Gray Matter Brain Regions Research Articles

Abstract 109: Towards Individualised Prediction of Neurodevelopmental Outcomes After Neonatal Stroke: A Brain Lesion Network Mapping Study Leveraging Large-Scale Datasets

Introduction: Prediction of adverse neurodevelopmental outcomes after neonatal arterial ischemic stroke (NAIS) is challenging. We identified brain regions functionally connected to stroke lesions (lesion networks), and investigated whether such lesion networks are related to the development of cerebral palsy (CP) after NAIS. Methods: We performed a novel lesion network mapping approach, involving: 1. Creation of a normative connectome using the developing Human Connectome Project (dHCP) dataset. Resting state functional magnetic resonance imaging (MRI) scans of 518 neonates born at term (>36 weeks) from the dHCP were aligned to a template, built from T 2 -weighted scans of the same neonates; 2. Manual segmentation of lesions using diffusion MRI scans of 85 term-born neonates with NAIS, who were identified from Australian and Swiss pediatric stroke registries. Lesion masks were aligned to the template; 3. Construction of lesion network maps, by computing functional correlations between lesion masks and other brain grey matter regions, making use of the normative connectome; 4. Investigation of relationships between lesion networks and CP, diagnosed by clinical examination at least 18 months after NAIS. Lesion network maps were compared between those who did (n=28) and did not (n=57) develop CP after NAIS, with two sample t-tests. Results: In participants who developed CP after NAIS, lesions were more strongly functionally connected to the following regions: frontal (inferior and orbital frontal), temporal (pole, superior, and mesial temporal), insula, basal ganglia, thalamus and cerebellum (Figure 1). Conclusions: Leveraging large-scale datasets and innovative connectomic methods, we uncovered brain networks related to adverse outcomes after NAIS. This provided novel findings compared to past methods such as voxel-based lesion-symptom mapping. Our results point to differences in network vulnerabilities after stroke in neonates compared to adults.

Meta-analysis of structural and functional brain abnormalities in early-onset schizophrenia.

Previous studies based on resting-state functional magnetic resonance imaging(rs-fMRI) and voxel-based morphometry (VBM) have demonstrated significant abnormalities in brain structure and resting-state functional brain activity in patients with early-onset schizophrenia (EOS), compared with healthy controls (HCs), and these alterations were closely related to the pathogenesis of EOS. However, previous studies suffer from the limitations of small sample sizes and high heterogeneity of results. Therefore, the present study aimed to effectively integrate previous studies to identify common and specific brain functional and structural abnormalities in patients with EOS. The PubMed, Web of Science, Embase, Chinese National Knowledge Infrastructure (CNKI), and WanFang databases were systematically searched to identify publications on abnormalities in resting-state regional functional brain activity and gray matter volume (GMV) in patients with EOS. Then, we utilized the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software to conduct a whole-brain voxel meta-analysis of VBM and rs-fMRI studies, respectively, and followed by multimodal overlapping on this basis to comprehensively identify brain structural and functional abnormalities in patients with EOS. A total of 27 original studies (28 datasets) were included in the present meta-analysis, including 12 studies (13 datasets) related to resting-state functional brain activity (496 EOS patients, 395 HCs) and 15 studies (15 datasets) related to GMV (458 EOS patients, 531 HCs). Overall, in the functional meta-analysis, patients with EOS showed significantly increased resting-state functional brain activity in the left middle frontal gyrus (extending to the triangular part of the left inferior frontal gyrus) and the right caudate nucleus. On the other hand, in the structural meta-analysis, patients with EOS showed significantly decreased GMV in the right superior temporal gyrus (extending to the right rolandic operculum), the right middle temporal gyrus, and the temporal pole (superior temporal gyrus). This meta-analysis revealed that some regions in the EOS exhibited significant structural or functional abnormalities, such as the temporal gyri, prefrontal cortex, and striatum. These findings may help deepen our understanding of the underlying pathophysiological mechanisms of EOS and provide potential biomarkers for the diagnosis or treatment of EOS.

Comparison of delay correction methods to estimate 18F‐florbetaben kinetics in the brain using an image derived input function on total‐body EXPLORER PET

AbstractBackgroundAbsolute quantification of β‐amyloid binding from 18F‐florbetaben PET requires compartment kinetic modeling and an input function. This study uses non‐invasive Image Derived Input functions (IDIFs), derived using a new total‐body EXPLORER PET/CT scanner (Spencer et al., 2021). For accurate kinetic modelling, it is imperative to correct for time delay from the IDIF location to tracer arrival to the tissue of interest. The standard approach of Joint Estimation (JE) fits for delay time in tandem with other kinetic parameters and is computationally extensive (Feng et al., 2021). This study investigates the utility of Leading Edge (LE) ‐a novel and computationally efficient pulse timing method to estimate delay (Li et al., 2021) compared to JE in estimating 18F‐florbetaben kinetics in the brain grey matter regions, known to be vulnerable in Alzheimer’s Disease (AD).MethodThe study cohort included 14 individuals (9 cognitively unimpaired, 2 MCI, and 3AD; age = 66‐86 years) of the UC Davis Alzheimer’s Disease Research Center. Dynamic total‐body 18F‐florbetaben PET images were acquired for 110min using the uEXPLORER, and reconstructed (resolution = 2.344 mm isotropic voxels, framing protocol:30×2s, 12×10s, 7×60s, 20×300s).The dynamic brain‐cropped images were motion corrected (Jenkinson et al., 2002), and linearly registered to individual subject’s T1W (Jenkinson & Smith, 2001). Individual T1W were segmented using DKT atlas to obtain cerebral grey matter ROIs (Desikan et al., 2006). Dynamic time activity curves for each ROI were fit to the two‐tissue compartmental model, using a subject‐specific IDIF (population metabolite‐corrected) derived from the descending aorta (Figure1). Kinetic parameters were estimated and compared between JE and LE methods.ResultStrong associations were observed between JE and LE estimated 18F‐florbetaben kinetic parameters, including vb(r = 0.84, p<0.001), K1(r = 1, p<0.001), k2(r = 0.9, p<0.001), k3(r = 0.93, p<0.001), and k4(r = 0.86, p<0.001), in all the brain regions (Figure2). Quantitative kinetic results averaged across the selected grey matter regions (N = 11) are reported in Figure3.ConclusionThis study demonstrated the utility of IDIF extracted from total‐body dynamic PET to estimate 18F‐florbetaben tracer kinetics in the brain grey matter regions. Furthermore, the results show that LE can be an efficient surrogate for JE based approach in grey matter focused PET kinetic modelling of 18F‐florbetaben.

Association of retinal nerve layers thickness and brain imaging in healthy young subjects from the i-Share-Bordeaux study.

Given the anatomical and functional similarities between the retina and the brain, the retina could be a "window" for viewing brain structures. We investigated the association between retinal nerve fiber layers (peripapillary retinal nerve fiber layer, ppRNFL; macular ganglion cell-inner plexiform layer, GC-IPL; and macular ganglion cell complex, GCC), and brain magnetic resonance imaging (MRI) parameters in young health adults. We included 857 students (mean age: 23.3 years, 71.3% women) from the i-Share study. We used multivariate linear models to study the cross-sectional association of each retinal nerve layer thickness assessed by spectral-domain optical coherence tomography (SD-OCT) with structural (volumes and cortical thickness), and microstructural brain markers, assessed on MRI globally and regionally. Microstructural MRI parameters included diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI). On global brain analysis, thicker ppRNFL, GC-IPL and GCC were all significantly associated with patterns of diffusion metrics consistent with higher WM microstructural integrity. In regional analyses, after multiple testing corrections, our results suggested significant associations of some retinal nerve layers with brain regional gray matter occipital volumes and with diffusion MRI parameters in a region involved in the visual pathway and in regions containing associative tracts. No associations were found with global volumes or with global or regional cortical thicknesses. Results of this study suggest that some retinal nerve layers may reflect brain structures. Further studies are needed to confirm these results in young subjects.

Brain Changes Linked to Cognitive Symptomatology in Homeless Youth.

Youth impacted by homelessness experience diminished cognition due to a variety of reasons including mental health symptoms, alcohol and substance use, and adverse childhood experiences. However, the status of specific brain regions which could impact important cognitive functions in homeless youth remains unclear. In this pilot comparative and correlational study, a series of demographic, psychological, cognitive assessments, and brain magnetic resonance imaging were performed in 10 male youth experiencing homelessness and 9 age-matched healthy male controls (age range: 18-25 years). Participants experiencing homelessness had significantly decreased regional brain gray matter tissue in comparison to the controls. Moreover, there were strong inverse correlations between the brain regions classically associated with executive decision-making (prefrontal cortices), depression (insular lobes), and conflict resolution (anterior cingulate), and the level of the symptoms detected by their questionnaires.

Brain glucose metabolism and gray matter volume in retired professional soccer players: a cross-sectional [18F]FDG-PET/MRI study.

Professional soccer athletes are exposed to repetitive head impacts and are at risk of developing chronic traumatic encephalopathy. To evaluate regional brain glucose metabolism (rBGM) and gray matter (GM) volume in retired soccer players (RSPs). Male RSPs and age and sex-matched controls prospectively enrolled between 2017 and 2019 underwent neurological and neuropsychological evaluations, brain MRI and [18F]FDG-PET in a 3.0-Tesla PET/MRI scanner. Visual analysis was performed by a blinded neuroradiologist and a blinded nuclear physician. Regional brain glucose metabolism and GM volume were assessed using SPM8 software. Groups were compared using appropriate statistical tests available at SPM8 and R. Nineteen RSPs (median [IQR]: 62 [50-64.5] years old) and 20 controls (60 [48-73] years old) were included. Retired soccer players performed worse on mini-mental state examination, digit span, clock drawing, phonemic and semantic verbal fluency tests, and had reduced rBGM in the left temporal pole (pFDR = 0.008) and the anterior left middle temporal gyrus (pFDR = 0.043). Semantic verbal fluency correlated with rBGM in the right hippocampus, left temporal pole, and posterior left middle temporal gyrus (p ≤ 0.042). Gray matter volume reduction was observed in similar anatomic regions but was less extensive and did not survive correction for multiple comparisons (pFDR ≥ 0.085). Individual [18F]FDG-PET visual analysis revealed seven RSPs with overt hypometabolism in the medial and lateral temporal lobes, frontal lobes, and temporoparietal regions. Retired soccer players had a higher prevalence of septum pellucidum abnormalities on MRI. Retired soccer players had reduced rBGM and GM volume in the temporal lobes and septum pellucidum abnormalities, findings possibly related to repetitive head impacts.

Toward a statistical validation of brain signatures as robust measures of behavioral substrates.

The "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of behavioral outcomes. Previously we presented a method for computing signatures of episodic memory. However, to be a robust brain measure, the signature approach requires a rigorous validation of model performance across a variety of cohorts. Here we report validation results and provide an example of extending it to a second behavioral domain. In each of two discovery data cohorts, we derived regional brain gray matter thickness associations for two domains: neuropsychological and everyday cognition memory. We computed regional association to outcome in 40 randomly selected discovery subsets of size 400 in each cohort. We generated spatial overlap frequency maps and defined high-frequency regions as "consensus" signature masks. Using separate validation datasets, we evaluated replicability of cohort-based consensus model fits and explanatory power by comparing signature model fits with each other and with competing theory-based models. Spatial replications produced convergent consensus signature regions. Consensus signature model fits were highly correlated in 50 random subsets of each validation cohort, indicating high replicability. In comparisons over each full cohort, signature models outperformed other models. In this validation study, we produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Signatures in two memory domains suggested strongly shared brain substrates. Robust brain signatures may therefore be achievable, yielding reliable and useful measures for modeling substrates of behavioral domains.

Sleep spindles and slow waves are physiological markers for age-related changes in gray matter in brain regions supporting problem-solving skills.

As we age, the added benefit of sleep for memory consolidation is lost. One of the hallmark age-related changes in sleep is the reduction of sleep spindles and slow waves. Gray matter neurodegeneration is related to both age-related changes in sleep and age-related changes in memory, including memory for problem-solving skills. Here, we investigated whether spindles and slow waves might serve as biological markers for neurodegeneration of gray matter and for the related memory consolidation deficits in older adults. Forty healthy young adults (20-35 yr) and 30 healthy older adults (60-85 yr) were assigned to either nap or wake conditions. Participants were trained on the Tower of Hanoi in the morning, followed by either a 90-min nap opportunity or period of wakefulness, and were retested afterward. We found that age-related changes in sleep spindles and slow waves were differentially related to gray matter intensity in young and older adults in brain regions that support sleep-dependent memory consolidation for problem-solving skills. Specifically, we found that spindles were related to gray matter in neocortical areas (e.g., somatosensory and parietal cortex), and slow waves were related to gray matter in the anterior cingulate, hippocampus, and caudate, all areas known to support problem-solving skills. These results suggest that both sleep spindles and slow waves may serve as biological markers of age-related neurodegeneration of gray matter and the associated reduced benefit of sleep for memory consolidation in older adults.

Smoking is associated with lower brain volume and cognitive differences: A large population analysis based on the UK Biobank

The evidence about the association of smoking with both brain structure and cognitive functions remains inconsistent. Using structural magnetic resonance imaging from the UK Biobank (n = 33,293), we examined the relationships between smoking status, dosage, and abstinence with total and 166 regional brain gray matter volumes (GMV). The relationships between the smoking parameters with cognitive function, and whether this relationship was mediated by brain structure, were then investigated. Smoking was associated with lower total and regional GMV, with the extent depending on the frequency of smoking and on whether smoking had ceased: active regular smokers had the lowest GMV (Cohen's d = −0.362), and former light smokers had a slightly smaller GMV (Cohen's d = −0.060). The smaller GMV in smokers was most evident in the thalamus. Higher lifetime exposure (i.e., pack-years) was associated with lower total GMV (β = −311.84, p = 8.35 × 10−36). In those who ceased smoking, the duration of abstinence was associated with a larger total GMV (β = 139.57, p = 2.36 × 10−08). It was further found that reduced cognitive function was associated with smoker parameters and that the associations were partially mediated by brain structure. This is the largest scale investigation we know of smoking and brain structure, and these results are likely to be robust. The findings are of associations between brain structure and smoking, and in the future, it will be important to assess whether brain structure influences smoking status, or whether smoking influences brain structure, or both.

Toward a statistical foundation for brain signatures of behavioral outcome

AbstractBackgroundThe “brain signature of cognition” concept has garnered interest as a data‐driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of clinical outcomes. However, to be a robust brain phenotype, the signature approach requires a statistical foundation showing that model performance replicates across a variety of cohorts. Here, we outline a procedure that provides this foundation for a signature models of episodic memory and extend this to a measure of functional everyday memory.MethodUniversity of California, Davis (UCD) and ADNI provided imaging and memory data. For cognitive and ECog memory, we derived regional brain gray matter (GM) cortical thickness (CT) measures, testing for replicability (Fig. 1). Signature model generation used two steps in each cohort: 1) Randomly select 40 discovery subsets of size N = 400. In each subset, use voxelwise regression to compute the CT signature regions for outcome at three t‐values of association. 2) Compile frequency maps of region selection across all 40 discovery sets and designate regions with selection frequency >70% as “consensus” signature masks for each cohort. Model validation used regressions of outcomes on consensus masks: 1) Compare adjusted R2 fits of both consensus signature models in 40 discovery sets in each cohort (thus, symmetrically compare same and oppositely generated models). 2) In each full cohort, compare signature model fits with competing models.ResultSpatial replications produced strongly convergent consensus signature regions derived from UCD and ADNI (Fig. 2). Consensus model fits were highly correlated in 40 random subsets of each cohort (Fig. 3 top) indicating high replicability, with tight (∼80%) ratios of within/outside cohort model fits (Fig. 3 bottom), indicating low bias. In comparisons over each full cohort, signature models outperformed other models with one exception (Fig. 4).ConclusionMultiple random model generations, followed by consensus selection of regional brain substrates, produced signature models that both consistently replicated model fits to memory and outperformed other commonly used measures. Results support consensus signature models as robust biomarkers of cognition and everyday function across imaging cohorts with differing demographic composition (see Table).

Chronic cerebral blood flow alterations in traumatic brain injury and sports-related concussions

ABSTRACT Primary Objective Traumatic brain injury (TBI) and sports-related concussion (SRC) may result in chronic functional and neuroanatomical changes. We tested the hypothesis that neuroimaging findings (cerebral blood flow (CBF), cortical thickness, and 1H-magnetic resonance (MR) spectroscopy (MRS)) were associated to cognitive function, TBI severity, and sex. Research Design Eleven controls, 12 athletes symptomatic following ≥3SRCs and 6 patients with moderate-severe TBI underwent MR scanning for evaluation of cortical thickness, brain metabolites (MRS), and CBF using pseudo-continuous arterial spin labeling (ASL). Cognitive screening was performed using the RBANS cognitive test battery. Main Outcomes and Results RBANS-index was impaired in both injury groups and correlated with the injury severity, although not with any neuroimaging parameter. Cortical thickness correlated with injury severity (p = 0.02), while neuronal density, using the MRS marker ((NAA+NAAG)/Cr, did not. On multivariate analysis, injury severity (p = 0.0003) and sex (p = 0.002) were associated with CBF. Patients with TBI had decreased gray (p = 0.02) and white matter (p = 0.02) CBF compared to controls. CBF was significantly lower in total gray, white matter and in 16 of the 20 gray matter brain regions in female but not male athletes when compared to female and male controls, respectively. Conclusions Injury severity correlated with CBF, cognitive function, and cortical thickness. CBF also correlated with sex and was reduced in female, not male, athletes. Chronic CBF changes may contribute to the persistent injury mechanisms in TBI and rSRC.

Multimodal Brain MRI of Deep Gray Matter Changes Associated With Inflammatory Bowel Disease.

Behavioral symptoms, including mood disorders, substantially impact the quality of life of patients with inflammatory bowel disease (IBD), even when clinical remission is achieved. Here, we used multimodal magnetic resonance imaging (MRI) to determine if IBD is associated with changes in the structure and function of deep gray matter brain regions that regulate and integrate emotional, cognitive, and stress responses. Thirty-five patients with ulcerative colitis (UC) or Crohn's disease (CD) and 32 healthy controls underwent 3 Tesla MRIs to assess volume, neural activity, functional connection strength (connectivity), inflammation, and neurodegeneration of key deep gray matter brain regions (thalamus, caudate, pallidum, putamen, amygdala, hippocampus, and hypothalamus) involved in emotional, cognitive and stress processing. Associations with sex, presence of pain, disease activity, and C-reactive protein (CRP) concentration were examined. Significantly increased activity and functional connectivity were observed in cognitive and emotional processing brain regions, including parts of the limbic system, basal ganglia, and hypothalamus of IBD patients compared with healthy controls. Inflammatory bowel disease patients exhibited significantly increased volumes of the amygdala and hypothalamus, as well as evidence of neurodegeneration in the putamen and pallidum. Hippocampal neural activity was increased in IBD patients with active disease. The volume of the thalamus was positively correlated with CRP concentration and was increased in females experiencing pain. Patients with IBD exhibit functional and structural changes in the limbic and striatal systems. These changes may be targets for assessing or predicting the response to therapeutic interventions aimed at improving comorbid emotional and cognitive symptoms.

Variable Voxel-based Morphometry Observations of Gray Matter Differences in Fibromyalgia: Individual Differences or Methodological Inconsistency?

Fibromyalgia is a prevalent chronic pain condition characterized by widespread pain and sensory hypersensitivity. While much remains to be learned about the neurobiological underpinnings of this condition, alterations to the central nervous system appear to be heavily implicated in fibromyalgia's pathophysiology. Previous research examining brain structural abnormalities among fibromyalgia patients has yielded inconsistent findings. Thus, we followed previous voxel-based morphometry methods in magnetic resonance imaging to examine brain gray matter differences in females (n=17) with fibromyalgia and female healthy controls (n=17). We hypothesized that, relative to healthy control participants, fibromyalgia participants would exhibit lower gray matter volume in regions consistently implicated in pain processing and, specifically, fibromyalgia: the anterior cingulate cortex and the medial prefrontal cortex. Previously reported peak coordinates are located in both the anterior cingulate cortex (ACC) and medial prefrontal cortex (mPFC), but interpretation of these locations is varied. Therefore, we first examined a large region of interest that encompassed both the mPFC and ACC, followed by a whole brain analysis. Group differences were analyzed with two-sample t-tests, controlling for total intracranial volume. No significant differences in regional or whole brain gray matter volumes were detected between fibromyalgia patients and healthy controls. These results add to an existing body of disparate findings regarding brain gray matter volume differences in fibromyalgia, and suggest structural differences previously detected among fibromyalgia patients should be rigorously examined for reproducibility and support the need for additional meta-analyses. Absent significant differences may also suggest that individual differences, rather than methodological variability, account for contradictory results. Grant support from K99DA040154.

Development of regional brain gray matter volume across the first 13 years of life is associated with childhood math computation ability for children born very preterm and full term

Very preterm birth (VP; <32 weeks’ gestation) is associated with altered brain gray matter development and lower math ability. In typically developing children, the neural correlates of math ability may change dynamically with age, though evidence in VP children is limited. In a prospective longitudinal cohort of children born VP and full term (FT), we aimed to investigate associations between 1) concurrent regional brain volumes and math ability at 7 (n = 148 VP; n = 34 FT) and 13-years (n = 130 VP; n = 46 FT), and 2) regional volumetric growth across childhood (term-equivalent age (TEA) to 7-years; 7 to 13-years) and math ability from 7 to 13-years, and improvement in ability from 7 to 13 years. For both aims we investigated whether associations differed between birth groups. Cross-sectionally, frontal, temporal and subcortical regional volumes were positively associated with math ability for both birth groups. For FT children, greater growth of specific temporal regions was associated with higher math ability, and greater improvements. For VP children, similar associations were only observed for growth from TEA to 7-years with 13-year ability and improvements in ability. In conclusion, VP birth appears to alter associations of brain development across the first 13 years with childhood math ability.

Altruistic Social Activity, Depressive Symptoms, and Brain Regional Gray Matter Volume: Voxel-Based Morphometry Analysis From 8,695 Old Adults.

Altruistic social activity, such as giving support to others, has shown protective benefits on dementia risk and cognitive decline. However, the pathological mechanism is unclear. In the present study, we investigated the association between altruistic social activity and brain regional gray matter. Furthermore, to explore the psychological interplay in altruistic social activity, we tested mediating effect of depressive symptoms on brain regional gray matter. We performed a cross-sectional voxel-based morphology (VBM) analysis including 8 695 old adults (72.9 ± 6.1 years) from Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) Cohort. We measured altruistic social activities by self-report questionnaires, depressive symptoms by Geriatric Depression Scale (GDS)-short version. We employed the whole-brain VBM method to detect relevant structural properties related to altruistic social activity. We then performed multiple regression models to detect the mediating effect of depressive symptoms on particular brain regional gray matter volume while adjusting possible physical and social lifestyle covariables. We found that altruistic social activity is associated with larger gray matter volume in posterior insula, middle cingulate gyrus, hippocampus, thalamus, superior temporal gyrus, anterior orbital gyrus, and middle occipital gyrus. Depressive symptoms mediated over 10% on altruistic social activity and hippocampus volume, over 20% on altruistic social activity and cingulate gyrus volume. Our results indicated that altruistic social activity might preserve brain regional gray matter which are sensitive to aging and cognitive decline. Meanwhile, this association may be explained by indirect effect on depressive symptoms, suggesting that altruistic social activity may mitigate the neuropathology of dementia.

Association of APOE ε4 with cerebral gray matter volumes in non-demented older adults: The MEMENTO cohort study

Data on 2,045 non-demented individuals with memory complaints were drawn from the Memento cohort study to examine the association between Apolipoprotein E ε4 allele (APOE4) and regional brain gray matter volumes. Linear regression was used to examine the association of APOE4 and measures of regional gray matter volumes in cross-sectional analysis and change therein using longitudinal analyses based on two brain MRI performed at baseline and at two-year follow-up. Overall, in analyses adjusted for age, sex, and intracranial volume, the presence of APOE4 was associated with lower total gray matter volume at baseline and with a higher atrophy rate over the follow-up. The hippocampus and entorhinal cortex were the two gray matter regions most associated with APOE4. Further adjustment for cardiovascular risk factors had little impact on these associations. There was an interaction between age, APOE4 status and total brain volume atrophy rate, with evidence of an earlier age at onset of atrophy in hippocampal volume in APOE4 carriers compared to non-carriers. Those results are in accordance with the role of medial temporal structures in the greater risk of dementia observed in people carrying the APOE4 allele.

Red Cell Distribution Width, Anemia, and Brain Volumetric Outcomes Among Middle-Aged Adults.

Anemia and red cell distribution width (RDW) have been linked to poor cognitive performance, pending studies of underlying mechanisms. We examined cross-sectional relationships of initial RDW status (v1), RDW change (δ), and anemia with brain structural magnetic resonance imaging (sMRI) markers, including global and cortical brain and hippocampal and white matter lesion (WML) volumes, 5-6 years later. Data were used from three prospective visits within the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS) study with complete v1 (2004-2009) and v2 (2009-2013) exposures and ancillary sMRI data at vscan (2011-2015, n = 213, mean v1 to vscan time: 5.7 years). Multivariable-adjusted linear regression models were conducted, overall, by sex, by race, and within non-anemics, correcting for multiple testing with q-values. In minimally adjusted models (socio-demographics and follow-up time), anemiav1 and RDWv1 were consistently associated with smaller bilateral hippocampal volumes overall, and among females (q < 0.05), without significant sex differences. RDWv1 was related to smaller select regional cortical brain gray and white matter volumes in hematological measure-adjusted models; anemiav1 was associated with larger WML volumes only among whites. In summary, baseline anemia and RDW were consistently associated with smaller bilateral hippocampal volumes, particularly among females, while anemia was linked to larger WML volume among Whites. In hematological measure-adjusted models, baseline RDW was linked to smaller regional gray and white matter volumes. Pending studies with sMRI repeats, randomized controlled trials are needed, demonstrating associations of anemia and elevated RDW with reduced brain volumes and cognitive dysfunction.

Regional brain morphology predicts pain relief in trigeminal neuralgia

BackgroundTrigeminal neuralgia, a severe chronic neuropathic pain disorder, is widely believed to be amenable to surgical treatments. Nearly 20% of patients, however, do not have adequate pain relief after surgery. Objective tools for personalized pre-treatment prognostication of pain relief following surgical interventions can minimize unnecessary surgeries and thus are of substantial benefit for patients and clinicians. PurposeTo determine if pre-treatment regional brain morphology-based machine learning models can prognosticate 1 year response to Gamma Knife radiosurgery for trigeminal neuralgia. MethodsWe used a data-driven approach that combined retrospective structural neuroimaging data and support vector machine-based machine learning to produce robust multivariate prediction models of pain relief following Gamma Knife radiosurgery for trigeminal neuralgia. Surgical response was defined as ≥ 75% pain relief 1 year post-treatment. We created two prediction models using pre-treatment regional brain gray matter morphology (cortical thickness or surface area) to distinguish responders from non-responders to radiosurgery. Feature selection was performed through sequential backwards selection algorithm. Model out-of-sample generalizability was estimated via stratified 10-fold cross-validation procedure and permutation testing. ResultsIn 51 trigeminal neuralgia patients (35 responders, 16 non-responders), machine learning models based on pre-treatment regional brain gray matter morphology (14 regional surface areas or 13 regional cortical thicknesses) provided robust a priori prediction of surgical response. Cross-validation revealed the regional surface area model was 96.7% accurate, 100.0% sensitive, and 89.1% specific while the regional cortical thickness model was 90.5% accurate, 93.5% sensitive, and 83.7% specific. Permutation testing revealed that both models performed beyond pure chance (p < 0.001). The best predictor for regional surface area model and regional cortical thickness model was contralateral superior frontal gyrus and contralateral isthmus cingulate gyrus, respectively. ConclusionsOur findings support the use of machine learning techniques in subsequent investigations of chronic neuropathic pain. Furthermore, our multivariate framework provides foundation for future development of generalizable, artificial intelligence-driven tools for chronic neuropathic pain treatments.

Regional brain glucose metabolism and gray matter volumetry for the evaluation of chronic traumatic encephalopathy in retired male soccer players: An [18F]FDG‐PET/MRI study

AbstractBackgroundChronic traumatic encephalopathy (CTE) is a progressive tauopathy mostly described in military personnel, boxers and American football players. Soccer / European football players are also exposed to long‐term repetitive mild traumatic brain injuries (mTBI), which can lead to CTE. We hypothesized that retired soccer players may present with brain damage, as measured by regional brain glucose metabolism (rBGM) and gray matter (GM) volume in comparison to individuals without exposure to traumatic brain injury. We aim to evaluate rBGM measured with [18F]FDG‐PET, GM volume and the load of white matter lesions (WML) measured with MRI in a group of retired soccer players.MethodsThis prospective study included 19 retired male soccer players (mean = 57,6 years old) and 20 controls matched by age (mean = 60,6 years old), submitted to brain MRI and [18F]FDG‐PET in a 3 Tesla SIGNA PET/MRI scanner (GE Healthcare) from January 2017 to September 2019. Assessment of rBGM, GM volume and load of WML were performed with the SPM8 software. Both groups were compared using the appropriate statistical tests available at SPM8 and R. The p‐value used for significance was 0.001, and correction for multiple comparisons was applied to the SPM analyses (pFWE/FDR&lt; 0.05).ResultsRetired soccer players presented with reduced rBGM in both temporal lobes, reaching statistical significance in left temporal pole and anterior aspect of left inferior temporal gyrus (pFWE/FDR&lt;0.05). Reduction of grey matter volume were observed in similar regions, however with a lower extension, and without surviving correction for multiple comparisons (puncorrected&lt;0.001). There were no differences between groups regarding WML.ConclusionOur study shows a significant reduction in rGBM and less evident reduction in GM volume in the lateral and medial temporal lobes of retired soccer players in comparison to controls, which may be attributable to repetitive mTBI.

Про COVID-19, психічне здоров’я та медитацію

The art of meditation has attracted vivid attention and considerable interest in contemporary unstable and unpredicted world, especially now when the outbreak of COVID-19 has created mental health concerns among the general population worldwide. Contemporary research on meditation for different conditions shows that meditation helps to control pain, may reduce blood pressure, leads to increases in regional brain gray matter density, may reduce age-related memory loss, enhances self-awareness, reduces feelings of loneliness and increases social contact, cultivates more creative problem-solving skills, promotes emotional health. Its positive impact on stress, anxiety, depression, chronic diseases is well-known. To enhance mental health and stabilize human beings in happiness and harmony, it is now more crucial than ever to turn to the Eastern spiritual practices and integrate them with the Western scientific discoveries. It will expand the functional field of human capabilities to achieve freedom and self-realization.