The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort

BACKGROUND

Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8-21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics.

METHODS

All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared with DTIPrep.

RESULTS

TSNR (AUC=0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC=0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n=374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of an age, sex and race matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images.

CONCLUSION

Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development.

Sex differences in thickness, and folding developments throughout the cortex

While significant differences in male and female brain structures have commonly been reported, only a few studies have focused on the sex differences in the way the cortex matures over time. Here, we investigated cortical thickness maturation between the age of 6 to 30 years, using 209 longitudinally-acquired brain MRI scans. Significant sex differences in the trajectories of cortical thickness change with age were evidenced using non-linear mixed effects models. Similar statistical analyses were computed to quantify the differences between cortical gyrification changes with age in males and females. During adolescence, we observed a statistically significant higher rate of cortical thinning in females compared to males in the right temporal regions, the left temporoparietal junction and the left orbitofrontal cortex. This finding is interpreted as a faster maturation of the social brain areas in females. Concomitantly, statistically significant sex differences in cortical folding changes with age were observed only in one cluster of the right prefrontal regions, suggesting that the mechanisms underlying cortical thickness and gyrification changes with age are quite distinct. Sexual dimorphism in the developmental course of the cortical maturation may be associated with the different age of onset and clinical presentation of many psychiatric disorders between males and females.

Review of sleep-EEG in preterm and term neonates

Neonatal sleep is a crucial state that involves endogenous driven brain activity, important for neuronal survival and guidance of brain networks. Sequential EEG-sleep analysis in preterm infants provides insights into functional brain integrity and can document deviations of the biologically pre-programmed process of sleep ontogenesis during the neonatal period. Visual assessment of neonatal sleep-EEG, with integration of both cerebral and non-cerebral measures to better define neonatal state, is still considered the gold standard. Electrographic patterns evolve over time and are gradually time locked with behavioural characteristics which allow classification of quiet sleep and active sleep periods during the last 10weeks of gestation. Near term age, the neonate expresses a short ultradian sleep cycle, with two distinct active and quiet sleep, as well as brief periods of transitional or indeterminate sleep. Qualitative assessment of neonatal sleep is however challenged by biological and environmental variables that influence the expression of EEG-sleep patterns and sleep organization. Developing normative EEG-sleep data with the aid of automated analytic methods, can further improve our understanding of extra-uterine brain development and state organization under stressful or pathological conditions. Based on those developmental biomarkers of normal and abnormal brain function, research can be conducted to support and optimise sleep in the NICU, with the ultimate goal to improve therapeutic interventions and neurodevelopmental outcome.

Electroencephalographic activity of preterm infants is increased by Family Nurture Intervention: a randomized controlled trial in the NICU

OBJECTIVE

To assess the impact of Family Nurture Intervention (FNI) on electroencephalogram (EEG) activity in preterm infants (26-34 weeks gestation).

METHODS

Two groups were tested in a single, level IV neonatal intensive care unit (NICU; standard care or standard care plus FNI) using a randomized controlled trial design. The intervention consists of sessions designed to achieve mutual calm and promote communication of affect between infants and their mothers throughout the NICU stay. EEG recordings were obtained from 134 infants during sleep at ∼35 and ∼40 weeks postmenstrual age (PMA). Regional brain activity (power) was computed for 10 frequency bands between 1 and 48 Hz in each of 125 electrodes.

RESULTS

Near to term age, compared to standard care infants, FNI infants showed robust increases in EEG power in the frontal polar region at frequencies 10 to 48 Hz (20% to 36% with p-values <0.0004). Effects were significant in both quiet and active sleep, regardless of gender, singleton-twin status, gestational age (26-30 or 30-35 weeks) or birth weight (<1500 or >1500 g).

CONCLUSION

FNI leads to increased frontal brain activity during sleep, which other investigators find predictive of better neurobehavioral outcomes.

SIGNIFICANCE

FNI may be a practicable means of improving outcomes in preterm infants.

Prediction of brain maturity based on cortical thickness at different spatial resolutions

Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity.

Preterm brain Injury: White matter injury

Despite the advances in neonatal intensive care, the preterm brain remains vulnerable to white matter injury (WMI) and disruption of normal brain development (i.e., dysmaturation). Compared to severe cystic WMI encountered in the past decades, contemporary cohorts of preterm neonates experience milder WMIs. More than destructive lesions, disruption of the normal developmental trajectory of cellular elements of the white and the gray matter occurs. In the acute phase, in response to hypoxia-ischemia and/or infection and inflammation, multifocal areas of necrosis within the periventricular white matter involve all cellular elements. Later, chronic WMI is characterized by diffuse WMI with aberrant regeneration of oligodendrocytes, which fail to mature to myelinating oligodendrocytes, leading to myelination disturbances. Complete neuronal degeneration classically accompanies necrotic white matter lesions, while altered neurogenesis, represented by a reduction of the dendritic arbor and synapse formation, is observed in response to diffuse WMI. Neuroimaging studies now provide more insight in assessing both injury and dysmaturation of both gray and white matter. Preterm brain injury remains an important cause of neurodevelopmental disabilities, which are still observed in up to 50% of the preterm survivors and take the form of a complex combination of motor, cognitive, and behavioral concerns.

Differences in white matter reflect atypical developmental trajectory in autism: A Tract-based Spatial Statistics study

Autism is a neurodevelopmental disorder in which white matter (WM) maturation is affected. We assessed WM integrity in 16 adolescents and 14 adults with high-functioning autism spectrum disorder (ASD) and in matched neurotypical controls (NT) using diffusion weighted imaging and Tract-based Spatial Statistics. Decreased fractional anisotropy (FA) was observed in adolescents with ASD in tracts involved in emotional face processing, language, and executive functioning, including the inferior fronto-occipital fasciculus and the inferior and superior longitudinal fasciculi. Remarkably, no differences in FA were observed between ASD and NT adults.

We evaluated the effect of age on WM development across the entire age range. Positive correlations between FA values and age were observed in the right inferior fronto-occipital fasciculus, the left superior longitudinal fasciculus, the corpus callosum, and the cortical spinal tract of ASD participants, but not in NT participants.

Our data underscore the dynamic nature of brain development in ASD, showing the presence of an atypical process of WM maturation, that appears to normalize over time and could be at the basis of behavioral improvements often observed in high-functioning autism.

Family Nurture Intervention in preterm infants alters frontal cortical functional connectivity assessed by EEG coherence

AIM

To assess the impact of Family Nurture Intervention (FNI) on cortical function in preterm infants at term age.

METHODS

Family Nurture Intervention is a NICU-based intervention designed to establish emotional connection between mothers and preterm infants. Infants born at 26-34 weeks postmenstrual age (PMA) were divided into two groups, standard care (SC, N = 49) and FNI (FNI, N = 56). Infants had EEG recordings of ~one hour duration with 124 lead nets between 37 and 44 weeks PMA. Coherence was measured between all pairs of electrodes in ten frequency bands. Data were summarised both within and between 12 regions during two sleep states (active, quiet).

RESULTS

Coherence levels were negatively correlated with PMA age in both groups. As compared to SC infants, FNI infants showed significantly lower levels of EEG coherence (1-18 Hz) largely within and between frontal regions.

CONCLUSION

Coherence in FNI infants was decreased in regions where we previously found robust increases in EEG power. As coherence decreases with age, results suggest that FNI may accelerate brain maturation particularly in frontal brain regions, which have been shown in research by others to be involved in regulation of attention, cognition and emotion regulation; domains deficient in preterm infants.

Early Parenting Intervention and Adverse Family Environments Affect Neural Function in Middle Childhood

BACKGROUND

Growing work points to the negative impact of early adverse experiences on the developing brain. An outstanding question concerns the extent to which early intervention can normalize trajectories of brain development in at-risk children. We tested this within the context of a randomized clinical trial of an early parenting program, the Attachment and Biobehavioral Catch-up (ABC), delivered to parents and infants monitored for maltreatment by Child Protective Services.

METHODS

Families participated in the randomized clinical trial when children were 2.5 years of age or younger. Parenting and home adversity was measured at baseline. Children were followed longitudinally, and resting brain activity was measured electrophysiologically (n = 106) when children reached 8 years of age. Spectral power was quantified and compared across children assigned to the experimental intervention (ABC), a control intervention, and a low-risk comparison group (n = 76) recruited at the follow-up assessment.

RESULTS

Higher early home adversity was associated with electrophysiological profiles indicative of cortical delays/immaturity in middle childhood, based on relatively greater power in lower frequency bands (theta, 4-6 Hz, and low alpha, 6-9 Hz) and lower power in a higher frequency band (high alpha, 9-12 Hz). Children assigned to ABC showed relatively greater high-frequency power (beta, 12-20 Hz) than children assigned to the control intervention. Beta power in the ABC did not differ from that of the low-risk comparison group.

CONCLUSIONS

Maltreatment risk and home adversity can affect indicators of middle childhood brain maturation. Early parenting programs can support more normative patterns of neural function during middle childhood.

A review of important electroencephalogram features for the assessment of brain maturation in premature infants

This review describes the maturational features of the baseline electroencephalogram (EEG) in the neurologically healthy preterm infant. Features such as continuity, sleep state, synchrony and transient waveforms are described, even from extremely preterm infants and includes abundant illustrated examples. The physiological significance of these EEG features and their relationship to neurodevelopment are highlighted where known. This review also demonstrates the importance of multichannel conventional EEG monitoring for preterm infants as many of the features described are not apparent if limited channel EEG monitors are used.

CONCLUSION

This review aims to provide healthcare professionals in the neonatal intensive care unit with guidance on the more common normal maturational features seen in the EEG of preterm infants.

MTE-NODDI: Multi-TE NODDI for disentangling non-T2-weighted signal fractions from compartment-specific T2 relaxation times

Neurite orientation dispersion and density imaging (NODDI) has become a popular diffusion MRI technique for investigating microstructural alternations during brain development, maturation and aging in health and disease. However, the NODDI model of diffusion does not explicitly account for compartment-specific T2 relaxation and its model parameters are usually estimated from data acquired with a single echo time (TE). Thus, the NODDI-derived measures, such as the intra-neurite signal fraction, also known as the neurite density index, could be T2-weighted and TE-dependent. This may confound the interpretation of studies as one cannot disentangle differences in diffusion from those in T2 relaxation. To address this challenge, we propose a multi-TE NODDI (MTE-NODDI) technique, inspired by recent studies exploiting the synergy between diffusion and T2 relaxation. MTE-NODDI could give robust estimates of the non-T2-weighted signal fractions and compartment-specific T2 values, as demonstrated by both simulation and in vivo data experiments. Results showed that the estimated non-T2 weighted intra-neurite fraction and compartment-specific T2 values in white matter were consistent with previous studies. The T2-weighted intra-neurite fractions from the original NODDI were found to be overestimated compared to their non-T2-weighted estimates; the overestimation increases with TE, consistent with the reported intra-neurite T2 being larger than extra-neurite T2. Finally, the inclusion of the free water compartment reduces the estimation error in intra-neurite T2 in the presence of cerebrospinal fluid contamination. With the ability to disentangle non-T2-weighted signal fractions from compartment-specific T2 relaxation, MTE-NODDI could help improve the interpretability of future neuroimaging studies, especially those in brain development, maturation and aging.

Line length as a robust method to detect high-activity events: automated burst detection in premature EEG recordings

OBJECTIVE

EEG is a valuable tool for evaluation of brain maturation in preterm babies. Preterm EEG constitutes of high voltage burst activities and more suppressed episodes, called interburst intervals (IBIs). Evolution of background characteristics provides information on brain maturation and helps in prediction of neurological outcome. The aim is to develop a method for automated burst detection.

METHODS

Thirteen polysomnography recordings were used, collected at preterm postmenstrual age of 31.4 (26.1-34.4)weeks. We developed a burst detection algorithm based on the feature line length and compared it with manual scorings of clinical experts and other published methods.

RESULTS

The line length-based algorithm is robust (84.27% accuracy, 84.00% sensitivity, 85.70% specificity). It is not critically dependent on the number of measurement channels, because two channels still provide 82% accuracy. Furthermore, it approximates well clinically relevant features, such as median IBI duration 5.45 (4.00-7.11)s, maximum IBI duration 14.02 (8.73-18.80)s and burst percentage 48.89 (35.45-60.12)%, with a median deviation of respectively 0.65s, 1.96s and 6.55%.

CONCLUSION

Automated assessment of long-term preterm EEG is possible and its use will optimize EEG interpretation in the NICU.

SIGNIFICANCE

This study takes a first step towards fully automatic analysis of the preterm brain.

Different maturational changes of fast and slow sleep spindles in the first four years of life

OBJECTIVE/BACKGROUND

Massive changes in brain morphology and function in the first years of life reveal a postero-anterior trajectory of cortical maturation accompanied by regional modifications of NREM sleep. One of the most sensible marker of this maturation process is represented by electroencephalographic (EEG) activity within the frequency range of sleep spindles. However, direct evidence that these changes actually reflect maturational modifications of fast and slow spindles still lacks. Our study aimed at answering the following questions: 1. Do cortical changes at 11.50 Hz frequency correspond to slow spindles? 2. Do fast and slow spindles show different age trajectories and different topographical distributions? 3. Do changes in peak frequency explain age changes of slow and fast spindles?

PATIENTS/METHODS

We measured the antero-posterior changes of slow and fast spindles in the first 60 min of nightly sleep of 39 infants and children (0-48 mo.).

RESULTS

We found that (A) changes of slow spindles from birth to childhood mostly affect frontal areas (B) variations of fast and slow spindles across age groups go in opposite direction, the latter progressively increasing across ages; (C) this process is not merely reducible to changes of spindle frequency.

CONCLUSIONS

As a main finding, our cross-sectional study shows that the first form of mature spindle (i.e., corresponding to the adult phasic event of NREM sleep) is marked by the emergence of slow spindles on anterior regions around the age of 12 months.

Microglia dynamics in adolescent traumatic brain injury

Repetitive, mild traumatic brain injuries (RmTBIs) are increasingly common in adolescents and encompass one of the largest neurological health concerns in the world. Adolescence is a critical period for brain development where RmTBIs can substantially impact neurodevelopmental trajectories and life-long neurological health. Our current understanding of RmTBI pathophysiology suggests key roles for neuroinflammation in negatively regulating neural health and function. Microglia, the brain’s resident immune population, play important roles in brain development by regulating neuronal number, and synapse formation and elimination. In response to injury, microglia activate to inflammatory phenotypes that may detract from these normal homeostatic, physiological, and developmental roles. To date, however, little is known regarding the impact of RmTBIs on microglia function during adolescent brain development. This review details key concepts surrounding RmTBI pathophysiology, adolescent brain development, and microglia dynamics in the developing brain and in response to injury, in an effort to formulate a hypothesis on how the intersection of these processes may modify long-term trajectories.

Quantification of myelin in children using multiparametric quantitative MRI: a pilot study

PURPOSE

The purpose of this study was to evaluate the usefulness of multiparametric quantitative MRI for myelination quantification in children.

METHODS

We examined 22 children (age 0-14 years) with multiparametric quantitative MRI. The total volume of myelin partial volume (Msum), the percentage of Msum within the whole brain parenchyma (Mbpv), and the percentage of Msum within the intracranial volume (Micv) were obtained. Four developmental models of myelin maturation (the logarithmic, logistic, Gompertz, and modified Gompertz models) were examined to find the most representative model of the three parameters. We acquired myelin partial volume values in different brain regions and assessed the goodness of fit for the models.

RESULTS

The ranges of Msum, Mbpv, and Micv were 0.8-160.9 ml, 0.2-13%, and 0.0-11.6%, respectively. The Gompertz model was the best fit for the three parameters. For developmental model analysis of myelin partial volume in each brain region, the Gompertz model was the best-fit model for pons (R ² = 74.6%), middle cerebeller peduncle (R ² = 76.4%), putamen (R² = 95.8%), and centrum semiovale (R ² = 77.7%). The logistic model was the best-fit model for the genu and splenium of the corpus callosum (R ² = 79.7-93.6%), thalamus (R ² = 81.7%), and frontal, parietal, temporal, and occipital white matter (R ² = 92.5-96.5%).

CONCLUSIONS

Multiparametric quantitative MRI depicts the normal developmental pattern of myelination in children. It is a potential tool for research studies on pediatric brain development evaluation.

Cerebral maturation in the early preterm period-A magnetization transfer and diffusion tensor imaging study using voxel-based analysis

The magnetization transfer ratio (MTR) and diffusion tensor imaging (DTI) correlates of early brain development were examined in cohort of 18 very preterm neonates (27-31 gestational weeks) presenting with normal radiological findings scanned within 2weeks after birth (28-32 gestational weeks). A combination of non-linear image registration, tissue segmentation, and voxel-wise regression was used to map the age dependent changes in MTR and DTI-derived parameters in 3D across the brain based on the cross-sectional in vivo preterm data. The regression coefficient maps obtained differed between brain regions and between the different quantitative MRI indices. Significant linear increases as well as decreases in MTR and DTI-derived parameters were observed throughout the preterm brain. In particular, the lamination pattern in the cerebral wall was evident on parametric and regression coefficient maps. The frontal white matter area (subplate and intermediate zone) demonstrated a linear decrease in MTR. While the intermediate zone showed an unexpected decrease in fractional anisotropy (FA) with age, with this decrease (and the increase in mean diffusivity (MD)) driven primarily by an increase in radial diffusivity (RD) values, the subplate showed no change in FA (and an increase in MD). The latter was the result of a concomitant similar increase in axial diffusivity (AD) and RD values. Interpreting the in vivo results in terms of available histological data, we present a biophysical model that describes the relation between various microstructural changes measured by complementary quantitative methods available on clinical scanners and a range of maturational processes in brain tissue.

Gyrification changes are related to cognitive strengths in autism

Background

Behavioral, cognitive and functional particularities in autism differ according to autism subgroups and might be associated with domain-specific cognitive strengths. It is unknown whether structural changes support this specialization. We investigated the link between cortical folding, its maturation and cognitive strengths in autism subgroups presenting verbal or visuo-spatial peaks of abilities.

Methods

We measured gyrification, a structural index related to function, in 55 autistic participants with (AS-SOD, N = 27) or without (AS-NoSOD, N = 28) a speech onset delay (SOD) with similar symptom severity but respectively perceptual and verbal cognitive strengths, and 37 typical adolescents and young adults matched for intelligence and age. We calculated the local Gyrification Index (lGI) throughout an occipito-temporal region of interest and independently modeled age and peak of ability effects for each group.

Results

Unique gyrification features in both autistic groups were detected in localized clusters. When comparing the three groups, gyrification was found lower in AS-SOD in a fusiform visual area, whereas it was higher in AS-NoSOD in a temporal language-related region. These particular areas presented age-related gyrification differences reflecting contrasting local maturation pathways in AS. As expected, peaks of ability were found in a verbal subtest for the AS-NoSOD group and in the Block Design IQ subtest for the AS-SOD group.

Conclusions

Irrespective of their direction, regional gyrification differences in visual and language processing areas respectively reflect AS-SOD perceptual and AS-NoSOD language-oriented peaks. Unique regional maturation trajectories in the autistic brain may underline specific cognitive strengths, which are key variables for understanding heterogeneity in autism.

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Subgrouping the autism spectrum (AS) partly accounts for its heterogeneity.

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AS individuals with a speech onset delay (SOD) show perceptual cognitive strengths.

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AS individuals without a SOD show language-related cognitive strengths.

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AS subgroups show unique gyrification patterns in areas related to their strengths.

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Cortical structural maturation may be related to domain-specific strengths in AS.

Chemotherapy-induced neurotoxicity in pediatric solid non-CNS tumor patients: An update on current state of research and recommended future directions

Neurocognitive sequelae are known to be induced by cranial radiotherapy and central-nervous-system-directed chemotherapy in childhood Acute Lymphoblastic Leukemia (ALL) and brain tumor patients. However, less evidence exists for solid non-CNS-tumor patients. To get a better understanding of the potential neurotoxic mechanisms of non-CNS-directed chemotherapy during childhood, we performed a comprehensive literature review of this topic. Here, we provide an overview of preclinical and clinical studies investigating neurotoxicity associated with chemotherapy in the treatment of pediatric solid non-CNS tumors. Research to date suggests that chemotherapy has deleterious biological and psychological effects, with animal studies demonstrating histological evidence for neurotoxic effects of specific agents and human studies demonstrating acute neurotoxicity. Although the existing literature suggests potential neurotoxicity throughout neurodevelopment, research into the long-term neurocognitive sequelae in survivors of non-CNS cancers remains limited. Therefore, we stress the critical need for neurodevelopmental focused research in children who are treated for solid non-CNS tumors, since they are at risk for potential neurocognitive impairment.

Awake surgery for hemispheric low-grade gliomas: oncological, functional and methodological differences between pediatric and adult populations

INTRODUCTION

Brain mapping through a direct cortical and subcortical electrical stimulation during an awake craniotomy has gained an increasing popularity as a powerful tool to prevent neurological deficit while increasing extent of resection of hemispheric diffuse low-grade gliomas in adults. However, few case reports or very limited series of awake surgery in children are currently available in the literature.

METHODS

In this paper, we review the oncological and functional differences between pediatric and adult populations, and the methodological specificities that may limit the use of awake mapping in pediatric low-grade glioma surgery.

RESULTS

This could be explained by the fact that pediatric low-grade gliomas have a different epidemiology and biologic behavior in comparison to adults, with pilocytic astrocytomas (WHO grade I glioma) as the most frequent histotype, and with WHO grade II gliomas less prone to anaplastic transformation than their adult counterparts. In addition, aside from the issue of poor collaboration of younger children under 10 years of age, some anatomical and functional peculiarities of children developing brain (cortical and subcortical myelination, maturation of neural networks and of specialized cortical areas) can influence direct electrical stimulation methodology and sensitivity, limiting its use in children.

CONCLUSIONS

Therefore, even though awake procedure with cortical and axonal stimulation mapping can be adapted in a specific subgroup of children with a diffuse glioma from the age of 10 years, only few pediatric patients are nonetheless candidates for awake brain surgery.

Amide Proton Transfer (APT) MR imaging and Magnetization Transfer (MT) MR imaging of pediatric brain development

OBJECTIVES

To quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla.

METHODS

Eighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis.

RESULTS

The APTW signals followed a decreasing exponential curve with age in all brain regions measured (R(2) = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation.

CONCLUSIONS

Together with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population.

KEY POINTS

• APTW signals followed a decreasing exponential curve with age. • The most significant APTW changes appeared within the first year • At maturation, larger APTW decreases and lower APTW appeared in white matter • MTR signals followed an increasing exponential curve with age.

Newborns and preterm infants at term equivalent age: A semi-quantitative assessment of cerebral maturity

BACKGROUND AND PURPOSE

Currently available MRI scoring systems of cerebral maturation in term and preterm infant at term equivalent age do not include the changes of transient fetal compartments that persist to term age. We studied the visibility and the pattern of these structures in healthy term newborns compared to preterm infants at term equivalent age in order to investigate if they can be included in a new MRI score system. We hypothesized that transient fetal compartments are different in both groups, and that these differences can be characterized using the clinical T2-weighted MRIs.

MATERIALS AND METHODS

Using 3T MRI T2-weighted brain sequences of 21 full-term and 41 preterm infants (< 32 weeks), scanned at term equivalent age, 3 raters independently scored the maturation level of 3 transient fetal compartments: the periventricular crossroads, von Monakow segments of the white matter, and the subplate compartment. These 3 new items were included in a scoring system along with validated parameters of brain maturation (germinal matrix, bands of migration, subarachnoid space and quality of gyrification). A cumulative maturity score was calculated separately for both groups of newborns by adding together each item. More mature were the brain structures, higher was the cumulative maturity score.

RESULTS

Cumulative maturity score distinguished full-term from preterm infants (mean score 41/60 ± 1.4 versus 37/60 ± 2.5 points, p < 0.001), with an increase of 0.5 points for each supplemental gestational week at birth (r = 0.5, 95% CI 0.5 - 0.85). While a majority of transient fetal compartments were less mature in preterm group at term equivalent age, von Monakow segments of the white matter and subplate compartment presented a more advanced maturational stage in the preterm group compared to the term group. No subject had all scored items in the most mature state. Except a slight intra-rater agreement for von Monakow segment II, inter- and intra-rater agreements were moderate to excellent indicating the potential of the developed scoring system in routine clinical practice.

CONCLUSION

Brain transient fetal structures can be assessed on regular T2-weighted MRI in newborns. Their appearance differs between term and preterm babies. However our results suggest a more complex situation, with both delayed and accelerated maturation pattern in preterm infants. It remains to be determined if these differences could be biomarkers of the future neurodevelopment of preterm infants.

Magnetoencephalographic signatures of conscious processing before birth

The concept of fetal consciousness is a widely discussed topic. In this study, we applied a hierarchical rule learning paradigm to investigate the possibility of fetal conscious processing during the last trimester of pregnancy. We used fetal magnetoencephalography, to assess fetal brain activity in 56 healthy fetuses between gestational week 25 and 40, during an auditory oddball paradigm containing first- and second-order regularities. The comparison of fetal brain responses towards standard and deviant tones revealed that the investigated fetuses show signs of hierarchical rule learning, and thus the formation of a memory trace for the second-order regularity. This ability develops over the course of the last trimester of gestation, in accordance with processes in physiological brain development and was only reliably present in fetuses older than week 35 of gestation. Analysis of fetal autonomic nervous system activity replicates findings in newborns, showing importance of activity state for cognitive processes. On the whole, our results support the assumption that fetuses in the last weeks of gestation are capable of consciously processing stimuli that reach them from outside the womb.

Localized Misfolding Within Broca's Area as a Distinctive Feature of Autistic Disorder

BACKGROUND

Recent neuroimaging studies suggest that autism spectrum disorder results from abnormalities in the cortical folding pattern. Usual morphometric measurements have failed to provide reliable neuroanatomic markers. Here, we propose that sulcal pits, which are the deepest points in each fold, are suitable candidates to uncover this atypical cortical folding.

METHODS

Sulcal pits were extracted from a magnetic resonance imaging database of 102 children (1.5-10 years old) distributed in three groups: children with autistic disorder (n = 59), typically developing children (n = 22), and children with pervasive developmental disorder not otherwise specified (n = 21). The geometrical properties of sulcal pits were compared between these three groups.

RESULTS

Fold-level analyses revealed a reduced pit depth in the left ascending ramus of the Sylvian fissure in children with autistic disorder only. The depth of this central fold of Broca's area was correlated with the social communication impairments that are characteristic of the pathology.

CONCLUSIONS

Our findings support an atypical gyrogenesis of this specific fold in autistic disorder that could be used for differential diagnosis. Sulcal pits constitute valuable markers of the cortical folding dynamics and could help for the early detection of atypical brain maturation.

Multivariate dynamical modelling of structural change during development

Here we introduce a multivariate framework for characterising longitudinal changes in structural MRI using dynamical systems. The general approach enables modelling changes of states in multiple imaging biomarkers typically observed during brain development, plasticity, ageing and degeneration, e.g. regional gray matter volume of multiple regions of interest (ROIs). Structural brain states follow intrinsic dynamics according to a linear system with additional inputs accounting for potential driving forces of brain development. In particular, the inputs to the system are specified to account for known or latent developmental growth/decline factors, e.g. due to effects of growth hormones, puberty, or sudden behavioural changes etc. Because effects of developmental factors might be region-specific, the sensitivity of each ROI to contributions of each factor is explicitly modelled. In addition to the external effects of developmental factors on regional change, the framework enables modelling and inference about directed (potentially reciprocal) interactions between brain regions, due to competition for space, or structural connectivity, and suchlike. This approach accounts for repeated measures in typical MRI studies of development and aging. Model inversion and posterior distributions are obtained using earlier established variational methods enabling Bayesian evidence-based comparisons between various models of structural change. Using this approach we demonstrate dynamic cortical changes during brain maturation between 6 and 22 years of age using a large openly available longitudinal paediatric dataset with 637 scans from 289 individuals. In particular, we model volumetric changes in 26 bilateral ROIs, which cover large portions of cortical and subcortical gray matter. We account for (1) puberty-related effects on gray matter regions; (2) effects of an early transient growth process with additional time-lag parameter; (3) sexual dimorphism by modelling parameter differences between boys and girls. There is evidence that the regional pattern of sensitivity to dynamic hidden growth factors in late childhood is similar across genders and shows a consistent anterior-posterior gradient with strongest impact to prefrontal cortex (PFC) brain changes. Finally, we demonstrate the potential of the framework to explore the coupling of structural changes across a priori defined subnetworks using an example of previously established resting state functional connectivity.

Effects of regional brain injury on the newborn autonomic nervous system

OBJECTIVE

Cerebral mapping of central autonomic nervous system (ANS)(1) function in mature animals and humans lateralizes sympathetic and parasympathetic influence predominantly to the right and left cerebral hemispheres, respectively. Spectral analysis of heart rate variability (HRV)(2) is an established measure of ANS function. We examined whether such lateralization is present in the term newborn.

METHODS

We retrospectively reviewed records of infants >36 weeks of gestation diagnosed with hypoxic ischemic encephalopathy (HIE).(3) We included infants with neonatal EEG and regional injury on brain MRI, which was scored using a schema. We extracted ECG signals from the EEG recording, but excluded periods of electrographic seizure activity to eliminate possible seizure influence on HRV. HRV was evaluated by spectral analysis in the high frequency (HF(4); 0.3-1 Hz) and low frequency (LF(5); 0.05-0.25 Hz) ranges, and the LF/HF ratio was examined to assess sympatho-vagal balance. The relation between the injured brain regions and HRV was studied using multiple linear regression models.

RESULTS

We studied 40 neonates with HIE. Injury to the right cerebral cortex (p=0.009) and right cerebellum (p=0.041) predicted a decreased LF/HF ratio. Injury to the left cerebral cortex (p=0.035) and left cerebellum (p=0.041) was associated with an increased LF/HF ratio. The association between brain injury location and the individual LF or HF spectral powers of brain injury did not reach significance.

CONCLUSIONS

Our data suggest that a functional lateralization for cerebral autonomic influence is established by term gestation.