Brain charts for the human lifespan.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Cortical remodelling in childhood is associated with genes enriched for neurodevelopmental disorders.

Cortical development during childhood and adolescence has been characterised in recent years using metrics derived from Magnetic Resonance Imaging (MRI). Changes in cortical thickness are greatest in the first two decades of life and recapitulate the genetic organisation of the cortex, highlighting the potential early impact of gene expression on differences in cortical architecture over the lifespan. It is important to further our understanding of the possible neurobiological mechanisms that underlie these changes as cortical thickness may be altered in several common neurodevelopmental and psychiatric disorders. In this study, we combine MRI acquired from a large typically-developing childhood population (n â€‹= â€‹768) with comprehensive human gene expression databases to test the hypothesis that disrupted mechanisms common to neurodevelopmental disorders are encoded by genes expressed early in development and nested within those associated with typical cortical remodelling in childhood. We find that differential rates of thinning across the developing cortex are associated with spatially-varying gradients of gene expression. Genes that are expressed highly in regions of accelerated thinning are expressed predominantly in cortical neurons, involved in synaptic remodelling, and associated with common cognitive and neurodevelopmental disorders. Further, we identify subsets of genes that are highly expressed in the prenatal period and jointly associated with both developmental cortical morphology and neurodevelopmental disorders.

Feasibility of a multi-modal exercise program on cognition in older adults with Type 2 diabetes - a pilot randomised controlled trial.

BACKGROUND: Type 2 Diabetes (T2D) is associated with increased risk of dementia. We aimed to determine the feasibility of a randomised controlled trial (RCT) examining the efficacy of exercise on cognition and brain structure in people with T2D. METHODS: A 6-month pilot parallel RCT of a progressive aerobic- and resistance-training program versus a gentle movement control group in people with T2D aged 50-75 years (n = 50) at the University of Tasmania, Australia. Assessors were blinded to group allocation. Brain volume (total, white matter, hippocampus), cortical thickness and white matter microstructure (fractional anisotrophy and mean diffusivity) were measured using magnetic resonance imaging, and cognition using a battery of neuropsychological tests. Study design was assessed by any changes (during the pilot or recommended) to the protocol, recruitment by numbers screened and time to enrol 50 participants; randomisation by similarity of characteristics in groups at baseline, adherence by exercise class attendance; safety by number and description of adverse events and retention by numbers withdrawn. RESULTS: The mean age of participants was 66.2 (SD 4.9) years and 48% were women. There were no changes to the design during the study. A total of 114 people were screened for eligibility, with 50 participants with T2D enrolled over 8 months. Forty-seven participants (94%) completed the study (23 of 24 controls; 24 of 26 in the intervention group). Baseline characteristics were reasonably balanced between groups. Exercise class attendance was 79% for the intervention and 75% for the control group. There were 6 serious adverse events assessed as not or unlikely to be due to the intervention. Effect sizes for each outcome variable are provided. CONCLUSION: This study supports the feasibility of a large scale RCT to test the benefits of multi-modal exercise to prevent cognitive decline in people with T2D. Design changes to the future trial are provided. TRIAL REGISTRATION: ANZCTR 12614000222640 ; Registered 3/3/2014; First participant enrolled 26/6/2014, study screening commenced 1/9/2014; Australian and New Zealand Clinical Trial Registry.

The Association of Type 2 Diabetes Mellitus with Cerebral Gray Matter Volume Is Independent of Retinal Vascular Architecture and Retinopathy.

It is uncertain whether small vessel disease underlies the relationship between Type 2 Diabetes Mellitus (T2DM) and brain atrophy. We aimed to study whether retinal vascular architecture, as a proxy for cerebral small vessel disease, may modify or mediate the associations of T2DM with brain volumes. In this cross-sectional study using Magnetic Resonance Imaging (MRI) scans and retinal photographs in 451 people with and without T2DM, we measured brain volumes, geometric measures of retinal vascular architecture, clinical retinopathy, and MRI cerebrovascular lesions. There were 270 people with (mean age 67.3 years) and 181 without T2DM (mean age 72.9 years). T2DM was associated with lower gray matter volume (p = 0.008). T2DM was associated with greater arteriolar diameter (p = 0.03) and optimality ratio (p = 0.04), but these associations were attenuated by adjustments for age and sex. Only optimality ratio was associated with lower gray matter volume (p = 0.03). The inclusion of retinal measures in regression models did not attenuate the association of T2DM with gray matter volume. The association of T2DM with lower gray matter volume was independent of retinal vascular architecture and clinical retinopathy. Retinal vascular measures or retinopathy may not be sufficiently sensitive to confirm a microvascular basis for T2DM-related brain atrophy.

Automatic intracranial space segmentation for computed tomography brain images.

Craniofacial disorders are routinely diagnosed using computed tomography imaging. Corrective surgery is often performed early in life to restore the skull to a more normal shape. In order to quantitatively assess the shape change due to surgery, we present an automated method for intracranial space segmentation. The method utilizes a two-stage approach which firstly initializes the segmentation with a cascade of mathematical morphology operations. This segmentation is then refined with a level-set-based approach that ensures that low-contrast boundaries, where bone is absent, are completed smoothly. We demonstrate this method on a dataset of 43 images and show that the method produces consistent and accurate results.

An assessment of methods for aligning two-dimensional microscope sections to create image volumes.

This study assessed five different methods for aligning microscope images of Nissl-stained sections of mouse brain to form three-dimensional image volumes. Methods exploiting both image content and information from un-sectioned tissue were investigated. The accuracy of reconstruction was estimated using fiducials with known physical properties, demonstrating that methods exploiting tissue content produced distorted image volumes while a method using artificial fiducials produced the most accurate and unbiased alignment. Methodological issues relating to methods of volume reconstruction are discussed and it is recommended that methods using information from un-sectioned tissue be used wherever possible.