In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences.

PURPOSE: We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements. METHODS: Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system. RESULTS: The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies. CONCLUSION: The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

Widespread, depth-dependent cortical microstructure alterations in pediatric focal epilepsy.

OBJECTIVE: Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes or treatment-related side effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilized quantitative magnetic resonance imaging (MRI), which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. METHODS: To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy (age range = 4-18 years) and 46 typically developing children (age range = 2-18 years). We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically defined abnormalities (MRI positive) and healthy controls, and tested whether this could classify patients without reported radiological abnormalities (MRI negative). RESULTS: We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 71.4% at 89.4% specificity on held-out MRI-negative patients. SIGNIFICANCE: These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically identified abnormalities.

Temporal Trends of Neonatal Surgical Conditions in Texas and Accessibility to Pediatric Surgical Care.

INTRODUCTION: Texas consistently accounts for approximately 10% of annual national births, the second highest of all US states. This temporal study aimed to evaluate incidences of neonatal surgical conditions across Texas and to delineate regional pediatric surgeon accessibility. METHODS: The Texas Birth Defects Registry was queried from 1999 to 2018, based on 11 well-established regions. Nine disorders (30,476 patients) were identified as being within the operative scope of pediatric surgeons: biliary atresia (BA), pyloric stenosis (PS), Hirschsprung's disease, stenosis/atresia of large intestine/rectum/anus, stenosis/atresia of small intestine, tracheoesophageal fistula/esophageal atresia, gastroschisis, omphalocele, and congenital diaphragmatic hernia. Annual and regional incidences were compared (/10,000 births). Statewide pediatric surgeons were identified through the American Pediatric Surgical Association directory. Regional incidences of neonatal disorder per surgeon were evaluated from 2010 to 2018 as a surrogate for provider disparity. RESULTS: PS demonstrated the highest incidence (14.405/10,000), while BA had the lowest (0.707/10,000). Overall, incidences of PS and BA decreased significantly, while incidences of Hirschsprung's disease and small intestine increased. Other diagnoses remained stable. Regions 2 (48.24/10,000) and 11 (47.79/10,000) had the highest incidence of neonatal conditions; Region 6 had the lowest (34.68/10,000). Three rural regions (#2, 4, 9) lacked pediatric surgeons from 2010 to 2018. Of regions with at least one surgeon, historically underserved regions (#10, 11) along the Texas-Mexico border consistently had the highest defect per surgeon rates. CONCLUSIONS: There are temporal and regional differences in incidences of neonatal conditions treated by pediatric surgeons across Texas. Improving access to neonatal care is a complex issue that necessitates collaborative efforts between state legislatures, health systems, and providers.

Development of neonatal brain functional centrality and alterations associated with preterm birth.

Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

Development of human white matter pathways in utero over the second and third trimester.

During the second and third trimesters of human gestation, rapid neurodevelopment is underpinned by fundamental processes including neuronal migration, cellular organization, cortical layering, and myelination. In this time, white matter growth and maturation lay the foundation for an efficient network of structural connections. Detailed knowledge about this developmental trajectory in the healthy human fetal brain is limited, in part, due to the inherent challenges of acquiring high-quality MRI data from this population. Here, we use state-of-the-art high-resolution multishell motion-corrected diffusion-weighted MRI (dMRI), collected as part of the developing Human Connectome Project (dHCP), to characterize the in utero maturation of white matter microstructure in 113 fetuses aged 22 to 37 wk gestation. We define five major white matter bundles and characterize their microstructural features using both traditional diffusion tensor and multishell multitissue models. We found unique maturational trends in thalamocortical fibers compared with association tracts and identified different maturational trends within specific sections of the corpus callosum. While linear maturational increases in fractional anisotropy were seen in the splenium of the corpus callosum, complex nonlinear trends were seen in the majority of other white matter tracts, with an initial decrease in fractional anisotropy in early gestation followed by a later increase. The latter is of particular interest as it differs markedly from the trends previously described in ex utero preterm infants, suggesting that this normative fetal data can provide significant insights into the abnormalities in connectivity which underlie the neurodevelopmental impairments associated with preterm birth.

Risk factors for pediatric intracranial neoplasms in the Kids' Inpatient Database (KID).

INTRODUCTION: In children and adolescents brain and central nervous system (CNS) tumors are the leading types of cancers. Past studies have found differing rates of intracranial cancers among races and identified additional cancer risk factors. This study aims to see if these differences can be substantiated with further investigation of the latest version (2019) of the Kids' Inpatient Database (KID). METHODS: A total of 7,818 pediatric patients <21 years old in KID with ICD-10 codes consisting of malignant neoplasms of the brain, brainstem, and cerebral meninges (C700, C709-C719) were queried. Modifiable risk factors evaluated include: hospital region, insurance type, hospital city size, the average income of patient zip code, and location/teaching status of a hospital. Non-modifiable risk factors were race and sex at birth. Dependent variables were tested in Excel and GraphPad Prism 9 using a Chi-squared test with Yates' continuity correction and Tukey's one-way and two-way ANOVAs. RESULTS: Mortality rates of females (2.88%) compared to males (1.99%) were significant (p<0.05). Mortality was (4.17%) in Black patients compared to (1.68%) for White (p<0.0001), Hispanic mortality (2.95%) compared to White (p<0.01), and mortality of Asian/Pacific Islander (3.86%) compared to White (p<0.01). Black patients had significantly higher mortality than White, Hispanic, Asian/Pacific Islander, Native American, and other races overall (p<0.01). There was no significant difference in the mortality rates between children's hospitals and large hospitals for any race. After accounting for patient race, mortality was still not significantly different for patients with Medicaid insurance compared to non-Medicaid insurance types. Of the children treated at children's hospitals, the most transferred in from outside hospitals were Native American (20.00%) followed by Asian/PI (15.09%) then Hispanic patients (13.67%). A significant difference between races was also seen regarding length of stay (p<0.001) and number of charges (p<0.001). CONCLUSION: These findings confirm prior studies suggesting gender and race are significant factors in mortality rates for children with intracranial neoplasms. However, the findings do not identify the root causes of these discrepancies but may serve as an impetus for clinicians, healthcare administrators, and governmental leaders to improve national resource allocation to better care for pediatric patients with intracranial neoplasms.

Open-source myocardial T1 mapping with simultaneous multi-slice acceleration: Combining an auto-calibrated blipped-bSSFP readout with VERSE-MB pulses.

PURPOSE: Enabling fast and accessible myocardial T1 mapping is crucial for extending its clinical application. We introduce Open-MOLLI-SMS combining simultaneous multi-slice (SMS) with auto-calibration and variable-rate selective excitation (VERSE)-multiband pulses to obtain all slices in a fast single-shot T1 mapping sequence. METHODS: Open-MOLLI-SMS was developed by integrating SMS with the open-source method Open-MOLLI previously implemented in Pulseq. Three methods were integrated for Open-MOLLI-SMS: (1) auto-calibration blip patterns to ensure consistency between the data and coil information; (2) a blipped-balanced SSFP (bSSFP) readout to induce controlled aliasing in parallel imaging shifts without disturbing the bSSFP frequency response; and (3) a VERSE-multiband pulse for minimizing the achievable TR and the specific absortion rate (SAR) impact of SMS. Two (SMS2) or three (SMS3) slices were excited simultaneously and encoded with an in-plane acceleration factor of 2. Experiments were performed in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom and five healthy volunteers. RESULTS: Phantom results show accurate T1 estimates for reference values between 400 to 2200 ms. Artifacts were visible for Open-MOLLI-SMS3 but not replicated in vivo. In vivo Open-MOLLI-SMS (T1 SMS2 = 993 ± 10 ms; T1 SMS3 = 1031 ± 17 ms) provided similar values to mean T1 single-band Open-MOLLI estimates (T1 Open-MOLLI = 1005 ± 47 ms). Open-MOLLI-SMS2 provided the closest estimates to the reference. CONCLUSION: This proof-of-principle implementation study demonstrates the feasibility of speeding up T1 -mapping acquisitions and increasing coverage by combining auto-calibration strategies with a blipped-bSFFP readout and VERSE multiband RF excitation pulses. The proposed methodology was built on the Open-MOLLI mapping sequence, which provides a fast means for prototyping and enables open-source sharing of the method.

Assessing within-subject rates of change of placental MRI diffusion metrics in normal pregnancy.

PURPOSE: Studying placental development informs when development is abnormal. Most placental MRI studies are cross-sectional and do not study the extent of individual variability throughout pregnancy. We aimed to explore how diffusion MRI measures of placental function and microstructure vary in individual healthy pregnancies throughout gestation. METHODS: Seventy-nine pregnant, low-risk participants (17 scanned twice and 62 scanned once) were included. T2 -weighted anatomical imaging and a combined multi-echo spin-echo diffusion-weighted sequence were acquired at 3 T. Combined diffusion-relaxometry models were performed using both a T 2 * $$ {\mathrm{T}}_2^{\ast } $$ -ADC and a bicompartmental T 2 * $$ {\mathrm{T}}_2^{\ast } $$ -intravoxel-incoherent-motion ( T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ ) model fit. RESULTS: There was a significant decline in placental T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC (both P < 0.01) over gestation. These declines are consistent in individuals for T 2 * $$ {\mathrm{T}}_2^{\ast } $$ (covariance = -0.47), but not ADC (covariance = -1.04). The T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model identified a consistent decline in individuals over gestation in T 2 * $$ {\mathrm{T}}_2^{\ast } $$ from both the perfusing and diffusing placental compartments, but not in ADC values from either. The placental perfusing compartment fraction increased over gestation (P = 0.0017), but this increase was not consistent in individuals (covariance = 2.57). CONCLUSION: Whole placental T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC values decrease over gestation, although only T 2 * $$ {\mathrm{T}}_2^{\ast } $$ values showed consistent trends within subjects. There was minimal individual variation in rates of change of T 2 * $$ {\mathrm{T}}_2^{\ast } $$ values from perfusing and diffusing placental compartments, whereas trends in ADC values from these compartments were less consistent. These findings probably relate to the increased complexity of the bicompartmental T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model, and differences in how different placental regions evolve at a microstructural level. These placental MRI metrics from low-risk pregnancies provide a useful benchmark for clinical cohorts.

In vivo T1 mapping of neonatal brain tissue at 64 mT.

PURPOSE: Ultralow-field (ULF) point-of-care MRI systems allow image acquisition without interrupting medical provision, with neonatal clinical care being an important potential application. The ability to measure neonatal brain tissue T1 is a key enabling technology for subsequent structural image contrast optimization, as well as being a potential biomarker for brain development. Here we describe an optimized strategy for neonatal T1 mapping at ULF. METHODS: Examinations were performed on a 64-mT portable MRI system. A phantom validation experiment was performed, and a total of 33 in vivo exams were acquired from 28 neonates with postmenstrual age ranging from 31+4 to 49+0  weeks. Multiple inversion-recovery turbo spin-echo sequences were acquired with differing inversion and repetition times. An analysis pipeline incorporating inter-sequence motion correction generated proton density and T1 maps. Regions of interest were placed in the cerebral deep gray matter, frontal white matter, and cerebellum. Weighted linear regression was used to predict T1 as a function of postmenstrual age. RESULTS: Reduction of T1 with postmenstrual age is observed in all measured brain tissue; the change in T1 per week and 95% confidence intervals is given by dT1  = -21 ms/week [-25, -16] (cerebellum), dT1  = -14 ms/week [-18, -10] (deep gray matter), and dT1  = -35 ms/week [-45, -25] (white matter). CONCLUSION: Neonatal T1 values at ULF are shorter than those previously described at standard clinical field strengths, but longer than those of adults at ULF. T1 reduces with postmenstrual age and is therefore a candidate biomarker for perinatal brain development.

Total and Regional Brain Volumes in Fetuses With Congenital Heart Disease.

BACKGROUND: Congenital heart disease (CHD) is common and is associated with impaired early brain development and neurodevelopmental outcomes, yet the exact mechanisms underlying these associations are unclear. PURPOSE: To utilize MRI data from a cohort of fetuses with CHD as well as typically developing fetuses to test the hypothesis that expected cerebral substrate delivery is associated with total and regional fetal brain volumes. STUDY TYPE: Retrospective case-control study. POPULATION: Three hundred eighty fetuses (188 male), comprising 45 healthy controls and 335 with isolated CHD, scanned between 29 and 37 weeks gestation. Fetuses with CHD were assigned into one of four groups based on expected cerebral substrate delivery. FIELD STRENGTH/SEQUENCE: T2-weighted single-shot fast-spin-echo sequences and a balanced steady-state free precession gradient echo sequence were obtained on a 1.5 T scanner. ASSESSMENT: Images were motion-corrected and reconstructed using an automated slice-to-volume registration reconstruction technique, before undergoing segmentation using an automated pipeline and convolutional neural network that had undergone semi-supervised training. Differences in total, regional brain (cortical gray matter, white matter, deep gray matter, cerebellum, and brainstem) and brain:body volumes were compared between groups. STATISTICAL TESTS: ANOVA was used to test for differences in brain volumes between groups, after accounting for sex and gestational age at scan. PFDR -values <0.05 were considered statistically significant. RESULTS: Total and regional brain volumes were smaller in fetuses where cerebral substrate delivery is reduced. No significant differences were observed in total or regional brain volumes between control fetuses and fetuses with CHD but normal cerebral substrate delivery (all PFDR > 0.12). Severely reduced cerebral substrate delivery is associated with lower brain:body volume ratios. DATA CONCLUSION: Total and regional brain volumes are smaller in fetuses with CHD where there is a reduction in cerebral substrate delivery, but not in those where cerebral substrate delivery is expected to be normal. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain.

Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder.

Predicting General Surgery Match Outcomes Using Standardized Ranking Metrics.

INTRODUCTION: Objective measurements for applicant ranking are becoming increasingly important, not only to help address the growing number of general surgery applicants each year but also to minimize bias and ensure consistency. We assessed if our general surgery applicant scoring system was an effective tool for accurately predicting the results of the resident match. METHODS: A retrospective review of applicant rank lists from 2017 to 2020 was conducted. Applicants were ranked based on the sum of preinterview and interview scores. The preinterview score is an objective metric related to the applicant's academic portfolio. The interview score is a standardized score based on interview performance. We reviewed match results from ranked candidates and categorized them as academic categorical (AC), community categorical (CC), preliminary surgical (PS), nonsurgical specialty (NS), or unmatched (UM) positions. RESULTS: A total of 378 applicants were interviewed. Forty-nine percent matched into AC, 22% into CC, 11% into PS, and 5% into NS positions, while 13% of the interviewees were UM. Applicants who matched into AC positions had significantly higher preinterview and interview scores than applicants in other categories. Applicants who matched into CC positions had significantly higher interview scores than those categorized as UM, but their preinterview scores did not differ significantly from the UM group. Applicants who did not match into a categorical position (PS, NS, or UM) did not have significantly different preinterview or interview scores from one another. CONCLUSIONS: Our standardized scoring system was effective in stratifying which applicants would match into categorical general surgery residency programs.

Normative ranges of biventricular volumes and function in healthy term newborns.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly used in newborns with congenital heart disease. However, reporting on ventricular volumes and mass is hindered by an absence of normative data in this population. DESIGN/METHODS: Healthy term (37-41 weeks gestation) newborns underwent non-sedated, free-breathing CMR within the first week of life using the 'feed and wrap' technique. End-diastolic volume (EDV), end-systolic volume (ESV) stroke volume (SV) and ejection fraction (EF) were calculated for both left ventricle (LV) and right ventricle (RV). Papillary muscles were separately contoured and included in the myocardial volume. Myocardial mass was calculated by multiplying myocardial volume by 1.05 g/ml. All data were indexed to weight and body surface area (BSA). Inter-observer variability (IOV) was performed on data from 10 randomly chosen infants. RESULTS: Twenty healthy newborns (65% male) with a mean (SD) birth weight of 3.54 (0.46) kg and BSA of 0.23 (0.02) m2 were included. Normative LV parameters were indexed EDV 39.0 (4.1) ml/m2, ESV 14.5 (2.5) ml/m2 and ejection fraction (EF) 63.2 (3.4)%. Normative RV indexed EDV, ESV and EF were 47.4 (4.5) ml/m2, 22.6 (2.9) ml/m2 and 52.5 (3.3)% respectively. Mean LV and RV indexed mass were 26.4 (2.8) g/m2 and 12.5 (2.0) g/m2, respectively. There was no difference in ventricular volumes by gender. IOV was excellent with an intra-class coefficient > 0.95 except for RV mass (0.94). CONCLUSION: This study provides normative data on LV and RV parameters in healthy newborns, providing a novel resource for comparison with newborns with structural and functional heart disease.

Predicting age and clinical risk from the neonatal connectome.

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p < 0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p < 0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to predominantly involve frontal and temporal regions, thalami, and basal ganglia. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome and suggest that a neural substrate of brain maturation with implications for future neurodevelopment is detectable at term equivalent age from the neonatal connectome.

Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies.

Infants born in early term (37-38 weeks gestation) experience slower neurodevelopment than those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain. Here we characterise brain volume and white matter correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome using T2 and diffusion weighted MRI acquired in the neonatal period from a cohort (n = 454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor-based morphometry and tract-based spatial statistics. Neurodevelopment was assessed at age 18 months using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III). Infants born earlier had higher relative ventricular volume and lower relative brain volume in the deep grey matter, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial, and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Regression models predicting outcome from gestational age at birth were significantly improved after adding neuroimaging features associated with gestational age at birth. This work adds to the body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.

Data-driven motion-corrected brain MRI incorporating pose-dependent B0 fields.

PURPOSE: To develop a fully data-driven retrospective intrascan motion-correction framework for volumetric brain MRI at ultrahigh field (7 Tesla) that includes modeling of pose-dependent changes in polarizing magnetic (B0 ) fields. THEORY AND METHODS: Tissue susceptibility induces spatially varying B0 distributions in the head, which change with pose. A physics-inspired B0 model has been deployed to model the B0 variations in the head and was validated in vivo. This model is integrated into a forward parallel imaging model for imaging in the presence of motion. Our proposal minimizes the number of added parameters, enabling the developed framework to estimate dynamic B0 variations from appropriately acquired data without requiring navigators. The effect on data-driven motion correction is validated in simulations and in vivo. RESULTS: The applicability of the physics-inspired B0 model was confirmed in vivo. Simulations show the need to include the pose-dependent B0 fields in the reconstruction to improve motion-correction performance and the feasibility of estimating B0 evolution from the acquired data. The proposed motion and B0 correction showed improved image quality for strongly corrupted data at 7 Tesla in simulations and in vivo. CONCLUSION: We have developed a motion-correction framework that accounts for and estimates pose-dependent B0 fields. The method improves current state-of-the-art data-driven motion-correction techniques when B0 dependencies cannot be neglected. The use of a compact physics-inspired B0 model together with leveraging the parallel imaging encoding redundancy and previously proposed optimized sampling patterns enables a purely data-driven approach.

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity.

The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5-44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37-43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts.

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

Simultaneous quantification of GABA, Glx and GSH in the neonatal human brain using magnetic resonance spectroscopy.

Balance between inhibitory and excitatory neurotransmitter systems and the protective role of the major antioxidant glutathione (GSH) are central to early healthy brain development. Disruption has been implicated in the early life pathophysiology of psychiatric disorders and neurodevelopmental conditions including Autism Spectrum Disorder. Edited magnetic resonance spectroscopy (MRS) methods such as HERMES have great potential for providing important new non-invasive insights into these crucial processes in human infancy. In this work, we describe a systematic approach to minimise the impact of specific technical challenges inherent to acquiring MRS data in a neonatal population, including automatic segmentation, full tissue-correction and optimised GABA+ fitting and consider the minimum requirements for a robust edited-MRS acquisition. With this approach we report for the first time simultaneous GABA+, Glx (glutamate + glutamine) and GSH concentrations in the neonatal brain (n = 18) in two distinct regions (thalamus and anterior cingulate cortex (ACC)) using edited MRS at 3T. The improved sensitivity provided by our method allows specific regional neurochemical differences to be identified including: significantly lower Glx and GSH ratios to total creatine in the thalamus compared to the ACC (p < 0.001 for both), and significantly higher GSH levels in the ACC following tissue-correction (p < 0.01). Furthermore, in contrast to adult GABA+ which can typically be accurately fitted with a single peak, all neonate spectra displayed a characteristic doublet GABA+ peak at 3 ppm, indicating a lower macromolecule (MM) contribution to the 3 ppm signal in neonates. Relatively high group-level variance shows the need to maximise voxel size/acquisition time in edited neonatal MRS acquisitions for robust estimation of metabolites. Application of this method to study how these levels and balance are altered by early-life brain injury or genetic risk can provide important new knowledge about the pathophysiology underlying neurodevelopmental disorders.

Scattered slice SHARD reconstruction for motion correction in multi-shell diffusion MRI.

Diffusion MRI offers a unique probe into neural microstructure and connectivity in the developing brain. However, analysis of neonatal brain imaging data is complicated by inevitable subject motion, leading to a series of scattered slices that need to be aligned within and across diffusion-weighted contrasts. Here, we develop a reconstruction method for scattered slice multi-shell high angular resolution diffusion imaging (HARDI) data, jointly estimating an uncorrupted data representation and motion parameters at the slice or multiband excitation level. The reconstruction relies on data-driven representation of multi-shell HARDI data using a bespoke spherical harmonics and radial decomposition (SHARD), which avoids imposing model assumptions, thus facilitating to compare various microstructure imaging methods in the reconstructed output. Furthermore, the proposed framework integrates slice-level outlier rejection, distortion correction, and slice profile correction. We evaluate the method in the neonatal cohort of the developing Human Connectome Project (650 scans). Validation experiments demonstrate accurate slice-level motion correction across the age range and across the range of motion in the population. Results in the neonatal data show successful reconstruction even in severely motion-corrupted subjects. In addition, we illustrate how local tissue modelling can extract advanced microstructure features such as orientation distribution functions from the motion-corrected reconstructions.