Hippocampal shape and volume changes with antipsychotics in early stage psychotic illness

Progression of hippocampal shape and volume abnormalities has been described in psychotic disorders such as schizophrenia. However it is unclear how specific antipsychotic medications influence the development of hippocampal structure. We conducted a longitudinal, randomized, controlled, multisite, double-blind study involving 14 academic medical centers (United States 11, Canada 1, Netherlands 1, and England 1). 134 first-episode psychosis (receiving either haloperidol or olanzapine) patients and 51 healthy controls were treated and followed up for up to 104 weeks using magnetic resonance imaging and large-deformation high-dimensional brain mapping of the hippocampus. Changes in hippocampal volume and shape metrics (i.e., percentage of negative surface vertex slopes, and surface deformation) were evaluated. Mixed-models analysis did not show a significant group-by-time interaction for hippocampal volume. However, the cumulative distribution function of hippocampal surface vertex slopes showed a notable left shift with haloperidol treatment compared to olanzapine treatment and to controls. Olanzapine treatment was associated with a significantly lower percentage of large magnitude negative surface vertex slopes compared to haloperidol treatment (p=0.004). Surface deformation maps however did not localize any hippocampal regions that differentially contracted over time with olanzapine treatment, after FDR correction. These results indicate that surface analysis provides supplementary information to volumetry in detecting differential treatment effects of the hippocampus. Our results suggest that olanzapine is associated with less longitudinal hippocampal surface deformation than haloperidol, however the hippocampal regions affected appear to be variable across patients

Use of High Resolution 3D Diffusion Tensor Imaging to Study Brain White Matter Development in Live Neonatal Rats

High resolution diffusion tensor imaging (DTI) can provide important information on brain development, yet it is challenging in live neonatal rats due to the small size of neonatal brain and motion-sensitive nature of DTI. Imaging in live neonatal rats has clear advantages over fixed brain scans, as longitudinal and functional studies would be feasible to understand neuro-developmental abnormalities. In this study, we developed imaging strategies that can be used to obtain high resolution 3D DTI images in live neonatal rats at postnatal day 5 (PND5) and PND14, using only 3 h of imaging acquisition time. An optimized 3D DTI pulse sequence and appropriate animal setup to minimize physiological motion artifacts are the keys to successful high resolution 3D DTI imaging. Thus, a 3D rapid acquisition relaxation enhancement DTI sequence with twin navigator echoes was implemented to accelerate imaging acquisition time and minimize motion artifacts. It has been suggested that neonatal mammals possess a unique ability to tolerate mild-to-moderate hypothermia and hypoxia without long term impact. Thus, we additionally utilized this ability to minimize motion artifacts in magnetic resonance images by carefully suppressing the respiratory rate to around 15/min for PND5 and 30/min for PND14 using mild-to-moderate hypothermia. These imaging strategies have been successfully implemented to study how the effect of cocaine exposure in dams might affect brain development in their rat pups. Image quality resulting from this in vivo DTI study was comparable to ex vivo scans. fractional anisotropy values were also similar between the live and fixed brain scans. The capability of acquiring high quality in vivo DTI imaging offers a valuable opportunity to study many neurological disorders in brain development in an authentic living environment

Maternal choline supplementation in a sheep model of first trimester binge alcohol fails to protect against brain volume reductions in peripubertal lambs

Fetal alcohol spectrum disorder (FASD) is a leading potentially preventable birth defect. Poor nutrition may contribute to adverse developmental outcomes of prenatal alcohol exposure, and supplementation of essential micronutrients such as choline has shown benefit in rodent models. The sheep model of first-trimester binge alcohol exposure was used in this study to model the dose of maternal choline supplementation used in an ongoing prospective clinical trial involving pregnancies at risk for FASD. Primary outcome measures included volumetrics of the whole brain, cerebellum, and pituitary derived from magnetic resonance imaging (MRI) in 6-month-old lambs, testing the hypothesis that alcohol-exposed lambs would have brain volume reductions that would be ameliorated by maternal choline supplementation. Pregnant sheep were randomly assigned to one of five groups – heavy binge alcohol (HBA; 2.5 g/kg/treatment ethanol), heavy binge alcohol plus choline supplementation (HBC; 2.5 g/kg/treatment ethanol and 10 mg/kg/day choline), saline control (SC), saline control plus choline supplementation (SCC; 10 mg/kg/day choline), and normal control (NC). Ewes were given intravenous alcohol (HBA, HBC; mean peak BACs of ~280 mg/dL) or saline (SC, SCC) on three consecutive days per week from gestation day (GD) 4–41; choline was administered on GD 4–148. MRI scans of lamb brains were performed postnatally on day 182. Lambs from both alcohol groups (with or without choline) showed significant reductions in total brain volume; cerebellar and pituitary volumes were not significantly affected. This is the first report of MRI-derived volumetric brain reductions in a sheep model of FASD following binge-like alcohol exposure during the first trimester. These results also indicate that maternal choline supplementation comparable to doses in human studies fails to prevent brain volume reductions typically induced by first-trimester binge alcohol exposure. Future analyses will assess behavioral outcomes along with regional brain and neurohistological measures

Kronecker Product Linear Exponent AR(1) Correlation Structures for Multivariate Repeated Measures

Longitudinal imaging studies have moved to the forefront of medical research due to their ability to characterize spatio-temporal features of biological structures across the lifespan. Credible models of the correlations in longitudinal imaging require two or more pattern components. Valid inference requires enough flexibility of the correlation model to allow reasonable fidelity to the true pattern. On the other hand, the existence of computable estimates demands a parsimonious parameterization of the correlation structure. For many one-dimensional spatial or temporal arrays, the linear exponent autoregressive (LEAR) correlation structure meets these two opposing goals in one model. The LEAR structure is a flexible two-parameter correlation model that applies to situations in which the within-subject correlation decreases exponentially in time or space. It allows for an attenuation or acceleration of the exponential decay rate imposed by the commonly used continuous-time AR(1) structure. We propose the Kronecker product LEAR correlation structure for multivariate repeated measures data in which the correlation between measurements for a given subject is induced by two factors (e.g., spatial and temporal dependence). Excellent analytic and numerical properties make the Kronecker product LEAR model a valuable addition to the suite of parsimonious correlation structures for multivariate repeated measures data. Longitudinal medical imaging data of caudate morphology in schizophrenia illustrates the appeal of the Kronecker product LEAR correlation structure

Separability tests for high-dimensional, low-sample size multivariate repeated measures data

Longitudinal imaging studies have moved to the forefront of medical research due to their ability to characterize spatio-temporal features of biological structures across the lifespan. Valid inference in longitudinal imaging requires enough flexibility of the covariance model to allow reasonable fidelity to the true pattern. On the other hand, the existence of computable estimates demands a parsimonious parameterization of the covariance structure. Separable (Kronecker product) covariance models provide one such parameterization in which the spatial and temporal covariances are modeled separately. However, evaluating the validity of this parameterization in high-dimensions remains a challenge. Here we provide a scientifically informed approach to assessing the adequacy of separable (Kronecker product) covariance models when the number of observations is large relative to the number of independent sampling units (sample size). We address both the general case, in which unstructured matrices are considered for each covariance model, and the structured case, which assumes a particular structure for each model. For the structured case, we focus on the situation where the within subject correlation is believed to decrease exponentially in time and space as is common in longitudinal imaging studies. However, the provided framework equally applies to all covariance patterns used within the more general multivariate repeated measures context. Our approach provides useful guidance for high dimension, low sample size data that preclude using standard likelihood based tests. Longitudinal medical imaging data of caudate morphology in schizophrenia illustrates the approaches appeal

A midas plugin to enable construction of reproducible web-based image processing pipelines

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline

Semiparametric Bayesian local functional models for diffusion tensor tract statistics

We propose a semiparametric Bayesian local functional model (BFM) for the analysis of multiple diffusion properties (e.g., fractional anisotropy) along white matter fiber bundles with a set of covariates of interest, such as age and gender. BFM accounts for heterogeneity in the shape of the fiber bundle diffusion properties among subjects, while allowing the impact of the covariates to vary across subjects. A nonparametric Bayesian LPP2 prior facilitates global and local borrowings of information among subjects, while an infinite factor model flexibly represents low-dimensional structure. Local hypothesis testing and credible bands are developed to identify fiber segments, along which multiple diffusion properties are significantly associated with covariates of interest, while controlling for multiple comparisons. Moreover, BFM naturally group subjects into more homogeneous clusters. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFM. We apply BFM to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment in new born infants

Maternal buffering beyond glucocorticoids: impact of early life stress on corticolimbic circuits that control infant responses to novelty

Maternal presence has a potent buffering effect on infant fear and stress responses in primates. We previously reported that maternal presence is not effective in buffering the endocrine stress response in infant rhesus monkeys reared by maltreating mothers. We have also reported that maltreating mothers show low maternal responsiveness and permissiveness/secure-base behavior. Although still not understood, it is possible that this maternal buffering effect is mediated, at least partially, through deactivation of amygdala response circuits when mothers are present. Here we studied rhesus monkey infants that differed in the quality of early maternal care to investigate how this early experience modulated maternal buffering effects on behavioral responses to novelty during the weaning period. We also examined the relationship between these behavioral responses and structural connectivity in one of the underlying regulatory neural circuits: amygdala-prefrontal pathways. Our findings suggest that infant exploration in a novel situation is predicted by maternal responsiveness and structural integrity of amygdala-prefrontal white matter depending on maternal presence (positive relationships when mother is absent). These results provide evidence that maternal buffering of infant behavioral inhibition is dependent on the quality of maternal care and structural connectivity of neural pathways that are sensitive to early life stress

Pharyngeal airway volume and shape from cone-beam computed tomography: Relationship to facial morphology

The aim of this study was to assess the differences in airway shape and volume among subjects with various facial patterns