A nonconservative Lagrangian framework for statistical fluid registration - SAFIRA

In this paper, we used a nonconservative Lagrangian mechanics approach to formulate a new statistical algorithm for fluid registration of 3-D brain images. This algorithm is named SAFIRA, acronym for statistically-assisted fluid image registration algorithm. A nonstatistical version of this algorithm was implemented, where the deformation was regularized by penalizing deviations from a zero rate of strain. In, the terms regularizing the deformation included the covariance of the deformation matrices Σ and the vector fields (q). Here, we used a Lagrangian framework to reformulate this algorithm, showing that the regularizing terms essentially allow nonconservative work to occur during the flow. Given 3-D brain images from a group of subjects, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the nonstatistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the nonconservative terms, creating four versions of SAFIRA. We evaluated and compared our algorithms' performance on 92 3-D brain scans from healthy monozygotic and dizygotic twins; 2-D validations are also shown for corpus callosum shapes delineated at midline in the same subjects. After preliminary tests to demonstrate each method, we compared their detection power using tensor-based morphometry (TBM), a technique to analyze local volumetric differences in brain structure. We compared the accuracy of each algorithm variant using various statistical metrics derived from the images and deformation fields. All these tests were also run with a traditional fluid method, which has been quite widely used in TBM studies. The versions incorporating vector-based empirical statistics on brain variation were consistently more accurate than their counterparts, when used for automated volumetric quantification in new brain images. This suggests the advantages of this approach for large-scale neuroimaging studies.

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.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.

Mapping genetic influences on ventricular structure in twins

Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

Common genetic variants influence human subcortical brain structures

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08×10 -33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

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.

Neuroimaging and genetics: Exploring, searching, and finding

This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.

The presence of executive deficits in patients with Obstructive Sleep Apnoea

Obstructive sleep apnoea (OSA) is a chronic condition in which the upper airways collapse repeatedly during sleep, completely or partially obstructing breathing. This obstruction leads to chronic intermittent hypoxia and severe sleep fragmentation, disrupting the restorative functions of sleep. Beebe and Gozal (2002)a developed a theory which hypothesises that disruption of the restorative functions of sleep lead to a chronic low level brain damage most evident in executive functions (EF). Neuropsychological testing of EF, volumetric MRI, magnetic resonance spectroscopy, event related potentials and CSF biomarkers all provide support for this theory. Little research has been done to explore the nature of the subjective complaint and it’s impact on the activities of daily living.

Settling behaviours of low alumina/caustic ratios during seawater neutralisation of Bayer liquor

Factors that affect the settleability of seawater neutralised bauxite refinery residues are poorly understood, in particular, the settleability of precipitates in the absence of red mud and those formed with different alumina/caustic (AC) ratios. The influence of temperature, AC ratio, caustic concentration and the volumetric ratio of seawater on the settleability of seawater neutralisation precipitates and their respective compositions and stabilities have been determined. An array of techniques have been used to determine the composition and stability of precipitates and include pH, conductivity, inductively coupled plasma optical emission spectroscopy, infrared spectroscopy and X-ray diffraction. Temperature has been shown to have a significant influence on the settleability and calcium carbonate phase distributions in precipitates, as well as the overall stability of the precipitates. More complex phase compositions have also been found for Bayer liquors with lower AC ratios. The caustic concentration and temperature of the reaction have the greatest influence on the settling efficiency of the precipitates. Assessments on the chemical stability of the precipitates, precipitate settleability and discharge water quality have been made. In addition, productivity and environmental impacts caused by changes in precipitate settleability have also been considered.

Solution chemistry impacts on the seawater neutralisation process: Benefits of nanofiltered seawater and reverse osmosis brine

It is well known that the neutralisation of Bayer liquor with seawater causes the precipitation of stable alkaline products and a reduction in pH and dissolved metal concentrations in the effluent. However, there is limited information available on solution chemistry effects on the stability and reaction kinetics of these precipitates. This investigation shows the influence of reactive species (magnesium and calcium) in seawater on precipitate stabilities and volumetric efficiencies during the neutralisation of bauxite refinery residues. Correlations between synthetic seawater solutions and real samples of seawater (filtered seawater, nanofiltered seawater and reverse osmosis brine) have been made. These investigations have been used to confirm that alternative seawater sources can be used to increase the productivity potential of the neutralisation process with minimal implications on the composition and stability of precipitates formed. The volume efficiency of the neutralisation process using synthetic analogues has been shown to be almost directly proportional with the concentration of magnesium. This was further confirmed in the nanofiltered seawater and reverse osmosis brine that showed increases in the efficiency of neutralisation by factors of 3 and 2 compared to seawater, which corresponds with relatively the same increase in the concentration of magnesium in these alternative seawater sources. An assessment of the chemical stability of the precipitates, volumetric efficiency, and discharge water quality have been determined using numerous techniques that include pH, conductivity, inductively coupled plasma optical emission spectroscopy, infrared spectroscopy, thermogravimetric analysis coupled to mass spectrometry and X-ray diffraction. Correlations between synthetic solution compositions and alternative seawater sources have been used to determine if alternative seawater sources are potential substitutes for seawater based on improvements in productivity, implementation costs, savings to operations and environmental benefits.

Meta-analysis of structural imaging findings in Attention-Deficit/Hyperactivity Disorder

Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.

The effect of LRP5 polymorphisms on bone mineral density is apparent in childhood

Bone mass acquired during childhood is the primary determinant of adult bone mineral density (BMD) and osteoporosis risk. Bone accrual is subject to genetic influences. Activating and inactivating LRP5 gene mutations elicit extreme bone phenotypes, while more common LRP5 polymorphisms are associated with normal variation of BMD. Our aim was to test the hypothesis that LRP5 gene polymorphisms influence bone mass acquisition during childhood. The association between LRP5 gene polymorphisms and bone size and mineralization was examined in 819 unrelated British Caucasian children (n = 429 boys) aged 9 years. Height, weight, pubertal status (where available), total-body and spinal bone area, bone mineral content (BMC), BMD, and area-adjusted BMC (aBMC) were assessed. Dual-energy X-ray absorptiometry (DXA)-gene associations were assessed by linear regression, with adjustment for age, gender, pubertal status, and body size parameters. There were 140, 79, 12, and 2 girls who achieved Tanner stages I-IV, respectively, and 179 and 32 boys who achieved Tanner stages I and II, respectively. The rs2306862 (N740N) coding polymorphism in exon 10 of the LRP5 gene was associated with spinal BMD and aBMC (each P = 0.01) and total-body BMD and aBMC (P = 0.04 and 0.03, respectively). Adjusting for pubertal stage strengthened associations between this polymorphism and spinal BMD and aBMC (P = 0.01 and 0.002, respectively). Individuals homozygous for the T allele had greater spinal BMD and aBMC scores than those homozygous for the C allele. A dose effect was apparent as the mean spinal BMD and aBMC of heterozygous TC individuals were intermediate between those of their TT and CC counterparts. The N740N polymorphism in exon 10 of LRP5 was associated with spinal BMD and aBMC in pre- and early pubertal children. These results indicate that LRP5 influences volumetric bone density in childhood, possibly through effects on trabecular bone formation.

Analysis of parameter uncertainty and sensitivity in PCPF-1 modeling for predicting concentrations of rice herbicides

This paper demonstrates the procedures for probabilistic assessment of a pesticide fate and transport model, PCPF-1, to elucidate the modeling uncertainty using the Monte Carlo technique. Sensitivity analyses are performed to investigate the influence of herbicide characteristics and related soil properties on model outputs using four popular rice herbicides: mefenacet, pretilachlor, bensulfuron-methyl and imazosulfuron. Uncertainty quantification showed that the simulated concentrations in paddy water varied more than those of paddy soil. This tendency decreased as the simulation proceeded to a later period but remained important for herbicides having either high solubility or a high 1st-order dissolution rate. The sensitivity analysis indicated that PCPF-1 parameters requiring careful determination are primarily those involve with herbicide adsorption (the organic carbon content, the bulk density and the volumetric saturated water content), secondary parameters related with herbicide mass distribution between paddy water and soil (1st-order desorption and dissolution rates) and lastly, those involving herbicide degradations. © Pesticide Science Society of Japan.

A three-dimensional hybrid smoothed finite element method (H-SFEM) for nonlinear solid mechanics problems

This paper presents a novel three-dimensional hybrid smoothed finite element method (H-SFEM) for solid mechanics problems. In 3D H-SFEM, the strain field is assumed to be the weighted average between compatible strains from the finite element method (FEM) and smoothed strains from the node-based smoothed FEM with a parameter α equipped into H-SFEM. By adjusting α, the upper and lower bound solutions in the strain energy norm and eigenfrequencies can always be obtained. The optimized α value in 3D H-SFEM using a tetrahedron mesh possesses a close-to-exact stiffness of the continuous system, and produces ultra-accurate solutions in terms of displacement, strain energy and eigenfrequencies in the linear and nonlinear problems. The novel domain-based selective scheme is proposed leading to a combined selective H-SFEM model that is immune from volumetric locking and hence works well for nearly incompressible materials. The proposed 3D H-SFEM is an innovative and unique numerical method with its distinct features, which has great potential in the successful application for solid mechanics problems.

Remarkable Capacity Retention of Nanostructured Manganese Oxide upon Cycling as an Electrode Material for Supercapacitor

Electrochemical capacity retention of nearly X-ray amorphous nanostructured manganese oxide (nanoMnO2) synthesized by mixing directly KMnO4 with ethylene glycol under ambient conditions for supercapacitor studies is enhanced significantly. Although X-ray diffraction (XRD) pattern of nanoMnO2 shows poor crystallinity, it is found that by Mn K-edge X-ray absorption near edge structure (XANES) measurement that the nanoMnO2 obtained is locally arranged in a δ-MnO2-type layered structure composed of edge-shared network of MnO6 octahedra. Field emission scanning electron microscopy and XANES measurements show that nanoMnO2 contains nearly spherical shaped morphology with δ-MnO2 structure, and 1D nanorods of α-MnO2 type structure (powder XRD) in the annealed (600 °C) sample. Volumetric nitrogen adsorption−desorption isotherms, inductively coupled plasma analysis, and thermal analysis are carried out to obtain physicochemical properties such as surface area (230 m2 g−1), porosity of nanoMnO2 (secondary mesopores of diameter 14.5 nm), water content, composition, etc., which lead to the promising electrochemical properties as an electrode for supercapacitor. The nanoMnO2 shows a very high stability even after 1200 cycles with capacity retention of about 250 F g−1.