BrainAgeNeXt: Advancing Brain Age Modeling for Individuals with Multiple Sclerosis.

Aging is associated with structural brain changes, cognitive decline, and neurodegenerative diseases. Brain age, an imaging biomarker sensitive to deviations from healthy aging, offers insights into structural aging variations and is a potential prognostic biomarker in neurodegenerative conditions. This study introduces BrainAgeNeXt, a novel convolutional neural network inspired by the MedNeXt framework, designed to predict brain age from T1-weighted magnetic resonance imaging (MRI) scans. BrainAgeNeXt was trained and validated on 11,574 MRI scans from 33 private and publicly available datasets of healthy volunteers, aged 5 to 95 years, imaged with 3T and 7T MRI. Performance was compared against three state-of-the-art brain age prediction methods. BrainAgeNeXt achieved a mean absolute error (MAE) of 2.78 ± 3.64 years, lower than the compared methods (MAE = 3.55, 3.59, and 4.16 years, respectively). We tested all methods also across different levels of image quality, and BrainAgeNeXt performed well even with motion artifacts and less common 7T MRI data. In three longitudinal multiple sclerosis (MS) cohorts (273 individuals), brain age was, on average, 4.21 ± 6.51 years greater than chronological age. Longitudinal analysis indicated that brain age increased by 1.15 years per chronological year in individuals with MS (95% CI = [1.05, 1.26]). Moreover, in early MS, individuals with worsening disability had a higher annual increase in brain age compared to those with stable clinical assessments (1.24 vs. 0.75, p < 0.01). These findings suggest that brain age is a promising prognostic biomarker for MS progression and potentially a valuable endpoint for clinical trials.

Portable UV-C Device to Treat High Flow of Infectious Aerosols Generated during Clinical Respiratory Care.

Respiratory interventions including noninvasive ventilation, continuous positive airway pressure and high-flow nasal oxygen generated infectious aerosols may increase risk of airborne disease (SARS-CoV-2, influenza virus) transmission to healthcare workers. We developed/tested a prototype portable UV-C254 device to sterilize high flows of viral-contaminated air from a simulated patient source at airflow rates of up to 100 l/m. Our device consisted of a central quartz tube surrounded 6 high-output UV-C254 lamps, within a larger cylinder allowing recirculation past the UV-C254 lamps a second time before exiting the device. Testing was with nebulized A/PR/8/34 (H1N1) influenza virus. RNA extraction and qRT-PCR showed virus transited through the prototype. Turning on varying numbers of lamps controlled the dose of UVC. Viability experiments at low, medium and high (100 l/min) flows of contaminated gas were conducted with 6, 4, 2 and 1 lamp activated (single-pass and recirculation were tested). Our data show 5-log reduction in particle forming units from a single lamp (single- pass and recirculated conditions) at high and low flows. UVC dose at 100 l/m was calculated at 11.6 mJ/cm2 single pass and 104 mJ/cm2 recirculated. The protype device shows high efficacy in killing nebulized influenza virus in a high flow of contaminated air.

Advanced neuroimaging of the trigeminal nerve and the whole brain in trigeminal neuralgia: a systematic review.

ABSTRACT: For trigeminal neuralgia (TN), a major role of imaging is to identify the causes, but recent studies demonstrated structural and microstructural changes in the affected nerve. Moreover, an increasing number of studies have reported central nervous system involvement in TN. In this systematic review, recent quantitative magnetic resonance imaging (MRI) studies of the trigeminal nerve and the brain in patients with TN were compiled, organized, and discussed, particularly emphasizing the possible background mechanisms and the interpretation of the results. A systematic search of quantitative MRI studies of the trigeminal nerve and the brain in patients with TN was conducted using PubMed. We included the studies of the primary TN published during 2013 to 2023, conducted for the assessment of the structural and microstructural analysis of the trigeminal nerve, and the structural, diffusion, and functional MRI analysis of the brain. Quantitative MRI studies of the affected trigeminal nerves and the trigeminal pathway demonstrated structural/microstructural alterations and treatment-related changes, which differentiated responders from nonresponders. Quantitative analysis of the brain revealed changes in the brain areas associated with pain processing/modulation and emotional networks. Studies of the affected nerve demonstrated evidence of demyelination and axonal damage, compatible with pathological findings, and have shown its potential value as a tool to assess treatment outcomes. Quantitative MRI has also revealed the possibility of dynamic microstructural, structural, and functional neuronal plasticity of the brain. Further studies are needed to understand these complex mechanisms of neuronal plasticity and to achieve a consensus on the clinical use of quantitative MRI in TN.

Improvement of MRS at ultra-high field using a wireless RF array.

We aim to assess a straightforward technique to enhance spectral quality in the brain, particularly in the cerebellum, during 7 T MRI scans. This is achieved through a wireless RF array insert designed to mitigate signal dropouts caused by the limited transmit field efficiency in the inferior part of the brain. We recently developed a wireless RF array to improve MRI and 1H-MRS at 7 T by augmenting signal via inductive coupling between the wireless RF array and the MRI coil. In vivo experiments on a Siemens 7 T whole-body human scanner with a Nova 1Tx/32Rx head coil quantified the impact of the dorsal cervical array in improving signal in the posterior fossa, including the cerebellum, where the transmit efficiency of the coil is inherently low. The 1H-MRS experimental protocol consisted of paired acquisition of data sets, both with and without the RF array, using the semi-LASER and SASSI sequences. The overall results indicate that the localized 1H-MRS is improved significantly in the presence of the array. Comparison of in vivo 1H-MRS plots in the presence versus absence of the array demonstrated an average SNR enhancement of a factor of 2.2. LCModel analysis reported reduced Cramér-Rao lower bounds, indicating more confident fits. This wireless RF array can significantly increase detection sensitivity. It may reduce the RF transmission power and data acquisition time for 1H-MRS and MRI applications, specifically at 7 T, where 1H-MRS requires a high-power RF pulse. The array could provide a cost-effective and efficient solution to improve detection sensitivity for human 1H-MRS and MRI in the regions with lower transmit efficiency.

Neuropsychiatric complications of coronavirus disease 2019: Mount Sinai Health System cohort study.

OBJECTIVE: To describe the frequency of neuropsychiatric complications among hospitalized patients with coronavirus disease 2019 (COVID-19) and their association with pre-existing comorbidities and clinical outcomes. METHODS: We retrospectively identified all patients hospitalized with COVID-19 within a large multicenter New York City health system between March 15, 2020 and May 17, 2021 and randomly selected a representative cohort for detailed chart review. Clinical data, including the occurrence of neuropsychiatric complications (categorized as either altered mental status [AMS] or other neuropsychiatric complications) and in-hospital mortality, were extracted using an electronic medical record database and individual chart review. Associations between neuropsychiatric complications, comorbidities, laboratory findings, and in-hospital mortality were assessed using multivariate logistic regression. RESULTS: Our study cohort consisted of 974 patients, the majority were admitted during the first wave of the pandemic. Patients were treated with anticoagulation (88.4%), glucocorticoids (24.8%), and remdesivir (10.5%); 18.6% experienced severe COVID-19 pneumonia (evidenced by ventilator requirement). Neuropsychiatric complications occurred in 58.8% of patients; 39.8% experienced AMS; and 19.0% experienced at least one other complication (seizures in 1.4%, ischemic stroke in 1.6%, hemorrhagic stroke in 1.0%) or symptom (headache in 11.4%, anxiety in 6.8%, ataxia in 6.3%). Higher odds of mortality, which occurred in 22.0%, were associated with AMS, ventilator support, increasing age, and higher serum inflammatory marker levels. Anticoagulant therapy was associated with lower odds of mortality and AMS. CONCLUSION: Neuropsychiatric complications of COVID-19, especially AMS, were common, varied, and associated with in-hospital mortality in a diverse multicenter cohort at an epicenter of the COVID-19 pandemic.

Older adults with epilepsy and COVID-19: Outcomes in a multi-hospital health system.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with high rates of mortality and morbidity in older adults, especially those with pre-existing conditions. There is little work investigating how neurological conditions affect older adults with COVID-19. We aimed to compare in-hospital outcomes, including mortality, in older adults with and without epilepsy. METHODS: This retrospective study in a large multicenter New York health system included consecutive older patients (age ≥65 years) either with or without epilepsy who were admitted with COVID-19 between 3/2020-5/2021. Epilepsy was identified using a validated International Classification of Disease (ICD) and antiseizure medicationbased case definition. Univariate comparisons were calculated using Chi-square, Fisher's exact, Mann-Whitney U, or Student's t-tests. Multivariable logistic regression models were generated to examine factors associated with mortality, discharge disposition and length of stay (LOS). RESULTS: We identified 5384 older adults admitted with COVID-19 of whom 173 (3.21 %) had epilepsy. Mean age was significantly lower in those with (75.44, standard deviation (SD): 7.23) compared to those without epilepsy (77.98, SD: 8.68, p = 0.007). Older adults with epilepsy were more likely to be ventilated (35.84 % vs. 16.18 %, p < 0.001), less likely to be discharged home (21.39 % vs. 43.12 %, p < 0.001), had longer median LOS (13 days vs. 8 days, p < 0.001), and had higher in-hospital death (35.84 % vs. 28.29 %, p = 0.030) compared to those without epilepsy. Epilepsy in older adults was associated with increased odds of in-hospital death (adjusted odds ratio (aOR), 1.55; 95 % CI 1.12-2.14, p = 0.032), non-routine discharge disposition (aOR, 3.34; 95 % CI 2.21-5.03, p < 0.001), and longer LOS (46.46 % 95 % CI 34 %-59 %, p < 0.001). CONCLUSIONS: In models that adjusted for multiple confounders including comorbidity and age, our study found that epilepsy was still associated with higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19 higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19. This work reinforces that epilepsy is a risk factor for worse outcomes in older adults admitted with COVID-19. Timely identification and treatment of COVID-19 in epilepsy may improve outcomes in older people with epilepsy.

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.

Gut microbiome association with brain imaging markers, APOE genotype, calcium and vegetable intakes, and obesity in healthy aging adults.

Introduction: Advanced 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. Methods: We 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. Results: Individuals 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. Discussion: These 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.

In-hospital outcomes in patients with and without epilepsy diagnosed with COVID-19-A cohort study.

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is associated with mortality in persons with comorbidities. The aim of this study was to evaluate in-hospital outcomes in patients with COVID-19 with and without epilepsy. METHODS: We conducted a retrospective study of patients with COVID-19 admitted to a multicenter health system between March 15, 2020, and May 17, 2021. Patients with epilepsy were identified using a validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/ICD-10-CM case definition. Logistic regression models and Kaplan-Meier analyses were conducted for mortality and non-routine discharges (i.e., not discharged home). An ordinary least-squares regression model was fitted for length of stay (LOS). RESULTS: We identified 9833 people with COVID-19 including 334 with epilepsy. On univariate analysis, people with epilepsy had significantly higher ventilator use (37.70% vs 14.30%, p < .001), intensive care unit (ICU) admissions (39.20% vs 17.70%, p < .001) mortality rate (29.60% vs 19.90%, p < .001), and longer LOS (12 days vs 7 days, p < .001). and fewer were discharged home (29.64% vs 57.37%, p < .001). On multivariate analysis, only non-routine discharge (adjusted odds ratio [aOR] 2.70, 95% confidence interval [CI] 2.00-3.70; p < .001) and LOS (32.50% longer, 95% CI 22.20%-43.60%; p < .001) were significantly different. Factors associated with higher odds of mortality in epilepsy were older age (aOR 1.05, 95% CI 1.03-1.08; p < .001), ventilator support (aOR 7.18, 95% CI 3.12-16.48; p < .001), and higher Charlson comorbidity index (CCI) (aOR 1.18, 95% CI 1.04-1.34; p = .010). In epilepsy, admissions between August and December 2020 or January and May 2021 were associated with a lower odds of non-routine discharge and decreased LOS compared to admissions between March and July 2020, but this difference was not statistically significant. SIGNIFICANCE: People with COVID-19 who had epilepsy had a higher odds of non-routine discharge and longer LOS but not higher mortality. Older age (≥65), ventilator use, and higher CCI were associated with COVID-19 mortality in epilepsy. This suggests that older adults with epilepsy and multimorbidity are more vulnerable than those without and should be monitored closely in the setting of COVID-19.

Neuroimaging findings and neurological manifestations in hospitalized COVID-19 patients: Impact of cancer and ventilatory support status.

INTRODUCTION: Coronavirus 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. METHODS: Eighty 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. RESULTS: Neuroimaging 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). DISCUSSION: This 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.

Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study.

Background: Major 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. Methods: Thirty-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. Results: Compared to HC, MDD and TRD patients showed reduced right-hemisphere CA2/3 subfield volume (p = 0.01, η 2 = 0.31 and p = 0.3, η 2 = 0.44, respectively). Additionally, negative associations were found between subfield volumes and life-stressor checklist scores, including left CA1 (p = 0.041, f 2 = 0.419), left CA4/DG (p = 0.010, f 2 = 0.584), right subiculum total (p = 0.038, f 2 = 0.354), left hippocampus total (p = 0.015, f 2 = 0.134), and right hippocampus total (p = 0.034, f 2 = 0.110). Caution should be exercised in interpreting these results due to the small sample size and low power. Conclusion: Determining 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.

Differential patterns of automatic segmentation of 3T and 7T MRI: Implications in neuropsychiatric disease.

Automatic segmentation was performed on T1-MPRAGE structural MRI data acquired at 3T and 7T from 37 and 69 distinct healthy controls, respectively. Additionally, segmentation was performed on imaging acquired from 215 major depressive disorder (MDD) patients at 3T and 40 MDD patients at 7T. Of 259 segmentation-derived imaging features evaluated, 120 showed significant 3T vs. 7T differences among controls, and 153 among patients. 7T imaging metrics showed consistently lower cortical thickness and cortical gray/white matter ratios. Subcortical and cortical volumes measured at 7T were more mixed, with 7T images showing greater frontal lobe volume, but lower cortical volumes elsewhere.

Multimodal Assessment of Bottlenose Dolphin Auditory Nuclei Using 7-Tesla MRI, Immunohistochemistry and Stereology.

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 <10%. Fibronectin immunoreactivity in the dolphin resembled the pattern in a human chronic traumatic encephalopathy brain, suggesting that neurochemical compensation for insults such as hypoxia may constitute a noxious response in humans, while being physiological in dolphins. These data contribute to a growing body of knowledge on the morphological and neurochemical properties of the dolphin brain and highlight a stereological and neuroimaging workflow that may enable quantitative and translational assessment of pathological processes in the dolphin brain in the future.

Ventral tegmental area integrity measured with high-resolution 7-Tesla MRI relates to motivation across depression and anxiety diagnoses.

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.

Perivascular spaces as a marker of psychological trauma in depression: A 7-Tesla MRI study.

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 < .01). CONCLUSIONS: These results suggest a relationship between glymphatic dysfunction related to BBB integrity and psychological trauma, and that glymphatic impairment may play a role in trauma-related symptomatology.

Altered hippocampus and amygdala subregion connectome hierarchy in major depressive disorder.

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.

Quantification of brain age using high-resolution 7 tesla MR imaging and implications for patients with epilepsy.

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.

Evidence of traumatic brain injury in headbutting bovids.

Traumatic brain injury (TBI) is a leading cause of neurologic impairment and death that remains poorly understood. Rodent models have yet to produce clinical therapies, and the exploration of larger and more diverse models remains relatively scarce. We investigated the potential for brain injury after headbutting in two combative bovid species by assessing neuromorphology and neuropathology through immunohistochemistry and stereological quantification. Postmortem brains of muskoxen (Ovibos moschatus, n = 3) and bighorn sheep (Ovis canadensis, n = 4) were analyzed by high-resolution MRI and processed histologically for evidence of TBI. Exploratory histological protocols investigated potential abnormalities in neurons, microglia, and astrocytes in the prefrontal and parietal cortex. Phosphorylated tau protein, a TBI biomarker found in the cerebrospinal fluid and in neurodegenerative lesions, was used to detect possible cellular consequences of chronic or acute TBI. MRI revealed no abnormal neuropathological changes; however, high amounts of tau-immunoreactive neuritic thread clusters, neurites, and neurons were concentrated in the superficial layers of the neocortex, preferentially at the bottom of the sulci in the muskoxen and occasionally around blood vessels. Tau-immunoreactive lesions were rare in the bighorn sheep. Additionally, microglia and astrocytes showed no grouping around tau-immunoreactive cells in either species. Our preliminary findings indicate that muskoxen and possibly other headbutting bovids suffer from chronic or acute brain trauma and that the males' thicker skulls may protect them to a certain extent.

Semi-automated Segmentation and Quantification of Perivascular Spaces at 7 Tesla in COVID-19.

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.

Feasibility of Upper Cranial Nerve Sonication in Human Application via Neuronavigated Single-Element Pulsed Focused Ultrasound.

Sonicating deep brain regions with pulsed focused ultrasound using magnetic resonance imaging-guided neuronavigation single-element piezoelectric transducers is a new area of exploration for neuromodulation. Upper cranial nerves such as the trigeminal nerve and other nerves responsible for sensory/motor functions in the head may be potential targets for ultrasound pain therapy. The location of upper cranial nerves close to the skull base poses additional challenges when compared with conventional cortical or middle brain targets. In the work described here, a series of computational and empirical testing methods using human skull specimens were conducted to assess the feasibility of sonicating the trigeminal pathway near the sphenoid bone region. The results indicate a transducer with a focal length of 120 mm and diameter of 85 mm (350 kHz) can deliver sonication to upper cranial nerve regions with spatial accuracy comparable to that of focused ultrasound brain targets used in previous human studies. Temperature measurements in cortical bone and in the skull base with embedded thermocouples yield evidence of minimal bone heating. Conventional pulse parameters were found to cause reverberation interference patterns near the cranial floor; therefore, changes in pulse cycles and pulse repetition frequency were examined for reducing standing waves. Limitations and considerations for conducting ultradeep focal targeting in human applications are discussed.