Brain Morphometry Research Articles

Hearing Function Moderates Age-Related Differences in Brain Morphometry in the HCP Aging Cohort.

There are well-established relationships between aging and neurodegenerative changes, and between aging and hearing loss. The goal of this study was to determine how structural brain aging is influenced by hearing loss. Human Connectome Project Aging data were analyzed, including T1-weighted Magnetic Resonance Imaging (MRI) and Words in noise (WIN) thresholds (n = 623). Freesurfer extracted gray and white matter volume, and cortical thickness, area, and curvature. Linear regression models targeted (1) interactions between age and WIN threshold and (2) correlations with WIN threshold adjusted for age, both corrected for false discovery rate (pFDR < 0.05). WIN threshold moderated age-related increase in volume in bilateral inferior lateral ventricles, with a higher threshold associated with increased age-related ventricle expansion. Age-related differences in the occipital cortex also increased with higher WIN thresholds. When controlling for age, high WIN threshold was correlated with reduced cortical thickness in Heschl's gyrus, calcarine sulcus, and other sensory regions, and reduced temporal lobe white matter. Older volunteers with poorer hearing and cognitive scores had the lowest volume in left parahippocampal white matter. These results suggest that better hearing is associated with reduced age-related differences in medial temporal lobe, while better hearing at any age is associated with greater cortical tissue in auditory and other sensory regions. Future longitudinal studies are needed to assess the causal nature of these relationships, but these results indicate interventions that preserve or protect hearing function may combat some neurodegenerative changes in aging.

Neuro-pharmacological Assessment of Coleus forskohlii for Anti-compulsive Activity in Swiss Albino Mice

Background: Obsessive-Compulsive Disorder (OCD) is a common psychiatric illness characterized by obsessions or compulsions that significantly disrupt or impair daily functioning. Coleus forskohlii, a significant medicinal crop, has forskolin in its roots. It is utilized extensively as food and medicine all over the world. Coleus forskohlii has reputed medicinal uses, which include antidepressant, antiaggregant, cAMP-genic, anticancer, etc. Objective: This study used mice models of marble burying and nestlet shredding to assess the potential efficacy of Coleus forskohlii against obsessive-compulsive disorder. 8-hydroxy-2-(di-npropylamino) tetralin (8-OH-DPAT) induced compulsive checking can demonstrate OCD-like repetitive and obsessive behavior as well as neurotransmitter imbalance (serotonin). Methods: Each group had six mice, and the therapy was administered to the animals for a total of 15 days. On days 1, 7, and 14, the marble burying test was assessed for 30 minutes, and on days 2, 8 and 15, the nestlet shredding test was assessed for 30 minutes. The T-maze paradigm was used to assess anti-OCD activity. The brain histology and morphometry were also performed. Results: When compared to the control group, treatments with Coleus forskohlii (50 and 100 mg/kg, p.o.) significantly enhanced performance on both behavior tests. The SAB score is dramatically increased following the administration of the 8-OH-DPAT (2 mg/kg, i.p.) group. Coleus forskohlii (50 and 100 mg/kg, p.o.) and fluoxetine (15 mg/kg, p.o.) groups showed significantly lowered results. Animals treated with 8-OH-DPAT showed a considerable reduction in serotonin levels. Following Coleus forskohlii administration, the histology of the brain tissues showed normal morphological structure with no toxicity or abnormalities. Conclusion: The combination of all these findings points to Coleus forskohlii delivering a possible therapeutic option for the treatment of OCD. The identification and anticompulsive properties of the components from Coleus forskohlii should be the main aim of future studies.

FONDUE: Robust resolution-invariant denoising of MR Images using Nested UNets

Abstract Recent human magnetic resonance imaging (MRI) studies continually push the boundaries of spatial resolution as a means to enhance levels of neuroanatomical detail and increase the accuracy and sensitivity of derived brain morphometry measures. However, acquisitions required to achieve these resolutions have a higher noise floor, potentially impacting segmentation and morphometric analysis results. This study proposes a novel, fast, robust, and resolution-invariant deep learning method to denoise structural human brain MRIs. We explore denoising of T1-weighted (T1w) brain images from varying field strengths (1.5T to 7T), voxel sizes (1.2mm to 250µm), scanner vendors (Siemens, GE, and Phillips), and diseased and healthy participants from a wide age range (young adults to aging individuals). Our proposed Fast-Optimized Network for Denoising through residual Unified Ensembles (FONDUE) method demonstrated stable denoising capabilities across multiple resolutions with performance on par or superior to the state-of-the-art methods while being several orders of magnitude faster at low relative cost when using a dedicated Graphics Processing Unit (GPU). FONDUE achieved the best performance on at least one of the four denoising-performance metrics on all the test datasets used, showing its generalization capabilities and stability. Due to its high-quality performance, robustness, fast execution times, and relatively low-GPU memory requirements, as well as its open-source public availability, FONDUE can be widely used for structural MRI denoising, especially in large-cohort studies. We have made the FONDUE repository and all training and evaluation scripts as well as the trained weights available at https://github.com/waadgo/FONDUE.

Brain morphometry and chronic inflammation in Bangladeshi children growing up in extreme poverty

Abstract Over three hundred million children live in environments of extreme poverty, and the biological and psychosocial hazards endemic to these environments often expose these children to infection, disease, and inflammatory responses. Chronic inflammation in early childhood has been associated with diminished cognitive outcomes, and despite this established relationship, the mechanisms explaining how inflammation affects brain development are not well known. Importantly, the prevalence of chronic inflammation in areas of extreme poverty raises the possibility that it may also serve as a mechanism explaining the known relationship between low socioeconomic status (SES) and altered brain development. To examine these potential pathways, seventy-nine children growing up in an extremely poor, urban area of Bangladesh underwent MRI scanning at 6 years of age. Structural brain images were submitted to Mindboggle software, a Docker-compliant and high-reproducibility tool for regional estimations of volume, surface area, cortical thickness, sulcal depth, and mean curvature. C-reactive protein was assayed at eight time points between infancy and 5 years of age, and the frequency with which children had elevated concentrations of inflammatory marker represented the measure of chronic inflammation. Childhood SES was measured with maternal education and income-to-needs (i.e., monthly household income divided by the number of household members). Chronic inflammation predicted volume in bilateral basal ganglia structures and mediated the link between maternal education and bilateral putamen volumes. These findings suggest that chronic inflammation is associated with brain morphometry in the basal ganglia, predominantly the putamen, and further offers inflammation as a potential mechanism linking SES to brain development.

Diagnosis of Alzheimer's Disease in Clinical Practice: Time to Incorporate Biomarkers?

Hippocampal dysfunction is associated with early clinical signs of Alzheimer's disease (AD). Due to the limited availability or invasiveness of current biomarkers, the AD diagnosis is usually based on cognitive assessment and structural brain imaging. The recent study by Lalive and colleagues examined the specificity of brain morphometry for the AD diagnosis in a memory clinic cohort with hippocampal-type amnestic syndrome. The results indicate that memory deficits and hippocampal atrophy are similar in AD and non-AD patients, highlighting their low diagnostic specificity. These findings challenge the traditional AD diagnosis and underscore the need for biomarkers to differentiate specific neuropathological entities.

Outer Retinal Thinning is Associated With Brain Atrophy in Early Age-Related Macular Degeneration

Both retinal changes and age-related macular degeneration (AMD) have been shown to be associated with Alzheimer's disease and related dementias (ADRD). In AMD, the outer retina is impacted significantly and early, but little is known about its association with cognition or changes in brain morphometry. This study investigates the relationship between retinal and brain morphometry in older adults with early and intermediate AMD. Cross-sectional study. Adults ≥70 years with normal, early, and intermediate AMD were recruited from Callahan Eye Hospital Clinics at the University of Alabama at Birmingham. Participants underwent cognitive testing, optical coherence tomography, and magnetic resonance imaging. Associations of retinal layer thickness with brain volume and thickness of specific brain regions were evaluated utilizing multivariable linear regression. The relevance of retinal thickness variables in brain volumetrics was quantified using least absolute shrinkage and selection operator regression models. Correlations between demographic variables, cognitive scores, and brain morphometry were evaluated. Participants with thinner outer retina had significantly smaller hippocampus (β = 0.019, P = .022), lower occipital cortex regions of interest (occipital ROIs) thickness (β = 5.68, P = .020), and lower cortical thickness in ADRD-related brain regions (β = 7.72, P = .006). People with thinner total retina had significantly lower occipital ROIs (β = 3.19, P = .009) and ADRD-related brain region (β = 3.94, P = .005) thickness. Outer retinal thickness in the outer Early Treatment of Diabetic Retinopathy Study ring was the most frequently reported retinal variable associated with brain morphometry on least absolute shrinkage and selection operator regression. Total gray matter volume showed positive correlations with education (Pearson's r = 0.30, P = .022). In older adults with normal retinal aging and early and intermediate AMD, thinner outer retina had specific associations with brain regions primarily involved in vision and cognition, such as lower hippocampal volume and lower thickness of the occipital ROIs and brain regions known to show early structural changes in dementia.

Neonicotinoid pesticides: evidence of developmental neurotoxicity from regulatory rodent studies.

Neonicotinoids are the most widely used class of insecticides in the United States (U.S.). and the world. Consistent with their high use and persistence, neonicotinoids are often found contaminating drinking water and food. They are also detected in human urine, breast milk, amniotic and cerebrospinal fluids, as well as the brains of treated rodents. Neonicotinoids were once thought to pose little neurotoxic risk to humans, but a growing body of research challenges that assumption. In this study we provide the first comprehensive assessment of unpublished rodent developmental neurotoxicity (DNT) studies on five neonicotinoids that were submitted to the U.S. Environmental Protection Agency (EPA) by neonicotinoid manufacturers. Groups of female rats were administered three different doses of a neonicotinoid during pregnancy and lactation, and their offspring subjected to various neurological tests and brain measurements. We identified nicotine-like effects such as reduced brain size, indicative of neuronal cell loss. Statistically significant shrinkage of brain tissue was observed in high-dose offspring for five neonicotinoids: acetamiprid, clothianidin, imidacloprid, thiacloprid, and thiamethoxam. Two brain regions reduced in the rodent studies-the corpus callosum and caudate-putamen-tend to be smaller in people diagnosed with attention-deficit hyperactivity disorder (ADHD), and in children of mothers who smoked during pregnancy, suggesting a possible link between perinatal neonicotinoid exposure and ADHD. A decreased auditory startle reflex was reported for acetamiprid at all doses and was statistically significant in the mid- and high-dose offspring, and for clothianidin in juvenile high-dose females. No mid- or low-dose brain morphometric data were submitted for acetamiprid, imidacloprid, or thiacloprid. Thiamethoxam mid- and low-dose brain morphometric data were provided to EPA upon request. Only partial mid-dose brain morphometry data were submitted for clothianidin, but no low-dose data. Yet despite this lack of data, EPA concluded that only the high-dose brain morphometric effects were treatment-related-setting the mid-dose as the study's No Observed Adverse Effect Level (NOAEL) or failing to find a definitive NOAEL for acetamiprid, clothianidin, imidacloprid, thiacloprid and thiamethoxam. We found numerous deficiencies in EPA's regulatory oversight and data analyses. EPA dismissed statistically significant adverse effects, accepted substandard DNT studies despite lack of valid positive control data, and allowed neonicotinoid registrants to unduly influence agency decision-making. We conclude that perinatal exposure to neonicotinoids and their metabolites induces adverse, nicotine-like neurotoxic effects in rodent bioassays, and that the exposure limits set by EPA for human exposure are either not protective or not supported by available neurotoxicity data. We propose regulatory changes to empower EPA to better protect public health from developmental neurotoxins like neonicotinoids.

Maternal Nutrition during Pregnancy and Offspring Brain Development: Insights from Neuroimaging.

Maternal nutrition during pregnancy is known to be important for offspring growth and health and has also been increasingly recognized for shaping offspring brain development. On the other hand, recent advancements in brain imaging technology have provided unprecedented insights into fetal, neonatal, and pediatric brain morphometry and function. This review synthesizes the current literature regarding the impact of maternal nutrition on offspring brain development, with a specific focus on findings from neuroimaging studies. The diverse effects of maternal nutrients intake or status during pregnancy on neurodevelopmental outcomes in children are discussed. Neuroimaging evidence showed associations between maternal nutrition such as food categories, macronutrients, and micronutrients including vitamins and minerals during pregnancy and child brain imaging features measured using imaging techniques such as ultrasound, magnetic resonance imaging (MRI), electroencephalography (EEG), and magnetoencephalography (MEG). This review demonstrates the capability of neuroimaging in characterizing how maternal nutrition during pregnancy impacts structure and function of the developing brain that may further influence long-term neuropsychological, cognitive, and behavioral outcomes in children. It aims to inspire future research utilizing neuroimaging to deepen our understanding of the critical impacts of maternal nutrition during pregnancy on offspring brain development.

The Douglas-Bell Canada Brain Bank Post-mortem Brain Imaging Protocol

Magnetic resonance imaging (MRI) is a valuable non-invasive tool that has been widely used for in vivo investigations of brain morphometry and microstructural characteristics. Post-mortem MRIs can provide complementary anatomical and microstructural information to in vivo imaging and ex vivo neuropathological assessments without compromising the sample for future investigations. We have developed a post-mortem MRI protocol for the brain specimens of the Douglas-Bell Canada Brain Bank (DBCBB), the largest brain bank in Canada housing over 3000 neurotypical and diseased brain specimens, that allows for acquisition of high-resolution 3T and 7T MRIs. Our protocol can be used to scan DBCBB specimens with minimal tissue manipulation, allowing for feasibly scanning large numbers of post-mortem specimens while retaining the quality of the tissue for downstream histology and immunohistochemistry assessments. We demonstrate the robustness of this protocol despite the dependency of image quality on fixation by acquiring data on the first day of extraction and fixation, to over twenty years post fixation. The acquired images can be used to perform volumetric segmentations, cortical thickness measurements, and quantitative analyses which can be potentially used to link MRI-derived and ex vivo histological measures, assaying both the normative organization of the brain and ex vivo measures of pathology.

Comparative analysis of cortical anatomy inmale participants with internet gaming disorder or tobacco use disorder: Insights fromnormative modeling.

Research on individual differences in brain structural features of internet gaming disorder (IGD) and established addictions such as tobacco use disorder (TUD) is currently limited. This study utilized normative modeling to analyze the cortical thickness (CT) development patterns of male patients with IGD and TUD, aiming to provide further insights into whether IGD qualifies as an addiction. Surface-based brain morphometry (SBM) was used to calculate CT from T1-weighted magnetic resonance imaging data of 804 male participants (665 healthy individuals, 68 IGD and 71 TUD). Gaussian process regression was employed to generate normative models of CT development. Deviation maps were produced to depict deviations of IGD and TUD participants from the typical developmental patterns. Both addiction groups exhibited widespread cortical thinning, particularly in regions such as the bilateral temporal pole and medial orbitofrontal cortex. The TUD group demonstrated a higher degree of individualization and limited spatial overlap compared to the IGD group. Opposite trends in CT changes were observed between the two groups in the bilateral pericalcarine cortex and pars triangularis. These findings regarding the similarities and differences between IGD and TUD provide support for the idea that IGD shares common features with substance-related addictions and contribute to a deeper understanding of the neural mechanisms underlyingIGD.

Glibenclamide alters the brain protein profile and morphometry of hippocampal regions in mice fed with a high-refined carbohydrate diet

A high-refined carbohydrate diet (HC diet) has shown impacts not only on metabolic disorders, but also on cognitive and behavioral functions. However, its effects at the protein and morphological level in the brain are not known. In order to investigate the differential expression of proteins in the brain of Balb/c mice fed with a HC diet and treated or not with glibenclamide, biochemical and histological assays were performed. The brains of animals fed for eight weeks with a standard rodent diet or HC diet, and treated or not with glibenclamide for four weeks were homogenized and the supernatant was subjected to 12.5% ​​SDS-PAGE. The brains were also blocked and 3 μm sections were stained with Hematoxylin-Eosin and analyzed using light microscopy. The electrophoretic profile of samples from untreated animals revealed protein expression without significant differences, while the group treated with glibenclamide revealed protein bands with differential expression (44.8, 42.2 and 39.8 KDa). The proteins were predicted using a bioinformatic tool and it is suggested that, for the most part, they are related to the energy metabolism of the brain. Histological analysis of the hippocampus demonstrated similarities between animals fed with a standard diet and HC diet, but with differences in the number of neurons in the CA2 and CA3 regions, and a tendency to cell death in the dentate gyrus of animals group HC diet. These results revealed one of the regions of the brain affected by excess carbohydrates, as well as candidate proteins for proteomic analysis to further investigate the effects of dietary sugars on molecular mechanisms and neurogenesis in the hippocampus.

Cognitive Polygenic Index is Associated with Occupational Complexity over and above Brain Morphometry.

Although the impact of occupation on cognitive skills has been extensively studied, there is limited research examining if genetically predicted cognitive score may influence occupation. We examined the association between Cognitive Polygenic Index (PGI) and occupation, including the role of brain measures. Participants were recruited for the Reference Ability Neural Network and the Cognitive Reserve studies. Occupational complexity ratings for Data, People, or Things came from the Dictionary of Occupational Titles. A previously-created Cognitive PGI and linear regression models were used for the analyses. Age, sex, education, and the first 20 genetic Principal Components (PCs) of the sample were covariates. Total cortical thickness and total gray matter volume were further covariates. We included 168 white-ethnicity participants, 20-80 years old. After initial adjustment, higher Cognitive PGI was associated with higher Data complexity (B=-0.526, SE = 0.227, Beta= -0.526 p = 0.022, R2 = 0.259) (lower score implies higher complexity). Associations for People or Things were not significant. After adding brain measures, association for Data remained significant (B=-0.496, SE: 0.245, Beta= -0.422, p = 0.045, R2 = 0.254). Similarly, for a further, fully-adjusted analysis including all the three occupational complexity measures (B=-0.568, SE = 0.237, Beta= -0.483, p = 0.018, R2 = 0.327). Cognitive genes were associated with occupational complexity over and above brain morphometry. Working with Data occupational complexity probably acquires higher cognitive status, which can be significantly genetically predetermined.

Non-linear development of brain morphometry in child and adolescent offspring of individuals with bipolar disorder or schizophrenia

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at increased risk of developing psychopathology. Structural brain alterations have been found in child and adolescent offspring of patients with bipolar disorder and schizophrenia, but the developmental trajectories of brain anatomy in this high-familial-risk population are still unclear. 300 T1-weighted scans were obtained of 187 offspring of at least one parent diagnosed with bipolar disorder (n=80) or schizophrenia (n=53) and offspring of parents without severe mental illness (n=54). The age range was 8 to 23 years old; 113 offspring underwent two scans. Global brain measures and regional cortical thickness and surface area were computed. A generalized additive mixed model was used to capture non-linear age trajectories. Offspring of parents with schizophrenia had smaller total brain volume than offspring of parents with bipolar disorder (d=-0.20, p=0.004) and control offspring (d=-0.22, p=0.005) and lower mean cortical thickness than control offspring (d=-0.23, p<0.001). Offspring of parents with schizophrenia showed differential age trajectories of mean cortical thickness and cerebral white matter volume compared with control offspring (both p’s=0.003). Regionally, offspring of parents with schizophrenia had a significantly different trajectory of cortical thickness in the middle temporal gyrus versus control offspring (p<0.001) and bipolar disorder offspring (p=0.001), which was no longer significant after correcting for mean cortical thickness. These findings suggest that particularly familial high risk of schizophrenia is related to reductions and deviating developmental trajectories of global brain structure measures, which were not driven by specific regions.

The causal relationship between human brain morphometry and knee osteoarthritis: a two-sample Mendelian randomization study.

Knee Osteoarthritis (KOA) is a prevalent and debilitating condition affecting millions worldwide, yet its underlying etiology remains poorly understood. Recent advances in neuroimaging and genetic methodologies offer new avenues to explore the potential neuropsychological contributions to KOA. This study aims to investigate the causal relationships between brain-wide morphometric variations and KOA using a genetic epidemiology approach. Leveraging data from 36,778 UK Biobank participants for human brain morphometry and 487,411 UK Biobank participants for KOA, this research employed a two-sample Mendelian Randomization (TSMR) approach to explore the causal effects of 83 brain-wide volumes on KOA. The primary method of analysis was the Inverse Variance Weighted (IVW) and Wald Ratio (WR) method, complemented by MR Egger and IVW methods for heterogeneity and pleiotropy assessments. A significance threshold of p < 0.05 was set to determine causality. The analysis results were assessed for heterogeneity using the MR Egger and IVW methods. Brain-wide volumes with Q_pval < 0.05 were considered indicative of heterogeneity. The MR Egger method was employed to evaluate the pleiotropy of the analysis results, with brain-wide volumes having a p-value < 0.05 considered suggestive of pleiotropy. Our findings revealed significant causal associations between KOA and eight brain-wide volumes: Left parahippocampal volume, Right posterior cingulate volume, Left transverse temporal volume, Left caudal anterior cingulate volume, Right paracentral volume, Left paracentral volume, Right lateral orbitofrontal volume, and Left superior temporal volume. These associations remained robust after tests for heterogeneity and pleiotropy, underscoring their potential role in the pathogenesis of KOA. This study provides novel evidence of the causal relationships between specific brain morphometries and KOA, suggesting that neuroanatomical variations might contribute to the risk and development of KOA. These findings pave the way for further research into the neurobiological mechanisms underlying KOA and may eventually lead to the development of new intervention strategies targeting these neuropsychological pathways.

Amnestic Syndrome in Memory Clinics: Similar Morphological Brain Patterns in Older Adults with and without Alzheimer’s Disease

Background: Amnestic syndrome of the hippocampal type (ASHT) in Memory Clinics is a presentation common to Alzheimer’s disease (AD). However, ASHT can be found in other neurodegenerative disorders. Objective: To compare brain morphometry including hippocampal volumes between amnestic older adults with and without AD pathology and investigate their relationship with memory performance and cerebrospinal fluid (CSF) biomarkers. Methods: Brain morphometry of 92 consecutive patients (72.5±6.8 years old; 39% female) with Free and Cued Selective Recall Reminding Test (FCSRT) total recall &lt; 40/48 was assessed with an automated algorithm and compared between AD and non-AD patients, as defined by CSF biomarkers. Results: AD and non-AD patients presented comparable brain morphology. Total recall was associated to hippocampal volume irrespectively from AD pathology. Conclusions: Brain morphometry, including hippocampal volumes, is similar between AD and non-AD older adults with ASHT evaluated in a Memory Clinic, underlying the importance of using molecular biomarkers for the diagnosis of AD.

The gut-brain axis in individuals with alcohol use disorder: Anexploratory study of associations among clinical symptoms, brain morphometry, and the gut microbiome.

Alcohol use disorder (AUD) is commonly associated with distressing psychological symptoms. Pathologic changes associated with AUD have been described in both the gut microbiome and brain, but the mechanisms underlying gut-brain signaling in individuals with AUD are unknown. This study examined associations among the gut microbiome, brain morphometry, and clinical symptoms in treatment-seeking individuals with AUD. We performed a secondary analysis of data collected during inpatient treatment for AUD in subjects who provided gut microbiome samples and had structural brain magnetic resonance imaging (MRI; n = 16). Shotgun metagenomics sequencing was performed, and the morphometry of brain regions of interest was calculated. Clinical symptom severity was quantified using validated instruments. Gut-brain modules (GBMs) used to infer neuroactive signaling potential from the gut microbiome were generated in addition to microbiome features (e.g., alpha diversity and bacterial taxa abundance). Bivariate correlations were performed between MRI and clinical features, microbiome and clinical features, and MRI and microbiome features. Amygdala volume was significantly associated with alpha diversity and the abundance of several bacteria including taxa classified to Blautia, Ruminococcus, Bacteroides, and Phocaeicola. There were moderate associations between amygdala volume and GBMs, including butyrate synthesis I, glutamate synthesis I, and GABA synthesis I & II, but these relationships were not significant after false discovery rate (FDR) correction. Other bacterial taxa with shared associations to MRI features and clinical symptoms included Escherichia coli and Prevotella copri. We identified gut microbiome features associated with MRI morphometry and AUD-associated symptom severity. Given the small sample size and bivariate associations performed, these results require confirmation in larger samples and controls to provide meaningful clinical inferences. Nevertheless, these results will inform targeted future research on the role of the gut microbiome in gut-brain communication and how signaling may be altered in patients with AUD.

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency.

With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subject privacy, several algorithms have been developed to de-identify imaging data using blurring, defacing or refacing. Completely removing facial structures provides the best re-identification protection but can significantly impact post-processing steps, like brain morphometry. As an alternative, refacing methods that replace individual facial structures with generic templates have a lower effect on the geometry and intensity distribution of original scans, and are able to provide more consistent post-processing results by the price of higher re-identification risk and computational complexity. In the current study, we propose a novel method for anonymized face generation for defaced 3D T1-weighted scans based on a 3D conditional generative adversarial network. To evaluate the performance of the proposed de-identification tool, a comparative study was conducted between several existing defacing and refacing tools, with two different segmentation algorithms (FAST and Morphobox). The aim was to evaluate (i) impact on brain morphometry reproducibility, (ii) re-identification risk, (iii) balance between (i) and (ii), and (iv) the processing time. The proposed method takes 9 s for face generation and is suitable for recovering consistent post-processing results after defacing.

Distinct brain morphometry patterns revealed by deep learning improve prediction of post-stroke aphasia severity

BackgroundEmerging evidence suggests that post-stroke aphasia severity depends on the integrity of the brain beyond the lesion. While measures of lesion anatomy and brain integrity combine synergistically to explain aphasic symptoms, substantial interindividual variability remains unaccounted. One explanatory factor may be the spatial distribution of morphometry beyond the lesion (e.g., atrophy), including not just specific brain areas, but distinct three-dimensional patterns.MethodsHere, we test whether deep learning with Convolutional Neural Networks (CNNs) on whole brain morphometry (i.e., segmented tissue volumes) and lesion anatomy better predicts chronic stroke individuals with severe aphasia (N = 231) than classical machine learning (Support Vector Machines; SVMs), evaluating whether encoding spatial dependencies identifies uniquely predictive patterns.ResultsCNNs achieve higher balanced accuracy and F1 scores, even when SVMs are nonlinear or integrate linear or nonlinear dimensionality reduction. Parity only occurs when SVMs access features learned by CNNs. Saliency maps demonstrate that CNNs leverage distributed morphometry patterns, whereas SVMs focus on the area around the lesion. Ensemble clustering of CNN saliencies reveals distinct morphometry patterns unrelated to lesion size, consistent across individuals, and which implicate unique networks associated with different cognitive processes as measured by the wider neuroimaging literature. Individualized predictions depend on both ipsilateral and contralateral features outside the lesion.ConclusionsThree-dimensional network distributions of morphometry are directly associated with aphasia severity, underscoring the potential for CNNs to improve outcome prognostication from neuroimaging data, and highlighting the prospective benefits of interrogating spatial dependence at different scales in multivariate feature space.

Accelerated Aging after Traumatic Brain Injury: An ENIGMA Multi-Cohort Mega-Analysis.

The long-term consequences of traumatic brain injury (TBI) on brain structure remain uncertain. Given evidence that a single significant brain injury event increases the risk of dementia, brain-age estimation could provide a novel and efficient indexing of the long-term consequences of TBI. Brain-age procedures use predictive modeling to calculate brain-age scores for an individual using structural magnetic resonance imaging (MRI) data. Complicated mild, moderate, and severe TBI (cmsTBI) is associated with a higher predicted age difference (PAD), but the progression of PAD over time remains unclear. We sought to examine whether PAD increases as a function of time since injury (TSI) and if injury severity and sex interacted to influence this progression. Through the ENIGMA Adult Moderate and Severe (AMS)-TBI working group, we examine the largest TBI sample to date (n = 343), along with controls, for a total sample size of n = 540, to replicate and extend prior findings in the study of TBI brain age. Cross-sectional T1w-MRI data were aggregated across 7 cohorts, and brain age was established using a similar brain age algorithm to prior work in TBI. Findings show that PAD widens with longer TSI, and there was evidence for differences between sexes in PAD, with men showing more advanced brain age. We did not find strong evidence supporting a link between PAD and cognitive performance. This work provides evidence that changes in brain structure after cmsTBI are dynamic, with an initial period of change, followed by relative stability in brain morphometry, eventually leading to further changes in the decades after a single cmsTBI. ANN NEUROL 2024;96:365-377.

The Mediterranean Diet in Pregnancy: Implications for Maternal Brain Morphometry in a Secondary Analysis of the IMPACT BCN Randomized Clinical Trial.

A Mediterranean diet has positive effects on the brain in mid-older adults; however, there is scarce information on pregnant individuals. We aimed to evaluate the effect of a structured Mediterranean diet intervention on the cortical structure of the maternal brain during pregnancy. This study was a secondary analysis of the IMPACT BCN, a randomized clinical trial with 1221 high-risk pregnant women randomly allocated into three groups at 19-23 weeks of gestation: Mediterranean diet intervention, a mindfulness-based stress reduction program, or usual care. Maternal brain magnetic resonance imaging was performed during the third trimester of pregnancy in a random subgroup of participants. For this study, data from the Mediterranean diet and usual groups were analyzed. Maternal dietary intake, adherence to the Mediterranean diet and metabolite biomarkers were evaluated using a food frequency questionnaire, a 17-item dietary screener and plasma/urine samples, respectively. The cluster-wise analysis showed that the Mediterranean diet group participants (n = 34) had significantly larger surface areas in the right precuneus (90%CI: <0.0001-0.0004, p < 0.001) and left superior parietal (90%CI: 0.026-0.033, p = 0.03) lobules compared to the usual care group participants (n = 37). A larger right precuneus area was associated with high improvements in adherence to the Mediterranean diet, a high intake of walnuts and high concentrations of urinary hydroxytyrosol. A larger left superior parietal area was associated with a high intake of walnuts and high concentrations of urinary hydroxytyrosol. The promotion of a Mediterranean diet during pregnancy has a significant effect on maternal brain structure.