Dilatation of Lateral Ventricles with Brain Volumes in Infants with 3D Transfontanelle US

Ultrasound (US) can be used to assess brain development in newborns, as MRI is challenging due to immobilization issues, and may require sedation. Dilatation of the lateral ventricles in the brain is a risk factor for poorer neurodevelopment outcomes in infants. Hence, 3D US has the ability to assess the volume of the lateral ventricles similar to clinically standard MRI, but manual segmentation is time consuming. The objective of this study is to develop an approach quantifying the ratio of lateral ventricular dilatation with respect to total brain volume using 3D US, which can assess the severity of macrocephaly. Automatic segmentation of the lateral ventricles is achieved with a multi-atlas deformable registration approach using locally linear correlation metrics for US-MRI fusion, followed by a refinement step using deformable mesh models. Total brain volume is estimated using a 3D ellipsoid modeling approach. Validation was performed on a cohort of 12 infants, ranging from 2 to 8.5 months old, where 3D US and MRI were used to compare brain volumes and segmented lateral ventricles. Automatically extracted volumes from 3D US show a high correlation and no statistically significant difference when compared to ground truth measurements. Differences in volume ratios was 6.0 +/- 4.8% compared to MRI, while lateral ventricular segmentation yielded a mean Dice coefficient of 70.8 +/- 3.6% and a mean absolute distance (MAD) of 0.88 +/- 0.2mm, demonstrating the clinical benefit of this tool in paediatric ultrasound

Non-local MRI upsampling.

International audienceIn Magnetic Resonance Imaging, image resolution is limited by several factors such as hardware or time constraints. In many cases, the acquired images have to be upsampled to match a specific resolution. In such cases, image interpolation techniques have been traditionally applied. However, traditional interpolation techniques are not able to recover high frequency information of the underlying high resolution data. In this paper, a new upsampling method is proposed to recover some of this high frequency information by using a data-adaptive patch-based reconstruction in combination with a subsampling coherence constraint. The proposed method has been evaluated on synthetic and real clinical cases and compared with traditional interpolation methods. The proposed method is shown to outperform classical interpolation methods compared in terms of quantitative measures and visual observation

From von Neumann architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications

Spatio/Spector-Temporal Data (SSTD) analyzing is a challenging task, as temporal features may manifest complex interactions that may also change over time. Making use of suitable models that can capture the “hidden” interactions and interrelationship among multivariate data, is vital in SSTD investigation. This chapter describes a number of prominent applications built using the Kasabov’s NeuCube-based Spiking Neural Network (SNN) architecture for mapping, learning, visualization, classification/regression and better understanding and interpretation of SSTD

A novel framework for the local extraction of extra-axial cerebrospinal fluid from MR brain images

The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain developmental. Extr a-axial fluid (EA-CSF), which is characterized by the CSF in the subarachnoid space, is promising in the early detection of children at risk for neurodevelopmental disorders. Currently, though, there is no tool to extract local EA-CSF measurements in a way that is suitable for localized analysis. In this paper, we propose a novel framework for the localized, cortical surface based analysis of EA-CSF. In our proposed processing, we combine probabilistic brain tissue segmentation, cortical surface reconstruction as well as streamline based local EA-CSF quantification. For streamline computation, we employ the vector field generated by solving a Laplacian partial differential equation (PDE) between the cortical surface and the outer CSF hull. To achieve sub-voxel accuracy while minimizing numerical errors, fourth-order Runge-Kutta (RK4) integration was used to generate the streamlines. Finally, the local EA-CSF is computed by integrating the CSF probability along the generated streamlines. The proposed local EA-CSF extraction tool was used to study the early postnatal brain development in typically developing infants. The results show that the proposed localized EA-CSF extraction pipeline can produce statistically significant regions that are not observed in previous global approach

Morphometric Changes of the Corpus Callosum in Congenital Blindness

We examined the effects of visual deprivation at birth on the development of the corpus callosum in a large group of congenitally blind individuals. We acquired high-resolution T1-weighted MRI scans in 28 congenitally blind and 28 normal sighted subjects matched for age and gender. There was no overall group effect of visual deprivation on the total surface area of the corpus callosum. However, subdividing the corpus callosum into five subdivisions revealed significant regional changes in its three most posterior parts. Compared to the sighted controls, congenitally blind individuals showed a 12 reduction in the splenium, and a 20 increase in the isthmus and the posterior part of the body. A shape analysis further revealed that the bending angle of the corpus callosum was more convex in congenitally blind compared to the sighted control subjects. The observed morphometric changes in the corpus callosum are in line with the well-described cross-modal functional and structural neuroplastic changes in congenital blindness

The increase of the functional entropy of the human brain with age

We use entropy to characterize intrinsic ageing properties of the human brain. Analysis of fMRI data from a large dataset of individuals, using resting state BOLD signals, demonstrated that a functional entropy associated with brain activity increases with age. During an average lifespan, the entropy, which was calculated from a population of individuals, increased by approximately 0.1 bits, due to correlations in BOLD activity becoming more widely distributed. We attribute this to the number of excitatory neurons and the excitatory conductance decreasing with age. Incorporating these properties into a computational model leads to quantitatively similar results to the fMRI data. Our dataset involved males and females and we found significant differences between them. The entropy of males at birth was lower than that of females. However, the entropies of the two sexes increase at different rates, and intersect at approximately 50 years; after this age, males have a larger entropy

Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system

We present the first three-dimensional, functional images of the human brain to be obtained using a fibre-less, high-density diffuse optical tomography system. Our technology consists of independent, miniaturized, silicone-encapsulated DOT modules that can be placed directly on the scalp. Four of these modules were arranged to provide up to 128, dual-wavelength measurement channels over a scalp area of approximately 60 × 65 mm2. Using a series of motor-cortex stimulation experiments, we demonstrate that this system can obtain high-quality, continuous-wave measurements at source-detector separations ranging from 14 to 55 mm in adults, in the presence of hair. We identify robust haemodynamic response functions in 5 out of 5 subjects, and present diffuse optical tomography images that depict functional haemodynamic responses that are well-localized in all three dimensions at both the individual and group levels. This prototype modular system paves the way for a new generation of wearable, wireless, high-density optical neuroimaging technologies

Dynamic amyloid and metabolic signatures of delayed recall performance within the clinical spectrum of Alzheimer’s disease

Associations between pathophysiological events and cognitive measures provide insights regarding brain networks affected during the clinical progression of Alzheimer’s disease (AD). In this study, we assessed patients’ scores in two delayed episodic memory tests, and investigated their associations with regional amyloid deposition and brain metabolism across the clinical spectrum of AD. We assessed the clinical, neuropsychological, structural, and positron emission tomography (PET) baseline measures of participants from the Alzheimer’s Disease Neuroimaging Initiative. Subjects were classified as cognitively normal (CN), or with early (EMCI) or late (LMCI) mild cognitive impairment, or AD dementia. The memory outcome measures of interest were logical memory 30 min delayed recall (LM30) and Rey Auditory Verbal Learning Test 30 min delayed recall (RAVLT30). Voxel-based [18F]florbetapir and [18F]FDG uptake-ratio maps were constructed and correlations between PET images and cognitive scores were calculated. We found that EMCI individuals had LM30 scores negatively correlated with [18F]florbetapir uptake on the right parieto-occipital region. LMCI individuals had LM30 scores positively associated with left lateral temporal lobe [18F]FDG uptake, and RAVLT30 scores positively associated with [18F]FDG uptake in the left parietal lobe and in the right enthorhinal cortex. Additionally, LMCI individuals had LM30 scores negatively correlated with [18F]florbetapir uptake in the right frontal lobe. For the AD group, [18F]FDG uptake was positively correlated with LM30 in the left temporal lobe and with RAVLT30 in the right frontal lobe, and [18F]florbetapir uptake was negatively correlated with LM30 scores in the right parietal and left frontal lobes. The results show that the association between regional brain metabolism and the severity of episodic memory deficits is dependent on the clinical disease stage, suggesting a dynamic relationship between verbal episodic memory deficits, AD pathophysiology, and clinical disease stages