Mapping the regional influence of genetics on brain structure variability - A Tensor-Based Morphometry study

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Sex differences in the human connectome: 4-Tesla high angular resolution diffusion imaging (HARDI) tractography in 234 young adult twins

Cortical connectivity is associated with cognitive and behavioral traits that are thought to vary between sexes. Using high-angular resolution diffusion imaging at 4 Tesla, we scanned 234 young adult twins and siblings (mean age: 23.4 2.0 SD years) with 94 diffusion-encoding directions. We applied a novel Hough transform method to extract fiber tracts throughout the entire brain, based on fields of constant solid angle orientation distribution functions (ODFs). Cortical surfaces were generated from each subject's 3D T1-weighted structural MRI scan, and tracts were aligned to the anatomy. Network analysis revealed the proportions of fibers interconnecting 5 key subregions of the frontal cortex, including connections between hemispheres. We found significant sex differences (147 women/87 men) in the proportions of fibers connecting contralateral superior frontal cortices. Interhemispheric connectivity was greater in women, in line with long-standing theories of hemispheric specialization. These findings may be relevant for ongoing studies of the human connectome.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

Automatic population HARDI white matter tract clustering by label fusion of multiple tract atlases

Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

The multivariate A/C/E model and the genetics of fiber architecture

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

A new combined surface and volume registration

3D registration of brain MRI data is vital for many medical imaging applications. However, purely intensitybased approaches for inter-subject matching of brain structure are generally inaccurate in cortical regions, due to the highly complex network of sulci and gyri, which vary widely across subjects. Here we combine a surfacebased cortical registration with a 3D fluid one for the first time, enabling precise matching of cortical folds, but allowing large deformations in the enclosed brain volume, which guarantee diffeomorphisms. This greatly improves the matching of anatomy in cortical areas. The cortices are segmented and registered with the software Freesurfer. The deformation field is initially extended to the full 3D brain volume using a 3D harmonic mapping that preserves the matching between cortical surfaces. Finally, these deformation fields are used to initialize a 3D Riemannian fluid registration algorithm, that improves the alignment of subcortical brain regions. We validate this method on an MRI dataset from 92 healthy adult twins. Results are compared to those based on volumetric registration without surface constraints; the resulting mean templates resolve consistent anatomical features both subcortically and at the cortex, suggesting that the approach is well-suited for cross-subject integration of functional and anatomic data.

Effectiveness of electrocardiographic guidance in CVAD tip placement

Background International standard practice for the correct confirmation of the central venous access device is the chest X-ray. The intracavitary electrocardiogram-based insertion method is radiation-free, and allows real-time placement verification, providing immediate treatment and reduced requirement for post-procedural repositioning. Methods Relevant databases were searched for prospective randomised controlled trials (RCTs) or quasi RCTs that compared the effectiveness of electrocardiogram-guided catheter tip positioning with placement using surface-anatomy-guided insertion plus chest X-ray confirmation. The primary outcome was accurate catheter tip placement. Secondary outcomes included complications, patient satisfaction and costs. Results Five studies involving 729 participants were included. Electrocardiogram-guided insertion was more accurate than surface anatomy guided insertion (odds ratio: 8.3; 95% confidence interval (CI) 1.38; 50.07; p=0.02). There was a lack of reporting on complications, patient satisfaction and costs. Conclusion The evidence suggests that intracavitary electrocardiogram-based positioning is superior to surface-anatomy-guided positioning of central venous access devices, leading to significantly more successful placements. This technique could potentially remove the requirement for post-procedural chest X-ray, especially during peripherally inserted central catheter (PICC) line insertion.

Supine to standing cobb angle change in idiopathic scoliosis: The effect of endplate preselection

INTRODUCTION Standing radiographs are the ‘gold standard’ for clinical assessment of adolescent idiopathic scoliosis (AIS), with the Cobb Angle used to measure the severity and progression of the scoliotic curve. Supine imaging modalities can provide valuable 3D information on scoliotic anatomy, however, due to changes in gravitational loading direction, the geometry of the spine alters between the supine and standing position which in turn affects the Cobb Angle measurement. Previous studies have consistently reported a 7-10° [1-3] Cobb Angle increase from supine to standing, however, none have reported the effect of endplate pre-selection and which (if any) curve parameters affect the supine to standing Cobb Angle difference. CONCLUSION There is a statistically significant relationship between supine to standing Cobb Angle change and fulcrum flexibility. Therefore, this difference can be considered a measure of spinal flexibility. Pre-selecting vertebral endplates causes only minor changes.

Variations in vertebral venous vasculature

INTRODUCTION Cadaveric studies have previously documented typical patterns of venous drainage within vertebral bodies (VBs) [1,2,3], comprised primarily of the basivertebral vein, a planar tree like structure at the mid-height of the VB. These studies, however, are limited in the number of samples available, and so have not examined any potential differences in this anatomy in conditions such as scoliosis. MRI is able to create 3D images of soft tissue structures in the spine, including the basivertebral vein without the use of contrast. As a non-invasive imaging technique this opens up the possibility of examining the venous network in multiple VBs within the same subject, in healthy controls as well as in subjects with abnormal anatomy such as adolescent idiopathic scoliosis (AIS). CONCLUSIONS High resolution MRI scans allow in vivo quantification of the vertebral venous system at multiple levels on healthy and scoliotic populations for the first time. The length of the basivertebral vein was seen to have a significant bias to the right hand side of the VB in both healthy and AIS adolescents. The spatial pattern of this vein showed large variations in branching both within and across individuals.

Automated fit assessment of intramedullary nail designs during insertion

Modern intramedullary nails, which are utilised for the treatment of bone fractures, need to be designed to fit the anatomy of the patient population. Traditional and recent semi-automated approaches for quantifying the anatomical fit between bones and nail designs suffer from various drawbacks. This thesis proposed an automated comprehensive nail design validation method. The developed software tool was utilised to quantify the anatomical fit of four commercial nail designs. Furthermore, the thesis demonstrated the existence of a bone-nail specific nail entry point. The developed method is of great benefit for the implant manufacturing industry as a nail design validation tool.

Using the factors that have a positive impact on the retention of low socioeconomic students to prepare accelerated enrolled nurses for the science units of a nursing degree : a practice report

At a campus in a low socioeconomic (SES) area, our University allows enrolled nurses entry into the second year of a Bachelor of Nursing, but attrition is high. Using the factors, described by Yorke and Thomas (2003) to have a positive impact on the attrition of low SES students, we developed strategies to prepare the enrolled nurses for the pharmacology and bioscience units of a nursing degree with the aim of reducing their attrition. As a strategy, the introduction of review lectures of anatomy, physiology and microbiology, was associated with significantly reduced attrition rates. The subsequent introduction of a formative website activity of some basic concepts in bioscience and pharmacology, and a workshop addressing study skills and online resources, were associated with a further reduction in attrition rates of enrolled nursing students in a Bachelor of Nursing.

Structural, physiological and molecular characterisation of the Australian native resurrection grass Tripogon loliiformis (F.Meull) C.E.Hubb during dehydration and rehydration

There is an urgent need to develop crops that can withstand future climates. Results from this thesis demonstrated that a native Australian resurrection grass exhibits structural, physiological and metabolic strategies to tolerate drying. These strategies may be utilized for the generation of stress tolerant crops.

Pathophysiology team teaching: Bioscientist contribution to knowledge integration in a nursing subject

Bioscience content within undergraduate nursing degrees provides foundational knowledge of pathophysiology, anatomy, physiology, microbiology and pharmacology. However, nursing students often find studying the bioscience components of undergraduate nursing program daunting (Friedel & Treagust 2005, Craft et al. 2013). This is related to factors such as the volume of content, degree of difficulty and insufficient linkage between bioscience concepts and nurses' clinical practice. Students who are unable to conceptualise the relevance of bioscience with nursing subjects and subsequent nursing practice may not appreciate the broader importance of bioscience, and hence may adopt a surface approach to learning (Craft et al. 2013). The aim of this study was to develop a model within Nursing Practice in the Context theory subject, to include a bioscientist lecturing to complement the nursing lecturer, in order to explicitly demonstrate links between physiology, pathophysiology and nursing practice.