Inhomogeneity Correction in High Field Magnetic Resonance Images

Projecte realitzat en col.laboració amb el centre Swiss Federal Institute of Technology (EPFL)Magnetic Resonance Imaging, MRI, is one of the most powerful and harmless ways to study human inner tissues. It gives the chance of having an accurate insight into the physiological condition of the human body, and specially, the brain. Following this aim, in the last decade MRI has moved to ever higher magnetic field strength that allow us to get advantage of a better signal-to-noise ratio. This improvement of the SNR, which increases almost linearly with the field strength, has several advantages: higher spatial resolution and/or faster imaging, greater spectral dispersion, as well as an enhanced sensitivity to magnetic susceptibility. However, at high magnetic resonance imaging, the interactions between the RF pulse and the high permittivity samples, which causes the so called Intensity Inhomogeneity or B1 inhomogeneity, can no longer be negligible. This inhomogeneity causes undesired efects that afects quantitatively image analysis and avoid the application classical intensity-based segmentation and other medical functions. In this Master thesis, a new method for Intensity Inhomogeneity correction at high ¯eld is presented. At high ¯eld is not possible to achieve the estimation and the correction directly from the corrupted data. Thus, this method attempt the correction by acquiring extra information during the image process, the RF map. The method estimates the inhomogeneity by the comparison of both acquisitions. The results are compared to other methods, the PABIC and the Low-Pass Filter which try to correct the inhomogeneity directly from the corrupted data

Structural Brain Connectivity in School-Age Preterm Infants Provides Evidence for Impaired Networks Relevant for Higher Order Cognitive Skills and Social Cognition

Extreme prematurity and pregnancy conditions leading to intrauterine growth restriction (IUGR) affect thousands of newborns every year and increase their risk for poor higher order cognitive and social skills at school age. However, little is known about the brain structural basis of these disabilities. To compare the structural integrity of neural circuits between prematurely born controls and children born extreme preterm (EP) or with IUGR at school age, long-ranging and short-ranging connections were noninvasively mapped across cortical hemispheres by connection matrices derived from diffusion tensor tractography. Brain connectivity was modeled along fiber bundles connecting 83 brain regions by a weighted characterization of structural connectivity (SC). EP and IUGR subjects, when compared with controls, had decreased fractional anisotropy-weighted SC (FAw-SC) of cortico-basal ganglia-thalamo-cortical loop connections while cortico-cortical association connections showed both decreased and increased FAw-SC. FAw-SC strength of these connections was associated with poorer socio-cognitive performance in both EP and IUGR childre

Corrigendum: Structural Brain Network Reorganization and Social Cognition Related to Adverse Perinatal Condition from Infancy to Early Adolescence

In the original article, we omitted a reference to Réveillon et al. (2016) regarding the description of the neuropsychological tests performed by the children and the association between IUGR and hyperactivity/inattention symptoms. This reference is cited in the description of the third cohort (Section Materials and Methods. Subjects) and in the Correlation between Network Metrics and Neuropsychological Score section, as appeared below. We also had neglected to thank the invaluable contribution of the team involved in recruitment, imaging acquisition, and neuropsychological testing. The revised version of the acknowledgments is provided below. The authors apologize for the oversight. These errors do not change the scientific conclusions of the article in any way

Structural Brain Connectivity in School-Age Preterm Infants Provides Evidence for Impaired Networks Relevant for Higher Order Cognitive Skills and Social Cognition.

Extreme prematurity and pregnancy conditions leading to intrauterine growth restriction (IUGR) affect thousands of newborns every year and increase their risk for poor higher order cognitive and social skills at school age. However, little is known about the brain structural basis of these disabilities. To compare the structural integrity of neural circuits between prematurely born controls and children born extreme preterm (EP) or with IUGR at school age, long-ranging and short-ranging connections were noninvasively mapped across cortical hemispheres by connection matrices derived from diffusion tensor tractography. Brain connectivity was modeled along fiber bundles connecting 83 brain regions by a weighted characterization of structural connectivity (SC). EP and IUGR subjects, when compared with controls, had decreased fractional anisotropy-weighted SC (FAw-SC) of cortico-basal ganglia-thalamo-cortical loop connections while cortico-cortical association connections showed both decreased and increased FAw-SC. FAw-SC strength of these connections was associated with poorer socio-cognitive performance in both EP and IUGR children

Neuroepigenetics of preterm white matter injury

Introduction: Preterm birth is increasing worldwide and is a major cause of neonatal death. Survivors are at increased risk of neurodisability, cognitive, social and psychiatric disorders in later life. Alterations to the white matter can be assessed using diffusion tensor imaging (DTI) MRI and are associated with poor neurodevelopmental outcome. The pathogenesis of white matter injury is multifactorial and several clinical risk and resilience factors have been identified. DNA methylation (DNAm) is an epigenetic process which links stressful early life experience to later life disease and is associated with normal brain development, neuronal processes and neurological disease. Several studies have shown DNAm is altered by the perinatal environment, however its role in preterm white mater injury is yet to be investigated. Aims: 1. To examine the relationship between preterm birth and white matter integrity 2. To investigate the effect of neuroprotective treatments and deleterious clinical states on white matter integrity in preterm infants 3. To assess the best DTI method of quantifying white matter integrity in a neonatal population 4. To investigate the effect of preterm birth on DNA methylation and 5. To determine the clinical and imaging factors that contribute to the variance in DNA Methylation caused by preterm birth Methods: DTI data was acquired from preterm infants (< 32 weeks’ gestation or < 1500 grams at birth) at term equivalent age (TEA) and term controls (> 37 weeks’ gestation at birth). Region-of-interests (ROI) and tract-averaged methods of DTI analysis were performed to obtain measurements of fractional anisotropy (FA) and mean diffusivity (MD) in the genu of corpus callosum, posterior limb of internal capsule and centrum semiovale. Clinical data was collected for all infants and the effect of prematurity, neuroprotective agents and clinical risk factors on white matter integrity were analysed. 8 major white matter tracts were segmented using probabilistic neighbourhood tractography (PNT), a tract-averaged technique which also allowed the calculation of tract shape. The two DTI techniques were compared to evaluate agreement between results. DNA was collected from preterm infants and term controls at TEA, and a genome-wide analysis of DNAm was performed. DTI parameters from probabilistic neighborhood tractography (PNT) methodology and clinical risk and resilience factors were used to inform a principal components analysis to investigate the contribution of white matter integrity and clinical variables to variance in DNAm. Results: FA and MD were significantly affected by preterm birth on ROI analysis. In addition, DTI parameters were affected by clinical factors that included antenatal magnesium sulphate, histological chorioamnionitis and bronchopulmonary dysplasia. Evaluation of DTI methodology revealed good accuracy in repeated ROI measurements but limited agreement with tract-averaged values. Differential methylation was found within 25 gene bodies and 58 promoters of protein-coding genes in preterm infants, compared with controls. 10 of these genes have a documented association with neural function or neurological disease. Differences detected in the array were validated with pyrosequencing which captured additional differentially methylated CpGs. Ninety-five percent of the variance in DNAm in preterm infants was explained by 23 principal components (PC); corticospinal tract shape associated with 6th PC, and gender and early nutritional exposure associated with the 7th PC. Conclusions: Preterm birth is associated with alterations in white matter integrity which is modifiable by clinical risk factors and neuroprotective agents. ROI analysis may not provide sufficient representation of white matter tracts in their entirety. Prematurity is related to alterations in the methylome at sites that influence neural development and function. Differential methylation analysis has identified several promising candidate genes for future work and contributed to the understanding of the pathogenesis of preterm brain injury

Inhomogeneity Correction in High Field Magnetic Resonance Images

Projecte realitzat en col.laboració amb el centre Swiss Federal Institute of Technology (EPFL)Magnetic Resonance Imaging, MRI, is one of the most powerful and harmless ways to study human inner tissues. It gives the chance of having an accurate insight into the physiological condition of the human body, and specially, the brain. Following this aim, in the last decade MRI has moved to ever higher magnetic field strength that allow us to get advantage of a better signal-to-noise ratio. This improvement of the SNR, which increases almost linearly with the field strength, has several advantages: higher spatial resolution and/or faster imaging, greater spectral dispersion, as well as an enhanced sensitivity to magnetic susceptibility. However, at high magnetic resonance imaging, the interactions between the RF pulse and the high permittivity samples, which causes the so called Intensity Inhomogeneity or B1 inhomogeneity, can no longer be negligible. This inhomogeneity causes undesired efects that afects quantitatively image analysis and avoid the application classical intensity-based segmentation and other medical functions. In this Master thesis, a new method for Intensity Inhomogeneity correction at high ¯eld is presented. At high ¯eld is not possible to achieve the estimation and the correction directly from the corrupted data. Thus, this method attempt the correction by acquiring extra information during the image process, the RF map. The method estimates the inhomogeneity by the comparison of both acquisitions. The results are compared to other methods, the PABIC and the Low-Pass Filter which try to correct the inhomogeneity directly from the corrupted data

Inhomogeneity Correction in High Field Magnetic Resonance Images

Projecte realitzat en col.laboració amb el centre Swiss Federal Institute of Technology (EPFL)Magnetic Resonance Imaging, MRI, is one of the most powerful and harmless ways to study human inner tissues. It gives the chance of having an accurate insight into the physiological condition of the human body, and specially, the brain. Following this aim, in the last decade MRI has moved to ever higher magnetic field strength that allow us to get advantage of a better signal-to-noise ratio. This improvement of the SNR, which increases almost linearly with the field strength, has several advantages: higher spatial resolution and/or faster imaging, greater spectral dispersion, as well as an enhanced sensitivity to magnetic susceptibility. However, at high magnetic resonance imaging, the interactions between the RF pulse and the high permittivity samples, which causes the so called Intensity Inhomogeneity or B1 inhomogeneity, can no longer be negligible. This inhomogeneity causes undesired efects that afects quantitatively image analysis and avoid the application classical intensity-based segmentation and other medical functions. In this Master thesis, a new method for Intensity Inhomogeneity correction at high ¯eld is presented. At high ¯eld is not possible to achieve the estimation and the correction directly from the corrupted data. Thus, this method attempt the correction by acquiring extra information during the image process, the RF map. The method estimates the inhomogeneity by the comparison of both acquisitions. The results are compared to other methods, the PABIC and the Low-Pass Filter which try to correct the inhomogeneity directly from the corrupted data

Structural Brain Network Reorganization and Social Cognition related to Adverse Perinatal Condition from Infancy to Early Adolescence

Adverse conditions during fetal life have been associated to both structural and functional changes in neurodevelopment from the neonatal period to adolescence. In this study, connectomics was used to assess the evolution of brain networks from infancy to early adolescence. Brain network reorganization over time in subjects who had suffered adverse perinatal conditions is characterized and related to neurodevelopment and cognition. Three cohorts of prematurely born infants and children (between 28 and 35 weeks of gestational age), including individuals with a birth weight appropriated for gestational age and with intrauterine growth restriction (IUGR), were evaluated at one, six and ten years of age respectively. A common developmental trajectory of brain networks was identified in both control and IUGR groups: network efficiencies of the fractional anisotropy (FA)-weighted and normalized connectomes increase with age, which can be related to maturation and myelination of fiber connections while the number of connections decreases, which can be associated to an axonal pruning process and reorganization. Comparing subjects with or without IUGR, a similar pattern of network differences between groups was observed in the three developmental stages, mainly characterized by IUGR group having reduced brain network efficiencies in binary and FA-weighted connectomes and increased efficiencies in the connectome normalized by its total connection strength (FA). Associations between brain networks and neurobehavioral impairments were also evaluated showing a relationship between different network metrics and specific social cognition-related scores, as well as a higher risk of inattention/hyperactivity and/or executive functional disorders in IUGR children