Development of the data registry for the Cardiac Neurodevelopmental Outcome Collaborative.

Children with congenital heart disease (CHD) can face neurodevelopmental, psychological, and behavioural difficulties beginning in infancy and continuing through adulthood. Despite overall improvements in medical care and a growing focus on neurodevelopmental screening and evaluation in recent years, neurodevelopmental disabilities, delays, and deficits remain a concern. The Cardiac Neurodevelopmental Outcome Collaborative was founded in 2016 with the goal of improving neurodevelopmental outcomes for individuals with CHD and pediatric heart disease. This paper describes the establishment of a centralised clinical data registry to standardize data collection across member institutions of the Cardiac Neurodevelopmental Outcome Collaborative. The goal of this registry is to foster collaboration for large, multi-centre research and quality improvement initiatives that will benefit individuals and families with CHD and improve their quality of life. We describe the components of the registry, initial research projects proposed using data from the registry, and lessons learned in the development of the registry.

Fetal Brain Volume Predicts Neurodevelopment in Congenital Heart Disease.

BACKGROUND: Neurodevelopmental impairment is common in children with congenital heart disease (CHD), but postnatal variables explain only 30% of the variance in outcomes. To explore whether the antecedents for neurodevelopmental disabilities might begin in utero, we analyzed whether fetal brain volume predicted subsequent neurodevelopmental outcome in children with CHD. METHODS: Fetuses with isolated CHD and sociodemographically comparable healthy control fetuses underwent fetal brain magnetic resonance imaging and 2-year neurodevelopmental evaluation with the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III) and the Adaptive Behavior Assessment System, Third Edition (ABAS-3). Hierarchical regression evaluated potential predictors of Bayley-III and ABAS-3 outcomes in the CHD group, including fetal total brain volume adjusted for gestational age and sex, sociodemographic characteristics, birth measures, and medical history. RESULTS: The CHD group (n=52) had lower Bayley-III cognitive, language, and motor scores than the control group (n=26), but fetal brain volumes were similar. Within the CHD group, larger fetal total brain volume correlated with higher Bayley-III cognitive, language, and motor scores and ABAS-3 adaptive functioning scores (r=0.32-0.47; all P<0.05), but this was not noted in the control group. Fetal brain volume predicted 10% to 21% of the variance in neurodevelopmental outcome measures in univariate analyses. Multivariable models that also included social class and postnatal factors explained 18% to 45% of the variance in outcome, depending on developmental domain. Moreover, in final multivariable models, fetal brain volume was the most consistent predictor of neurodevelopmental outcome across domains. CONCLUSIONS: Small fetal brain volume is a strong independent predictor of 2-year neurodevelopmental outcomes and may be an important imaging biomarker of future neurodevelopmental risk in CHD. Future studies are needed to support this hypothesis. Our findings support inclusion of fetal brain volume in risk stratification models and as a possible outcome in fetal neuroprotective intervention studies.

Placental delayed villous maturation is associated with fetal congenital heart disease.

BACKGROUND: The placenta is crucial for the overall development and lifelong health of the fetus. Abnormal placental development and function occur in pregnancies with fetal congenital heart disease. However, studies that use standardized diagnostic criteria and incorporate control populations are lacking. This limits the generalizability of current research and the ability to determine the specific placental abnormalities associated with congenital heart disease. OBJECTIVE: This study applied consensus statement guidelines (known as the Amsterdam criteria) for placental pathology interpretation to compare the frequency and pattern of abnormalities in pregnancies with fetal congenital heart disease to demographically matched control pregnancies and evaluate for differences in placental abnormalities by cardiac physiology. STUDY DESIGN: A single-center retrospective cohort study was conducted from January 2013 to June 2019. Infants with a prenatal diagnosis of moderate-severe congenital heart disease who were born at ≥37 weeks of gestation were included. A control group born at ≥37 weeks of gestation but without fetal congenital heart disease or other major pregnancy complications was matched to the congenital heart disease group on maternal race and ethnicity and infant sex. Using the Amsterdam criteria, placental pathology findings were categorized as delayed villous maturation, maternal vascular malperfusion, fetal vascular malperfusion, and inflammatory lesions. The frequency of placental abnormalities was compared between groups, and logistic regression was performed to evaluate the association of clinical and sociodemographic factors with delayed villous maturation, maternal vascular malperfusion, and fetal vascular malperfusion. RESULTS: There were 194 pregnancies with fetal congenital heart disease and 105 controls included, of whom 83% in the congenital heart disease group and 82% in the control group were of non-Hispanic White race and ethnicity. Compared with controls, pregnancies with fetal congenital heart disease had higher rates of delayed villous maturation (6% vs 19%; P<.001) and maternal vascular malperfusion (19% vs 34%; P=.007) but not fetal vascular malperfusion (6% vs 10%; P=.23). Infants with congenital heart disease with 2-ventricle anatomy displayed the highest odds of delayed villous maturation compared with controls (odds ratio, 5.5; 95% confidence interval, 2.2-15.7; P<.01). Maternal vascular malperfusion was 2.2 times higher (P=.02) for infants with 2-ventricle anatomy and 2.9 times higher (P=.02) for infants with single-ventricle physiology with pulmonic obstruction. Within the congenital heart disease group, delayed villous maturation was associated with higher maternal body mass index, polyhydramnios, larger infant birth head circumference, and infant respiratory support in the delivery room, whereas maternal vascular malperfusion was associated with oligohydramnios. In multivariable models adjusting for cardiac diagnosis, associations of delayed villous maturation persisted for infant birth head circumference (odds ratio, 1.2; 95% confidence interval, 1.0-1.5; P=.02) and infant respiratory support in the delivery room (odds ratio, 3.0; 95% confidence interval, 1.3-6.5; P=.007). CONCLUSION: Pregnancies with fetal congenital heart disease displayed higher rates of delayed villous maturation and maternal vascular malperfusion than controls, suggesting that placental maldevelopment may relate to maternal factors. Future investigations are needed to determine the association of these abnormalities with postnatal infant outcomes.

Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference.

Human fetal brains show regionally different temporal patterns of sulcal emergence following a regular timeline, which may be associated with spatiotemporal patterns of gene expression among cortical regions. This study aims to quantify the timing of sulcal emergence and its temporal variability across typically developing fetuses by fitting a logistic curve to presence or absence of sulcus. We found that the sulcal emergence started from the central to the temporo-parieto-occipital lobes and frontal lobe, and the temporal variability of emergence in most of the sulci was similar between 1 and 2 weeks. Small variability (< 1 week) was found in the left central and postcentral sulci and larger variability (>2 weeks) was shown in the bilateral occipitotemporal and left superior temporal sulci. The temporal variability showed a positive correlation with the emergence timing that may be associated with differential contributions between genetic and environmental factors. Our statistical analysis revealed that the right superior temporal sulcus emerged earlier than the left. Female fetuses showed a trend of earlier sulcal emergence in the right superior temporal sulcus, lower temporal variability in the right intraparietal sulcus, and higher variability in the right precentral sulcus compared to male fetuses. Our quantitative and statistical approach quantified the temporal patterns of sulcal emergence in detail that can be a reference for assessing the normality of developing fetal gyrification.

Regional Brain Growth Trajectories in Fetuses with Congenital Heart Disease.

OBJECTIVE: Congenital heart disease (CHD) is associated with abnormal brain development in utero. We applied innovative fetal magnetic resonance imaging (MRI) techniques to determine whether reduced fetal cerebral substrate delivery impacts the brain globally, or in a region-specific pattern. Our novel design included two control groups, one with and the other without a family history of CHD, to explore the contribution of shared genes and/or fetal environment to brain development. METHODS: From 2014 to 2018, we enrolled 179 pregnant women into 4 groups: "HLHS/TGA" fetuses with hypoplastic left heart syndrome (HLHS) or transposition of the great arteries (TGA), diagnoses with lowest fetal cerebral substrate delivery; "CHD-other," with other CHD diagnoses; "CHD-related," healthy with a CHD family history; and "optimal control," healthy without a family history. Two MRIs were obtained between 18 and 40 weeks gestation. Random effect regression models assessed group differences in brain volumes and relationships to hemodynamic variables. RESULTS: HLHS/TGA (n = 24), CHD-other (50), and CHD-related (34) groups each had generally smaller brain volumes than the optimal controls (71). Compared with CHD-related, the HLHS/TGA group had smaller subplate (-13.3% [standard error = 4.3%], p < 0.01) and intermediate (-13.7% [4.3%], p < 0.01) zones, with a similar trend in ventricular zone (-7.1% [1.9%], p = 0.07). These volumetric reductions were associated with lower cerebral substrate delivery. INTERPRETATION: Fetuses with CHD, especially those with lowest cerebral substrate delivery, show a region-specific pattern of small brain volumes and impaired brain growth before 32 weeks gestation. The brains of fetuses with CHD were more similar to those of CHD-related than optimal controls, suggesting genetic or environmental factors also contribute. ANN NEUROL 2021;89:143-157.

Temporal Patterns of Emergence and Spatial Distribution of Sulcal Pits During Fetal Life.

Sulcal pits are thought to represent the first cortical folds of primary sulci during neurodevelopment. The uniform spatial distribution of sulcal pits across individuals is hypothesized to be predetermined by a human-specific protomap which is related to functional localization under genetic controls in early fetal life. Thus, it is important to characterize temporal and spatial patterns of sulcal pits in the fetal brain that would provide additional information of functional development of the human brain and crucial insights into abnormal cortical maturation. In this paper, we investigated temporal patterns of emergence and spatial distribution of sulcal pits using 48 typically developing fetal brains in the second half of gestation. We found that the position and spatial variance of sulcal pits in the fetal brain are similar to those in the adult brain, and they are also temporally uniform against dynamic brain growth during fetal life. Furthermore, timing of pit emergence shows a regionally diverse pattern that may be associated with the subdivisions of the protomap. Our findings suggest that sulcal pits in the fetal brain are useful anatomical landmarks containing detailed information of functional localization in early cortical development and maintaining their spatial distribution throughout the human lifetime.

Dynamic patterns of cortical expansion during folding of the preterm human brain.

During the third trimester of human brain development, the cerebral cortex undergoes dramatic surface expansion and folding. Physical models suggest that relatively rapid growth of the cortical gray matter helps drive this folding, and structural data suggest that growth may vary in both space (by region on the cortical surface) and time. In this study, we propose a unique method to estimate local growth from sequential cortical reconstructions. Using anatomically constrained multimodal surface matching (aMSM), we obtain accurate, physically guided point correspondence between younger and older cortical reconstructions of the same individual. From each pair of surfaces, we calculate continuous, smooth maps of cortical expansion with unprecedented precision. By considering 30 preterm infants scanned two to four times during the period of rapid cortical expansion (28-38 wk postmenstrual age), we observe significant regional differences in growth across the cortical surface that are consistent with the emergence of new folds. Furthermore, these growth patterns shift over the course of development, with noninjured subjects following a highly consistent trajectory. This information provides a detailed picture of dynamic changes in cortical growth, connecting what is known about patterns of development at the microscopic (cellular) and macroscopic (folding) scales. Since our method provides specific growth maps for individual brains, we are also able to detect alterations due to injury. This fully automated surface analysis, based on tools freely available to the brain-mapping community, may also serve as a useful approach for future studies of abnormal growth due to genetic disorders, injury, or other environmental variables.

In vivo characterization of emerging white matter microstructure in the fetal brain in the third trimester.

The third trimester of pregnancy is a period of rapid development of fiber bundles in the fetal white matter. Using a recently developed motion-tracked slice-to-volume registration (MT-SVR) method, we aimed to quantify tract-specific developmental changes in apparent diffusion coefficient (ADC), fractional anisotropy (FA), and volume in third trimester healthy fetuses. To this end, we reconstructed diffusion tensor images from motion corrected fetal diffusion magnetic resonance imaging data. With an approved protocol, fetal MRI exams were performed on healthy pregnant women at 3 Tesla and included multiple (2-8) diffusion scans of the fetal head (1-2 b = 0 s/mm2 images and 12 diffusion-sensitized images at b = 500 s/mm2 ). Diffusion data from 32 fetuses (13 females) with median gestational age (GA) of 33 weeks 4 days were processed with MT-SVR and deterministic tractography seeded by regions of interest corresponding to 12 major fiber tracts. Multivariable regression analysis was used to evaluate the association of GA with volume, FA, and ADC for each tract. For all tracts, the volume and FA increased, and the ADC decreased with GA. Associations reached statistical significance for: FA and ADC of the forceps major; volume and ADC for the forceps minor; FA, ADC, and volume for the cingulum; ADC, FA, and volume for the uncinate fasciculi; ADC of the inferior fronto-occipital fasciculi, ADC of the inferior longitudinal fasciculi; and FA and ADC for the corticospinal tracts. These quantitative results demonstrate the complex pattern and rates of tract-specific, GA-related microstructural changes of the developing white matter in human fetal brain.

Early-Emerging Sulcal Patterns Are Atypical in Fetuses with Congenital Heart Disease.

Fetuses with congenital heart disease (CHD) have third trimester alterations in cortical development on brain magnetic resonance imaging (MRI). However, the intersulcal relationships contributing to global sulcal pattern remain unknown. This study applied a novel method for examining the geometric and topological relationships between sulci to fetal brain MRIs from 21-30 gestational weeks in CHD fetuses (n = 19) and typically developing (TD) fetuses (n = 17). Sulcal pattern similarity index (SI) to template fetal brain MRIs was determined for the position, area, and depth for corresponding sulcal basins and intersulcal relationships for each subject. CHD fetuses demonstrated altered global sulcal patterns in the left hemisphere compared with TD fetuses (TD [SI, mean ± SD]: 0.822 ± 0.023, CHD: 0.795 ± 0.030, P = 0.002). These differences were present in the earliest emerging sulci and were driven by differences in the position of corresponding sulcal basins (TD: 0.897 ± 0.024, CHD: 0.878 ± 0.019, P = 0.006) and intersulcal relationships (TD: 0.876 ± 0.031, CHD: 0.857 ± 0.018, P = 0.033). No differences in cortical gyrification index, mean curvature, or surface area were present. These data suggest our methods may be more sensitive than traditional measures for evaluating cortical developmental alterations early in gestation.

Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images.

Altered structural fetal brain development has been linked to neuro-developmental disorders. These structural alterations can be potentially detected in utero using diffusion tensor imaging (DTI). However, acquisition and reconstruction of in utero fetal brain DTI remains challenging. Until now, motion-robust DTI methods have been employed for reconstruction of in utero fetal DTIs. However, due to the unconstrained fetal motion and permissible in utero acquisition times, these methods yielded limited success and have typically resulted in noisy DTIs. Consequently, atlases and methods that could enable groupwise studies, multi-modality imaging, and computer-aided diagnosis from in utero DTIs have not yet been developed. This paper presents the first DTI atlas of the fetal brain computed from in utero diffusion-weighted images. For this purpose an algorithm for computing an unbiased spatiotemporal DTI atlas, which integrates kernel-regression in age with a diffeomorphic tensor-to-tensor registration of motion-corrected and reconstructed individual fetal brain DTIs, was developed. Our new algorithm was applied to a set of 67 fetal DTI scans acquired from healthy fetuses each scanned at a gestational age between 21 and 39 weeks. The neurodevelopmental trends in the fetal brain, characterized by the atlas, were qualitatively and quantitatively compared with the observations reported in prior ex vivo and in utero studies, and with results from imaging gestational-age equivalent preterm infants. Our major findings revealed early presence of limbic fiber bundles, followed by the appearance and maturation of projection pathways (characterized by an age related increase in FA) during late 2nd and early 3rd trimesters. During the 3rd trimester association fiber bundles become evident. In parallel with the appearance and maturation of fiber bundles, from 21 to 39 gestational weeks gradual disappearance of the radial coherence of the telencephalic wall was qualitatively identified. These results and analyses show that our DTI atlas of the fetal brain is useful for reliable detection of major neuronal fiber bundle pathways and for characterization of the fetal brain reorganization that occurs in utero. The atlas can also serve as a useful resource for detection of normal and abnormal fetal brain development in utero.

Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification.

Accurate parcellation and labeling of primary cortical sulci in the human fetal brain is useful for regional analysis of brain development. However, human fetal brains show large spatio-temporal changes in brain size, cortical folding patterns, and relative position/size of cortical regions, making accurate automatic sulcal labeling challenging. Here, we introduce a novel sulcal labeling method for the fetal brain using spatio-temporal gyrification information from multiple fetal templates. First, spatial probability maps of primary sulci are generated on the templates from 23 to 33 gestational weeks and registered to an individual brain. Second, temporal weights, which determine the level of contribution to the labeling for each template, are defined by similarity of gyrification between the individual and the template brains. We combine the weighted sulcal probability maps from the multiple templates and adopt sulcal basin-wise approach to assign sulcal labels to each basin. Our labeling method was applied to 25 fetuses (22.9-29.6 gestational weeks), and the labeling accuracy was compared to manually assigned sulcal labels using the Dice coefficient. Moreover, our multi-template basin-wise approach was compared to a single-template approach, which does not consider the temporal dynamics of gyrification, and a fully-vertex-wise approach. The mean accuracy of our approach was 0.958 across subjects, significantly higher than the accuracies of the other approaches. This novel approach shows highly accurate sulcal labeling and provides a reliable means to examine characteristics of cortical regions in the fetal brain.

Intraventricular Hemorrhage in Moderate to Severe Congenital Heart Disease.

OBJECTIVES: Determine the prevalence of intraventricular hemorrhage in infants with moderate to severe congenital heart disease, investigate the impact of gestational age, cardiac diagnosis, and cardiac intervention on intraventricular hemorrhage, and compare intraventricular hemorrhage rates in preterm infants with and without congenital heart disease. DESIGN: A single-center retrospective review. SETTING: A tertiary care children's hospital. PATIENTS: All infants admitted to St. Louis Children's Hospital from 2007 to 2012 with moderate to severe congenital heart disease requiring cardiac intervention in the first 90 days of life and all preterm infants without congenital heart disease or congenital anomalies/known genetic diagnoses admitted during the same time period. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Cranial ultrasound data were reviewed for presence/severity of intraventricular hemorrhage. Head CT and brain MRI data were also reviewed in the congenital heart disease infants. Univariate analyses were undertaken to determine associations with intraventricular hemorrhage, and a final multivariate logistic regression model was performed. There were 339 infants with congenital heart disease who met inclusion criteria and 25.4% were born preterm. Intraventricular hemorrhage was identified on cranial ultrasound in 13.3% of infants, with the majority of intraventricular hemorrhage being low-grade (grade I/II). The incidence increased as gestational age decreased such that intraventricular hemorrhage was present in 8.7% of term infants, 19.2% of late preterm infants, 26.3% of moderately preterm infants, and 53.3% of very preterm infants. There was no difference in intraventricular hemorrhage rates between cardiac diagnoses. Additionally, the rate of intraventricular hemorrhage did not increase after cardiac intervention, with only three infants demonstrating new/worsening high-grade (grade III/IV) intraventricular hemorrhage after surgery. In a multivariate model, only gestational age at birth and African-American race were predictors of intraventricular hemorrhage. In the subset of infants with CT/MRI data, there was good sensitivity and specificity of cranial ultrasound for presence of intraventricular hemorrhage. CONCLUSIONS: Infants with congenital heart disease commonly develop intraventricular hemorrhage, particularly when born preterm. However, the vast majority of intraventricular hemorrhage is low-grade and is associated with gestational age and African-American race.

Diffusion tractography and neuromotor outcome in very preterm children with white matter abnormalities.

BACKGROUND: Moderate-to-severe white matter abnormality (WMA) in the newborn has been shown to produce persistent disruptions in cerebral connectivity but does not universally result in neurodevelopmental disability in very preterm (VPT) children. The aims of this hypothesis-driven study were to apply diffusion imaging to: (i) examine whether bilateral WMA detected in VPT children in the newborn period can predict microstructural organization at the age of 7 y and (ii) compare corticospinal tract and corpus callosum (CC) measures in VPT children at the age of 7 y with neonatal WMA with normal vs. impaired motor functioning. METHODS: Diffusion parameters of the corticospinal tract and CC were compared between VPT 7-y olds with (n = 20) and without (n = 42) bilateral WMA detected in the newborn period. For those with WMA, diffusion parameters were further examined. RESULTS: Microstructural organization of corticospinal tract and CC tracts at the age of 7 y were altered in VPT children with moderate-to-severe WMA detected at term equivalent age as compared with those without injury. Furthermore, diffusion parameters differed in the CC for children with WMA categorized by motor outcome (n = 8). CONCLUSION: WMA on conventional magnetic resonance imaging at term equivalent age is associated with altered microstructural organization of the corticospinal tract and CC at 7 y of age.

Factors Associated With Attendance for Cardiac Neurodevelopmental Evaluation.

BACKGROUND AND OBJECTIVES: Neurodevelopmental evaluation of toddlers with complex congenital heart disease is recommended but reported frequency is low. Data on barriers to attending neurodevelopmental follow-up are limited. This study aims to estimate the attendance rate for a toddler neurodevelopmental evaluation in a contemporary multicenter cohort and to assess patient and center level factors associated with attending this evaluation. METHODS: This is a retrospective cohort study of children born between September 2017 and September 2018 who underwent cardiopulmonary bypass in their first year of life at a center contributing data to the Cardiac Neurodevelopmental Outcome Collaborative and Pediatric Cardiac Critical Care Consortium clinical registries. The primary outcome was attendance for a neurodevelopmental evaluation between 11 and 30 months of age. Sociodemographic and medical characteristics and center factors specific to neurodevelopmental program design were considered as predictors for attendance. RESULTS: Among 2385 patients eligible from 16 cardiac centers, the attendance rate was 29.0% (692 of 2385), with a range of 7.8% to 54.3% across individual centers. In multivariable logistic regression models, hospital-initiated (versus family-initiated) scheduling for neurodevelopmental evaluation had the largest odds ratio in predicting attendance (odds ratio = 4.24, 95% confidence interval, 2.74-6.55). Other predictors of attendance included antenatal diagnosis, absence of Trisomy 21, higher Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery mortality category, longer postoperative length of stay, private insurance, and residing a shorter distance from the hospital. CONCLUSIONS: Attendance rates reflect some improvement but remain low. Changes to program infrastructure and design and minimizing barriers affecting access to care are essential components for improving neurodevelopmental care and outcomes for children with congenital heart disease.

Optimizing Neurodevelopmental Outcomes in Neonates With Congenital Heart Disease.

Neurodevelopmental impairment is a common and important long-term morbidity among infants with congenital heart disease (CHD). More than half of those with complex CHD will demonstrate some form of neurodevelopmental, neurocognitive, and/or psychosocial dysfunction requiring specialized care and impacting long-term quality of life. Preventing brain injury and treating long-term neurologic sequelae in this high-risk clinical population is imperative for improving neurodevelopmental and psychosocial outcomes. Thus, cardiac neurodevelopmental care is now at the forefront of clinical and research efforts. Initial research primarily focused on neurocritical care and operative strategies to mitigate brain injury. As the field has evolved, investigations have shifted to understanding the prenatal, genetic, and environmental contributions to impaired neurodevelopment. This article summarizes the recent literature detailing the brain abnormalities affecting neurodevelopment in children with CHD, the impact of genetics on neurodevelopmental outcomes, and the best practices for neonatal neurocritical care, focusing on developmental care and parental support as new areas of importance. A framework is also provided for the infrastructure and resources needed to support CHD families across the continuum of care settings.

Partnering With Stakeholders to Inform the Co-Design of a Psychosocial Intervention for Prenatally Diagnosed Congenital Heart Disease.

Input from diverse stakeholders is critical to the process of designing healthcare interventions. This study applied a novel mixed-methods, stakeholder-engaged approach to co-design a psychosocial intervention for mothers expecting a baby with congenital heart disease (CHD) and their partners to promote family wellbeing. The research team included parents and clinicians from 8 health systems. Participants were 41 diverse parents of children with prenatally diagnosed CHD across the 8 health systems. Qualitative data were collected through online crowdsourcing and quantitative data were collected through electronic surveys to inform intervention co-design. Phases of intervention co-design were: (I) Engage stakeholders in selection of intervention goals/outcomes; (II) Engage stakeholders in selection of intervention elements; (III) Obtain stakeholder input to increase intervention uptake/utility; (IV) Obtain stakeholder input on aspects of intervention design; and (V) Obtain stakeholder input on selection of outcome measures. Parent participants anticipated the resulting intervention, HEARTPrep, would be acceptable, useful, and feasible for parents expecting a baby with CHD. This model of intervention co-design could be used for the development of healthcare interventions across chronic diseases.

Practical approaches to sedation and analgesia in the newborn.

The prevention, assessment, and treatment of neonatal pain and agitation continues to challenge clinicians and researchers. Substantial progress has been made in the past three decades, but numerous outstanding questions remain. In this setting, clinicians must establish safe and compassionate standardized practices that consider available efficacy data, long-term outcomes, and research gaps. Novel approaches with limited data must be carefully considered against historic standards of care with robust data suggesting limited benefit and clear adverse effects. This review summarizes available evidence while suggesting practical clinical approaches to pain assessment and avoidance, procedural analgesia, postoperative analgesia, sedation during mechanical ventilation and therapeutic hypothermia, and the issues of tolerance and withdrawal. Further research in all areas represents an urgent priority for optimal neonatal care. In the meantime, synthesis of available data offers clinicians challenging choices as they balance benefit and risk in vulnerable critically ill neonates.

Management of comfort and sedation in neonates with neonatal encephalopathy treated with therapeutic hypothermia.

Ensuring comfort for neonates undergoing therapeutic hypothermia (TH) after neonatal encephalopathy (NE) exemplifies a vital facet of neonatal neurocritical care. Physiologic markers of stress are frequently present in these neonates. Non-pharmacologic comfort measures form the foundation of care, benefitting both the neonate and parents. Pharmacological sedatives may also be indicated, yet have the potential to both mitigate and intensify the neurotoxicity of a hypoxic-ischemic insult. Morphine represents current standard of care with a history of utilization and extensive pharmacokinetic data to guide safe and effective dosing. Dexmedetomidine, as an alternative to morphine, has several appealing characteristics, including neuroprotective effects in animal models; robust pharmacokinetic studies in neonates with NE treated with TH are required to ensure a safe and effective standard dosing approach. Future studies in neonates treated with TH must address comfort, adverse events, and long-term outcomes in the context of specific sedation practices.

A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI.

Fetal cortical plate segmentation is essential in quantitative analysis of fetal brain maturation and cortical folding. Manual segmentation of the cortical plate, or manual refinement of automatic segmentations is tedious and time-consuming. Automatic segmentation of the cortical plate, on the other hand, is challenged by the relatively low resolution of the reconstructed fetal brain MRI scans compared to the thin structure of the cortical plate, partial voluming, and the wide range of variations in the morphology of the cortical plate as the brain matures during gestation. To reduce the burden of manual refinement of segmentations, we have developed a new and powerful deep learning segmentation method. Our method exploits new deep attentive modules with mixed kernel convolutions within a fully convolutional neural network architecture that utilizes deep supervision and residual connections. We evaluated our method quantitatively based on several performance measures and expert evaluations. Results show that our method outperforms several state-of-the-art deep models for segmentation, as well as a state-of-the-art multi-atlas segmentation technique. We achieved average Dice similarity coefficient of 0.87, average Hausdorff distance of 0.96 mm, and average symmetric surface difference of 0.28 mm on reconstructed fetal brain MRI scans of fetuses scanned in the gestational age range of 16 to 39 weeks (28.6± 5.3). With a computation time of less than 1 minute per fetal brain, our method can facilitate and accelerate large-scale studies on normal and altered fetal brain cortical maturation and folding.

Optimal Method for Fetal Brain Age Prediction Using Multiplanar Slices From Structural Magnetic Resonance Imaging.

The accurate prediction of fetal brain age using magnetic resonance imaging (MRI) may contribute to the identification of brain abnormalities and the risk of adverse developmental outcomes. This study aimed to propose a method for predicting fetal brain age using MRIs from 220 healthy fetuses between 15.9 and 38.7 weeks of gestational age (GA). We built a 2D single-channel convolutional neural network (CNN) with multiplanar MRI slices in different orthogonal planes without correction for interslice motion. In each fetus, multiple age predictions from different slices were generated, and the brain age was obtained using the mode that determined the most frequent value among the multiple predictions from the 2D single-channel CNN. We obtained a mean absolute error (MAE) of 0.125 weeks (0.875 days) between the GA and brain age across the fetuses. The use of multiplanar slices achieved significantly lower prediction error and its variance than the use of a single slice and a single MRI stack. Our 2D single-channel CNN with multiplanar slices yielded a significantly lower stack-wise MAE (0.304 weeks) than the 2D multi-channel (MAE = 0.979, p < 0.001) and 3D (MAE = 1.114, p < 0.001) CNNs. The saliency maps from our method indicated that the anatomical information describing the cortex and ventricles was the primary contributor to brain age prediction. With the application of the proposed method to external MRIs from 21 healthy fetuses, we obtained an MAE of 0.508 weeks. Based on the external MRIs, we found that the stack-wise MAE of the 2D single-channel CNN (0.743 weeks) was significantly lower than those of the 2D multi-channel (1.466 weeks, p < 0.001) and 3D (1.241 weeks, p < 0.001) CNNs. These results demonstrate that our method with multiplanar slices accurately predicts fetal brain age without the need for increased dimensionality or complex MRI preprocessing steps.