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Background: Today, magnetic resonance imaging (MRI) is rarely used in managing the care of premature neonates. This is in large part due to the medical and logistical challenges associated with moving neonates from the neonatal intensive care unit (NICU) to the radiology department. Furthermore, acoustic noise associated with MR scanning poses safety concerns for both practitioners and neonatal patients. A small-format 3.0-T neonatal scanner was recently developed and placed within the NICU to address these logistical and acoustic challenges. Objective: To compare acoustic noise measurements of a small-format 3.0-T neonatal MRI scanner with conventional adult-sized 1.5-T and 3.0-T MRI scanners using identical neonatal head imaging protocols. Materials and methods: Sound pressure level (SPL) measurements of a standard imaging protocol were made in a small-format neonatal 3.0-T MRI scanner as well as in adult-sized 1.5-T and 3.0-T scanners. SPL measurements were made with a Brüel & Kjær sound level meter model 2250. The statistical significance of the differences in SPL between scanners was determined using one-way ANOVA. Results: Average sound pressure level values were measured in unweighted decibels (dB) and A-weighted decibels (dBA) for all imaging sequences in the protocol. The average A-weighted SPLs for the NICU from 1.5-T and 3.0-T MRI scanners were 81.02 ± 0.28 dBA, 87.00 ± 0.85 dBA, and 94.91 ± 0.65 dBA, respectively. SPLs at the isocenter of the NICU MRI scanner were 5.98 dBA quieter than in the 1.5-T scanner (P=0.007), and 13.89 dBA quieter than in the 3.0-T scanner (P<0.001). For staff standing next to the scanner, the NICU scanner was 20.24 dBA quieter than the 1.5-T scanner (P<0.001) and 19.28 dBA quieter than the 3.0-T scanner (P<0.001). Conclusion: The NICU 3.0-T MRI system is significantly quieter than conventional adult-sized MRI systems, improving safety for neonatal patients. Significant reductions in SPL were also noted inside the screen room where clinicians may be present during scanning. [ABSTRACT FROM AUTHOR]

Recent research has reported effects of socioeconomic status on neurobehavioral development as early as infancy, including positive associations between income and brain structure, functional connectivity, and behavior later in childhood (Ramphal, Whalen, et al., 2020; Triplett et al., 2022). This study extends this literature by investigating the relation of maternal prenatal social disadvantage (PSD) to neonatal amygdala and hippocampus functional connectivity and whether socioeconomic-related alterations in functional connectivity subsequently predict behavior at age 12 months in a large, socioeconomically diverse sample (N = 261 mother–infant dyads). PSD was assessed across gestation; neonatal magnetic resonance imaging was completed within the first weeks of life; and infant internalizing and externalizing symptoms were evaluated using the Infant–Toddler Social and Emotional Assessment at age 12 months. The results showed that PSD was significantly related to neonatal right amygdala and left hippocampus functional connectivity with prefrontal and motor-related regions. Social disadvantage-related right amygdala and left hippocampus functional connectivity with these regions was subsequently related to infant externalizing and internalizing symptoms at age 12 months. Building off an emerging literature exploring prenatal impacts on neonatal functional connectivity, this study further emphasizes the important role of the maternal environment during gestation on infant brain function and its relationship with externalizing and internalizing behavior in the first years of life. The results suggest that the prenatal socioeconomic environment may be a promising target for interventions aimed at improving infant neurobehavioral outcomes. Public Significance Statement: This study suggests that mothers' prenatal social disadvantage (PSD) impacts the brain function of their infants in the weeks shortly after birth. Additionally, the study reports a link between infant brain function shortly after birth and infant behavior 1 year later. The study results suggest that mother's PSD may be a promising target for interventions that improve infant health. [ABSTRACT FROM AUTHOR]

Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed to produce high quality diagnostic images in children, due to their small physical size and immaturity. Patient motion, cooperation and medical condition dictate the methods and equipment used. A customized approach tailored to each child's age and functional status with the appropriate combination of dedicated staff, imaging hardware, and software is key; these range from low-tech techniques, such as feed and swaddle, to specialized small bore MRI scanners, MRI compatible incubators and neonatal head coils. New pre-and post-processing techniques can also compensate for the motion artifacts and low signal that often degrade neonatal scans.

Internal hernias are a rare but serious complication that typically present in older children and adults and can be congenital or iatrogenic in origin. They are often difficult to diagnose due to their similar radiological and clinical presentation to more common abdominal pathologies. We describe three cases of congenital internal hernias presenting in preterm infants followed by a literature review of congenital internal hernias presenting shortly after birth. When presenting in the neonatal period, congenital internal hernias have been exclusively reported as transmesenteric type. The exact etiology of transmesenteric congenital internal hernias is unclear, but may be a result of vascular compromise to the mesentery creating a small defect in which bowel may become entrapped. Certain genetic factors may also play a role in increasing risk for congenital internal hernias as they can be comorbid with other pathologies. Delayed diagnosis postpones surgical treatment, increasing risk of hernia incarceration, strangulation, irreversible bowel ischemia, and long-term risks inherent to bowel resection. Multimodal imaging plays a key role in the evaluation of these infants by excluding many causes of neonatal intestinal obstruction, however, a definitive prospective radiologic diagnosis has not been reported to date. Radiographic findings and comorbidities associated with these cases can be used along with future reported cases to potentially aid in timely diagnosis.

Congenital infections represent a challenging and varied clinical scenario in which the brain is frequently involved. Therefore, fetal and neonatal neuro-imaging plays a pivotal role in reaching an accurate diagnosis and in predicting the clinical outcome. Congenital brain infections are characterized by various clinical manifestations, ranging from nearly asymptomatic diseases to syndromic disorders, often associated with severe neurological symptoms. Brain damage results from the complex interaction among the infectious agent, its specific cellular tropism, and the stage of development of the central nervous system at the time of the maternal infection. Therefore, neuroradiological findings vary widely and are the result of complex events. An early detection is essential to establishing a proper diagnosis and prognosis, and to guarantee an optimal and prompt therapeutic perinatal management. Recently, emerging infective agents (i.e., Zika virus and SARS-CoV2) have been related to possible pre- and perinatal brain damage, thus expanding the spectrum of congenital brain infections. The purpose of this pictorial review is to provide an overview of the current knowledge on fetal and neonatal brain neuroimaging patterns in congenital brain infections used in clinical practice. [ABSTRACT FROM AUTHOR]

Aberrant cerebellar development and the associated neurocognitive deficits has been postulated in infants with congenital heart disease (CHD). Our objective is to investigate the effect of postnatal head and somatic growth on cerebellar development in neonates with CHD. We compared term-born neonates with a history of CHD with a cohort of preterm-born neonates, two cohorts at similar risk for neurodevelopment impairment, in order to determine if they are similarly affected in the early developmental period. Study Design: 51 preterms-born healthy neonates, 62 term-born CHD neonates, and 54 term-born healthy neonates underwent a brain MRI with volumetric imaging. Cerebellar volumes were extracted through an automated segmentation pipeline that was developed in-house. Volumes were correlated with clinical growth parameters at both the birth and time of MRI. Results: The CHD cohort showed significantly lower cerebellar volumes when compared with both the control (p < 0.015) and preterm (p < 0.004) groups. Change in weight from birth to time of MRI showed a moderately strong correlation with cerebellar volume at time of MRI (r = 0.437, p < 0.002) in the preterms, but not in the CHD neonates (r = 0.205, p < 0.116). Changes in birth length and head circumference showed no significant correlation with cerebellar volume at time of MRI in either cohort. Conclusions: Cerebellar development in premature-born infants is associated with change in birth weight in the early post-natal period. This association is not observed in term-born neonates with CHD, suggesting differential mechanisms of aberrant cerebellar development in these perinatal at-risk populations. [ABSTRACT FROM AUTHOR]

Advanced brain imaging of neonatal macrostructure and microstructure, which has prognosticating importance, is more frequently being incorporated into multi-center trials of neonatal neuroprotection. Multicenter neuroimaging studies, designed to overcome small sample sized clinical cohorts, are essential but lead to increased technical variability. Few harmonization techniques have been developed for neonatal brain microstructural (diffusion tensor) analysis. The work presented here aims to remedy two common problems that exist with the current state of the art approaches: 1) variance in scanner and protocol in data collection can limit the researcher's ability to harmonize data acquired under different conditions or using different clinical populations. 2) The general lack of objective guidelines for dealing with anatomically abnormal anatomy and pathology. Often, subjects are excluded due to subjective criteria, or due to pathology that could be informative to the final analysis, leading to the loss of reproducibility and statistical power. This proves to be a barrier in the analysis of large multi-center studies and is a particularly salient problem given the relative scarcity of neonatal imaging data. We provide an objective, data-driven, and semi-automated neonatal processing pipeline designed to harmonize compartmentalized variant data acquired under different parameters. This is done by first implementing a search space reduction step of extracting the along-tract diffusivity values along each tract of interest, rather than performing whole-brain harmonization. This is followed by a data-driven outlier detection step, with the purpose of removing unwanted noise and outliers from the final harmonization. We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. After applying our pipeline to this large multi-site dataset of neonates and infants with congenital heart disease (n = 398 subjects recruited across 4 centers, with a total of n = 763 MRI pre-operative/post-operative time points), we show that infants with single ventricle cardiac physiology demonstrate greater white matter microstructural alterations compared to infants with bi-ventricular heart disease, supporting what has previously been shown in literature. Our method is an open-source pipeline for delineating white matter tracts in subject space but provides the necessary modular components for performing atlas space analysis. As such, we validate and introduce Diffusion Imaging of Neonates by Group Organization (DINGO), a high-level, semi-automated framework that can facilitate harmonization of subject-space tractography generated from diffusion tensor imaging acquired across varying scanners, institutions, and clinical populations. Datasets acquired using varying protocols or cohorts are compartmentalized into subsets, where a cohort-specific template is generated, allowing for the propagation of the tractography mask set with higher spatial specificity. Taken together, this pipeline can reduce multi-scanner technical variability which can confound important biological variability in relation to neonatal brain microstructure.

Abdominal emergencies in neonates require surgical management in almost all cases and complications may include bowel perforation, sepsis, shock, and even death. Radiological imaging has become a very important aid in the clinical setting as it shortens time to diagnosis. The objective of this review is to discuss the more prevalent neonatal gastrointestinal emergencies, review appropriate imaging options, and illustrate common radiological presentations of these entities. Despite advancements in imaging techniques, it is important to keep in mind that neonates have a higher susceptibility to the adverse effects of ionizing radiation, and therefore radiography and ultrasonography remain the main diagnostic modalities for ruling out the diseases with the worst prognosis. Other modalities (fluoroscopy, computed tomography, and magnetic resonance imaging) may have limited use in very specific conditions. All providers in an emergency department should be familiar with the basic radiological findings that may indicate a gastrointestinal emergency, especially in health institutions that do not have 24-h radiologist coverage. [ABSTRACT FROM AUTHOR]

Diffusion kurtosis imaging (DKI) has undisputed advantages over the more classical diffusion magnetic resonance imaging (dMRI) as witnessed by the fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized, in particular in spinal cord (SC) imaging, because of its inherently demanding technological requirements. Due to its extreme sensitivity to non-Gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, which are not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between the SC region and the brain above, managing to apply such a method to the neonatal cohort becomes of utmost importance. This study will (i) mention current methodological challenges associated with the application of advanced dMRI methods, like DKI, in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox for handling the DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present results of its application in a pilot clinical case study. With the proposed pipeline, we preliminarily show that DKI is more sensitive than DTI-related measures to alterations caused by brain white matter injuries in the underlying cervical SC.

Infants prenatally suspected of having a choledochal cyst (CDC) typically undergo ultrasound imaging shortly after birth. This study sought to evaluate features on the initial postnatal ultrasound (IPU) that could identify newborns at risk for early complications. Following IRB approval, patients from four US fetal centers with prenatal suspicion for CDC and postnatal imaging from 2000 to 2017 were reviewed. Imaging and clinical courses were assessed. Forty-two patients had prenatal ultrasounds suspicious for CDC. Nineteen (45.2%) were excluded due to diagnostic revision (n = 9), cyst resolution (n = 5), lack of IPU measurements (n = 3), or lack of follow-up (n = 2). The 23 remaining patients were included in the study. Of these, five (21.7%) developed symptoms at a median age of 16.5 days (IQR 16–19 days), and 18 (78.3%) remained asymptomatic throughout the first year after birth. Five patients (21.7%) had cysts ≥ 4.5 cm on IPU (Symptomatic: n = 3; Asymptomatic: n = 2). Eighteen patients (78.3%) had cysts < 4.5 cm on IPU (Symptomatic: n = 2; Asymptomatic: n = 16). An IPU cyst size ≥ 4.5 cm was associated with neonatal symptom manifestation (p = 0.048), with 88.9% specificity (95% CI 65.3–98.6%) and 60% sensitivity (95% CI 14.7–94.7%). In newborns with prenatally diagnosed CDC, a cyst size ≥ 4.5 cm on IPU is associated with symptom development during the first month after birth and therefore early cyst excision is recommended. [ABSTRACT FROM AUTHOR]

Purpose: Functional magnetic resonance imaging (fMRI) during infancy poses challenges due to practical, methodological, and analytical considerations. The aim of this study was to implement a hardware‐related approach to increase subject compliance for fMRI involving awake infants. To accomplish this, we designed, constructed, and evaluated an adaptive 32‐channel array coil. Methods: To allow imaging with a close‐fitting head array coil for infants aged 1‐18 months, an adjustable head coil concept was developed. The coil setup facilitates a half‐seated scanning position to improve the infant's overall scan compliance. Earmuff compartments are integrated directly into the coil housing to enable the usage of sound protection without losing a snug fit of the coil around the infant's head. The constructed array coil was evaluated from phantom data using bench‐level metrics, signal‐to‐noise ratio (SNR) performances, and accelerated imaging capabilities for both in‐plane and simultaneous multislice (SMS) reconstruction methodologies. Furthermore, preliminary fMRI data were acquired to evaluate the in vivo coil performance. Results: Phantom data showed a 2.7‐fold SNR increase on average when compared with a commercially available 32‐channel head coil. At the center and periphery regions of the infant head phantom, the SNR gains were measured to be 1.25‐fold and 3‐fold, respectively. The infant coil further showed favorable encoding capabilities for undersampled k‐space reconstruction methods and SMS techniques. Conclusions: An infant‐friendly head coil array was developed to improve sensitivity, spatial resolution, accelerated encoding, motion insensitivity, and subject tolerance in pediatric MRI. The adaptive 32‐channel array coil is well‐suited for fMRI acquisitions in awake infants. [ABSTRACT FROM AUTHOR]

Purpose: To investigate safe limits for neonatal imaging using a 7T head coil, including both specific absorption rate (SAR) and temperature predictions. Methods: Head‐centered neonate models were simulated using finite‐difference time domain–based electromagnetic and thermal solvers. The effects of higher water content of neonatal tissues compared with adults, position shifts, and thermal insulation were also considered. An adult model was simulated for comparison. Results: Maximum and average SAR are both elevated in the neonate when compared with an adult model. When normalized to B1+, the SAR experienced by a neonate is greater than an adult by approximately a factor of 2; when normalized to net forward power (forward‐reflected), this increases to a factor of 2.5‐3.0; and when normalized to absorbed power, approximately a factor of 4. Use of age‐adjusted dielectric properties significantly increases the predicted SAR, compared with using adult tissue properties for the neonates. Thermal simulations predict that change in core temperature/maximum temperature remain compliant with International Electrotechnical Commission limits when a thermally insulated neonate is exposed at the SAR limit for up to an hour. Conclusion: This study of two neonate models cannot quantify the variability expected within a larger population. Likewise, the use of age‐adjusted dielectric properties have a significant effect, but while their use is well motivated by literature, there is uncertainty in the true dielectric properties of neonatal tissue. Nevertheless, the main finding is that unlike at lower field strengths, operational limits for 7T neonatal MRI using an adult head coil should be more conservative than limits for use on adults. [ABSTRACT FROM AUTHOR]

Congenital infections represent a challenging and varied clinical scenario in which the brain is frequently involved. Therefore, fetal and neonatal neuro-imaging plays a pivotal role in reaching an accurate diagnosis and in predicting the clinical outcome. Congenital brain infections are characterized by various clinical manifestations, ranging from nearly asymptomatic diseases to syndromic disorders, often associated with severe neurological symptoms. Brain damage results from the complex interaction among the infectious agent, its specific cellular tropism, and the stage of development of the central nervous system at the time of the maternal infection. Therefore, neuroradiological findings vary widely and are the result of complex events. An early detection is essential to establishing a proper diagnosis and prognosis, and to guarantee an optimal and prompt therapeutic perinatal management. Recently, emerging infective agents (i.e., Zika virus and SARS-CoV2) have been related to possible pre- and perinatal brain damage, thus expanding the spectrum of congenital brain infections. The purpose of this pictorial review is to provide an overview of the current knowledge on fetal and neonatal brain neuroimaging patterns in congenital brain infections used in clinical practice.

Aberrant cerebellar development and the associated neurocognitive deficits has been postulated in infants with congenital heart disease (CHD). Our objective is to investigate the effect of postnatal head and somatic growth on cerebellar development in neonates with CHD. We compared term-born neonates with a history of CHD with a cohort of preterm-born neonates, two cohorts at similar risk for neurodevelopment impairment, in order to determine if they are similarly affected in the early developmental period. Study Design: 51 preterms-born healthy neonates, 62 term-born CHD neonates, and 54 term-born healthy neonates underwent a brain MRI with volumetric imaging. Cerebellar volumes were extracted through an automated segmentation pipeline that was developed in-house. Volumes were correlated with clinical growth parameters at both the birth and time of MRI. Results: The CHD cohort showed significantly lower cerebellar volumes when compared with both the control (p < 0.015) and preterm (p < 0.004) groups. Change in weight from birth to time of MRI showed a moderately strong correlation with cerebellar volume at time of MRI (r = 0.437, p < 0.002) in the preterms, but not in the CHD neonates (r = 0.205, p < 0.116). Changes in birth length and head circumference showed no significant correlation with cerebellar volume at time of MRI in either cohort. Conclusions: Cerebellar development in premature-born infants is associated with change in birth weight in the early post-natal period. This association is not observed in term-born neonates with CHD, suggesting differential mechanisms of aberrant cerebellar development in these perinatal at-risk populations.

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.

Objective: To describe the radiographic appearance of subclinical calcified brown fat necrosis and the associated clinical and laboratory findings. Materials and Methods: Picture Archiving and Communications Sytem (PACS) was searched using keywords “soft tissue calcification” and “chest.” The clinical record was searched for prior cardiac surgery, bypass, Extracorporeal Membrane Oxygentation (ECMO) and prostaglandin use. Age when calcifications were first detected, location, resolution, and associated laboratory abnormalities were recorded. Results: Nine patients were identified. None had skin lesions. All patients had congenital heart disease and had experienced cardiac/respiratory arrest and/or severe hypotension 1–6 weeks before soft tissue calcifications occurred. Calcifications resolved by 9 weeks to 5 months in 3 patients. The remaining were either deceased or lacked follow-up imaging. Renal ultrasound was performed in all but 1 patient. Nephrocalcinosis was only seen in 1 patient. Conclusion: Brown fat necrosis is subclinical, diagnosed on plain film, and likely self-limited. It occurs in term and preterm infants who have undergone significant systemic stress and carries a poor prognosis.

Diffusion MRI has the potential to provide important information about the connectivity and microstructure of the human brain during normal and abnormal development, noninvasively and in vivo. Recent developments in MRI hardware and reconstruction methods now permit the acquisition of large amounts of data within relatively short scan times. This makes it possible to acquire more informative multi‐shell data, with diffusion sensitisation applied along many directions over multiple b‐value shells. Such schemes are characterised by the number of shells acquired, and the specific b‐value and number of directions sampled for each shell. However, there is currently no clear consensus as to how to optimise these parameters. In this work, we propose a means of optimising multi‐shell acquisition schemes by estimating the information content of the diffusion MRI signal, and optimising the acquisition parameters for sensitivity to the observed effects, in a manner agnostic to any particular diffusion analysis method that might subsequently be applied to the data. This method was used to design the acquisition scheme for the neonatal diffusion MRI sequence used in the developing Human Connectome Project (dHCP), which aims to acquire high quality data and make it freely available to the research community. The final protocol selected by the algorithm, and currently in use within the dHCP, consists of 20 b=0 images and diffusion‐weighted images at b = 400, 1000 and 2600 s/mm2 with 64, 88 and 128 directions per shell, respectively. Highlights: A data‐driven method is presented to design multi‐shell diffusion MRI acquisition schemes (b‐values and no. of directions).This method optimises the multi‐shell scheme for maximum sensitivity to the information content in the signal.When applied in neonates, the data suggest that a b=0 + 3 shell strategy is appropriate. [ABSTRACT FROM AUTHOR]

Purpose: Novel demonstration of R2∗ and tissue density estimation in infant lungs using 3D ultrashort echo time MRI. Differences between adult and neonates with no clinical indication of lung pathology is explored, as well as relationships between parameter estimates and gravitationally dependent position and lung inflation state. This provides a tool for probing physiologic processes that may be relevant to pulmonary disease and progression in newborns. Methods: R2∗ and tissue density were estimated in a phantom consisting of standards allowing for ground truth comparisons and in human subjects (N = 5 infants, N = 4 adults, no clinical indication of lung dysfunction) using a 3D radial multiecho ultrashort echo time MRI sequence. Whole lung averages were compared between infants and adults. Dependence of the metrics on anterior‐posterior position as well as between end‐tidal inspiration and expiration were explored, in addition to the general relationship between R2∗ and tissue density. Results: Estimates in the phantom did not differ significantly from ground truth. Neonates had significantly lower mean R2∗ (P =.006) and higher mean tissue density (P = 1.5e‐5) than adults. Tissue density and R2∗ were both significantly dependent on anterior‐posterior position and lung inflation state (P <.005). An overall inverse relationship was found between R2∗ and tissue density, which was similar in both neonates and adults. Conclusion: Estimation of tissue density and R2∗ in free breathing, nonsedated, neonatal patients is feasible using multiecho ultrashort echo time MRI. R2∗ was no different between infants and adults when matched for tissue density, although density of lung parenchyma was, on average, lower in adults than neonates. [ABSTRACT FROM AUTHOR]

Abstract Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed to produce high quality diagnostic images in children, due to their small physical size and immaturity. Patient motion, cooperation and medical condition dictate the methods and equipment used. A customized approach tailored to each child's age and functional status with the appropriate combination of dedicated staff, imaging hardware, and software is key; these range from low-tech techniques, such as feed and swaddle, to specialized small bore MRI scanners, MRI compatible incubators and neonatal head coils. New pre-and post-processing techniques can also compensate for the motion artifacts and low signal that often degrade neonatal scans. Highlights • Rapid brain growth and development make pediatric neuroimaging challenging. • Imaging infants using feed and swaddle can minimize motion without sedation. • Custom hardware, software, and well-trained staff produce high quality images. • Automated and quantitative techniques are revolutionizing pediatric neuroimaging. [ABSTRACT FROM AUTHOR]

Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsupervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuroimaging datasets requires adequate sample size for training and well-defined signal intensity based structural differentiation. There is a lack of effective automated diagnostic tools for the reliable detection of brain dysmaturation in the neonatal period, related to small sample size and complex undifferentiated brain structures, despite both translational research and clinical importance. Volumetric information alone is insufficient for diagnosis. In this study, we developed a computational framework for the automated classification of brain dysmaturation from neonatal MRI, by combining a specific deep neural network implementation with neonatal structural brain segmentation as a method for both clinical pattern recognition and data-driven inference into the underlying structural morphology. We implemented three-dimensional convolution neural networks (3D-CNNs) to specifically classify dysplastic cerebelli, a subset of surface-based subcortical brain dysmaturation, in term infants born with congenital heart disease. We obtained a 0.985 ± 0. 0241-classification accuracy of subtle cerebellar dysplasia in CHD using 10-fold cross-validation. Furthermore, the hidden layer activations and class activation maps depicted regional vulnerability of the superior surface of the cerebellum, (composed of mostly the posterior lobe and the midline vermis), in regards to differentiating the dysplastic process from normal tissue. The posterior lobe and the midline vermis provide regional differentiation that is relevant to not only to the clinical diagnosis of cerebellar dysplasia, but also genetic mechanisms and neurodevelopmental outcome correlates. These findings not only contribute to the detection and classification of a subset of neonatal brain dysmaturation, but also provide insight to the pathogenesis of cerebellar dysplasia in CHD. In addition, this is one of the first examples of the application of deep learning to a neuroimaging dataset, in which the hidden layer activation revealed diagnostically and biologically relevant features about the clinical pathogenesis. The code developed for this project is open source, published under the BSD License, and designed to be generalizable to applications both within and beyond neonatal brain imaging. [ABSTRACT FROM AUTHOR]

Objective: To describe the radiographic appearance of subclinical calcified brown fat necrosis and the associated clinical and laboratory findings. Materials and Methods: Picture Archiving and Communications Sytem (PACS) was searched using keywords "soft tissue calcification" and "chest." The clinical record was searched for prior cardiac surgery, bypass, Extracorporeal Membrane Oxygentation (ECMO) and prostaglandin use. Age when calcifications were first detected, location, resolution, and associated laboratory abnormalities were recorded. Results: Nine patients were identified. None had skin lesions. All patients had congenital heart disease and had experienced cardiac/respiratory arrest and/or severe hypotension 1-6 weeks before soft tissue calcifications occurred. Calcifications resolved by 9 weeks to 5 months in 3 patients. The remaining were either deceased or lacked follow-up imaging. Renal ultrasound was performed in all but 1 patient. Nephrocalcinosis was only seen in 1 patient. Conclusion: Brown fat necrosis is subclinical, diagnosed on plain film, and likely self-limited. It occurs in term and preterm infants who have undergone significant systemic stress and carries a poor prognosis. [ABSTRACT FROM AUTHOR]

Internal hernias are a rare but serious complication that typically present in older children and adults and can be congenital or iatrogenic in origin. They are often difficult to diagnose due to their similar radiological and clinical presentation to more common abdominal pathologies. We describe three cases of congenital internal hernias presenting in preterm infants followed by a literature review of congenital internal hernias presenting shortly after birth. When presenting in the neonatal period, congenital internal hernias have been exclusively reported as transmesenteric type. The exact etiology of transmesenteric congenital internal hernias is unclear, but may be a result of vascular compromise to the mesentery creating a small defect in which bowel may become entrapped. Certain genetic factors may also play a role in increasing risk for congenital internal hernias as they can be comorbid with other pathologies. Delayed diagnosis postpones surgical treatment, increasing risk of hernia incarceration, strangulation, irreversible bowel ischemia, and long-term risks inherent to bowel resection. Multimodal imaging plays a key role in the evaluation of these infants by excluding many causes of neonatal intestinal obstruction, however, a definitive prospective radiologic diagnosis has not been reported to date. Radiographic findings and comorbidities associated with these cases can be used along with future reported cases to potentially aid in timely diagnosis. • Congenital internal hernias presenting in neonates are difficult to diagnose preoperatively. • They often present with nonspecific findings of bowel obstruction. • Intrauterine vascular injury may be a cause of congenital internal hernia. • Multimodal imaging may aid in earlier diagnosis and decreased complications. [ABSTRACT FROM AUTHOR]

The sick preterm infant monitoring is an intriguing job that medical staff in Neonatal Intensive Care Units (NICU) must deal with on a daily basis. As a standards monitoring procedure, preterm infants are monitored via sensors and electrodes that are firmly attached to their fragile and delicate skin and connected to processing monitors. However, an alternative exists in contactless imaging to record such physiological signals (we call it as Physio-Markers), detecting superficial changes and internal structures activities which can be used independently of, or aligned with, conventional monitors. Countless advantages can be gained from unobtrusive monitoring not limited to: (1) quick data generation; (2) decreasing physical and direct contact with skin, which reduces skin breakdown and minimizes risk of infection; and (3) reduction of electrodes and probes connected to clinical monitors and attached to the skin, which allows greater body surface-area for better care. This review is an attempt to build a solid ground for and to provide a clear perspective of the potential clinical applications of technologies inside NICUs that use contactless imaging modalities such as Visible Light Imaging (VLI), Near Infrared Spectroscopy (NIRS), and Infrared Thermography (IRT).

Very preterm (VP) survivors are at increased risk of autism spectrum disorder (ASD) compared with term-born children. This study explored whether neonatal magnetic resonance (MR) brain features differed in VP children with and without ASD at 7 years. One hundred and seventy-two VP children (<30 weeks' gestation or <1250 g birth weight) underwent structural brain MR scans at term equivalent age (TEA; 40 weeks' gestation ±2 weeks) and were assessed for ASD at 7 years of age. The presence and severity of white matter, cortical gray matter, deep nuclear gray matter, and cerebellar abnormalities were assessed, and total and regional brain volumes were measured. ASD was diagnosed using a standardized parent report diagnostic interview and confirmed via an independent assessment. Eight VP children (4.7%) were diagnosed with ASD. Children with ASD had more cystic lesions in the cortical white matter at TEA compared with those without ASD (odds ratio [OR] 8.7, 95% confidence interval [CI] 1.5, 51.3, P = 0.02). There was also some evidence for smaller cerebellar volumes in children with ASD compared with those without ASD (OR = 0.82, CI = 0.66, 1.00, P = 0.06). Overall, the results suggest that VP children with ASD have different brain structure in the neonatal period compared with those who do not have ASD. Autism Res 2016, 9: 543-552. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

No abstract available.

Purpose To measure cerebral blood flow (CBF) using Look-Locker arterial spin labeling (ASL) in children under 1 year of age and to investigate the advantages of using subject-specific estimates of ASL model parameters in this population. Materials and Methods Of 12 scanned infants, we successfully acquired CBF maps in 7 (postmenstrual age: 32 to 78 weeks) using a Look-Locker ASL scheme and both adult literature-derived and subject-specific model parameters. ASL global CBF measurements were compared with independent global CBF measurements obtained in the same scanning session using phase-contrast angiography. Results Measured global CBF values ranged from 24 to 56 mL/100g/min in the scanned infants, increasing significantly with postmenstrual age (ρSpearman = 0.89, P-value = 0.01). Using subject-specific model parameters yielded CBF estimates in significantly better agreement with phase-contrast angiography values ( P-value: 0.80) than when standard adult parameters were used ( P-value: 0.04). Conclusion Look-Locker ASL can be used to measure CBF in infants and its accuracy is improved with the use of infant-specific auxiliary parameters, particularly blood and tissue T1, which were much more variable in the imaged infants in than adults. J. Magn. Reson. Imaging 2015;41:1591-1600. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Advanced brain imaging of neonatal macrostructure and microstructure, which has prognosticating importance, is more frequently being incorporated into multi-center trials of neonatal neuroprotection. Multicenter neuroimaging studies, designed to overcome small sample sized clinical cohorts, are essential but lead to increased technical variability. Few harmonization techniques have been developed for neonatal brain microstructural (diffusion tensor) analysis. The work presented here aims to remedy two common problems that exist with the current state of the art approaches: 1) variance in scanner and protocol in data collection can limit the researcher's ability to harmonize data acquired under different conditions or using different clinical populations. 2) The general lack of objective guidelines for dealing with anatomically abnormal anatomy and pathology. Often, subjects are excluded due to subjective criteria, or due to pathology that could be informative to the final analysis, leading to the loss of reproducibility and statistical power. This proves to be a barrier in the analysis of large multi-center studies and is a particularly salient problem given the relative scarcity of neonatal imaging data. We provide an objective, data-driven, and semi-automated neonatal processing pipeline designed to harmonize compartmentalized variant data acquired under different parameters. This is done by first implementing a search space reduction step of extracting the along-tract diffusivity values along each tract of interest, rather than performing whole-brain harmonization. This is followed by a data-driven outlier detection step, with the purpose of removing unwanted noise and outliers from the final harmonization. We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. After applying our pipeline to this large multi-site dataset of neonates and infants with congenital heart disease (n= 398 subjects recruited across 4 centers, with a total of n=763 MRI pre-operative/post-operative time points), we show that infants with single ventricle cardiac physiology demonstrate greater white matter microstructural alterations compared to infants with bi-ventricular heart disease, supporting what has previously been shown in literature. Our method is an open-source pipeline for delineating white matter tracts in subject space but provides the necessary modular components for performing atlas space analysis. As such, we validate and introduce Diffusion Imaging of Neonates by Group Organization (DINGO), a high-level, semi-automated framework that can facilitate harmonization of subject-space tractography generated from diffusion tensor imaging acquired across varying scanners, institutions, and clinical populations. Datasets acquired using varying protocols or cohorts are compartmentalized into subsets, where a cohort-specific template is generated, allowing for the propagation of the tractography mask set with higher spatial specificity. Taken together, this pipeline can reduce multi-scanner technical variability which can confound important biological variability in relation to neonatal brain microstructure.

Alterations in cerebral blood flow (CBF) are believed to be linked to many of the neurological pathologies that affect neonates and small infants. CBF measurements are nonetheless often difficult to perform in this population, as many techniques rely on radioactive tracers or other invasive methods. In this study, mean global CBF was measured in 21 infants under the age of one, using non-invasive MRI techniques adapted to the neonatal population. Mean CBF was computed as the ratio of blood flow delivered to the brain (measured using phase contrast MRI) and brain volume (computed by segmenting anatomical MR images). Tests in adult volunteers and repeated measurements showed the flow measurements using the proposed method to be both accurate and reproducible. It was also found that cardiac gating need not be employed in infants with no known cardiac pathology. The developed technique can easily be appended to a neonatal MRI examination to provide rapid, robust, and non-invasive estimates of mean CBF, thus providing a means to monitor developmental or pathology-related alterations in cerebral perfusion and the impact of different treatment courses. In the imaged cohort, mean CBF and flow to the brain were found to rapidly increase during the first year of life (from approx. 25 to 60 ml blood/100 ml tissue/min), in good agreement with literature from other modalities where available. Mean CBF also showed a significant correlation with arterial oxygen saturation level and heart rate, but no significant correlation was found between CBF and the hematocrit or body temperature. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to develop a computer model to simulate the image acquisition for two computed radiography (CR) imaging systems used for neonatal chest imaging: (1) The Agfa ADC Compact, a flying spot reader with powder phosphor image plates (MD 40.0); and (2) the Agfa DX-S, a line-scanning CR reader with needle crystal phosphor image plates (HD 5.0). The model was then applied to compare the image quality of the two CR imaging systems. Methods: Monte Carlo techniques were used to simulate the transport of primary and scattered x rays in digital x-ray systems. The output of the Monte Carlo program was an image representing the energy absorbed in the detector material. This image was then modified using physical characteristics of the CR imaging systems to account for the signal intensity variations due to the heel effect along the anode-cathode axis, the spatial resolution characteristics of the imaging system, and the various sources of image noise. The simulation was performed for typical acquisition parameters of neonatal chest x-ray examinations. To evaluate the computer model, the authors compared the threshold-contrast detectability in simulated and experimentally acquired images of a contrast-detail phantom. Threshold-contrast curves were computed using a commercially available scoring program. Results: The threshold-contrast curves of the simulated and experimentally acquired images show good agreement; for the two CR systems, 93% of the threshold diameters calculated from the simulated images fell within the confidence intervals of the threshold diameter calculated from the experimentally assessed images. Moreover, the superiority of needle based CR plates for neonatal imaging was confirmed. Conclusions: The good agreement between simulated and experimental acquired results indicates that the computer model is accurate. [ABSTRACT FROM AUTHOR]

Diffusion kurtosis imaging (DKI) has undisputed advantages over the more classical diffusion magnetic resonance imaging (dMRI) as witnessed by the fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized, in particular in spinal cord (SC) imaging, because of its inherently demanding technological requirements. Due to its extreme sensitivity to non-Gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, which are not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between the SC region and the brain above, managing to apply such a method to the neonatal cohort becomes of utmost importance. This study will (i) mention current methodological challenges associated with the application of advanced dMRI methods, like DKI, in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox for handling the DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present results of its application in a pilot clinical case study. With the proposed pipeline, we preliminarily show that DKI is more sensitive than DTI-related measures to alterations caused by brain white matter injuries in the underlying cervical SC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Trò, Roascio, Tortora, Severino, Rossi, Cohen-Adad, Fato and Arnulfo.)

• Subject motion in dMRI leads to a set of scattered slices with unique contrast. • We introduce a slice-to-volume reconstruction framework for multi-shell HARDI data • Based on a data-driven representation as spherical harmonics and radial decomposition (SHARD). • The method is evaluated in test-retest scans and in the neonatal dHCP cohort. • Results show robust reconstruction in severely motion-corrupted scans. 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. [ABSTRACT FROM AUTHOR]

Purpose: Novel demonstration of R 2 ∗ and tissue density estimation in infant lungs using 3D ultrashort echo time MRI. Differences between adult and neonates with no clinical indication of lung pathology is explored, as well as relationships between parameter estimates and gravitationally dependent position and lung inflation state. This provides a tool for probing physiologic processes that may be relevant to pulmonary disease and progression in newborns., Methods: R 2 ∗ and tissue density were estimated in a phantom consisting of standards allowing for ground truth comparisons and in human subjects (N = 5 infants, N = 4 adults, no clinical indication of lung dysfunction) using a 3D radial multiecho ultrashort echo time MRI sequence. Whole lung averages were compared between infants and adults. Dependence of the metrics on anterior-posterior position as well as between end-tidal inspiration and expiration were explored, in addition to the general relationship between R 2 ∗ and tissue density., Results: Estimates in the phantom did not differ significantly from ground truth. Neonates had significantly lower mean R 2 ∗ (P = .006) and higher mean tissue density (P = 1.5e-5) than adults. Tissue density and R 2 ∗ were both significantly dependent on anterior-posterior position and lung inflation state (P < .005). An overall inverse relationship was found between R 2 ∗ and tissue density, which was similar in both neonates and adults., Conclusion: Estimation of tissue density and R 2 ∗ in free breathing, nonsedated, neonatal patients is feasible using multiecho ultrashort echo time MRI. R 2 ∗ was no different between infants and adults when matched for tissue density, although density of lung parenchyma was, on average, lower in adults than neonates., (© 2019 International Society for Magnetic Resonance in Medicine.)

The sick preterm infant monitoring is an intriguing job that medical staff in Neonatal Intensive Care Units (NICU) must deal with on a daily basis. As a standards monitoring procedure, preterm infants are monitored via sensors and electrodes that are firmly attached to their fragile and delicate skin and connected to processing monitors. However, an alternative exists in contactless imaging to record such physiological signals (we call it as Physio-Markers), detecting superficial changes and internal structures activities which can be used independently of, or aligned with, conventional monitors. Countless advantages can be gained from unobtrusive monitoring not limited to: (1) quick data generation; (2) decreasing physical and direct contact with skin, which reduces skin breakdown and minimizes risk of infection; and (3) reduction of electrodes and probes connected to clinical monitors and attached to the skin, which allows greater body surface-area for better care. This review is an attempt to build a solid ground for and to provide a clear perspective of the potential clinical applications of technologies inside NICUs that use contactless imaging modalities such as Visible Light Imaging (VLI), Near Infrared Spectroscopy (NIRS), and Infrared Thermography (IRT).