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Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors., (© 2024. The Author(s).)

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about spatial properties of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genetics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose network enrichment significance testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study enrichment of associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study phenotype associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study., Competing Interests: Russell T. Shinohara receives consulting income from Octave Bioscience and compensation for reviewership duties from the American Medical Association. Aaron Alexander-Bloch receives consulting income from Octave Bioscience and holds equity and serves on the board of directors of Centile Biosciences. Mingyao Li receives research funding from Biogen Inc. that is unrelated to the current manuscript.

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors., Competing Interests: Competing Interests Statement Lena Palaniyappan reports personal fees from Janssen Canada, Otsuka Canada, SPMM Course Limited UK and the Canadian Psychiatric Association; book royalties from Oxford University Press; and investigator-initiated educational grants from Sunovion, Janssen Canada and Otsuka Canada, outside the submitted work. Tilo Kircher received unrestricted educational grants from Servier, Janssen, Recordati, Aristo, Otsuka, neuraxpharm. Philipp Homan has received grants and honoraria from Novartis, Lundbeck, Mepha, Janssen, Boehringer Ingelheim, Neurolite outside of this work. Ole A. Andreassen is a consultant to Cortechs.ai and received speakers honorarium from Lundbeck, Janssen, Sunovion. These interests played no role in the research reported here. Other authors disclose no conflict of interest.

Autism presents with significant phenotypic and neuroanatomical heterogeneity, and neuroimaging studies of the thalamus, globus pallidus and striatum in autism have produced inconsistent and contradictory results. These structures are critical mediators of functions known to be atypical in autism, including sensory gating and motor function. We examined both volumetric and fine-grained localized shape differences in autism using a large ( n =3145, 1045-1318 after strict quality control), cross-sectional dataset of T1-weighted structural MRI scans from 32 sites, including both males and females (assigned-at-birth). We investigated three potentially important sources of neuroanatomical heterogeneity: sex, age, and intelligence quotient (IQ), using a meta-analytic technique after strict quality control to minimize non-biological sources of variation. We observed no volumetric differences in the thalamus, globus pallidus, or striatum in autism. Rather, we identified a variety of localized shape differences in all three structures. Including age, but not sex or IQ, in the statistical model improved the fit for both the pallidum and striatum, but not for the thalamus. Age-centered shape analysis indicated a variety of age-dependent regional differences. Overall, our findings help confirm that the neurodevelopment of the striatum, globus pallidus and thalamus are atypical in autism, in a subtle location-dependent manner that is not reflected in overall structure volumes, and that is highly non-uniform across the lifespan., Competing Interests: Conflict of Interest EO is an employee of Genentech, Inc. DGMM has served on advisory Boards to Roche and Servier. He also receives a stipend for editorial work from Springer. M-CL serves as an editor of the journal Autism and has received editorial honorarium from SAGE Publications.

Cholinergic dysfunction has been implicated in the pathophysiology of psychosis and psychiatric disorders such as schizophrenia, depression, and bipolar disorder. The basal forebrain (BF) cholinergic nuclei, defined as cholinergic cell groups Ch1-3 and Ch4 (Nucleus Basalis of Meynert; NBM), provide extensive cholinergic projections to the rest of the brain. Here, we examined microstructural neuroimaging measures of the cholinergic nuclei in patients with untreated psychosis (~31 weeks of psychosis, <2 defined daily dose of antipsychotics) and used magnetic resonance spectroscopy (MRS) and transcriptomic data to support our findings. We used a cytoarchitectonic atlas of the BF to map the nuclei and obtained measures of myelin (quantitative T1, or qT1 as myelin surrogate) and microstructure (axial diffusion; AxD). In a clinical sample (n = 85; 29 healthy controls, 56 first-episode psychosis), we found significant correlations between qT1 of Ch1-3, left NBM and MRS-based dorsal anterior cingulate choline in healthy controls while this relationship was disrupted in FEP (p > 0.05). Case-control differences in qT1 and AxD were observed in the Ch1-3, with increased qT1 (reflecting reduced myelin content) and AxD (reflecting reduced axonal integrity). We found clinical correlates between left NBM qT1 with manic symptom severity, and AxD with negative symptom burden in FEP. Intracortical and subcortical myelin maps were derived and correlated with BF myelin. BF-cortical and BF-subcortical myelin correlations demonstrate known projection patterns from the BF. Using data from the Allen Human Brain Atlas, cholinergic nuclei showed significant enrichment for schizophrenia and depression-related genes. Cell-type specific enrichment indicated enrichment for cholinergic neuron markers as expected. Further relating the neuroimaging correlations to transcriptomics demonstrated links with cholinergic receptor genes and cell type markers of oligodendrocytes and cholinergic neurons, providing biological validity to the measures. These results provide genetic, neuroimaging, and clinical evidence for cholinergic dysfunction in schizophrenia., (© 2022. The Author(s).)

Schizophrenia continues to be an illness with poor outcome. Most mechanistic changes occur many years before the first episode of schizophrenia; these are not reversible after the illness onset. A developmental mechanism that is still modifiable in adult life may center on intracortical glutathione (GSH). A large body of pre-clinical data has suggested the possibility of notable GSH-deficit in a subgroup of patients with schizophrenia. Nevertheless, studies of intracortical GSH are not conclusive in this regard. In this review, we highlight the recent ultra-high field magnetic resonance spectroscopic studies linking GSH to critical outcome measures across various stages of schizophrenia. We discuss the methodological steps required to conclusively establish or refute the persistence of GSH-deficit subtype and clarify the role of the central antioxidant system in disrupting the brain structure and connectivity in the early stages of schizophrenia. We propose in-vivo GSH quantification for patient selection in forthcoming antioxidant trials in psychosis. This review offers directions for a promising non-dopaminergic early intervention approach in schizophrenia.

Disrupted serotonergic and glutamatergic signaling interact and contribute to the pathophysiology of schizophrenia, which is particularly relevant for the hippocampus where diverse expression of serotonin receptors is noted. Hippocampal atrophy is a well-established feature of schizophrenia, with select subfields hypothesized as particularly vulnerable due to variation in glutamate receptor densities. We investigated hippocampal anomalies in first-episode psychosis (FEP) in relation to receptor distributions by leveraging 4 sources of data: (1) ultra high-field (7-Tesla) structural neuroimaging, and (2) proton magnetic resonance spectroscopy (1H-MRS) of glutamate from 27 healthy and 41 FEP subjects, (3) gene expression data from the Allen Human Brain Atlas and (4) atlases of the serotonin receptor system. Automated methods delineated the hippocampus to map receptor density across subfields. We used gene expression data to correlate serotonin and glutamate receptor genes across the hippocampus. Measures of individual hippocampal shape-receptor alignment were derived through normative modelling and correlations to receptor distributions, termed Receptor-Specific Morphometric Signatures (RSMS). We found reduced hippocampal volumes in FEP, while CA4-dentate gyrus showed greatest reductions. Gene expression indicated 5-HT1A and 5-HT4 to correlate with AMPA and NMDA expression, respectively. Magnitudes of subfield volumetric reduction in FEP correlated most with 5-HT1A (R = 0.64, p = 4.09E-03) and 5-HT4 (R = 0.54, p = 0.02) densities as expected, and replicated using previously published data from two FEP studies. Right-sided 5-HT4-RSMS was correlated with MRS glutamate (R = 0.357, p = 0.048). We demonstrate a putative glutamate-driven hippocampal variability in FEP through a serotonin receptor-density gated mechanism, thus outlining a mechanistic interplay between serotonin and glutamate in determining the hippocampal morphology in schizophrenia., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multicenter structural magnetic resonance imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male), and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. Increases were observed in different brain regions in males and females, with larger effect sizes in females. BSC correlated with ADOS-2 Calibrated Severity Score in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared with cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Significant heterogeneity across aetiologies, neurobiology and clinical phenotypes have been observed in individuals with autism spectrum disorder (ASD). Neuroimaging-based neuroanatomical studies of ASD have often reported inconsistent findings which may, in part, be attributable to an insufficient understanding of the relationship between factors influencing clinical heterogeneity and their relationship to brain anatomy. To this end, we performed a large-scale examination of cortical morphometry in ASD, with a specific focus on the impact of three potential sources of heterogeneity: sex, age and full-scale intelligence (FIQ). To examine these potentially subtle relationships, we amassed a large multi-site dataset that was carefully quality controlled (yielding a final sample of 1327 from the initial dataset of 3145 magnetic resonance images; 491 individuals with ASD). Using a meta-analytic technique to account for inter-site differences, we identified greater cortical thickness in individuals with ASD relative to controls, in regions previously implicated in ASD, including the superior temporal gyrus and inferior frontal sulcus. Greater cortical thickness was observed in sex specific regions; further, cortical thickness differences were observed to be greater in younger individuals and in those with lower FIQ, and to be related to overall clinical severity. This work serves as an important step towards parsing factors that influence neuroanatomical heterogeneity in ASD and is a potential step towards establishing individual-specific biomarkers.

Beginning in the early stages of Alzheimer's disease (AD), the hippocampus reduces its functional connections to other cortical regions due to synaptic depletion. However, little is known regarding connectivity abnormalities within the hippocampus. Here, we describe rostral-caudal hippocampal convergence (rcHC), a metric of the overlap between the rostral and caudal hippocampal functional networks, across the clinical spectrum of AD. We predicted a decline in rostral-caudal hippocampal convergence in the early stages of the disease. Using fMRI, we generated resting-state hippocampal functional networks across 56 controls, 48 early MCI (EMCI), 35 late MCI (LMCI), and 31 AD patients from the Alzheimer's Disease Neuroimaging Initiative cohort. For each diagnostic group, we performed a conjunction analysis and compared the rostral and caudal hippocampal network changes using a mixed effects linear model to estimate the convergence and differences between these networks, respectively. The conjunction analysis showed a reduction of rostral-caudal hippocampal convergence strength from early MCI to AD, independent of hippocampal atrophy. Our results demonstrate a parallel between the functional convergence within the hippocampus and disease stage, which is independent of brain atrophy. These findings support the concept that network convergence might contribute as a biomarker for connectivity dysfunction in early stages of AD.

Altered hippocampal morphology and reduced volumes have been found in children born preterm compared to full-term. Stress inhibits neurogenesis in the hippocampus, and neonatal stress/noxious stimulation in rodent pups are associated with long-term alterations in hippocampal volumes. We have previously shown reduced cortical thickness and cerebellar volumes in relation to more exposure to pain-related stress of neonatal invasive procedures in children born very preterm. We have reported targeted gene-by-pain environment interactions that contribute to long-term brain development and outcomes in this population. We now aim to determine whether exposure to pain-related stress (adjusted for clinical factors and genotype) differentially impacts regional structures within the limbic system and thalamus, and investigate relationships with outcomes in very preterm children. Our study included 57 children born very preterm (<32 weeks GA) followed longitudinally from birth who underwent 3-D T1 MRI neuroimaging at ∼8 years. Hippocampal subfields and white matter tracts, thalamus and amygdala were automatically segmented using the MAGeT Brain algorithm. The relationship between those subcortical brain volumes (adjusted for total brain volume) and neonatal invasive procedures, gestational age (GA), illness severity, postnatal infection, days of mechanical ventilation, number of surgeries, morphine exposure, and genotype ( COMT, SLC6A4 , and BDNF ) was examined using constrained principal component analysis. We found that neonatal clinical factors and genotypes accounted for 46% of the overall variance in volumes of hippocampal subregions, tracts, basal ganglia, thalamus and amygdala. After controlling for clinical risk factors and total brain volume, greater neonatal invasive procedures was associated with lower volumes in the amygdala and thalamus ( p = 0.0001) and an interaction with COMT genotype predicted smaller hippocampal subregional volume ( p = 0.0001). More surgeries, days of ventilation, and lower GA were also related to smaller volumes in various subcortical regions ( p < 0.002). These reduced volumes were in turn differentially related to poorer cognitive, visual-motor and behavioral outcomes. Our findings highlight the complexity that interplays when examining how exposure to early-life stress may impact brain development both at the structural and functional level, and provide new insight on possible novel avenues of research to discover brain-protective treatments to improve the care of children born preterm.

Twin study designs have been previously used to investigate the heritability of neuroanatomical measures, such as regional cortical volumes. Volume can be fractionated into surface area and cortical thickness, where both measures are considered to have independent genetic and environmental bases. Region of interest (ROI) and vertex-wise approaches have been used to calculate heritability of cortical thickness and surface area in twin studies. In our study, we estimate heritability using the Human Connectome Project magnetic resonance imaging dataset composed of healthy young twin and non-twin siblings (mean age of 29, sample size of 757). Both ROI and vertex-wise methods were used to compare regional heritability of cortical thickness and surface area. Heritability estimates were controlled for age, sex, and total ipsilateral surface area or mean cortical thickness. In both approaches, heritability estimates of cortical thickness and surface area were lower when accounting for average ipsilateral cortical thickness and total surface area respectively. When comparing both approaches at a regional level, the vertex-wise approach showed higher surface area and lower cortical thickness heritability estimates compared to the ROI approach. The calcarine fissure had the highest surface area heritability estimate (ROI: 44%, vertex-wise: 50%) and posterior cingulate gyrus had the highest cortical thickness heritability (ROI: 50%, vertex-wise 40%). We also observed that limitations in image processing and variability in spatial averaging errors based on regional size may make obtaining true estimates of cortical thickness and surface area challenging in smaller regions. It is important to identify which approach is best suited to estimate heritability based on the research hypothesis and the size of the regions being investigated., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Previous work from our group demonstrated the use of multiple input atlases to a modified multi-atlas framework (MAGeT-Brain) to improve subject-based segmentation accuracy. Currently, segmentation of the striatum, globus pallidus and thalamus are generated from a single high-resolution and -contrast MRI atlas derived from annotated serial histological sections. Here, we warp this atlas to five high-resolution MRI templates to create five de novo atlases. The overall goal of this work is to use these newly warped atlases as input to MAGeT-Brain in an effort to consolidate and improve the workflow presented in previous manuscripts from our group, allowing for simultaneous multi-structure segmentation. The work presented details the methodology used for the creation of the atlases using a technique previously proposed, where atlas labels are modified to mimic the intensity and contrast profile of MRI to facilitate atlas-to-template nonlinear transformation estimation. Dice's Kappa metric was used to demonstrate high quality registration and segmentation accuracy of the atlases. The final atlases are available at https://github.com/CobraLab/atlases/tree/master/5-atlas-subcortical.

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Background: There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations., Methods: First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are "enriched" within functional resting-state networks., Results: We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032)., Limitations: We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories., Conclusion: These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.

Recently, much attention has been focused on the definition and structure of the hippocampus and its subfields, while the projections from the hippocampus have been relatively understudied. Here, we derive a reliable protocol for manual segmentation of hippocampal white matter regions (alveus, fimbria, and fornix) using high-resolution magnetic resonance images that are complementary to our previous definitions of the hippocampal subfields, both of which are freely available at https://github.com/cobralab/atlases. Our segmentation methods demonstrated high inter- and intra-rater reliability, were validated as inputs in automated segmentation, and were used to analyze the trajectory of these regions in both healthy aging (OASIS), and Alzheimer's disease (AD) and mild cognitive impairment (MCI; using ADNI). We observed significant bilateral decreases in the fornix in healthy aging while the alveus and cornu ammonis (CA) 1 were well preserved (all p's<0.006). MCI and AD demonstrated significant decreases in fimbriae and fornices. Many hippocampal subfields exhibited decreased volume in both MCI and AD, yet no significant differences were found between MCI and AD cohorts themselves. Our results suggest a neuroprotective or compensatory role for the alveus and CA1 in healthy aging and suggest that an improved understanding of the volumetric trajectories of these structures is required., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The hippocampus is composed of distinct subfields linked to diverse functions and disorders. The subfields can be mapped using high-resolution magnetic resonance images, and their volumes can potentially be used as quantitative phenotypes for genetic investigation of hippocampal function. We estimated the heritability of hippocampus subfield volumes of 465 subjects from the Human Connectome Project (twins and non-twin siblings) using two methods. The first used a univariate model to estimate heritability with and without adjustment for total brain volume (TBV) and ipsilateral hippocampal volume to determine if heritability was uniquely attributable to subfield volume rather than confounds that attributed to global volumes. We observed the right: subiculum, cornu ammonis 2/3, and cornu ammonis 4/dentate gyrus subfields had the highest significant heritability estimates after adjusting for ipsilateral hippocampal volume. In the second analysis, we used a bivariate model to investigate the shared heritability and genetic correlation of the subfield volumes with TBV and ipsilateral hippocampal volume. Genetic correlation demonstrates shared genetic architecture between phenotypes and shared heritability is what proportion of the genetic architecture of one trait is shared by the other. Highest genetic correlations were between subfield volumes and ipsilateral hippocampal volume than with TBV. The pattern was opposite for shared heritability suggesting that subfields share greater proportion of the genetic architecture with TBV than with ipsilateral hippocampal volume. The relationship between the genetic architecture of TBV, hippocampal volume, and of individual subfields should be accounted for when using hippocampal subfield volumes as quantitative phenotypes for imaging genetics studies. Hum Brain Mapp 38:4337-4352, 2017. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Hippocampal atrophy rate-measured using automated techniques applied to structural MRI scans-is considered a sensitive marker of disease progression in Alzheimer's disease, frequently used as an outcome measure in clinical trials. Using publicly accessible data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we examined 1-year hippocampal atrophy rates generated by each of five automated or semiautomated hippocampal segmentation algorithms in patients with Alzheimer's disease, subjects with mild cognitive impairment, or elderly controls. We analyzed MRI data from 398 and 62 subjects available at baseline and at 1 year at MRI field strengths of 1.5 T and 3 T, respectively. We observed a high rate of hippocampal segmentation failures across all algorithms and diagnostic categories, with only 50.8% of subjects at 1.5 T and 58.1% of subjects at 3 T passing stringent segmentation quality control. We also found that all algorithms identified several subjects (between 2.94% and 48.68%) across all diagnostic categories showing increases in hippocampal volume over 1 year. For any given algorithm, hippocampal "growth" could not entirely be explained by excluding patients with flawed hippocampal segmentations, scan-rescan variability, or MRI field strength. Furthermore, different algorithms did not uniformly identify the same subjects as hippocampal "growers," and showed very poor concordance in estimates of magnitude of hippocampal volume change over time (intraclass correlation coefficient 0.319 at 1.5 T and 0.149 at 3 T). This precluded a meaningful analysis of whether hippocampal "growth" represents a true biological phenomenon. Taken together, our findings suggest that longitudinal hippocampal volume change should be interpreted with considerable caution as a biomarker. Hum Brain Mapp 38:2875-2896, 2017. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences-including their spatial distribution, potential biological determinants, and independence from brain volume variation-lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male-female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy., (Copyright © 2017 the authors 0270-6474/17/375222-11$15.00/0.)

Aβ deposition is a driving force of Alzheimer's disease pathology and can be detected early by amyloid positron emission tomography. Identifying presymptomatic structural brain changes associated with Aβ deposition might lead to a better understanding of its consequences and provide early diagnostic information. In this respect we analyzed measures of cortical thickness and subcortical volumes along with hippocampal, thalamic and striatal shape and surface area by applying novel analysis strategies for structural magnetic resonance imaging. We included 69 cognitively normal elderly subjects after careful clinical and neuropsychological workup. Standardized uptake value ratios (cerebellar reference) for uptake of 11-C-Pittsburgh Compound B (PiB) were calculated from positron emission tomographic data for a cortical measurement and for bilateral hippocampus, thalamus and striatum. Associations to shape, surface area, volume and cortical thickness were tested using regression models that included significant predictors as covariates. Left anterior hippocampal shape was associated with regional PiB uptake (P < 0.05, FDR corrected), whereas volumes of the hippocampi and their subregions were not associated with cortical or regional PiB uptake (all P > 0.05, FDR corrected). Within the entorhinal cortical region of both hemispheres, thickness was negatively associated with cortical PiB uptake (P < 0.05, FDR corrected). Hence, localized shape measures and cortical thickness may be potential biomarkers of presymptomatic Alzheimer's disease., (© 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

The human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly desirable to measure and understand the cerebellum role in normal and pathological brain development. In this work, we propose a patch-based multi-atlas segmentation tool called CERES (CEREbellum Segmentation) that is able to automatically parcellate the cerebellum lobules. The proposed method works with standard resolution magnetic resonance T1-weighted images and uses the Optimized PatchMatch algorithm to speed up the patch matching process. The proposed method was compared with related recent state-of-the-art methods showing competitive results in both accuracy (average DICE of 0.7729) and execution time (around 5 minutes)., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Longitudinal studies of illness progression in patients with major depressive disorder (MDD) indicate that the onset of subsequent depressive episodes becomes increasingly decoupled from external stressors. A possible mechanism underlying this phenomenon is that multiple episodes induce long-lasting neurobiological changes that confer increased risk for recurrence. Prior morphometric studies have frequently reported volumetric reductions in patients with MDD--especially in medial prefrontal cortex (mPFC) and the hippocampus--but few studies have investigated whether these changes are exacerbated by prior episodes., Methods: In a sample of 103 medication-free patients with depression and control subjects with no history of depression, structural magnetic resonance imaging was performed to examine relationships between number of prior episodes, current stress, hippocampal subfield volume and cortical thickness. Volumetric analyses of the hippocampus were performed using a recently validated subfield segmentation approach, and cortical thickness estimates were obtained using vertex-based methods. Participants were grouped on the basis of the number of prior depressive episodes and current depressive diagnosis., Results: Number of prior episodes was associated with both lower reported stress levels and reduced volume in the dentate gyrus. Cortical thinning of the left mPFC was associated with a greater number of prior depressive episodes but not current depressive diagnosis., Conclusions: Collectively, these findings are consistent with preclinical models suggesting that the dentate gyrus and mPFC are especially vulnerable to stress exposure and provide evidence for morphometric changes that are consistent with stress-sensitization models of recurrence in MDD., (Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The pituitary gland is a key structure in the hypothalamic-pituitary-gonadal (HPG) axis--it plays an important role in sexual maturation during puberty. Despite its small size, its volume can be quantified using magnetic resonance imaging (MRI). Here, we study a cohort of 962 typically developing adolescents from the Saguenay Youth Study and estimate pituitary volumes using a newly developed multi-atlas segmentation method known as the MAGeT Brain algorithm. We found that age and puberty stage (controlled for age) each predicts adjusted pituitary volumes (controlled for total brain volume) in both males and females. Controlling for the effects of age and puberty stage, total testosterone and estradiol levels also predict adjusted pituitary volumes in males and pre-menarche females, respectively. These findings demonstrate that the pituitary gland grows during adolescence, and its volume relates to circulating plasma-levels of sex steroids in both males and females., (Copyright © 2014 Elsevier Inc. All rights reserved.)