A COMPUTATIONAL FRAMEWORK FOR NEONATAL BRAIN MRI STRUCTURE SEGMENTATION AND CLASSIFICATION

Deep Learning is increasingly being used in both supervised and unsupervised learning to derive complex patterns from data. However, the successful implementation of deep learning using medical imaging requires careful consideration for the quality and availability of data. Infants diagnosed with CHD are at a higher risk for neurodevelopmental impairment. Many of these deficits may be attenuated by early detection and intervention. However, we currently lack effective diagnostic tools for the reliable detection of these disorders at the neonatal period. We believe that the structural correlates of the cognitive deficits associated with developmental abnormalities can be measured within the first few months of life. Based on this assumption, we hypothesize that we can use an atlas registration based structural segmentation pipeline to sufficiently reduce the search space of neonatal structural brain MRI to viably implement convolutional neural networks for dysplasia classification. Secondly, we hypothesize that convolutional neural networks can successfully identify morphological biomarkers capable of detecting structurally abnormal brain substructures. In this study, we develop a computational framework for the automated classification of dysplastic substructures from neonatal MRI. We validate our implementation on a dataset of neonates born with CHD, as this is a vulnerable population for structural dysmaturation. We chose the cerebellum as the initial test substructure because of its relatively simple structure and known vulnerability to structural dysplasia in infants born with CHD. We then apply the same method to the hippocampus, a more challenging substructure due to its complex morphological properties. We attempt to overcome the limited availability of clinical data in neonatal populations by first extracting each brain substructure of interest and individually registering them into a standard space. This greatly reduces the search space required to learn the subtle abnormalities associated with a given pathology, making it feasible to implement a 3-D CNN as the classification algorithm. We achieved excellent classification accuracy in detecting dysplastic cerebelli, and demonstrate a viable computational framework for search space reduction using limited clinical datasets. All methods developed in this work are designed to be extensible, reproducible, and generalizable diagnostic tools for future neuroimaging problems

Ações de fomento do BNDES em renda variável via fundos de investimentos à Região Sul

Bibliografia: p. 245Caracterizada pelo empreendedorismo, pelo conhecimento tecnológico e por investimentos em infraestrutura, a Região Sul conta com um grande número de empresas que vêm sendo alvo dos investimentos de diversos fundos dos quais o Sistema BNDES, via BNDESPAR, participa em conjunto com agentes privados e outros investidores. Essa atuação da BNDESPAR contribui para estimular o empreendedorismo, desenvolver empresas inovadoras, modernizar a infraestrutura e estimular a cultura de capital de risco na região, além de preconizar a adoção de melhores práticas de gestão e governança.Acknowledged for its entrepreneurship, its technological knowhow and investments in infrastructure, the South Region of Brazil has a large number of companies receiving investment from several funds in which the BNDES System, via BNDESPAR, works with private agents and other investors. BNDESPAR's operations help not only boost entrepreneurship, but also develop innovating companies, modernize infrastructure and foster the risk capital culture in the region. In addition, they promote good management and governance practices

An alternative route to obtain carbon quantum dots from photoluminescent materials in peat

Peat, an organic compound easily found in the soil (easy to acquire), has more than 50% elemental carbon in its composition and can be used as raw material to produce carbon quantum dots (CQDs, C-dots, Carbon Dots). In this work we describe two simple and low-cost routes for the acquisition of these photoluminescent materials based on peat. The final products were characterized by Fourier transform infrared spectroscopy (FTIR), absorption (UV-Vis) and emission (PL) spectra and high-resolution transmission electron microscopy (HRTEM). The produced CQDs have an average size of 3.5 nm and exhibit coloration between blue and green. In addition, it is possible to produce photoluminescence by means of the aromatic compounds also present in the composition of the peat, in turn exhibiting an intense green coloration. The results indicate great versatility of peat for the production of photoluminescent materials

SQUATI - sistema de qualidade de TI

Acompanhado de CD-ROMInclui apendicesOrientador : Prof. Jaime WojciechowskiMonografia (graduação) - Universidade Federal do Paraná, Setor Educação Profissional e Tecnológica, Curso de Graduação em Tecnologia em Sistemas de InformaçãoInclui bibliografi

Regional vulnerability of longitudinal cortical association connectivity

Preterm born children with spastic diplegia type of cerebral palsy and white matter injury or periventricular leukomalacia (PVL), are known to have motor, visual and cognitive impairments. Most diffusion tensor imaging (DTI) studies performed in this group have demonstrated widespread abnormalities using averaged deterministic tractography and voxel-based DTI measurements. Little is known about structural network correlates of white matter topography and reorganization in preterm cerebral palsy, despite the availability of new therapies and the need for brain imaging biomarkers. Here, we combined novel post-processing methodology of probabilistic tractography data in this preterm cohort to improve spatial and regional delineation of longitudinal cortical association tract abnormalities using an along-tract approach, and compared these data to structural DTI cortical network topology analysis. DTI images were acquired on 16 preterm children with cerebral palsy (mean age 5.6 ± 4) and 75 healthy controls (mean age 5.7 ± 3.4). Despite mean tract analysis, Tract-Based Spatial Statistics (TBSS) and voxel-based morphometry (VBM) demonstrating diffusely reduced fractional anisotropy (FA) reduction in all white matter tracts, the along-tract analysis improved the detection of regional tract vulnerability. The along-tract map-structural network topology correlates revealed two associations: (1) reduced regional posterior–anterior gradient in FA of the longitudinal visual cortical association tracts (inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiation, posterior thalamic radiation) correlated with reduced posterior–anterior gradient of intra-regional (nodal efficiency) metrics with relative sparing of frontal and temporal regions; and (2) reduced regional FA within frontal–thalamic–striatal white matter pathways (anterior limb/anterior thalamic radiation, superior longitudinal fasciculus and cortical spinal tract) correlated with alteration in eigenvector centrality, clustering coefficient (inter-regional) and participation co-efficient (inter-modular) alterations of frontal–striatal and fronto-limbic nodes suggesting re-organization of these pathways. Both along tract and structural topology network measurements correlated strongly with motor and visual clinical outcome scores. This study shows the value of combining along-tract analysis and structural network topology in depicting not only selective parietal occipital regional vulnerability but also reorganization of frontal–striatal and frontal–limbic pathways in preterm children with cerebral palsy. These finding also support the concept that widespread, but selective posterior–anterior neural network connectivity alterations in preterm children with cerebral palsy likely contribute to the pathogenesis of neurosensory and cognitive impairment in this group

Reduced Cerebellar Volume in Term Infants with Complex Congenital Heart Disease: Correlation with Postnatal Growth Measurements

Aberrant cerebellar development and the associated neurocognitive deficits has been postulated in infants with congenital heart disease (CHD). Our objective is to investigate the effect of postnatal head and somatic growth on cerebellar development in neonates with CHD. We compared term-born neonates with a history of CHD with a cohort of preterm-born neonates, two cohorts at similar risk for neurodevelopment impairment, in order to determine if they are similarly affected in the early developmental period. Study Design: 51 preterms-born healthy neonates, 62 term-born CHD neonates, and 54 term-born healthy neonates underwent a brain MRI with volumetric imaging. Cerebellar volumes were extracted through an automated segmentation pipeline that was developed in-house. Volumes were correlated with clinical growth parameters at both the birth and time of MRI. Results: The CHD cohort showed significantly lower cerebellar volumes when compared with both the control (p < 0.015) and preterm (p < 0.004) groups. Change in weight from birth to time of MRI showed a moderately strong correlation with cerebellar volume at time of MRI (r = 0.437, p < 0.002) in the preterms, but not in the CHD neonates (r = 0.205, p < 0.116). Changes in birth length and head circumference showed no significant correlation with cerebellar volume at time of MRI in either cohort. Conclusions: Cerebellar development in premature-born infants is associated with change in birth weight in the early post-natal period. This association is not observed in term-born neonates with CHD, suggesting differential mechanisms of aberrant cerebellar development in these perinatal at-risk populations

A Descriptive Review of the Impact of Patient Motion in Early Childhood Resting-State Functional Magnetic Resonance Imaging

Resting-state functional magnetic images (rs-fMRIs) can be used to map and delineate the brain activity occurring while the patient is in a task-free state. These resting-state activity networks can be informative when diagnosing various neurodevelopmental diseases, but only if the images are high quality. The quality of an rs-fMRI rapidly degrades when the patient moves during the scan. Herein, we describe how patient motion impacts an rs-fMRI on multiple levels. We begin with how the electromagnetic field and pulses of an MR scanner interact with a patient’s physiology, how movement affects the net signal acquired by the scanner, and how motion can be quantified from rs-fMRI. We then present methods for preventing motion through educational and behavioral interventions appropriate for different age groups, techniques for prospectively monitoring and correcting motion during the acquisition process, and pipelines for mitigating the effects of motion in existing scans

Developmental synergy between thalamic structure and interhemispheric connectivity in the visual system of preterm infants

Thalamic structural co-variation with cortical regions has been demonstrated in preterm infants, but its relationship to cortical function and severity of non-cystic white matter injury (non-cystic WMI) is unclear. The relationship between thalamic morphology and both cortical network synchronization and cortical structural connectivity has not been established. We tested the hypothesis that in preterm neonates, thalamic volume would correlate with primary cortical visual function and microstructural integrity of cortico-cortical visual association pathways. A total of 80 term-equivalent preterm and 44 term-born infants underwent high-resolution structural imaging coupled with visual functional magnetic resonance imaging or diffusion tensor imaging. There was a strong correlation between thalamic volume and primary visual cortical activation in preterms with non-cystic WMI (r = 0.81, p-value = 0.001). Thalamic volume also correlated strongly with interhemispheric cortico-cortical connectivity (splenium) in preterm neonates with a relatively higher severity of non-cystic WMI (p-value < 0.001). In contrast, there was lower correlation between thalamic volume and intrahemispheric cortico-cortical connectivity, including the inferior longitudinal fasciculus and inferior frontal orbital fasciculus. This study shows distinct temporal overlap in the disruption of thalamo-cortical and interhemispheric cortico-cortical connectivity in preterm infants suggesting developmental synergy between thalamic morphology and the emergence of cortical networks in the last trimester