A Multivariate Surface-Based Analysis of the Putamen in Premature Newborns: Regional Differences within the Ventral Striatum

Many children born preterm exhibit frontal executive dysfunction, behavioral problems including attentional deficit/hyperactivity disorder and attention related learning disabilities. Anomalies in regional specificity of cortico-striato-thalamo-cortical circuits may underlie deficits in these disorders. Nonspecific volumetric deficits of striatal structures have been documented in these subjects, but little is known about surface deformation in these structures. For the first time, here we found regional surface morphological differences in the preterm neonatal ventral striatum. We performed regional group comparisons of the surface anatomy of the striatum (putamen and globus pallidus) between 17 preterm and 19 term-born neonates at term-equivalent age. We reconstructed striatal surfaces from manually segmented brain magnetic resonance images and analyzed them using our in-house conformal mapping program. All surfaces were registered to a template with a new surface fluid registration method. Vertex-based statistical comparisons between the two groups were performed via four methods: univariate and multivariate tensor-based morphometry, the commonly used medial axis distance, and a combination of the last two statistics. We found statistically significant differences in regional morphology between the two groups that are consistent across statistics, but more extensive for multivariate measures. Differences were localized to the ventral aspect of the striatum. In particular, we found abnormalities in the preterm anterior/inferior putamen, which is interconnected with the medial orbital/prefrontal cortex and the midline thalamic nuclei including the medial dorsal nucleus and pulvinar. These findings support the hypothesis that the ventral striatum is vulnerable, within the cortico-stiato-thalamo-cortical neural circuitry, which may underlie the risk for long-term development of frontal executive dysfunction, attention deficit hyperactivity disorder and attention-related learning disabilities in preterm neonates. © 2013 Shi et al

Role of the advanced MRI sequences in predicting the outcome of preterm neonates

AIM The aim of the project is to evaluate the role of advanced MRI sequences (susceptibility weight imaging (SWI), diffusion tensor imaging (DTI), and arterial spin labeling (ASL) perfusion) in detecting early changes that affect preterm neonatal brain, especially in those patients without lesions at conventional MRI or with small brain injuries (i.e. low grade germinal matrix-intraventricular hemorrhage (GMHIVH)), and to correlate these subtle brain abnormalities with neurodevelopmental outcome at 24 months. METHODS Since November 2015 until June 2017, 287 preterm neonates and 108 term neonates underwent a 3T or 1.5T MRI study at term corrected age (40\ub11 weeks). SWI, DTI and ASL sequences were performed in all neonates. SWI sequences were evaluated using both a qualitative (SWI venography) and quantitative (Quantitative Susceptibility Map analysis (SWI-QSM)) approach. DTI data were analyzed using a Tract-Based Spatial Statistics analysis (TBSS). ASL studies were processed to estimate Cerebral Blood Flow (CBF) maps. Perinatal clinical data were collected for all neonates. Neurodevelopmental data were evaluated at 24 months in 175 neonates using 0-2 Griffiths Developmental Scales. RESULTS The analysis performed on SWI-venography revealed differences in subependymal veins morphology between preterm and term neonates with normal brain MRI, with a higher variability from the typical anatomical pattern in preterm neonates. The same analysis performed in preterm neonates with GMH-IVH revealed that the anatomical features of subependymal veins may play a potential role as predisposing factor for GMH-IVH. Moreover, the SWI-QSM analysis revealed a greater paramagnetic susceptibility in several periventricular white matter (WM) regions in preterm neonates with GMH-IVH than in healthy controls. This finding is likely related to the accumulation of hemosiderin/ferritin following the diffusion of large amounts of intraventricular blood products into the WM, and it is also supposed to trigger the cascade of lipid peroxidation and free radical formation that promote oxidative and inflammatory injury of the WM in neonatal brain after GMH-IVH. The TBSS analysis confirmed that microstructural WM injury can occur in preterm neonates with low grade GMH-IVH even in the absence of overt signal changes on conventional MRI, with different patterns of WM involvement depending on gestational age. Moreover, the distribution of these WM microstructural alterations after GMH-IVH correlates with specific neurodevelopmental impairments at 24 months of age. Finally, the analysis of brain perfusion at term-corrected age revealed lower CBF in preterms with sub-optimal neuromotor development, reinforcing the hypothesis that impaired autoregulation of CBF may contribute to the development of brain damage in preterm neonates. CONCLUSION Advanced MRI sequences can assist the standard perinatal brain imaging in the early diagnosis of preterm neonatal brain lesions and can provide new insights for predicting the neurodevelopmental trajectory. However, detailed and serial imaging of carefully chosen cohorts of neonates coupled with longer clinical follow-up are essential to ensure the clinical significance of these novel findings

Cerebral Hemodynamics in High-Risk Neonates Probed by Diffuse Optical Spectroscopies

Advances in medical and surgical care of the critically ill neonates have decreasedmortality, yet a significant number of these neonates suffer from neurodevelopmentaldelays and failure in school. Thus, clinicians are now focusing on prevention ofneurologic injury and improvement of neurocognitive outcome in these high-risk infants. Assessment of cerebral oxygenation, cerebral blood volume, and the regulation of cerebral blood flow (CBF) during the neonatal period is vital for evaluating brain health. Traditional CBF imaging methods fail, however, for both ethical and logistical reasons. In this dissertation, I demonstrate the use of non-invasive optical modalities, i.e., diffuse optical spectroscopy and diffuse correlation spectroscopy, to study cerebral oxygenation and cerebral blood flow in the critically ill neonatal population. The optical techniques utilize near-infrared (NIR) light to probe the static and dynamic physiological properties of deep tissues. Diffuse correlation spectroscopy (DCS) employs the transport of temporal correlation functions of diffusing light to extract relative changes in blood flow in biological tissues. Diffuse optical spectroscopy (DOS) employs the wavelength-dependent attenuation of NIR light to assess the concentrations of the primary chromophores in the tissue, namely oxy- and deoxy-hemoglobin. This dissertation presents both validation and clinical applications of novel diffuse optical spectroscopies in two specific critically ill neonatal populations: very-low birth weight preterm infants,and infants born with complex congenital heart defects. For validation of DCS in neonates, the blood flow index quantified by DCS is shown to correlate well with velocity measurements in the middle cerebral artery acquired by transcranial Doppler ultrasound. In patients with congenital heart defects DCS-measured relative changes in CBF due to hypercapnia agree strongly with relative changes in blood flow in the jugular veins as measured by phase-encoded velocity mapping magnetic resonance. For applications in the clinic, CO2 reactivity in patients with congenital heart defects prior to various stages of reconstructive surgery was quantified; our initial results suggest that CO2 reactivity is not systematically related to brain injury in this population. Additionally, the cerebral effects of various interventions, such as blood transfusion and sodium bicarbonate infusion, were investigated. In preterm infants, monitoring with DCS reveals a resilience of these patients to maintain constant CBF during a small postural manipulation

Effect of perinatal adversity on structural connectivity of the developing brain

Globally, preterm birth (defined as birth at <37 weeks of gestation) affects around 11% of deliveries and it is closely associated with cerebral palsy, cognitive impairments and neuropsychiatric diseases in later life. Magnetic Resonance Imaging (MRI) has utility for measuring different properties of the brain during the lifespan. Specially, diffusion MRI has been used in the neonatal period to quantify the effect of preterm birth on white matter structure, which enables inference about brain development and injury. By combining information from both structural and diffusion MRI, is it possible to calculate structural connectivity of the brain. This involves calculating a model of the brain as a network to extract features of interest. The process starts by defining a series of nodes (anatomical regions) and edges (connections between two anatomical regions). Once the network is created, different types of analysis can be performed to find features of interest, thereby allowing group wise comparisons. The main frameworks/tools designed to construct the brain connectome have been developed and tested in the adult human brain. There are several differences between the adult and the neonatal brain: marked variation in head size and shape, maturational processes leading to changes in signal intensity profiles, relatively lower spatial resolution, and lower contrast between tissue classes in the T1 weighted image. All of these issues make the standard processes to construct the brain connectome very challenging to apply in the neonatal population. Several groups have studied the neonatal structural connectivity proposing several alternatives to overcome these limitations. The aim of this thesis was to optimise the different steps involved in connectome analysis for neonatal data. First, to provide accurate parcellation of the cortex a new atlas was created based on a control population of term infants; this was achieved by propagating the atlas from an adult atlas through intermediate childhood spatio-temporal atlases using image registration. After this the advanced anatomically-constrained tractography framework was adapted for the neonatal population, refined using software tools for skull-stripping, tissue segmentation and parcellation specially designed and tested for the neonatal brain. Finally, the method was used to test the effect of early nutrition, specifically breast milk exposure, on structural connectivity in preterm infants. We found that infants with higher exposure to breastmilk in the weeks after preterm birth had improved structural connectivity of developing networks and greater fractional anisotropy in major white matter fasciculi. These data also show that the benefits are dose dependent with higher exposure correlating with increased white matter connectivity. In conclusion, structural connectivity is a robust method to investigate the developing human brain. We propose an optimised framework for the neonatal brain, designed for our data and using tools developed for the neonatal brain, and apply it to test the effect of breastmilk exposure on preterm infants

Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study

Background: Widespread lasting functional connectivity (FC) and brain volume changes in cortices and subcortices after premature birth have been researched in recent studies. However, the relationship remains unclear between spontaneously slow blood oxygen dependent level (BOLD) fluctuations and gray matter volume (GMV) changes in specific brain areas, such as temporal insular cortices, and whether classification methods based on MRI could be successfully applied to the identification of preterm individuals. In this thesis I hypothesized that in prematurely born adults 1. Ongoing neural excitability and brain activity, as estimated by regional functional connectivity of resting state functional MRI (rs-fMRI) is accompanied with altered low-frequency fluctuations and neonatal complications; 2. Altered regional functional connectivity is connected with superimposed cerebral structural reductions; and 3. multivariate neuroanatomical and functional brain patterns could be treated as features to identify preterm subjects from term subjects individually. Methods: To investigate these hypotheses, the principal results of structural alterations were measured with voxel-based morphometry (VBM), while rs-fMRI outcomes were estimated with amplitude of low-frequency fluctuations (ALFF) in analysis with ninety-four very preterm/very low birth weight (VP/VLBW) and ninety-two full-term (FT) born young adults. Results: The results of the thesis support the hypotheses by showing that, in univariate results, first in VP/VLBW grownups, ALFF was decreased in the left lateral temporal cortices no matter with global signal regression, and this reduction was closely associated with neonatal complications and cognitive variables. Second overlapped brain regions were found between reduced ALFF and reduced brain volumes in the left temporal cortices, and positively associated with each other, demonstrating a potential relationship between VBM and ALFF in this brain area. In multimodal multivariate pattern recognition analysis (MVPA), the gray matter volume (GMV) classifier displayed a higher accuracy (80.7%) contrast with the ALFF classifier (77.4%). The late fusion of GMV and ALFF did not outperform single GMV modality classification by reaching 80.4% accuracy. Moderator analysis from both rs-fMRI and structural MRI (sMRI) uncovered that the neuro-prematurity performance was predominantly determined by neonatal complications. Conclusions: In conclusion, these outcomes exhibit the long term effects of premature labour on lateral temporal cortices, which changed in both ongoing BOLD fluctuations and decreased cerebral structural volumes. This thesis further provided evidence that multivariate pattern analysis such as support vector machine (SVM) may identify imaging-based biomarkers and reliably detect signatures of preterm birth

Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study

Background: Widespread lasting functional connectivity (FC) and brain volume changes in cortices and subcortices after premature birth have been researched in recent studies. However, the relationship remains unclear between spontaneously slow blood oxygen dependent level (BOLD) fluctuations and gray matter volume (GMV) changes in specific brain areas, such as temporal insular cortices, and whether classification methods based on MRI could be successfully applied to the identification of preterm individuals. In this thesis I hypothesized that in prematurely born adults 1. Ongoing neural excitability and brain activity, as estimated by regional functional connectivity of resting state functional MRI (rs-fMRI) is accompanied with altered low-frequency fluctuations and neonatal complications; 2. Altered regional functional connectivity is connected with superimposed cerebral structural reductions; and 3. multivariate neuroanatomical and functional brain patterns could be treated as features to identify preterm subjects from term subjects individually. Methods: To investigate these hypotheses, the principal results of structural alterations were measured with voxel-based morphometry (VBM), while rs-fMRI outcomes were estimated with amplitude of low-frequency fluctuations (ALFF) in analysis with ninety-four very preterm/very low birth weight (VP/VLBW) and ninety-two full-term (FT) born young adults. Results: The results of the thesis support the hypotheses by showing that, in univariate results, first in VP/VLBW grownups, ALFF was decreased in the left lateral temporal cortices no matter with global signal regression, and this reduction was closely associated with neonatal complications and cognitive variables. Second overlapped brain regions were found between reduced ALFF and reduced brain volumes in the left temporal cortices, and positively associated with each other, demonstrating a potential relationship between VBM and ALFF in this brain area. In multimodal multivariate pattern recognition analysis (MVPA), the gray matter volume (GMV) classifier displayed a higher accuracy (80.7%) contrast with the ALFF classifier (77.4%). The late fusion of GMV and ALFF did not outperform single GMV modality classification by reaching 80.4% accuracy. Moderator analysis from both rs-fMRI and structural MRI (sMRI) uncovered that the neuro-prematurity performance was predominantly determined by neonatal complications. Conclusions: In conclusion, these outcomes exhibit the long term effects of premature labour on lateral temporal cortices, which changed in both ongoing BOLD fluctuations and decreased cerebral structural volumes. This thesis further provided evidence that multivariate pattern analysis such as support vector machine (SVM) may identify imaging-based biomarkers and reliably detect signatures of preterm birth

Motor and cortico-striatal-thalamic connectivity alterations in intrauterine growth restriction

BACKGROUND: Intrauterine growth restriction is associated with short-and long-term neurodevelopmental problems. Structural brain changes underlying these alterations have been described with the use of different magnetic resonance-based methods that include changes in whole structural brain networks. However, evaluation of specific brain circuits and its correlation with related functions has not been investigated in intrauterine growth restriction.OBJECTIVES: In this study, we aimed to investigate differences in tractography-related metrics in cortico-striatal-thalamic and motor networks in intrauterine growth restricted children and whether these parameters were related with their specific function in order to explore its potential use as an imaging biomarker of altered neurodevelopment.METHODS: We included a group of 24 intrauterine growth restriction subjects and 27 control subjects that were scanned at 1 year old; we acquired T1-weighted and 30 directions diffusion magnetic resonance images. Each subject brain was segmented in 93 regions with the use of anatomical automatic labeling atlas, and deterministic tractography was performed. Brain regions included in motor and cortico-striatal-thalamic networks were defined based in functional and anatomic criteria. Within the streamlines that resulted from the whole brain tractography, those belonging to each specific circuit were selected and tractography-related metrics that included number of streamlines, fractional anisotropy, and integrity were calculated for each network. We evaluated differences between both groups and further explored the correlation of these parameters with the results of socioemotional, cognitive, and motor scales from Bayley Scale at 2 years of age.RESULTS: Reduced fractional anisotropy (cortico-striatal-thalamic, 0.319 +/- 0.018 vs 0.315 +/- 0.015; P =.010; motor, 0.322 +/- 0.019 vs 0.319 +/- 0.020; P =.019) and integrity cortico-striatal-thalamic (0.407 +/- 0.040 vs 0.399 +/- 0.034; P =.018; motor, 0.417 +/- 0.044 vs 0.409 +/- 0.046; P =.016) in both networks were observed in the intrauterine growth restriction group, with no differences in number of streamlines. More importantly, strong specific correlation was found between tractography-related metrics and its relative function in both networks in intrauterine growth restricted children. Motor network metrics were correlated specifically with motor scale results (fractional anisotropy: rho = 0.857; integrity: rho = 0.740); cortico-striatal-thalamic network metrics were correlated with cognitive (fractional anisotropy: rho = 0.793; integrity, rho = 0.762) and socioemotional scale (fractional anisotropy: rho = 0.850; integrity: rho = 0.877).CONCLUSIONS: These results support the existence of altered brain connectivity in intrauterine growth restriction demonstrated by altered connectivity in motor and cortico-striatal-thalamic networks, with reduced fractional anisotropy and integrity. The specific correlation between tractography-related metrics and neurodevelopmental outcomes in intrauterine growth restriction shows the potential to use this approach to develop imaging biomarkers to predict specific neurodevelopmental outcome in infants who are at risk because of intrauterine growth restriction and other prenatal diseases

Explicit Motor Imagery for Grasping Actions in Children With Spastic Unilateral Cerebral Palsy

Background: Motor Imagery (MI) refers to mental simulation of a motor action without producing any overt movement. Previous studies showed that children with Unilateral Cerebral Palsy (UCP) are impaired in implicit MI, as demonstrated by the performance of Hand Laterality Judgment tasks. The aim of this study was to examine the specificity of explicit MI deficits in UCP children.Methods: A group of UCP children (n = 10; aged 9-14) performed a mental chronometry task consisting in grasping an object and placing it into a container, or in imagining to perform the same action. As control, a group of typically developing (TD) children, matched by age, performed the same task. Movement durations for executed and imagined trials were recorded. A subgroup of 7 UCP children and 10 TD children also underwent a session of functional MRI to examine the activation of parieto-frontal areas typically associated to MI processes, during the imagination of reaching-grasping actions performed with the paretic hand.Results: Behavioral results revealed the existence of a correlation between executed and imaginedmovement durations both in TD and UCP groups. Moreover, the regression analysis in TD children showed that higher scores in mental chronometry tasks were positively correlated to increased bilateral activation of the intraparietal sulcus (IPS), superior parietal lobule (SPL), and dorsal premotor (PMd) cortex. A similar analysis revealed in the UCP group a positive correlation between a higher score in the mental chronometry task and bilateral activations of IPS, and to activation of contralesional, right PMd, and putamen during imagination of grasping movements.Conclusions: These results provide new insights on the relationship between MI capacity and motor deficits in UCP children, suggesting the possibility of the use of explicit MI training to improve patient's upper limb motor functions