Brain volume, energy balance, and cardiovascular health in two nonindustrial South American populations.

Little is known about brain aging or dementia in nonindustrialized environments that are similar to how humans lived throughout evolutionary history. This paper examines brain volume (BV) in middle and old age among two indigenous South American populations, the Tsimane and Moseten, whose lifestyles and environments diverge from those in high-income nations. With a sample of 1,165 individuals aged 40 to 94, we analyze population differences in cross-sectional rates of decline in BV with age. We also assess the relationships of BV with energy biomarkers and arterial disease and compare them against findings in industrialized contexts. The analyses test three hypotheses derived from an evolutionary model of brain health, which we call the embarrassment of riches (EOR). The model hypothesizes that food energy was positively associated with late life BV in the physically active, food-limited past, but excess body mass and adiposity are now associated with reduced BV in industrialized societies in middle and older ages. We find that the relationship of BV with both non-HDL cholesterol and body mass index is curvilinear, positive from the lowest values to 1.4 to 1.6 SDs above the mean, and negative from that value to the highest values. The more acculturated Moseten exhibit a steeper decrease in BV with age than Tsimane, but still shallower than US and European populations. Lastly, aortic arteriosclerosis is associated with lower BV. Complemented by findings from the United States and Europe, our results are consistent with the EOR model, with implications for interventions to improve brain health.

A causal relationship between gut microbiota and subcortical brain structures contributes to the microbiota-gut-brain axis: a Mendelian randomization study.

A correlation between gut microbiota and brain structure, referring to as a component of the gut-brain axis, has been observed in observational studies. However, the causality of this relationship and its specific bacterial taxa remains uncertain. To reveal the causal effects of gut microbiota on subcortical brain volume, we applied Mendelian randomization (MR) studies in this study. Genome-wide association study data were obtained from the MiBioGen Consortium (n = 18,340) and the Enhancing Neuro Imaging Genetics through Meta-Analysis Consortium (n = 13,170). The primary estimate was obtained utilizing the inverse-variance weighted, while heterogeneity and pleiotropy were assessed using the Cochrane Q statistic, MR Pleiotropy RESidual Sum and Outlier, and MR-Egger intercept. Our findings provide strong evidence that a higher abundance of the genus Parasutterella is causally correlated with a decrease in intracranial volume (ß = -30,921.33, 95% CI -46,671.78 to -15,170.88, P = 1.19 × 10-4), and the genus FamilyXIIIUCG001 is associated with a decrease in thalamus volume (ß = -141.96, 95% CI: -214.81 to -69.12, P = 1.0× 10-4). This MR study offers novel perspectives on the intricate interplay between the gut microbiota and subcortical brain volume, thereby lending some support to the existence of the microbiota-gut-brain axis.

Physiological and behavioural implications of the portosystemic shunt in C57Bl/6J mice.

A significant fraction of the popular inbred C57Bl/6J mice show structural and biochemical features of the congenital portosystemic shunt (PSS). How this hepatic abnormality affects physiological and behavioural parameters has not been explored in detail. Here, we confirmed the frequent occurrence of the PSS in C57Bl/6J mice by three different methods. We screened a cohort of 119 C57Bl/6J mice for total bile acids (TBA) in plasma, identified 11 animals (9.2%) with high TBA (>11 µm; 171.1 ± 76.8 µm), and confirmed PSS presence in that subset by magnetic resonance angiography and 1H-magnetic resonance spectroscopy of brain metabolites in the hippocampal area. In addition to the high glutamine and low myo-inositol levels, we detected lower levels of several neurotransmitters and metabolites in the hippocampus, higher brain weight and volume, as well as enhanced brain glucose utilisation in the PSS mice. We also observed differences in peripheral organ weights, haematological cell counts and clinical chemistry parameters in C57Bl/6J mice with and without PSS. Animals with PSS were slightly hyperlocomotive, had better balance on the rotarod, showed altered gait properties, and displayed attenuated fear memory in the fear conditioning test. Furthermore, we revealed a significant alteration of the pharmacokinetic profile of diazepam in C57Bl/6J mice with PSS. Our data support previous reports of hepatic disturbances and demonstrate an altered neurobiological phenotype in C57Bl/6J mice with PSS. Such congenital differences between inbred C57Bl/6J littermates may significantly distort experimental outcomes of pharmacological, behavioural and genetic studies. KEY POINTS: A significant proportion of C57Bl/6J mice, an inbred strain popular in preclinical research, have congenital portosystemic shunts (PSS) that allow venous blood to enter systemic circulation bypassing the liver. In this study, we extended existing knowledge of PSS consequences, particularly with respect to the effects on brain structure and function. We demonstrated that C57Bl/6J mice with PSS differ from their normal counterparts in brain size and contents of several neuroactive substances, as well as in peripheral organ weights, rate of glucose utilisation, blood cell counts and blood clinical chemistry parameters. C57Bl/6J mice with PSS showed altered locomotor behaviour, performed worse in a memory test and had abnormal blood pharmacokinetics of a benzodiazepine drug after a single administration. PSS presence may significantly complicate the interpretation of experiments in C57Bl/6J mice; therefore, we propose that before their use in biomedical studies, these mice should be screened with a simple blood test.

MGA-Net: A novel mask-guided attention neural network for precision neonatal brain imaging.

In this study, we introduce MGA-Net, a novel mask-guided attention neural network, which extends the U-net model for precision neonatal brain imaging. MGA-Net is designed to extract the brain from other structures and reconstruct high-quality brain images. The network employs a common encoder and two decoders: one for brain mask extraction and the other for brain region reconstruction. A key feature of MGA-Net is its high-level mask-guided attention module, which leverages features from the brain mask decoder to enhance image reconstruction. To enable the same encoder and decoder to process both MRI and ultrasound (US) images, MGA-Net integrates sinusoidal positional encoding. This encoding assigns distinct positional values to MRI and US images, allowing the model to effectively learn from both modalities. Consequently, features learned from a single modality can aid in learning a modality with less available data, such as US. We extensively validated the proposed MGA-Net on diverse and independent datasets from varied clinical settings and neonatal age groups. The metrics used for assessment included the DICE similarity coefficient, recall, and accuracy for image segmentation; structural similarity for image reconstruction; and root mean squared error for total brain volume estimation from 3D ultrasound images. Our results demonstrate that MGA-Net significantly outperforms traditional methods, offering superior performance in brain extraction and segmentation while achieving high precision in image reconstruction and volumetric analysis. Thus, MGA-Net represents a robust and effective preprocessing tool for MRI and 3D ultrasound images, marking a significant advance in neuroimaging that enhances both research and clinical diagnostics in the neonatal period and beyond.

Menstrual cycle-driven hormone concentrations co-fluctuate with white and gray matter architecture changes across the whole brain.

Cyclic fluctuations in hypothalamic-pituitary-gonadal axis (HPG-axis) hormones exert powerful behavioral, structural, and functional effects through actions on the mammalian central nervous system. Yet, very little is known about how these fluctuations alter the structural nodes and information highways of the human brain. In a study of 30 naturally cycling women, we employed multidimensional diffusion and T1-weighted imaging during three estimated menstrual cycle phases (menses, ovulation, and mid-luteal) to investigate whether HPG-axis hormone concentrations co-fluctuate with alterations in white matter (WM) microstructure, cortical thickness (CT), and brain volume. Across the whole brain, 17ß-estradiol and luteinizing hormone (LH) concentrations were directly proportional to diffusion anisotropy (µFA; 17ß-estradiol: ß1 = 0.145, highest density interval (HDI) = [0.211, 0.4]; LH: ß1 = 0.111, HDI = [0.157, 0.364]), while follicle-stimulating hormone (FSH) was directly proportional to CT (ß1 = 0 .162, HDI = [0.115, 0.678]). Within several individual regions, FSH and progesterone demonstrated opposing relationships with mean diffusivity (Diso) and CT. These regions mainly reside within the temporal and occipital lobes, with functional implications for the limbic and visual systems. Finally, progesterone was associated with increased tissue (ß1 = 0.66, HDI = [0.607, 15.845]) and decreased cerebrospinal fluid (CSF; ß1 = -0.749, HDI = [-11.604, -0.903]) volumes, with total brain volume remaining unchanged. These results are the first to report simultaneous brain-wide changes in human WM microstructure and CT coinciding with menstrual cycle-driven hormone rhythms. Effects were observed in both classically known HPG-axis receptor-dense regions (medial temporal lobe, prefrontal cortex) and in other regions located across frontal, occipital, temporal, and parietal lobes. Our results suggest that HPG-axis hormone fluctuations may have significant structural impacts across the entire brain.

Region-Specific Brain Volume Changes Emerge in Adolescence in the Valproic Acid Model of Autism and Parallel Human Findings.

INTRODUCTION: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication deficits, cognitive dysfunction, and stereotyped repetitive behaviors. Regional volume changes are commonly observed in individuals with ASD. To examine volumetric dysregulation across adolescence, the valproic acid (VPA) model was used to induce ASD-like phenotypes in rats. METHOD: Regional volumes were obtained via magnetic resonance imaging at either postnatal day 28 or postnatal day 40 (P40), which correspond to early and late adolescence, respectively. RESULTS: Consistent with prior research, VPA animals had reduced total brain volume compared to control animals. A novel outcome was that VPA animals had overgrown right hippocampi at P40. Differences in the pattern of development of the anterior cingulate cortex were also observed in VPA animals. Differences for the posterior cingulate were only observed in males, but not females. CONCLUSION: These results demonstrate differences in region-specific developmental trajectories between control and VPA animals and suggest that the VPA model may capture regional volume changes consistent with human ASD.

Effects of Early Enteral to Parenteral Protein Ratios on Brain Volume and Somatic Growth in Very Low Birth Weight Infants.

OBJECTIVE: To evaluate whether a higher proportion of enteral vs parenteral protein ratio (E:P ratio) in the first 28 days after birth is associated with increased brain volume and somatic growth in very low birth weight (VLBW; birth weight <1500 g) infants. STUDY DESIGN: This was a retrospective analysis of a subcohort of VLBW infants (n = 256, gestational age mean 28.07 [SD 2.17] weeks, birth weight 1038.80 [SD 262.95] grams) from the Cincinnati Infant Neurodevelopment Early Prediction Study, a regional prospective study of infants born at ≤32 weeks' gestation. Brain magnetic resonance imaging was obtained at term-equivalent age. Macronutrient intake and growth metrics for the first 28 days were collected retrospectively. The primary outcome was total brain tissue volume. The relationships between E:P ratio, total and regional brain tissue volumes, and somatic growth were analyzed by multivariable linear regression models; composite variables were used to adjust for potential confounders including pregnancy risk factors and initial severity of illness. RESULTS: Higher E:P ratio was associated with increased total brain tissue volume but was not associated with change in head circumference z score. In secondary analyses, higher E:P ratio was associated with increased weight velocity. There were no significant associations between E:P ratio and change in weight or length z scores or regional brain volumes. CONCLUSIONS: Higher E:P ratio in the first 28 days was positively associated with total brain volume and weight gain. Promoting the provision of enteral over parenteral protein may improve brain and somatic growth in VLBW infants.

Brain volume in infants with metopic synostosis: Less white matter volume with an accelerated growth pattern in early life.

Metopic synostosis patients are at risk for neurodevelopmental disorders despite a negligible risk of intracranial hypertension. To gain insight into the underlying pathophysiology of metopic synostosis and associated neurodevelopmental disorders, we aimed to investigate brain volumes of non-syndromic metopic synostosis patients using preoperative MRI brain scans. MRI brain scans were processed with HyperDenseNet to calculate total intracranial volume (TIV), total brain volume (TBV), total grey matter volume (TGMV), total white matter volume (TWMV) and total cerebrospinal fluid volume (TCBFV). We compared global brain volumes of patients with controls corrected for age and sex using linear regression. Lobe-specific grey matter volumes were assessed in secondary analyses. We included 45 metopic synostosis patients and 14 controls (median age at MRI 0.56 years [IQR 0.36] and 1.1 years [IQR 0.47], respectively). We found no significant differences in TIV, TBV, TGMV or TCBFV in patients compared to controls. TWMV was significantly smaller in patients (-62,233 mm3 [95% CI = -96,968; -27,498], Holm-corrected p = 0.004), and raw data show an accelerated growth pattern of white matter in metopic synostosis patients. Grey matter volume analyses per lobe indicated increased cingulate (1378 mm3 [95% CI = 402; 2355]) and temporal grey matter (4747 [95% CI = 178; 9317]) volumes in patients compared to controls. To conclude, we found smaller TWMV with an accelerated white matter growth pattern in metopic synostosis patients, similar to white matter growth patterns seen in autism. TIV, TBV, TGMV and TCBFV were comparable in patients and controls. Secondary analyses suggest larger cingulate and temporal lobe volumes. These findings suggest a generalized intrinsic brain anomaly in the pathophysiology of neurodevelopmental disorders associated with metopic synostosis.

Five-Year Serial Brain MRI Analysis of Military Members Exposed to Chronic Sub-Concussive Overpressures.

BACKGROUND: The Canadian Special Operations Forces Command conducts explosives operations and training which exposes members to explosive charges at close proximity. This 5-year longitudinal trial was conducted in follow-up to our initial trial which examined military breachers with MRI and EEG pre and post blast exposure. PURPOSE: To examine brain MRI findings in military personnel exposed to multiple repeated blast exposures. STUDY TYPE: Five-year longitudinal prospective trial. POPULATION: Ninety-two males aged 23-42 with an average of 9.4 years of blast exposure. FIELD STRENGTH/SEQUENCE: 3 T brain MRI/T1-weighted 3D with reconstruction in three planes, T2-weighted, T2-weighted fluid attenuated inversion recovery (FLAIR) 3D with reconstruction in three planes, T2-weighted gradient spin echo (GRE), saturation weighted images, DWI and ADC maps, diffusion tensor imaging. ASSESSMENT: All MRI scans were interpreted by the two neuroradiologists and one neuroradiology Fellow in a blinded fashion using a customized neuroradiology reporting form. STATISTICAL TESTS: Matching parametric statistics represented the number of participants whose brain parameters improved or deteriorated over time. Odds ratio (OR) and 95% confidence intervals (CI) were computed using log regression modeling to determine volume loss, white matter lesions, hemosiderosis, gliosis, cystic changes and enlarged Virchow Robin (VR) spaces. A Kappa (κ) statistic with a 95% CI was calculated to determine rater variability between readers. RESULTS: A significant deterioration was observed in volume loss (OR = 1.083, 95% CI 0.678-1.731, permutation test), white matter changes (OR: 0.754, 95% CI 0.442-1.284, permutation test), and enlargement of VR spaces (OR: 0.775, 95% CI 0.513-1.171). Interrater reliability was low: κ = 0.283, 0.156, and 0.557 for volume loss, white matter changes, and enlargement of VR spaces, respectively. DATA CONCLUSION: There were significant changes in brain volume, white matter lesions, and enlargement of VR spaces. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Cross-sectional associations between 24-hour time-use composition, grey matter volume and cognitive function in healthy older adults.

BACKGROUND: Increasing physical activity (PA) is an effective strategy to slow reductions in cortical volume and maintain cognitive function in older adulthood. However, PA does not exist in isolation, but coexists with sleep and sedentary behaviour to make up the 24-hour day. We investigated how the balance of all three behaviours (24-hour time-use composition) is associated with grey matter volume in healthy older adults, and whether grey matter volume influences the relationship between 24-hour time-use composition and cognitive function. METHODS: This cross-sectional study included 378 older adults (65.6 ± 3.0 years old, 123 male) from the ACTIVate study across two Australian sites (Adelaide and Newcastle). Time-use composition was captured using 7-day accelerometry, and T1-weighted magnetic resonance imaging was used to measure grey matter volume both globally and across regions of interest (ROI: frontal lobe, temporal lobe, hippocampi, and lateral ventricles). Pairwise correlations were used to explore univariate associations between time-use variables, grey matter volumes and cognitive outcomes. Compositional data analysis linear regression models were used to quantify associations between ROI volumes and time-use composition, and explore potential associations between the interaction between ROI volumes and time-use composition with cognitive outcomes. RESULTS: After adjusting for covariates (age, sex, education), there were no significant associations between time-use composition and any volumetric outcomes. There were significant interactions between time-use composition and frontal lobe volume for long-term memory (p = 0.018) and executive function (p = 0.018), and between time-use composition and total grey matter volume for executive function (p = 0.028). Spending more time in moderate-vigorous PA was associated with better long-term memory scores, but only for those with smaller frontal lobe volume (below the sample mean). Conversely, spending more time in sleep and less time in sedentary behaviour was associated with better executive function in those with smaller total grey matter volume. CONCLUSIONS: Although 24-hour time use was not associated with total or regional grey matter independently, total grey matter and frontal lobe grey matter volume moderated the relationship between time-use composition and several cognitive outcomes. Future studies should investigate these relationships longitudinally to assess whether changes in time-use composition correspond to changes in grey matter volume and cognition.

Brain volume loss in relapsing multiple sclerosis: indirect treatment comparisons of available disease-modifying therapies.

BACKGROUND: Brain volume loss (BVL) has been identified as a predictor of disability progression in relapsing multiple sclerosis (RMS). As many available disease-modifying treatments (DMTs) have shown an effect on slowing BVL, this is becoming an emerging clinical endpoint in RMS clinical trials. METHODS: In this study, a systematic literature review was conducted to identify BVL results from randomized controlled trials of DMTs in RMS. Indirect treatment comparisons (ITCs) were conducted to estimate the relative efficacy of DMTs on BVL using two approaches: a model-based meta-analysis (MBMA) with adjustment for measurement timepoint and DMT dosage, and a network meta-analysis (NMA). RESULTS: In the MBMA, DMTs associated with significantly reduced BVL versus placebo at two years included fingolimod (mean difference [MD] = 0.25; 95% confidence interval [CI] = 0.15 - 0.36), ozanimod (MD = 0.26; 95% CI = 0.12 - 0.41), teriflunomide (MD = 0.38; 95% CI = 0.20 - 0.55), alemtuzumab (MD = 0.38; 95% CI = 0.10 - 0.67) and ponesimod (MD = 0.71; 95% CI = 0.48 - 0.95), whereas interferons and natalizumab performed the most poorly. The results of NMA analysis were generally comparable with those of the MBMA. CONCLUSIONS: Limitations of these analyses included the potential for confounding due to pseudoatrophy, and a lack of long-term clinical data for BVL. Our findings suggest that important differences in BVL may exist between DMTs. Continued investigation of BVL in studies of RMS is important to complement traditional disability endpoints, and to foster a better understanding of the mechanisms by which DMTs can slow BVL.

Mapping brain volume change across time in primary-progressive multiple sclerosis.

PURPOSE: Detection and prediction of the rate of brain volume loss with age is a significant unmet need in patients with primary progressive multiple sclerosis (PPMS). In this study we construct detailed brain volume maps for PPMS patients. These maps compare age-related changes in both cortical and sub-cortical regions with those in healthy individuals. METHODS: We conducted retrospective analyses of brain volume using T1-weighted Magnetic Resonance Imaging (MRI) scans of a large cohort of PPMS patients and healthy subjects. The volume of brain parenchyma (BP), cortex, white matter (WM), deep gray matter, thalamus, and cerebellum were measured using the robust SynthSeg segmentation tool. Age- and gender-related regression curves were constructed based on data from healthy subjects, with the 95% prediction interval adopted as the normality threshold for each brain region. RESULTS: We analyzed 495 MRI scans from 169 PPMS patients, aged 20-79 years, alongside 563 exams from healthy subjects aged 20-86. Compared to healthy subjects, a higher proportion of PPMS patients showed lower than expected brain volumes in all regions except the cerebellum. The most affected areas were BP, WM, and thalamus. Lower brain volumes correlated with longer disease duration for BP and WM, and higher disability for BP, WM, cortex, and thalamus. CONCLUSIONS: Constructing age- and gender-related brain volume maps enabled identifying PPMS patients at a higher risk of brain volume loss. Monitoring these high-risk patients may lead to better treatment decisions and improve patient outcomes.

Associations of tau, Aß, and brain volume of the Papez circuit with cognition in Alzheimer's disease.

This study aimed to investigate the cross-sectional associations between regional Alzheimer's disease (AD) biomarkers, including tau, ß-amyloid (Aß), and brain volume, within the Papez circuit, and neuropsychological functioning across the preclinical and clinical spectrum of AD. We utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including 251 Aß-positive participants. Participants were categorized into three groups based on the Clinical Dementia Rating (CDR): 73 individuals with preclinical AD (CDR = 0), 114 with prodromal AD (CDR = 0.5), and 64 with clinical AD dementia (CDR ≥ 1). Linear regression analyses, adjusted for age, gender, and education years, were employed to evaluate the associations between five regions of interest (the hippocampus, para-hippocampus, entorhinal cortex, posterior cingulate cortex, and thalamus) and five neuropsychological tests across the three imaging modalities. In the preclinical stage of AD, flortaucipir PET was associated with impaired global cognition and episodic memory (range standardized ß = 0.255-0.498, p < 0.05 corrected for multiple comparisons), while florbetapir PET and brain volume were marginally related to global cognition (range standardized ß = 0.221-0.231, p < 0.05). In the clinical stages of AD (prodromal and dementia), both increased flortaucipir uptake and decreased brain volume were significantly associated with poorer global neuropsychological and episodic memory performance (range standardized ß = 0.222-0.621, p < 0.05, most regions of interest survived correction for multiple comparisions). However, a slight relationship was observed between florbetapir uptake and poorer global cognitive function. The regions most affected by flortaucipir PET were the hippocampus, para-hippocampus, and posterior cingulate cortex. During the clinical stages, the hippocampus and entorhinal cortex exhibited the most significant volumetric changes. Tau PET and brain volume measurements within the Papez circuit are more sensitive indicators of early cognitive deficits in AD than Aß PET. Furthermore, during the clinical stages of AD, both flortaucipir PET and brain volume of the Papez circuit are closely correlated with cognitive decline. These findings underscore the importance of integrating multiple biomarkers for the comprehensive evaluation of AD pathology and its impact on cognition.

Cortical thickness, gray matter volume, and cognitive performance: a crosssectional study of the moderating effects of age on their interrelationships.

In a sample comprising younger, middle-aged, and older cognitively healthy adults (N = 375), we examined associations between mean cortical thickness, gray matter volume (GMV), and performance in 4 cognitive domains-memory, speed, fluency, and crystallized intelligence. In almost all cases, the associations were moderated significantly by age, with the strongest associations in the older age group. An exception to this pattern was identified in a younger adult subgroup aged <23 years when a negative association between cognitive performance and cortical thickness was identified. Other than for speed, all associations between structural metrics and performance in specific cognitive domains were fully mediated by mean cognitive ability. Cortical thickness and GMV explained unique fractions of the variance in mean cognitive ability, speed, and fluency. In no case, however, did the amount of variance jointly explained by the 2 metrics exceed 7% of the total variance. These findings suggest that cortical thickness and GMV are distinct correlates of domain-general cognitive ability, that the strength and, for cortical thickness, the direction of these associations are moderated by age, and that these structural metrics offer only limited insights into the determinants of individual differences in cognitive performance across the adult lifespan.

Predicting mild cognitive impairments from cognitively normal brains using a novel brain age estimation model based on structural magnetic resonance imaging.

Brain age prediction is a practical method used to quantify brain aging and detect neurodegenerative diseases such as Alzheimer's disease (AD). However, very few studies have considered brain age prediction as a biomarker for the conversion of cognitively normal (CN) to mild cognitive impairment (MCI). In this study, we developed a novel brain age prediction model using brain volume and cortical thickness features. We calculated an acceleration of brain age (ABA) derived from the suggested model to estimate different diagnostic groups (CN, MCI, and AD) and to classify CN to MCI and MCI to AD conversion groups. We observed a strong association between ABA and the 3 diagnostic groups. Additionally, the classification models for CN to MCI conversion and MCI to AD conversion exhibited acceptable and robust performances, with area under the curve values of 0.66 and 0.76, respectively. We believe that our proposed model provides a reliable estimate of brain age for elderly individuals and can identify those at risk of progressing from CN to MCI. This model has great potential to reveal a diagnosis associated with a change in cognitive decline.

Striatal brain volume linked to severity of substance use in high-risk incarcerated youth.

Substance use disorders among juveniles are a major public health concern and are often intertwined with other psychosocial risk factors including antisocial behavior. Identifying etiological risks and mechanisms promoting substance use disorders remains a high priority for informing more focused interventions in high-risk populations. The present study examined brain gray matter structure in relation to substance use severity among n = 152 high-risk, incarcerated boys (aged 14-20). Substance use severity was positively associated with gray matter volume across several frontal/striatal brain regions including amygdala, pallidum, putamen, insula, and orbitofrontal cortex. Effects were apparent when using voxel-based-morphometric analysis, as well as in whole-brain, data-driven, network-based approaches (source-based morphometry). These findings support the hypothesis that elevated gray matter volume in striatal reward circuits may be an endogenous marker for vulnerability to severe substance use behaviors among youth.

The association between adverse childhood experiences and alterations in brain volume and cortical thickness in adults with alcohol use disorder.

BACKGROUND: Previous studies have established a connection between adverse childhood experiences (ACE) and alcohol use disorder (AUD), both of which are associated with alterations in grey matter volume (GMV) and cortical thickness (CT). The current study aimed to assess the neurobiological impact of ACE specifically in the context of AUD, as well as the role of maltreatment type (i.e., abuse or neglect) and timing. METHODS: Structural MRI data were collected from 35 adults with AUD (mean age: 40; 31% female) and 28 healthy controls (mean age: 36; 61% female). ACE were assessed retrospectively using the Childhood Trauma Questionnaire, and the Maltreatment and Abuse Chronology interview. Global and regional GMV and CT were estimated using voxel- and surface-based morphometry. RESULTS: Relative to the healthy controls, the AUD group had significantly reduced CT in the left inferior frontal gyrus, left circular sulcus of the insula and subcentral gyrus and sulci (cluster C1), and in the central sulcus and precentral gyrus (cluster C2). Within the AUD group, a reduction of CT in cluster C1 was significantly associated with higher severity of ACE and AUD. Type and timing analyses revealed a significant association between higher levels of abuse at ages 13 to 15 and reduced CT in cluster C1 within the AUD group. CONCLUSIONS: In adults with AUD, abuse experienced during early adolescence is associated with reduced CT in regions involved in inhibitory control, indicating the potential relevance of cognitive pathways in the association between ACE and AUD. Longitudinal studies are needed to confirm and expand upon current findings.

Deep learning-based super-resolution of structural brain MRI at 1.5 T: application to quantitative volume measurement.

OBJECTIVE: This study investigated the feasibility of using deep learning-based super-resolution (DL-SR) technique on low-resolution (LR) images to generate high-resolution (HR) MR images with the aim of scan time reduction. The efficacy of DL-SR was also assessed through the application of brain volume measurement (BVM). MATERIALS AND METHODS: In vivo brain images acquired with 3D-T1W from various MRI scanners were utilized. For model training, LR images were generated by downsampling the original 1 mm-2 mm isotropic resolution images. Pairs of LR and HR images were used for training 3D residual dense net (RDN). For model testing, actual scanned 2 mm isotropic resolution 3D-T1W images with one-minute scan time were used. Normalized root-mean-square error (NRMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were used for model evaluation. The evaluation also included brain volume measurement, with assessments of subcortical brain regions. RESULTS: The results showed that DL-SR model improved the quality of LR images compared with cubic interpolation, as indicated by NRMSE (24.22% vs 30.13%), PSNR (26.19 vs 24.65), and SSIM (0.96 vs 0.95). For volumetric assessments, there were no significant differences between DL-SR and actual HR images (p > 0.05, Pearson's correlation > 0.90) at seven subcortical regions. DISCUSSION: The combination of LR MRI and DL-SR enables addressing prolonged scan time in 3D MRI scans while providing sufficient image quality without affecting brain volume measurement.

Serum NfL and GFAP as biomarkers of progressive neurodegeneration in TBI.

BACKGROUND: We examined spatial patterns of brain atrophy after mild, moderate, and severe traumatic brain injury (TBI), the relationship between progression of brain atrophy with initial traumatic axonal injury (TAI), cognitive outcome, and with serum biomarkers of brain injury. METHODS: A total of 143 patients with TBI and 43 controls were studied cross-sectionally and longitudinally up to 5 years with multiple assessments, which included brain magnetic resonance imaging, cognitive testing, and serum biomarkers. RESULTS: TBI patients showed progressive volume loss regardless of injury severity over several years, and TAI was independently associated with accelerated brain atrophy. Cognitive performance improved over time. Higher baseline serum neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) were associated with greater rate of brain atrophy over 5 years. DISCUSSSION: Spatial patterns of atrophy differ by injury severity and TAI is associated with the progression of brain atrophy. Serum NfL and GFAP show promise as non-invasive prognostic biomarkers of progressive neurodegeneration in TBI. HIGHLIGHTS: In this longitudinal study of patient with mild, moderate, and severe traumatic brain injury (TBI) who were assessed with paired magnetic resonance imaging (MRI), blood biomarkers, and cognitive assessments, we found that brain atrophy after TBI is progressive and continues for many years even after a mild head trauma without signs of brain injury on conventional MRI. We found that spatial pattern of brain atrophy differs between mild, moderate, and severe TBI, where in patients with mild TBI , atrophy is mainly seen in the gray matter, while in those with moderate to severe brain injury atrophy is predominantly seen in the subcortical gray matter and whiter matter. Cognitive performance improves over time after a TBI. Serum measures of neurofilament light or glial fibrillary acidic protein are associated with progression of brain atrophy after TBI.

Thinner inner retinal layers are associated with lower cognitive performance, lower brain volume, and altered white matter network structure-The Maastricht Study.

INTRODUCTION: The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration. METHODS: We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency). RESULTS: After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency. DISCUSSION: The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.