogeusia (reduction of taste). In animal models, NT expresses ACE-2 receptors, suggesting a possible SARS-CoV-2 viral entry site in humans. The purpose of this study was to determine whether ultra-high-field 7 T magnetic resonance imaging (MRI) could visualize the NT, olfactory bulbs (OB), and olfactory tract (OT) in healthy controls and COVID-19 anosmia or hypogeusia and to qualitatively assess for volume loss and T2 alterations.MethodsIn this study, 7 T MRI was used to evaluate the brain and olfactory regions in 45 COVID-19 patients and 29 healthy controls. Neuroimaging was qualitatively assessed by four board-certified neuroradiologists who were blinded to outcome assignments: for the presence or absence of NT; for OB, OT, and brain volume loss; and altered T2 signal, white matter T2 hyperintensities, microhemorrhages, enlarged perivascular spaces, and brainstem involvement.ResultsNT was identifiable in all COVID-19 patients and controls. T2 hyperintensity in the NT, OB, and OT in COVID-19 patients with anosmia or hypogeusia was statistically significant compared to controls and COVID-19 patients without anosmia or hypogeusia.DiscussionOn 7 T MRI, NT was radiographically identifiable, adjacent to OB and OT. In COVID-19 anosmia and hypogeusia, T2 hyperintensity of NT, OB, and OT was statistically significant compared to COVID-19 patients without anosmia or hypogeusia and controls. The NT may be a potential entry site for SARs-CoV-2 and may play a role in the pathophysiology of COVID-19 anosmia.

Diffusion magnetic resonance imaging (dMRI) allows for a non-invasive visualization and quantitative assessment of white matter architecture in the brain by characterizing restrictions on the random motion of water molecules. Ultra-high field MRI scanners, such as those operating at 7 Tesla (7T) or higher, can boost the signal-to-noise ratio (SNR) to improve dMRI compared with what is attainable at conventional field strengths such as 3T or 1.5T. However, wavelength effects at 7T cause reduced transmit magnetic field efficiency in the human brain, mainly in the posterior fossa, manifesting as signal dropouts in this region. Recently, we reported a simple approach of using a wireless radiofrequency (RF) surface array to improve transmit efficiency and signal sensitivity at 7T. In this study, we demonstrate the feasibility and effectiveness of the RF enhancer in improving in vivo dMRI at 7T. The electromagnetic simulation results demonstrated a 2.1-fold increase in transmit efficiency with the use of the RF enhancer. The experimental results similarly showed a 1.9-fold improvement in transmit efficiency and a 1.4-fold increase in normalized SNR. These improvements effectively mitigated signal dropouts in regions with inherently lower SNR, such as the cerebellum, resulting in a better depiction of principal fiber orientations and an enhanced visualization of extended tracts.

Background and purpose: Epilepsy 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 methods: We 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. Results: We 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. Conclusion: Here 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 Significance: We 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.

IntroductionAdvanced age is a significant factor in changes to brain physiology and cognitive functions. Recent research has highlighted the critical role of the gut microbiome in modulating brain functions during aging, which can be influenced by various factors such as apolipoprotein E (APOE) genetic variance, body mass index (BMI), diabetes, and dietary intake. However, the associations between the gut microbiome and these factors, as well as brain structural, vascular, and metabolic imaging markers, have not been well explored.MethodsWe recruited 30 community dwelling older adults between age 55-85 in Kentucky. We collected the medical history from the electronic health record as well as the Dietary Screener Questionnaire. We performed APOE genotyping with an oral swab, gut microbiome analysis using metagenomics sequencing, and brain structural, vascular, and metabolic imaging using MRI.ResultsIndividuals with APOE e2 and APOE e4 genotypes had distinct microbiota composition, and higher level of pro-inflammatory microbiota were associated higher BMI and diabetes. In contrast, calcium- and vegetable-rich diets were associated with microbiota that produced short chain fatty acids leading to an anti-inflammatory state. We also found that important gut microbial butyrate producers were correlated with the volume of the thalamus and corpus callosum, which are regions of the brain responsible for relaying and processing information. Additionally, putative proinflammatory species were negatively correlated with GABA production, an inhibitory neurotransmitter. Furthermore, we observed that the relative abundance of bacteria from the family Eggerthellaceae, equol producers, was correlated with white matter integrity in tracts connecting the brain regions related to language, memory, and learning.DiscussionThese findings highlight the importance of gut microbiome association with brain health in aging population and could have important implications aimed at optimizing healthy brain aging through precision prebiotic, probiotic or dietary interventions.

Abstract The hippocampus and amygdala limbic structures are critical to the etiology of major depressive disorder (MDD). However, there are no high-resolution characterizations of the role of their subregions in the whole brain network (connectome). Connectomic examination of these subregions can uncover disorder-related patterns that are otherwise missed when treated as single structures. 38 MDD patients and 40 healthy controls (HC) underwent anatomical and diffusion imaging using 7-Tesla MRI. Whole-brain segmentation was performed along with hippocampus and amygdala subregion segmentation, each representing a node in the connectome. Graph theory analysis was applied to examine the importance of the limbic subregions within the brain network using centrality features measured by node strength (sum of weights of the node’s connections), Betweenness (number of shortest paths that traverse the node), and clustering coefficient (how connected the node’s neighbors are to one another and forming a cluster). Compared to HC, MDD patients showed decreased node strength of the right hippocampus cornu ammonis (CA) 3/4, indicating decreased connectivity to the rest of the brain, and decreased clustering coefficient of the right dentate gyrus, implying it is less embedded in a cluster. Additionally, within the MDD group, the greater the embedding of the right amygdala central nucleus (CeA) in a cluster, the greater the severity of depressive symptoms. The altered role of these limbic subregions in the whole-brain connectome is related to diagnosis and depression severity, contributing to our understanding of the limbic system involvement in MDD and may elucidate the underlying mechanisms of depression.

BackgroundMajor depressive disorder (MDD) is a prevalent health problem with complex pathophysiology that is not clearly understood. Prior work has implicated the hippocampus in MDD, but how hippocampal subfields influence or are affected by MDD requires further characterization with high-resolution data. This will help ascertain the accuracy and reproducibility of previous subfield findings in depression as well as correlate subfield volumes with MDD symptom scores. The objective of this study was to assess volumetric differences in hippocampal subfields between MDD patients globally and healthy controls (HC) as well as between a subset of treatment-resistant depression (TRD) patients and HC using automatic segmentation of hippocampal subfields (ASHS) software and ultra-high field MRI.MethodsThirty-five MDD patients and 28 HC underwent imaging using 7-Tesla MRI. ASHS software was applied to the imaging data to perform automated hippocampal segmentation and provide volumetrics for analysis. An exploratory analysis was also performed on associations between symptom scores for diagnostic testing and hippocampal subfield volumes.ResultsCompared to HC, MDD and TRD patients showed reduced right-hemisphere CA2/3 subfield volume (p = 0.01, η2 = 0.31 and p = 0.3, η2 = 0.44, respectively). Additionally, negative associations were found between subfield volumes and life-stressor checklist scores, including left CA1 (p = 0.041, f2 = 0.419), left CA4/DG (p = 0.010, f2 = 0.584), right subiculum total (p = 0.038, f2 = 0.354), left hippocampus total (p = 0.015, f2 = 0.134), and right hippocampus total (p = 0.034, f2 = 0.110). Caution should be exercised in interpreting these results due to the small sample size and low power.ConclusionDetermining biomarkers for MDD and TRD pathophysiology through segmentation on high-resolution MRI data and understanding the effects of stress on these regions can enable better assessment of biological response to treatment selection and may elucidate the underlying mechanisms of depression.

IntroductionCoronavirus 2019 (COVID-19) is known to affect the central nervous system. Neurologic morbidity associated with COVID-19 is commonly attributed to sequelae of some combination of thrombotic and inflammatory processes. The aim of this retrospective observational study was to evaluate neuroimaging findings in hospitalized COVID-19 patients with neurological manifestations in cancer versus non-cancer patients, and in patients with versus without ventilatory support (with ventilatory support defined as including patients with intubation and noninvasive ventilation). Cancer patients are frequently in an immunocompromised or prothrombotic state with side effects from chemotherapy and radiation that may cause neurological issues and increase vulnerability to systemic illness. We wanted to determine whether neurological and/or neuroimaging findings differed between patients with and without cancer.MethodsEighty adults (44 male, 36 female, 64.5 ±14 years) hospitalized in the Mount Sinai Health System in New York City between March 2020 and April 2021 with reverse-transcriptase polymerase chain reaction-confirmed COVID-19 underwent magnetic resonance imaging (MRI) during their admissions. The cohort consisted of four equal subgroups based on cancer and ventilatory support status. Clinical and imaging data were acquired and analyzed.ResultsNeuroimaging findings included non-ischemic parenchymal T2/FLAIR signal hyperintensities (36.3%), acute/subacute infarcts (26.3%), chronic infarcts (25.0%), microhemorrhages (23.8%), chronic macrohemorrhages (10.0%), acute macrohemorrhages (7.5%), and encephalitis-like findings (7.5%). There were no significant differences in neuroimaging findings between cancer and non-cancer subgroups. Clinical neurological manifestations varied. The most common was encephalopathy (77.5%), followed by impaired responsiveness/coma (38.8%) and stroke (26.3%). There were significant differences between patients with versus without ventilatory support. Encephalopathy and impaired responsiveness/coma were more prevalent in patients with ventilatory support (p = 0.02). Focal weakness was more frequently seen in patients without ventilatory support (p = 0.01).DiscussionThis study suggests COVID-19 is associated with neurological manifestations that may be visible with brain imaging techniques such as MRI. In our COVID-19 cohort, there was no association between cancer status and neuroimaging findings. Future studies might include more prospectively enrolled systematically characterized patients, allowing for more rigorous statistical analysis.

Abstract 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.

Abstract Particulate respirators such as N95s are an essential component of personal protective equipment (PPE) for front-line workers. This study describes a rapid and effective UVC irradiation system that would facilitate the safe re-use of N95 respirators and provides supporting information for deploying UVC for decontamination of SARS-CoV-2 during the COVID-19 pandemic. To assess the inactivation potential of the proposed UVC germicidal device as a function of time by using 3 M 8211-N95 particulate respirators inoculated with SARS-CoV-2. A germicidal UVC device to deliver tailored UVC dose was developed and test coupons (2.5 cm2) of the 3 M-N95 respirator were inoculated with 106 plaque-forming units (PFU) of SARS-CoV-2 and were UV irradiated. Different exposure times were tested (0–164 s) by fixing the distance between the lamp and the test coupon to 15.2 cm while providing an exposure of at least 5.43 mWcm−2. Primary measure of outcome was titration of infectious virus recovered from virus-inoculated respirator test coupons after UVC exposure. Other measures included the method validation of the irradiation protocol, using lentiviruses (biosafety level-2 agent) and establishment of the germicidal UVC exposure protocol. An average of 4.38 × 103 PFU ml−1 (SD 772.68) was recovered from untreated test coupons while 4.44 × 102 PFU ml−1 (SD 203.67), 4.00 × 102 PFU ml−1 (SD 115.47), 1.56 × 102 PFU ml−1 (SD 76.98) and 4.44 × 101 PFU ml−1 (SD 76.98) was recovered in exposures 2, 6, 18 and 54 s per side respectively. The germicidal device output and positioning was monitored and a minimum output of 5.43 mW cm−2 was maintained. Infectious SARS-CoV-2 was not detected by plaque assays (minimal level of detection is 67 PFU ml−1) on N95 respirator test coupons when irradiated for 120 s per side or longer suggesting 3.5 log reduction in 240 s of irradiation, 1.3 J cm−2. A scalable germicidal UVC device to deliver tailored UVC dose for rapid decontamination of SARS-CoV-2 was developed. UVC germicidal irradiation of N95 test coupons inoculated with SARS-CoV-2 for 120 s per side resulted in 3.5 log reduction of virus. These data support the reuse of N95 particle-filtrate apparatus upon irradiation with UVC and supports use of UVC-based decontamination of SARS-CoV-2 during the COVID-19 pandemic.

The ventral tegmental area (VTA) is one of the major sources of dopamine in the brain and has been associated with reward prediction, error-based reward learning, volitional drive and anhedonia. However, precise anatomical investigations of the VTA have been prevented by the use of standard-resolution MRI, reliance on subjective manual tracings, and lack of quantitative measures of dopamine-related signal. Here, we combine ultra-high field 400 µm3 quantitative MRI with dopamine-related signal mapping, and a mixture of machine learning and supervised computational techniques to delineate the VTA in a transdiagnostic sample of subjects with and without depression and anxiety disorders. Subjects also underwent cognitive testing to measure intrinsic and extrinsic motivational tone. Fifty-one subjects were scanned in total, including healthy control (HC) and mood/anxiety (MA) disorder subjects. MA subjects had significantly larger VTA volumes compared to HC but significantly lower signal intensity within VTA compared to HC, indicating reduced structural integrity of the dopaminergic VTA. Interestingly, while VTA integrity did not significantly correlate with self-reported depression or anxiety symptoms, it was correlated with an objective cognitive measure of extrinsic motivation, whereby lower VTA integrity was associated with lower motivation. This is the first study to demonstrate a computational pipeline for detecting and delineating the VTA in human subjects with 400 μm3 resolution. We highlight the use of objective transdiagnostic measures of cognitive function that link neural integrity to behavior across clinical and non-clinical groups.

Abstract Background Trigeminal Neuralgia (TN) is a chronic neurological disease that is strongly associated with neurovascular compression (NVC) of the trigeminal nerve near its root entry zone. The trigeminal nerve at the site of NVC has been extensively studied but limbic structures that are potentially involved in TN have not been adequately characterized. Specifically, the hippocampus is a stress-sensitive region which may be structurally impacted by chronic TN pain. As the center of the emotion-related network, the amygdala is closely related to stress regulation and may be associated with TN pain as well. The thalamus, which is involved in the trigeminal sensory pathway and nociception, may play a role in pain processing of TN. The objective of this study was to assess structural alterations in the trigeminal nerve and subregions of the hippocampus, amygdala, and thalamus in TN patients using ultra-high field MRI and examine quantitative differences in these structures compared with healthy controls. Methods Thirteen TN patients and 13 matched controls were scanned at 7-Tesla MRI with high resolution, T1-weighted imaging. Nerve cross sectional area (CSA) was measured and an automated algorithm was used to segment hippocampal, amygdaloid, and thalamic subregions. Nerve CSA and limbic structure subnuclei volumes were compared between TN patients and controls. Results CSA of the posterior cisternal nerve on the symptomatic side was smaller in patients (3.75 mm2) compared with side-matched controls (5.77 mm2, p = 0.006). In TN patients, basal subnucleus amygdala volume (0.347 mm3) was reduced on the symptomatic side compared with controls (0.401 mm3, p = 0.025) and the paralaminar subnucleus volume (0.04 mm3) was also reduced on the symptomatic side compared with controls (0.05 mm3, p = 0.009). The central lateral thalamic subnucleus was larger in TN patients on both the symptomatic side (0.033 mm3) and asymptomatic side (0.035 mm3), compared with the corresponding sides in controls (0.025 mm3 on both sides, p = 0.048 and p = 0.003 respectively). The inferior and lateral pulvinar thalamic subnuclei were both reduced in TN patients on the symptomatic side (0.2 mm3 and 0.17 mm3 respectively) compared to controls (0.23 mm3, p = 0.04 and 0.18 mm3, p = 0.04 respectively). No significant findings were found in the hippocampal subfields analyzed. Conclusions These findings, generated through a highly sensitive 7 T MRI protocol, provide compelling support for the theory that TN neurobiology is a complex amalgamation of local structural changes within the trigeminal nerve and structural alterations in subnuclei of limbic structures directly and indirectly involved in nociception and pain processing.

Abstract Introduction Emerging evidence in depression suggests that blood–brain barrier (BBB) breakdown and elevated inflammatory cytokines in states of persistent stress or trauma may contribute to the development of symptoms. Signal‐to‐noise ratio afforded by ultra‐high field MRI may aid in the detection of maladaptations of the glymphatic system related to BBB integrity that may not be visualized at lower field strengths. Methods We investigated the link between glymphatic neuroanatomy via perivascular spaces (PVS) and trauma experience in patients with major depressive disorder (MDD) and in healthy controls using 7‐Tesla MRI and a semi‐automated segmentation algorithm. Results After controlling for age and gender, the number of traumatic events was correlated with total PVS volume in MDD patients (r = 0.50, p = .028) and the overall population (r = 0.34, p = .024). The number of traumatic events eliciting horror was positively correlated with total PVS volume in MDD patients (r = 0.50, p = .030) and the overall population (r = 0.32, p = .023). Age correlated positively with PVS count, PVS total volume, and PVS density in all participants (r > 0.35, p

While COVID-19 is primarily considered a respiratory disease, it has been shown to affect the central nervous system. Mounting evidence shows that COVID-19 is associated with neurological complications as well as effects thought to be related to neuroinflammatory processes. Due to the novelty of COVID-19, there is a need to better understand the possible long-term effects it may have on patients, particularly linkage to neuroinflammatory processes. Perivascular spaces (PVS) are small fluid-filled spaces in the brain that appear on MRI scans near blood vessels and are believed to play a role in modulation of the immune response, leukocyte trafficking, and glymphatic drainage. Some studies have suggested that increased number or presence of PVS could be considered a marker of increased blood-brain barrier permeability or dysfunction and may be involved in or precede cascades leading to neuroinflammatory processes. Due to their size, PVS are better detected on MRI at ultrahigh magnetic field strengths such as 7 Tesla, with improved sensitivity and resolution to quantify both concentration and size. As such, the objective of this prospective study was to leverage a semi-automated detection tool to identify and quantify differences in perivascular spaces between a group of 10 COVID-19 patients and a similar subset of controls to determine whether PVS might be biomarkers of COVID-19-mediated neuroinflammation. Results demonstrate a detectable difference in neuroinflammatory measures in the patient group compared to controls. PVS count and white matter volume were significantly different in the patient group compared to controls, yet there was no significant association between PVS count and symptom measures. Our findings suggest that the PVS count may be a viable marker for neuroinflammation in COVID-19, and other diseases which may be linked to neuroinflammatory processes.

Purpose: Epilepsy patients exhibit morphological differences on neuroimaging compared to age-matched healthy controls, including cortical and sub-cortical volume loss and altered gray-white matter ratios. The objective was to develop a model of normal aging using the 7T MRIs of healthy controls. This model can then be used to determine if the changes in epilepsy patients resemble the changes seen in aging, and potentially give a marker for the severity of those changes. Methods: Sixty-nine healthy controls (24F/45M, mean age 36.5 ± 10.5 years) and forty-four epilepsy patients (24F/20M, 33.2 ± 9.9 years) non-lesional at 3T were scanned with volumetric T1-MPRAGE at 7T. These images were segmented and quantified using FreeSurfer. A linear regression-based model trained on healthy controls was developed to predict ages using derived imaging features among the epilepsy patient cohort. The model used 114 features with significant linear correlation with age. Results: The regression-based model estimated brain age with mean absolute error (MAE) of 6.6 years among controls. Comparable prediction accuracy of 6.9 years MAE was seen epilepsy patients. T-test of mean absolute error showed no difference in the prediction accuracy with controls and epilepsy patients (p = 0.68). However, average signed error showed elevated (+5.0 years, p = 0.0007) predicted age differences (PAD; brain-PAD=, predicted minus biological age) among epilepsy patients. Morphological metrics in the medial temporal lobe were major contributors to PAD. Additionally, patients with seizure frequency greater than once a week showed significantly elevated brain-PAD (+8.2 ± 5.3 years, n = 13) compared to patients with lower seizure frequency (3.7 ± 6.5 years, n = 31, p = 0.033). Major conclusions: Morphological patterns suggestive of premature aging were observed in non-lesional epilepsy patients vs. controls and in high seizure frequency patients vs. low frequency patients. Modeling brain age with 7T MRI may provide a sensitive imaging marker to assess the differential effects of the aging process in diseases such as epilepsy.

While the etiology of hippocampal sclerosis (HS) in epilepsy patients remains unknown, distinct phenotypes of hippocampal subfield atrophy have been associated with different clinical presentations and surgical outcomes. The advent of novel techniques including ultra-high field 7T magnetic resonance imaging (MRI) and automated subfield volumetry have further enabled detection of hippocampal pathology in patients with epilepsy, however, studies combining both 7T MRI and automated segmentation in epilepsy patients with normal-appearing clinical MRI are limited. In this study, we present a novel application of the automated segmentation of hippocampal subfields (ASHS) software to determine subfield volumes of the CA1, CA2/3, CA4/DG, and the subiculum using ultra high-field 7T MRI scans, including T1-weighted MP2RAGE and T2-TSE sequences, in 27 patients with either mesial temporal lobe epilepsy (mTLE) or neocortical epilepsy (NE) compared to age and gender matched healthy controls. We found that 7T improved visualization of structural abnormalities not otherwise seen on clinical strength MRIs in patients with unilateral mTLE. Additionally, our automated segmentation algorithm was able to detect structural differences in volume and asymmetry across hippocampal subfields in unilateral mTLE patients compared to controls. Specifically, amongst unilateral mTLE patients with longer disease durations, volume loss was observed in the ipsilateral CA1 and CA2/3 subfields and contralateral CA1. There were no differences in subfield volumes in patients with NE compared to controls. We report the first application of 7T with automated segmentation to characterize the relationship between disease duration burden and asymmetry across specific hippocampal subfields in this population. Disease duration was found to have a statistically significant positive relationship with subfield asymmetry within the unilateral mTLE cohort. These findings highlight the ability of 7T MRI and automated segmentation to provide novel qualitative and quantitative information in epilepsy patients who are otherwise MRI-negative at clinical field strengths.

The importance of assessing neurochemical processes in the cetacean brain as a tool for monitoring their cognitive health and to indirectly model human neurodegenerative conditions is increasingly evident, although available data are largely semiquantitative. High-resolution MRI for post-mortem brains and stereology allow for quantitative assessments of the cetacean brain. In this study, we scanned two brains of bottlenose dolphins in a 7-Tesla (7T) MR scanner and assessed the connectivity of the inferior colliculi and ventral cochlear nuclei using diffusion tensor imaging (DTI). Serial thick sections were investigated stereologically in one of the dolphins to generate rigorous quantitative estimates of identifiable cell types according to their morphology and expression of molecular markers, yielding reliable cell counts with most coefficients of error

Importance: A significant limitation of many neuroimaging studies examining mild traumatic brain injury (mTBI) is the unavailability of pre-injury data.Objective: We therefore aimed to utilize pre-injury ultra-high field brain MRI and compare a collection of neuroimaging metrics pre- and post-injury to determine mTBI related changes and evaluate the enhanced sensitivity of high-resolution MRI.Design: In the present case study, we leveraged multi-modal 7 Tesla MRI data acquired at two timepoints prior to mTBI (23 and 12 months prior to injury), and at two timepoints post-injury (2 weeks and 8 months after injury) to examine how a right parietal bone impact affects gross brain structure, subcortical volumetrics, microstructural order, and connectivity.Setting: This research was carried out as a case investigation at a single primary care site.Participants: The case participant was a 38-year-old female selected for inclusion based on a mTBI where a right parietal impact was sustained.Main outcomes: The main outcome measurements of this investigation were high spatial resolution structural brain metrics including volumetric assessment and connection density of the white matter connectome.Results: At the first scan timepoint post-injury, the cortical gray matter and cerebral white matter in both hemispheres appeared to be volumetrically reduced compared to the pre-injury and subsequent post-injury scans. Connectomes produced from whole-brain diffusion-weighted probabilistic tractography showed a widespread decrease in connectivity after trauma when comparing mean post-injury and mean pre-injury connection densities. Findings of reduced fractional anisotropy in the cerebral white matter of both hemispheres at post-injury time point 1 supports reduced connection density at a microstructural level. Trauma-related alterations to whole-brain connection density were markedly reduced at the final scan timepoint, consistent with symptom resolution.Conclusions and Relevance: This case study investigates the structural effects of traumatic brain injury for the first time using pre-injury and post-injury 7 Tesla MRI longitudinal data. We report findings of initial volumetric changes, decreased structural connectivity and reduced microstructural order that appear to return to baseline 8 months post-injury, demonstrating in-depth metrics of physiological recovery. Default mode, salience, occipital, and executive function network alterations reflect patient-reported hypersomnolence, reduced cognitive processing speed and dizziness.

The objective is to quantitatively assess surgical outcomes in epilepsy patients who underwent scanning at 7T MRI whose lesions were undetectable at conventional field strengths (1.5T/3T).16 patients who underwent an initial 1.5T/3T scan that was marked as non-lesional by a neuroradiologist and were candidates for epilepsy surgery were scanned at 7T. The 7T findings were evaluated by an expert neuroradiologist blinded to the suspected seizure onset zone (sSOZ). The relation of the neuroradiologist’s findings compared with the sSOZ was classified as non-definite (no 7T lesion or lesion of no epileptogenic significance, or lesion of epileptogenic potential which localizes to the patient’s sSOZ but is not the definitive cause), or definite (7T lesion of epileptogenic potential that highly localizes to the sSOZ and is confirmed through surgical intervention).. Each patient underwent neurosurgical intervention and postoperative Engel outcomes were obtained through retrospective chart review by an epileptologist.Of the 16 patients, 7 had imaging findings of definite epileptogenic potential at 7T while 9 had non-definite imaging findings. 15 out of 16 patients had Engel I, II, or III outcomes indicating worthwhile improvement. Patients with definite lesion status achieved Engel I surgical outcomes at higher rates (57.1%) than patients with non-definite lesion status (33.3%). Patients with normal clinical diagnostic scans at lower field strengths who have definite radiological findings on 7T corresponding to the sSOZ may experience worthwhile improvement from surgical intervention.

Accurate quantification and characterization of atherosclerotic plaques with MRI requires high spatial resolution acquisitions with excellent image quality. The intrinsically better signal-to-noise ratio (SNR) at high-field clinical 7T compared to the widely employed lower field strengths of 1.5 and 3T may yield significant improvements to vascular MRI. However, 7T atherosclerosis imaging also presents specific challenges, related to local transmit coils and B1 field inhomogeneities, which may overshadow these theoretical gains. We present the development and evaluation of 3D, black-blood, ultra-high resolution vascular MRI on clinical high-field 7T in comparison lower-field 3T. These protocols were applied for in vivo imaging of atherosclerotic rabbits, which are often used for development, testing, and validation of translatable cardiovascular MR protocols. Eight atherosclerotic New Zealand White rabbits were imaged on clinical 7T and 3T MRI scanners using 3D, isotropic, high (0.63 mm3) and ultra-high (0.43 mm3) spatial resolution, black-blood MR sequences with extensive spatial coverage. Following imaging, rabbits were sacrificed for validation using fluorescence imaging and histology. Image quality parameters such as SNR and contrast-to-noise ratio (CNR), as well as morphological and functional plaque measurements (plaque area and permeability) were evaluated at both field strengths. Using the same or comparable imaging parameters, SNR and CNR were in general higher at 7T compared to 3T, with a median (interquartiles) SNR gain of +40.3 (35.3-80.1)%, and a median CNR gain of +68.1 (38.5-95.2)%. Morphological and functional parameters, such as vessel wall area and permeability, were reliably acquired at 7T and correlated significantly with corresponding, widely validated 3T vessel wall MRI measurements. In conclusion, we successfully developed 3D, black-blood, ultra-high spatial resolution vessel wall MRI protocols on a 7T clinical scanner. 7T imaging was in general superior to 3T with respect to image quality, and comparable in terms of plaque area and permeability measurements.

The locus coeruleus (LC) has a long-established role in the attentional and arousal response to threat, and in the emergence of pathological anxiety in pre-clinical models. However, human evidence of links between LC function and pathological anxiety has been restricted by limitations in discerning LC with current neuroimaging techniques. We combined ultra-high field 7-Tesla and 0.4 × 0.4 × 0.5 mm quantitative MR imaging with a computational LC localization and segmentation algorithm to delineate the LC in 29 human subjects including subjects with and without an anxiety or stress-related disorder. Our automated, data-driven LC segmentation algorithm provided LC delineations that corresponded well with postmortem anatomic definitions of the LC. There was variation of LC size in healthy subjects (125.7 +/- 59.3 mm3), which recapitulates histological reports. Patients with an anxiety or stress-related disorder had larger LC compared to controls (Cohen's d = 1.08, p = 0.024). Larger LC was additionally associated with poorer attentional and inhibitory control and higher anxious arousal (FDR-corrected p's

Patients with major depressive disorder (MDD) exhibit higher levels of rumination, i.e., repetitive thinking patterns and exaggerated focus on negative states. Rumination is known to be associated with the cortical midline structures / default mode network (DMN) region activity, although the brain network topological organization underlying rumination remains unclear. Implementing a graph theoretical analysis based on ultra-high field 7-Tesla functional MRI data, we tested whether whole brain network connectivity hierarchies during resting state are associated with rumination in a dimensional manner across 20 patients with MDD and 20 healthy controls. Applying this data-driven approach we found a significant correlation between rumination tendency and connectivity strength degree of the right precuneus, a key node of the DMN. In order to interrogate this region further, we then applied the Dependency Network Analysis (DEPNA), a recently developed method used to quantify the connectivity influence of network nodes. This revealed that rumination was associated with lower connectivity influence of the left medial orbito-frontal cortex (MOFC) cortex on the right precuneus. Lastly, we used an information theory entropy measure that quantifies the cohesion of a network's correlation matrix. We show that subjects with higher rumination scores exhibit higher entropy levels within the DMN i.e. decreased overall connectivity within the DMN. These results emphasize the general DMN involvement during self-reflective processing related to maladaptive rumination in MDD. This work specifically highlights the impact of the MOFC on the precuneus, which might serve as a target for clinical neuromodulation treatment. Keywords: Default mode network, Depression, Entropy, Graph Theory, High-field MRI, Precuneus

ObjectiveTo compare by 7 Tesla (7T) magnetic resonance imaging (MRI) in patients with focal epilepsy who have non-lesional clinical MRI scans with healthy controls.Methods37 patients with focal epilepsy, based on clinical and electroencephalogram (EEG) data, with non-lesional MRIs at clinical field strengths and 21 healthy controls were recruited for the 7T imaging study. The MRI protocol consisted of high resolution T1-weighted, T2-weighted and susceptibility weighted imaging sequences of the entire cortex. The images were read by two neuroradiologists, who were initially blind to clinical data, and then reviewed a second time with knowledge of the seizure onset zone.ResultsA total of 25 patients had findings with epileptogenic potential. In five patients these were definitely related to their epilepsy, confirmed through surgical intervention, in three they co-localized to the suspected seizure onset zone and likely caused the seizures. In seven patients the imaging findings co-localized to the suspected seizure onset zone but were not the definitive cause, and ten had cortical lesions with epileptogenic potential that did not localize to the suspected seizure onset zone. There were multiple other findings of uncertain significance found in both epilepsy patients and healthy controls. The susceptibility weighted imaging sequence was instrumental in guiding more targeted inspection of the other structural images and aiding in the identification of cortical lesions.SignificanceInformation revealed by the improved resolution and enhanced contrast provided by 7T imaging is valuable in noninvasive identification of lesions in epilepsy patients who are non-lesional at clinical field strengths.