Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis

Systems-level identification and analysis of cellular circuits in the brain will require the development of whole-brain imaging with single-cell resolution. To this end, we performed comprehensive chemical screening to develop a whole-brain clearing and imaging method, termed CUBIC (clear, unobstructed brain imaging cocktails and computational analysis). CUBIC is a simple and efficient method involving the immersion of brain samples in chemical mixtures containing aminoalcohols, which enables rapid whole-brain imaging with single-photon excitation microscopy. CUBIC is applicable to multicolor imaging of fluorescent proteins or immunostained samples in adult brains and is scalable from a primate brain to subcellular structures. We also developed a whole-brain cell-nuclear counterstaining protocol and a computational image analysis pipeline that, together with CUBIC reagents, enable the visualization and quantification of neural activities induced by environmental stimulation. CUBIC enables time-course expression profiling of whole adult brains with single-cell resolution.

Whole-Body Imaging with Single-Cell Resolution by Tissue Decolorization

The development of whole-body imaging at single-cell resolution enables system-level approaches to studying cellular circuits in organisms. Previous clearing methods focused on homogenizing mismatched refractive indices of individual tissues, enabling reductions in opacity but falling short of achieving transparency. Here, we show that an aminoalcohol decolorizes blood by efficiently eluting the heme chromophore from hemoglobin. Direct transcardial perfusion of an aminoalcohol-containing cocktail that we previously termed CUBIC coupled with a 10 day to 2 week clearing protocol decolorized and rendered nearly transparent almost all organs of adult mice as well as the entire body of infant and adult mice. This CUBIC-perfusion protocol enables rapid whole-body and whole-organ imaging at single-cell resolution by using light-sheet fluorescent microscopy. The CUBIC protocol is also applicable to 3D pathology, anatomy, and immunohistochemistry of various organs. These results suggest that whole-body imaging of colorless tissues at high resolution will contribute to organism-level systems biology.

A three dimensional virtual medical imaging computed tomography suite: Innovation in education

Aims: The Medical Imaging Training Immersive Environment(MITIE) Computed Tomography(CT) system is an innovative virtual reality (VR) platform that allows students to practice a range of CT techniques. The aim of this pilot study was to harvest user feedback about the educational value of teh application and inform future pedagogical development. This presentation explores the use of this technology for skills training. Background: MITIE CT is a 3D VR environment that allows students to position a patient,and set CT technical parameters including IV contrast dose and dose rate. As with VR initiatives in other health disciplines the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software is new and was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia 'Simulated Learning Environments' grant Methods: Current third year medical imaging students were provided with additional 1 hour MITIE laboratory tutorials and studnet feedback was collated with regard to educational value and performance. Ethical approval for the project was provided by the university ethics panel Results: This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application's significance as a pre-clinical tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either on campus or during their clinical placement. Conclusion: Student feedback indicates that MITIE CT has a valuable role to play in the clinial skills training for medical imaging students both in the academic and clinical environment. Future work will establish a framework for an appropriate supprting pedagogy that can cross the boundary between the two environments

Medical imaging and Biomechanical analysis of scoliosis progression in the growing adolescent spine

Progression of spinal deformity in children was studied with Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) to identify how gravity affects the deformity and to determine the full three-dimensional character of the deformity. The CT study showed that gravity is significant in deformity progression in some patients which has implications for clinical patient management. The world first MRI study showed that the standard clinical measure used to define the extent of the deformity is inadequate and further use of three-dimensional MRI should be considered by spinal surgeons.

Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Mapping genetic influences on brain fiber architecture with high angular resolution diffusion imaging (HARDI)

We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.

Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Prefrontal cortex involvement in selective letter generation: A functional magnetic resonance imaging study

Cerebral responses to alternating periods of a control task and a selective letter generation paradigm were investigated with functional Magnetic Resonance Imaging (fMRI). Subjects selectively generated letters from four designated sets of six letters from the English language alphabet, with the instruction that they were not to produce letters in alphabetical order either forward or backward, repeat or alternate letters. Performance during this condition was compared with that of a control condition in which subjects recited the same letters in alphabetical order. Analyses revealed significant and extensive foci of activation in a number of cerebral regions including mid-dorsolateral frontal cortex, inferior frontal gyrus, precuneus, supramarginal gyrus, and cerebellum during the selective letter generation condition. These findings are discussed with respect to recent positron emission tomography (PET) and fMRI studies of verbal working memory and encoding/retrieval in episodic memory.

Development of brain structural connectivity between ages 12 and 30: A 4-Tesla diffusion imaging study in 439 adolescents and adults

Understanding how the brain matures in healthy individuals is critical for evaluating deviations from normal development in psychiatric and neurodevelopmental disorders. The brain's anatomical networks are profoundly re-modeled between childhood and adulthood, and diffusion tractography offers unprecedented power to reconstruct these networks and neural pathways in vivo. Here we tracked changes in structural connectivity and network efficiency in 439 right-handed individuals aged 12 to 30 (211 female/126 male adults, mean age=23.6, SD=2.19; 31 female/24 male 12 year olds, mean age=12.3, SD=0.18; and 25 female/22 male 16 year olds, mean age=16.2, SD=0.37). All participants were scanned with high angular resolution diffusion imaging (HARDI) at 4 T. After we performed whole brain tractography, 70 cortical gyral-based regions of interest were extracted from each participant's co-registered anatomical scans. The proportion of fiber connections between all pairs of cortical regions, or nodes, was found to create symmetric fiber density matrices, reflecting the structural brain network. From those 70 × 70 matrices we computed graph theory metrics characterizing structural connectivity. Several key global and nodal metrics changed across development, showing increased network integration, with some connections pruned and others strengthened. The increases and decreases in fiber density, however, were not distributed proportionally across the brain. The frontal cortex had a disproportionate number of decreases in fiber density while the temporal cortex had a disproportionate number of increases in fiber density. This large-scale analysis of the developing structural connectome offers a foundation to develop statistical criteria for aberrant brain connectivity as the human brain matures.

Development of insula connectivity between ages 12 and 30 revealed by high angular resolution diffusion imaging

The insula, hidden deep within the Sylvian fissures, has proven difficult to study from a connectivity perspective. Most of our current information on the anatomical connectivity of the insula comes from studies of nonhuman primates and post mortem human dissections. To date, only two neuroimaging studies have successfully examined the connectivity of the insula. Here we examine how the connectivity of the insula develops between ages 12 and 30, in 307 young adolescent and adult subjects scanned with 4-Tesla high angular resolution diffusion imaging (HARDI). The density of fiber connections between the insula and the frontal and parietal cortex decreased with age, but the connection density between the insula and the temporal cortex generally increased with age. This trajectory is in line with well-known patterns of cortical development in these regions. In addition, males and females showed different developmental trajectories for the connection between the left insula and the left precentral gyrus. The insula plays many different roles, some of them affected in neuropsychiatric disorders; this information on the insula's connectivity may help efforts to elucidate mechanisms of brain disorders in which it is implicated.

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.

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Diffusion imaging protocol effects on genetic associations

Large multi-site image-analysis studies have successfully discovered genetic variants that affect brain structure in tens of thousands of subjects scanned worldwide. Candidate genes have also associated with brain integrity, measured using fractional anisotropy in diffusion tensor images (DTI). To evaluate the heritability and robustness of DTI measures as a target for genetic analysis, we compared 417 twins and siblings scanned on the same day on the same high field scanner (4-Tesla) with two protocols: (1) 94-directions; 2mm-thick slices, (2) 27-directions; 5mm-thickness. Using mean FA in white matter ROIs and FA skeletons derived using FSL, we (1) examined differences in voxelwise means, variances, and correlations among the measures; and (2) assessed heritability with structural equation models, using the classical twin design. FA measures from the genu of the corpus callosum were highly heritable, regardless of protocol. Genome-wide analysis of the genu mean FA revealed differences across protocols in the top associations.