Interpreting Age Effects of Human Fetal Brain from Spontaneous fMRI using Deep 3D Convolutional Neural Networks

Understanding human fetal neurodevelopment is of great clinical importance as abnormal development is linked to adverse neuropsychiatric outcomes after birth. Recent advances in functional Magnetic Resonance Imaging (fMRI) have provided new insight into development of the human brain before birth, but these studies have predominately focused on brain functional connectivity (i.e. Fisher z-score), which requires manual processing steps for feature extraction from fMRI images. Deep learning approaches (i.e., Convolutional Neural Networks) have achieved remarkable success on learning directly from image data, yet have not been applied on fetal fMRI for understanding fetal neurodevelopment. Here, we bridge this gap by applying a novel application of deep 3D CNN to fetal blood oxygen-level dependence (BOLD) resting-state fMRI data. Specifically, we test a supervised CNN framework as a data-driven approach to isolate variation in fMRI signals that relate to younger v.s. older fetal age groups. Based on the learned CNN, we further perform sensitivity analysis to identify brain regions in which changes in BOLD signal are strongly associated with fetal brain age. The findings demonstrate that deep CNNs are a promising approach for identifying spontaneous functional patterns in fetal brain activity that discriminate age groups. Further, we discovered that regions that most strongly differentiate groups are largely bilateral, share similar distribution in older and younger age groups, and are areas of heightened metabolic activity in early human development.Comment: 9 page

Automated brain masking of fetal functional MRI with open data

Fetal resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a critical new approach for characterizing brain development before birth. Despite the rapid and widespread growth of this approach, at present, we lack neuroimaging processing pipelines suited to address the unique challenges inherent in this data type. Here, we solve the most challenging processing step, rapid and accurate isolation of the fetal brain from surrounding tissue across thousands of non-stationary 3D brain volumes. Leveraging our library of 1,241 manually traced fetal fMRI images from 207 fetuses, we trained a Convolutional Neural Network (CNN) that achieved excellent performance across two held-out test sets from separate scanners and populations. Furthermore, we unite the auto-masking model with additional fMRI preprocessing steps from existing software and provide insight into our adaptation of each step. This work represents an initial advancement towards a fully comprehensive, open-source workflow, with openly shared code and data, for fetal functional MRI data preprocessing

Maternal stress during pregnancy alters fetal cortico-cerebellar connectivity in utero and increases child sleep problems after birth

Child sleep disorders are increasingly prevalent and understanding early predictors of sleep problems, starting in utero, may meaningfully guide future prevention efforts. Here, we investigated whether prenatal exposure to maternal psychological stress is associated with increased sleep problems in toddlers. We also examined whether fetal brain connectivity has direct or indirect influence on this putative association. Pregnant women underwent fetal resting-state functional connectivity MRI and completed questionnaires on stress, worry, and negative affect. At 3-year follow-up, 64 mothers reported on child sleep problems, and in the subset that have reached 5-year follow-up, actigraphy data (N = 25) has also been obtained. We observe that higher maternal prenatal stress is associated with increased toddler sleep concerns, with actigraphy sleep metrics, and with decreased fetal cerebellar-insular connectivity. Specific mediating effects were not identified for the fetal brain regions examined. The search for underlying mechanisms of the link between maternal prenatal stress and child sleep problems should be continued and extended to other brain areas

Developmental variation in regional brain iron and its relation to cognitive functions in childhood

Non-heme iron is a vital metabolic cofactor for many core processes of brain development including myelination, dendritogenesis, and neurotransmitter synthesis, and accumulates in the brain with age. However, little is known about development-related differences in brain iron and its association with emerging cognitive abilities during formative years. In this study, we estimated brain iron via R2* relaxometry in children ages 7–16 (N = 57; 38 females) and examined its relation to age-related differences in cognitive ability. As we hypothesized, age correlated positively with iron content in the hippocampus and across subregions of the basal ganglia. The magnitude of age differences in iron content differed between regions such that the largest effects were observed in basal ganglia subregions: globus pallidus, substantia nigra, caudate nucleus, and putamen, as compared to values obtained for the hippocampus and red nucleus. We did not observe sex or hemispheric differences in iron content. Notably, greater brain iron content was associated with both faster processing speed and higher general intelligence, and shared 21.4% of the age-related improvement in processing speed and 12.5% of the improvement in general intelligence. These results suggest that non-heme iron plays a central neurobiological role in the development of critical cognitive abilities during childhood. Keywords: Non-heme iron, Development, Cognition, R2* relaxometr

Altered mental status with mirror giant middle cerebral artery aneurysms: A case report

Introduction: Mirror aneurysms of the middle cerebral artery (MCA) constitute 14% of all MCA aneurysms, which commonly arise from the MCA bifurcation. Giant MCA aneurysms (>25 mm in diameter) have a reported 5-year rupture rate of 40%, though can be difficult to treat surgically given their complex nature. Giant aneurysms may present with symptoms of mass effect, including neurological deficit, headaches, and/or cranial neuropathies. To our knowledge, no case of mirror bilateral giant MCA aneurysms exists in the neurosurgical literature. Case description: Here we present a case of mirror bilateral giant MCA aneurysms in an 84-year-old man who presented with altered mental status and increased falls in the last year. Imaging revealed mirror MCA aneurysms, 3.5 and 4 cm in diameter respectively, arising from bilateral M1 segments. The patient opted to forego further evaluation or surgical intervention and was discharged home. Conclusion: We report the first known case of mirror bilateral giant MCA aneurysms were found in an 84-year-old man presenting with altered mental status and progressive decline across the last year

An examination of maternal prenatal BMI and human fetal brain development

Background: Prenatal development is a time when the brain is acutely vulnerable to insult and alteration by environmental factors (e.g., toxins, maternal health). One important risk factor is maternal obesity (Body Mass Index > 30). Recent research indicates that high maternal BMI during pregnancy is associated with increased risk for numerous physical health, cognitive, and mental health problems in offspring across the lifespan. It is possible that heightened maternal prenatal BMI influences the developing brain even before birth. Methods: The present study examines this possibility at the level of macrocircuitry in the human fetal brain. Using a data-driven strategy for parcellating the brain into subnetworks, we test whether MRI functional connectivity within or between fetal neural subnetworks varies with maternal prenatal BMI in 109 fetuses between the ages of 26 and 39weeks. Results: We discovered that strength of connectivity between two subnetworks, left anterior insula/inferior frontal gyrus (aIN/IFG) and bilateral prefrontal cortex (PFC), varied with maternal BMI. At the level of individual aIN/IFG-PFC connections, we observed both increased and decreased between-network connectivity with a tendency for increased within-hemisphere connectivity and reduced cross-hemisphere connectivity in higher BMI pregnancies. Maternal BMI was not associated with global differences in network topography based on network-based statistical analyses. Conclusions: Overall effects were localized in regions that will later support behavioral regulation and integrative processes, regions commonly associated with obesity-related deficits. By establishing onset in neural differences prior to birth, this study supports a model in which maternal BMI-related risk is associated with fetal connectome-level brain organization with implications for offspring long-term cognitive development and mental health

Hubs in the human fetal brain network

Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging. Consistent with prior reports in infants, visual and motor regions were identified as emerging hub areas, specifically in cerebellar areas. We also found evidence for network hubs in association cortex, including areas remarkably close to the adult fusiform facial and Wernicke areas. Functional significance of hub structure was confirmed by computationally deleting hub versus random nodes and observing that global efficiency decreased significantly more when hubs were removed (p <.001). Taken together, we conclude that both primary and association brain regions demonstrate centrality in network organization before birth. While fetal hubs may be important for facilitating network communication, they may also form potential points of vulnerability in fetal brain development

Hubs in the human fetal brain network

Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging. Consistent with prior reports in infants, visual and motor regions were identified as emerging hub areas, specifically in cerebellar areas. We also found evidence for network hubs in association cortex, including areas remarkably close to the adult fusiform facial and Wernicke areas. Functional significance of hub structure was confirmed by computationally deleting hub versus random nodes and observing that global efficiency decreased significantly more when hubs were removed (p <.001). Taken together, we conclude that both primary and association brain regions demonstrate centrality in network organization before birth. While fetal hubs may be important for facilitating network communication, they may also form potential points of vulnerability in fetal brain development

Quantitative Sodium (²³Na) MRI in Pediatric Gliomas: Initial Experience

Background: 23Na MRI correlates with tumor proliferation, and studies in pediatric patients are lacking. The purpose of the study: (1) to compare total sodium concentration (TSC) between pediatric glioma and non-neoplastic brain tissue using 23Na MRI; (2) compare tissue conspicuity of bound sodium concentration (BSC) using 23Na MRI dual echo relative to TSC imaging. Methods: TSC was measured in: (1) non-neoplastic brain tissues and (2) three types of manually segmented gliomas (diffuse intrinsic brainstem glioma (DIPG), recurrent supratentorial low-grade glioma (LGG), and high-grade glioma (HGG)). In a subset of patients, serial changes in both TSC and BSC (dual echo 23Na MRI) were assessed. Results: Twenty-six pediatric patients with gliomas (median age of 12.0 years, range 4.9–23.3 years) were scanned with 23Na MRI. DIPG treated with RT demonstrated higher TSC values than the uninvolved infratentorial tissues (p p p 23Na MRI suppressed the sodium signal within both CSF and necrotic foci. Conclusion: Quantitative 23Na MRI of pediatric gliomas demonstrates a range of values that are higher than non-neoplastic tissues. Dual echo 23Na MRI of BCS improves tissue conspicuity relative to TSC imaging

Prenatal neural origins of infant motor development:Associations between fetal brain and infant motor development

Functional circuits of the human brain emerge and change dramatically over the second half of gestation. It is possible that variation in neural functional system connectivity in utero predicts individual differences in infant behavioral development, but this possibility has yet to be examined. The current study examines the association between fetal sensorimotor brain system functional connectivity and infant postnatal motor ability. Resting-state functional connectivity data was obtained in 96 healthy human fetuses during the second and third trimesters of pregnancy. Infant motor ability was measured 7 months after birth using the Bayley Scales of Infant Development. Increased connectivity between the emerging motor network and regions of the prefrontal cortex, temporal lobes, posterior cingulate, and supplementary motor regions was observed in infants that showed more mature motor functions. In addition, females demonstrated stronger fetal-brain to infant-behavior associations. These observations extend prior longitudinal research back into prenatal brain development and raise exciting new ideas about the advent of risk and the ontogeny of early sex differences