The hippocampi of children with chromosome 22q11.2 deletion syndrome have localized anterior alterations that predict severity of anxiety

BACKGROUND: Individuals with 22q11.2 deletion syndrome (22q11.2DS) have an elevated risk for schizophrenia, which increases with history of childhood anxiety. Altered hippocampal morphology is a common neuroanatomical feature of 22q11.2DS and idiopathic schizophrenia. Relating hippocampal structure in children with 22q11.2DS to anxiety and impaired cognitive ability could lead to hippocampus-based characterization of psychosis-proneness in this at-risk population. METHODS: We measured hippocampal volume using a semiautomated approach on MRIs collected from typically developing children and children with 22q11.2DS. We then analyzed hippocampal morphology with Localized Components Analysis. We tested the modulating roles of diagnostic group, hippocampal volume, sex and age on local hippocampal shape components. Lastly, volume and shape components were tested as covariates of IQ and anxiety. RESULTS: We included 48 typically developing children and 69 children with 22q11.2DS in our study. Hippocampal volume was reduced bilaterally in children with 22q11.2DS, and these children showed greater variation in the shape of the anterior hippocampus than typically developing children. Children with 22q11.2DS had greater inward deformation of the anterior hippocampus than typically developing children. Greater inward deformation of the anterior hippocampus was associated with greater severity of anxiety, specifically fear of physical injury, within the 22q11.2DS group. LIMITATIONS: Shape alterations are not specific to hippocampal subfields. CONCLUSION: Alterations in the structure of the anterior hippocampus likely affect function and may impact limbic circuitry. We suggest these alterations potentially contribute to anxiety symptoms in individuals with 22q11.2DS through modulatory pathways. Altered hippocampal morphology may be uniquely linked to anxiety risk factors for schizophrenia, which could be a powerful neuroanatomical marker of schizophrenia risk and hence protection

Visual analytics methods for shape analysis of biomedical images exemplified on rodent skull morphology

In morphometrics and its application fields like medicine and biology experts are interested in causal relations of variation in organismic shape to phylogenetic, ecological, geographical, epidemiological or disease factors - or put more succinctly by Fred L. Bookstein, morphometrics is "the study of covariances of biological form". In order to reveal causes for shape variability, targeted statistical analysis correlating shape features against external and internal factors is necessary but due to the complexity of the problem often not feasible in an automated way. Therefore, a visual analytics approach is proposed in this thesis that couples interactive visualizations with automated statistical analyses in order to stimulate generation and qualitative assessment of hypotheses on relevant shape features and their potentially affecting factors. To this end long established morphometric techniques are combined with recent shape modeling approaches from geometry processing and medical imaging, leading to novel visual analytics methods for shape analysis. When used in concert these methods facilitate targeted analysis of characteristic shape differences between groups, co-variation between different structures on the same anatomy and correlation of shape to extrinsic attributes. Here a special focus is put on accurate modeling and interactive rendering of image deformations at high spatial resolution, because that allows for faithful representation and communication of diminutive shape features, large shape differences and volumetric structures. The utility of the presented methods is demonstrated in case studies conducted together with a collaborating morphometrics expert. As exemplary model structure serves the rodent skull and its mandible that are assessed via computed tomography scans

Exploration of shape variation using localized components analysis.

Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania

Localized hippocampus measures are associated with Alzheimer pathology and cognition independent of total hippocampal volume.

Item does not contain fulltextHippocampal injury in the Alzheimer's disease (AD) pathological process is region-specific and magnetic resonance imaging (MRI)-based measures of localized hippocampus (HP) atrophy are known to detect region-specific changes associated with clinical AD, but it is unclear whether these measures provide information that is independent of that already provided by measures of total HP volume. Therefore, this study assessed the strength of association between localized HP atrophy measures and AD-related measures including cerebrospinal fluid (CSF) amyloid beta and tau concentrations, and cognitive performance, in statistical models that also included total HP volume as a covariate. A computational technique termed localized components analysis (LoCA) was used to identify 7 independent patterns of HP atrophy among 390 semiautomatically delineated HP from baseline magnetic resonance imaging of participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among cognitively normal participants, multiple measures of localized HP atrophy were significantly associated with CSF amyloid concentration, while total HP volume was not. In addition, among all participants, localized HP atrophy measures and total HP volume were both independently and additively associated with CSF tau concentration, performance on numerous neuropsychological tests, and discrimination between normal, mild cognitive impairment (MCI), and AD clinical diagnostic groups. Together, these results suggest that regional measures of hippocampal atrophy provided by localized components analysis may be more sensitive than total HP volume to the effects of AD pathology burden among cognitively normal individuals and may provide information about HP regions whose deficits may have especially profound cognitive consequences throughout the AD clinical course.1 juni 201

Localized hippocampus measures are associated with Alzheimer pathology and cognition independent of total hippocampal volume.

Hippocampal injury in the Alzheimer's disease (AD) pathological process is region-specific and magnetic resonance imaging (MRI)-based measures of localized hippocampus (HP) atrophy are known to detect region-specific changes associated with clinical AD, but it is unclear whether these measures provide information that is independent of that already provided by measures of total HP volume. Therefore, this study assessed the strength of association between localized HP atrophy measures and AD-related measures including cerebrospinal fluid (CSF) amyloid beta and tau concentrations, and cognitive performance, in statistical models that also included total HP volume as a covariate. A computational technique termed localized components analysis (LoCA) was used to identify 7 independent patterns of HP atrophy among 390 semiautomatically delineated HP from baseline magnetic resonance imaging of participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among cognitively normal participants, multiple measures of localized HP atrophy were significantly associated with CSF amyloid concentration, while total HP volume was not. In addition, among all participants, localized HP atrophy measures and total HP volume were both independently and additively associated with CSF tau concentration, performance on numerous neuropsychological tests, and discrimination between normal, mild cognitive impairment (MCI), and AD clinical diagnostic groups. Together, these results suggest that regional measures of hippocampal atrophy provided by localized components analysis may be more sensitive than total HP volume to the effects of AD pathology burden among cognitively normal individuals and may provide information about HP regions whose deficits may have especially profound cognitive consequences throughout the AD clinical course

Localized measures of callosal atrophy are associated with late-life hypertension: AGES-Reykjavik Study.

Hypertension is highly prevalent in elderly individuals and may be associated with cognitive decline, but the mechanisms by which hypertension may impact brain structure, and thereby modulate the time course of late-life cognitive performance, are not well understood. Therefore we used Localized Components Analysis, a novel computational method, to measure spatially-localized patterns of corpus callosum (CC) atrophy in 28 right-handed female subjects aged 75-79 years in the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik), a large-scale epidemiological study of aging. Localized callosal atrophy in the posterior midbody and splenium was significantly associated with systolic blood pressure in linear statistical models that controlled for age, while associations between blood pressure and anterior CC atrophy measures were not statistically significant. Additionally, overall measures of global CC atrophy were not significantly associated with blood pressure. The posterior CC may be differentially vulnerable to hypertension-associated atrophy, possibly due to its relatively tenuous vascularization