Christopher L. Adamson

White and gray matter alterations in adults with Niemann-Pick disease type C A cross-sectional study

Objective: Niemann-Pick disease type C (NPC) is a progressive neurovisceral disorder with disrupted intracellular cholesterol metabolism that results in significant alterations to neuronal and axonal structure. Adult patients present with ataxia, gaze palsy, impaired cognition, and neuropsychiatric illness, but the neural substrate has not been well-characterized in vivo. Our aim was to investigate a well-characterized sample of adults with confirmed NPC for gray and white matter abnormalities. Methods: We utilized a combination of optimized voxel-based morphometry of T1-weighted images and tract-based spatial statistics of diffusion tensor images to examine gray matter volume and white matter structural differences in 6 adult patients with NPC and 18 gender- and age-matched controls. Results: Patients with NPC demonstrated bilateral gray matter reductions in large clusters in bilateral hippocampus, thalamus, superior cerebellum, and insula, in addition to smaller regions of inferoposterior cortex. Patients demonstrated widespread reductions in fractional anisotropy in major white matter tracts. Subsequent analysis of measures of axial and radial diffusivity suggest that these changes are contributed to by both impaired myelination and altered axonal structure. Conclusions: Findings in gray matter areas are broadly consistent with human and animal studies of selective vulnerability of neuronal populations to the neuropathology of NPC, whereas more widespread white matter changes are consistent with the hypothesis that disrupted myelination and axonal structure predate changes to the neuronal cell body. These findings suggest that volumetric analysis of gray matter and diffusion tensor imaging may be useful modalities for indexing illness stage and monitoring response to emerging treatment.

Anterior cingulate cortex abnormalities associated with a first psychotic episode in bipolar disorder

BACKGROUND The anterior cingulate cortex is frequently implicated in the pathophysiology of bipolar disorder, but magnetic resonance imaging (MRI) studies have reported variable findings owing to a reliance on patient samples with chronic illness and to limited appreciation of the regions heterogeneity. AIMS To characterise anterior cingulate cortex abnormalities in patients with bipolar disorder experiencing their first episode of psychosis while accounting for regional anatomical variability. METHOD Grey matter volume, surface area and cortical thickness were measured in six anterior cingulate cortex subregions per hemisphere using MRI scans acquired from 26 patients with bipolar I disorder experiencing first-episode psychosis and 26 healthy controls matched for age, gender and regional morphological variability. RESULTS Relative to controls, male patients displayed increased thickness in the right subcallosal limbic anterior cingulate cortex. No significant differences were identified in females for grey matter volume or surface area measures. The findings were not attributable to medication effects. CONCLUSIONS These data suggest that first-episode psychosis in bipolar disorder is associated with a gender-specific, right-lateralised thickness increase in anterior cingulate cortex subregions known to play a role in regulating physiological stress responses.

Grey and white matter abnormalities are associated with impaired spatial working memory ability in first-episode schizophrenia

Spatial working memory (SWM) dysfunction has been suggested as a trait marker of schizophrenia and implicates a diffuse network involving prefrontal, temporal and parietal cortices. However, structural abnormalities in both grey and white matter in relation to SWM deficits are largely unexplored. The current magnetic resonance imaging (MRI) study examined this relationship in a sample of young first-episode schizophrenia (FES) patients using a whole-brain voxel-based method. SWM ability of 21 FES patients and 41 comparable controls was assessed by the CANTAB SWM task. Using an automated morphometric analysis of brain MRI scans, we assessed the relationship between SWM abilities and both grey matter volume and white matter density in both groups. Our findings demonstrated the different directionality of the association between SWM errors and grey matter volume in left frontal regions and white matter tracts connecting these regions with temporal and occipital areas between FES patients and controls. This suggests that the substrate underpinning the normal variability in SWM function in healthy individuals may be abnormal in FES, and that the normal neurodevelopmental processes that drive the development of SWM networks are disrupted in schizophrenia.

Thickness profile generation for the corpus callosum using Laplace's equation

The corpus callosum facilitates communication between the cerebral hemispheres. Morphological abnormalities of the corpus callosum have been identified in numerous psychiatric and neurological disorders. To quantitatively analyze the thickness profile of the corpus callosum, we adapted an automatic thickness measurement method, which was originally used on magnetic resonance (MR) images of the cerebral cortex (Hutton et al. [ 2008 ]: NeuroImage 40:1701–10; Jones et al. [ 2002 ]: Hum Brain Mapp 11:12–32; Schmitt and Böhme [ 2002 ]: NeuroImage 16:1103–9; Yezzi and Prince [ 2003 ]: IEEE Trans Med Imaging 22:1332–9), to MR images of the corpus callosum. The thickness model was derived by computing a solution to Laplaces equation evaluated on callosal voxels. The streamlines from this solution form non‐overlapping, cross‐sectional contours the lengths of which are modeled as the callosal thickness. Apart from the semi‐automated segmentation and endpoint selection procedures, the method is fully automated, robust, and reproducible. We compared the Laplace method with the orthogonal projection technique previously published (Walterfang et al. [ 2009a ]: Psych Res Neuroimaging 173:77–82; Walterfang et al. [ 2008a ]: Br J Psychiatry 192:429–34; Walterfang et al. [ 2008b ]: Schizophr Res 103:1–10) on a cohort of 296 subjects, composed of 86 patients with chronic schizophrenia (CSZ), 110 individuals with first‐episode psychosis, 100 individuals at ultra‐high risk for psychosis (UHR; 27 of whom later developed psychosis, UHR‐P, and 73 who did not, UHR‐NP), and 55 control subjects (CTL). We report similar patterns of statistically significant differences in regional callosal thickness with respect to the comparisons CSZ vs. CTL, UHR vs. CTL, UHR‐P vs. UHR‐NP, and UHR vs. CTL. Hum Brain Mapp, 2011.

Saccadic eye movement characteristics in adult Niemann-Pick Type C disease: relationships with disease severity and brain structural measures.

Niemann-Pick Type C disease (NPC) is a rare genetic disorder of lipid metabolism. A parameter related to horizontal saccadic peak velocity was one of the primary outcome measures in the clinical trial assessing miglustat as a treatment for NPC. Neuropathology is widespread in NPC, however, and could be expected to affect other saccadic parameters. We compared horizontal saccadic velocity, latency, gain, antisaccade error percentage and self-paced saccade generation in 9 adult NPC patients to data from 10 age-matched controls. These saccadic measures were correlated with appropriate MRI-derived brain structural measures (e.g., dorsolateral prefrontal cortex, frontal eye fields, supplemental eye fields, parietal eye fields, pons, midbrain and cerebellar vermis) and with measures of disease severity and duration. The best discriminators between groups were reflexive saccade gain and the two volitional saccade measures. Gain was also the strongest correlate with disease severity and duration. Most of the saccadic measures showed strongly significant correlations with neurophysiologically appropriate brain regions. While our patient sample is small, the apparent specificity of these relationships suggests that as new diagnostic methods and treatments become available for NPC, a broader range of saccadic measures may be useful tools for the assessment of disease progression and treatment efficacy.

Software pipeline for midsagittal corpus callosum thickness profile processing : automated segmentation, manual editor, thickness profile generator, group-wise statistical comparison and results display.

This paper presents a fully automated pipeline for thickness profile evaluation and analysis of the human corpus callosum (CC) in 3D structural T1-weighted magnetic resonance images. The pipeline performs the following sequence of steps: midsagittal plane extraction, CC segmentation algorithm, quality control tool, thickness profile generation, statistical analysis and results figure generator. The CC segmentation algorithm is a novel technique that is based on a template-based initialisation with refinement using mathematical morphology operations. The algorithm is demonstrated to have high segmentation accuracy when compared to manual segmentations on two large, publicly available datasets. Additionally, the resultant thickness profiles generated from the automated segmentations are shown to be highly correlated to those generated from the ground truth segmentations. The manual editing tool provides a user-friendly environment for correction of errors and quality control. Statistical analysis and a novel figure generator are provided to facilitate group-wise morphological analysis of the CC.

Longitudinal growth and morphology of the hippocampus through childhood: Impact of prematurity and implications for memory and learning.

The effects of prematurity on hippocampal development through early childhood are largely unknown. The aims of this study were to (1) compare the shape of the very preterm (VPT) hippocampus to that of full‐term (FT) children at 7 years of age, and determine if hippocampal shape is associated with memory and learning impairment in VPT children, (2) compare change in shape and volume of the hippocampi from term‐equivalent to 7 years of age between VPT and FT children, and determine if development of the hippocampi over time predicts memory and learning impairment in VPT children. T1 and T2 magnetic resonance images were acquired at both term equivalent and 7 years of age in 125 VPT and 25 FT children. Hippocampi were manually segmented and shape was characterized by boundary point distribution models at both time‐points. Memory and learning outcomes were measured at 7 years of age. The VPT group demonstrated less hippocampal infolding than the FT group at 7 years. Hippocampal growth between infancy and 7 years was less in the VPT compared with the FT group, but the change in shape was similar between groups. There was little evidence that the measures of hippocampal development were related to memory and learning impairments in the VPT group. This study suggests that the developmental trajectory of the human hippocampus is altered in VPT children, but this does not predict memory and learning impairment. Further research is required to elucidate the mechanisms for memory and learning difficulties in VPT children. Hum Brain Mapp 35:4129–4139, 2014.

Brain extraction using the watershed transform from markers

Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important step in many types of neuro-imaging research using both humans and animal subjects. The importance of brain extraction is well appreciated—numerous approaches have been published and the benefits of good extraction methods to subsequent processing are well known. We describe a tool—the marker based watershed scalper (MBWSS)—for isolating the brain in T1-weighted MR images built using filtering and segmentation components from the Insight Toolkit (ITK) framework. The key elements of MBWSS—the watershed transform from markers and aggressive filtering with large kernels—are techniques that have rarely been used in neuroimaging segmentation applications. MBWSS is able to reliably isolate the brain without expensive preprocessing steps, such as registration to an atlas, and is therefore useful as the first stage of processing pipelines. It is an informative example of the level of accuracy achievable without using priors in the form of atlases, shape models or libraries of examples. We validate the MBWSS using a publicly available dataset, a paediatric cohort, an adolescent cohort, intra-surgical scans and demonstrate flexibility of the approach by modifying the method to extract macaque brains.

Cortical morphometry in attention deficit/hyperactivity disorder: contribution of thickness and surface area to volume

Although lower brain volume is a consistent neuroimaging finding in attention deficit hyperactivity disorder (ADHD), we lack an understanding of whether this effect is driven by changes in cortical thickness or surface area, which are governed by distinct neurodevelopmental processes. This study examined ADHD-control differences in cortical thickness, surface area and volume, and tests whether thickness and surface area mediates any observed volume differences. Magnetic resonance imaging (MRI) data was collected from 35 males with ADHD-combined type and 35 typically developing control participants aged 9-17 years. Morphometric measures were examined for between group differences and the specific contribution of surface area and thickness to group differences in volume tested using mediation analysis. Individuals with ADHD had smaller total cortical volume (7.3%), surface area (4.3%), and mean cortical thickness (2.8%) compared to controls. Differences were pronounced in frontal and parietal lobes. Variance in volume as a function of ADHD diagnosis was accounted for at least in part by the relationship between diagnosis and each of cortical thickness and surface area, with regional variation in the relative contributions of these measures. The surface area of the precuneus was a major driver of volume differences, attesting to the potential relevance of this region for neurodevelopment in ADHD. Both surface area and cortical thickness play a significant mediating role in determining diagnostic differences in volume, with regional variation in the contribution of thickness and surface area to those volume differences, highlighting the importance of examining both cortical thickness and surface area in examining ADHD.

A new neonatal cortical and subcortical brain atlas: the Melbourne Children's Regional Infant Brain (M-CRIB) atlas

ABSTRACT Investigating neonatal brain structure and function can offer valuable insights into behaviour and cognition in healthy and clinical populations; both at term age, and longitudinally in comparison with later time points. Parcellated brain atlases for adult populations are readily available, however warping infant data to adult template space is not ideal due to morphological and tissue differences between these groups. Several parcellated neonatal atlases have been developed, although there remains strong demand for manually parcellated ground truth data with detailed cortical definition. Additionally, compatibility with existing adult atlases is favourable for use in longitudinal investigations. We aimed to address these needs by replicating the widely‐used Desikan‐Killiany (2006) adult cortical atlas in neonates. We also aimed to extend brain coverage by complementing this cortical scheme with basal ganglia, thalamus, cerebellum and other subcortical segmentations. Thus, we have manually parcellated these areas volumetrically using high‐resolution neonatal T2‐weighted MRI scans, and initial automated and manually edited tissue classification, providing 100 regions in all. Linear and nonlinear T2‐weighted structural templates were also generated. In this paper we provide manual parcellation protocols, and present the parcellated probability maps and structural templates together as the Melbourne Childrens Regional Infant Brain (M‐CRIB) atlas. HIGHLIGHTSNovel cortical and subcortical atlas based on 10 neonatal T2 MRI scans.Volumetric replication of Desikan‐Killiany (2006) cortical atlas.Subcortical and cerebellar segmentations.Detailed manual parcellation provides valuable ground truth data.