Management of fetal head and neck masses: Evaluation of prenatal factors associated with airway obstruction and decision for definitive airway and ex-utero intrapartum treatment at birth.

OBJECTIVE: Fetal head and neck masses can result in critical airway obstruction. Our study aimed to evaluate prenatal factors associated with the decision for a definitive airway, including ex-utero intrapartum treatment (EXIT), at birth among at-risk fetuses. METHODS: A single-institution retrospective review evaluated all fetal head and neck masses prenatally diagnosed from 2005 to 2023. The primary outcome was the decision for a definitive airway at birth, including intubation, tracheostomy, or EXIT. RESULTS: Thirty four patients were included, with 23 deliveries occurring at our institution. 8/23 (35%) patients received a definitive airway at birth, six underwent an EXIT procedure, and two required intubation only. Patients who received a definitive airway had higher rates of polyhydramnios (50% vs. 7%, p = 0.03), tracheal narrowing on ultrasound (US) (50% vs. 0%, p = 0.01), tracheal displacement on US (63% vs. 0%, p < 0.01), abnormal fetal breathing on US (50% vs. 0%, p = 0.01), tracheal narrowing or displacement on magnetic resonance imaging (MRI) (75% vs. 7%, p < 0.01), and larger mass maximum diameter (7.9 vs. 4.3 cm, p = 0.02). In our series, 100% of patients with polyhydramnios, tracheal narrowing or displacement on either US or MRI, and abnormal fetal breathing on US received a definitive airway at birth. CONCLUSION: Prenatal findings of tracheal narrowing or displacement, polyhydramnios, and abnormal fetal breathing are strongly associated with the decision for a definitive airway at birth and warrant mobilization of appropriate resources.

Understanding Bilateral Skull Fractures in Infancy: A Retrospective Multicenter Case Review.

BACKGROUND: Bilateral skull fractures in infancy often raise suspicion for abuse. Nevertheless, literature suggests that they may occur accidentally. However, empiric data are lacking. OBJECTIVE: This multicenter retrospective review aimed to characterize bilateral skull fractures in a large sample. PARTICIPANTS AND SETTING: Medical records for infants younger than 24 months with bilateral skull fractures involving hospital consultation with a child abuse pediatrician (CAP) were reviewed from 2005 to 2020 at 13 nationally represented institutions. METHODS: Standardized data collection across institutions included historical features, fracture characteristics, and additional injuries, as well as the CAP's determination of accident versus abuse. Pooled data were analyzed for descriptive and bivariate analyses. RESULTS: For 235 cases, 141 were accidental, and 94 abuse. The majority occurred in young infants, and a history of a fall was common in 70% of cases. More than 80% involved both parietal bones. Bilateral simple linear fractures were more common in accidental cases, 79% versus 35%, whereas a complex fracture was more frequent in abuse cases, 55% versus 21% ( P < 0.001). Almost two thirds of accidental cases showed approximation of the fractures at the sagittal suture, compared with one third of abuse cases ( P < 0.001). Whereas focal intracranial hemorrhage was seen in 43% of all cases, diffuse intracranial hemorrhage was seen more in abuse cases (45%) than accidents (11%). Skin trauma was more common in abusive than accidental injury (67% vs 17%, P < 0.001), as were additional fractures on skeletal survey (49% vs 3%, P < 0.001). CONCLUSIONS: A fall history was common in bilateral skull fractures deemed accidental by a CAP. Most accidental cases involved young infants with biparietal simple linear fractures, without skin trauma or additional fractures. A skeletal survey may aid in the determination of accidental or abusive injury for unwitnessed events resulting in bilateral skull fractures in infants.

Convolutional neural network-aided tuber segmentation in tuberous sclerosis complex patients correlates with electroencephalogram.

OBJECTIVE: One of the clinical hallmarks of tuberous sclerosis complex (TSC) is radiologically identified cortical tubers, which are present in most patients. Intractable epilepsy may require surgery, often involving invasive diagnostic procedures such as intracranial electroencephalography (EEG). Identifying the location of the dominant tuber responsible for generating epileptic activities is a critical issue. However, the link between cortical tubers and epileptogenesis is poorly understood. Given this, we hypothesized that tuber voxel intensity may be an indicator of the dominant epileptogenic tuber. Also, via tuber segmentation based on deep learning, we explored whether an automatic quantification of the tuber burden is feasible. METHODS: We annotated tubers from structural magnetic resonance images across 29 TSC subjects, summarized tuber statistics in eight brain lobes, and determined suspected epileptogenic lobes from the same group using EEG monitoring data. Then, logistic regression analyses were performed to demonstrate the linkage between the statistics of cortical tuber and the epileptogenic zones. Furthermore, we tested the ability of a neural network to identify and quantify tuber burden. RESULTS: Logistic regression analyses showed that the volume and count of tubers per lobe, not the mean or variance of tuber voxel intensity, were positively correlated with electrophysiological data. In 47.6% of subjects, the lobe with the largest tuber volume concurred with the epileptic brain activity. A neural network model on the test dataset showed a sensitivity of .83 for localizing individual tubers. The predicted masks from the model correlated highly with the neurologist labels, and thus may be a useful tool for determining tuber burden and searching for the epileptogenic zone. SIGNIFICANCE: We have proven the feasibility of an automatic segmentation of tubers and a derivation of tuber burden across brain lobes. Our method may provide crucial insights regarding the treatment and outcome of TSC patients.

Extracardiac imaging findings in COVID-19-associated multisystem inflammatory syndrome in children.

BACKGROUND: Coronavirus disease 2019 (COVID-19)-associated multisystem inflammatory syndrome in children (MIS-C) is an emerging syndrome that presents with a Kawasaki-like disease and multiorgan damage in children previously exposed to COVID-19. OBJECTIVE: To review the extracardiac radiologic findings of MIS-C in a group of children and young adults with a confirmed diagnosis of MIS-C. MATERIALS AND METHODS: In a retrospective study from April 1, 2020, to July 31, 2020, we reviewed the imaging studies of 47 children and adolescents diagnosed with MIS-C, 25 females (53%) and 22 males (47%), with an average age of 8.4 years (range 1.3-20 years). Forty-five had chest radiographs, 8 had abdominal radiographs, 13 had abdominal US or MRI, 2 had neck US, and 4 had brain MRI. RESULTS: Thirty-seven of 45 (82%) patients with chest radiographs had findings, with pulmonary opacities being the most common finding (n=27, 60%), most often bilateral and diffuse, followed by peribronchial thickening (n=26, 58%). Eight patients had normal chest radiographs. On abdominal imaging, small-volume ascites was the most common finding (n=7, 54%). Other findings included right lower quadrant bowel wall thickening (n=3, 23%), gallbladder wall thickening (n=3, 23%), and cervical (n=2) or abdominal (n=2) lymphadenopathy. Of the four patients with brain MRI, one had bilateral parieto-occipital abnormalities and another papilledema. CONCLUSION: The diagnosis of MIS-C and its distinction from other pathologies should be primarily based on clinical presentation and laboratory evidence of inflammation because imaging findings are nonspecific. However, it should be considered in the setting of bilateral diffuse pulmonary opacities, peribronchial thickening, right lower quadrant bowel inflammation or unexplained ascites in a child presenting with Kawasaki-like symptoms and a history of COVID-19 infection or recent COVID-19 exposure.

Tailored magnetic resonance fingerprinting of post-operative pediatric brain tumor patients.

PURPOSE: Brain and spinal cord tumors are the second most common cancer in children and account for one out of four cancers diagnosed. However, the long acquisition times associated with acquiring both data types prohibit using quantitative MR (qMR) in pediatric imaging protocols. This study aims to demonstrate the tailored magnetic resonance fingerprinting's (TMRF) ability to simultaneously provide quantitative maps (T1, T2) and multi-contrast qualitative images (T1 weighted, T1 FLAIR, T2 weighted) rapidly in pediatric brain tumor patients. METHODS: In this work, we imaged five pediatric patients with brain tumors (resected/residual) using TMRF at 3 T. We compared the TMRF-derived T2 weighted images with those from the vendor-supplied sequence (as the gold standard, GS) for healthy and pathological tissue signal intensities. The relaxometric maps from TMRF were subjected to a region of interest (ROI) analysis to differentiate between healthy and pathological tissues. We performed the Wilcoxon rank sum test to check for significant differences between the two tissue types. RESULTS: We found significant differences (p < 0.05) in both T1 and T2 ROI values between the two tissue types. A strong correlation was found between the TMRF-based T2 weighted and GS signal intensities for the healthy (correlation coefficient, r = 0.99) and pathological tissues (r = 0.88). CONCLUSION: The TMRF implementation provides the two relaxometric maps and can potentially save ~2 min if it replaces the T2-weighted imaging in the current protocol.

Prenatal ultrasound-and MRI-based imaging predictors of respiratory symptoms at birth for congenital lung malformations.

BACKGROUND: Congenital lung malformations (CLM) are rare developmental anomalies of the fetal lung with a minority of patients exhibiting symptoms around the time of birth. Although ultrasound remains the gold standard, fetal MRI has recently been incorporated as an adjunct imaging modality in the workup and prenatal counseling of patients with CLM as it is thought to more accurately delineate lesion boundaries and diagnose lesion type. We evaluate what prenatal variables correlate with postnatal respiratory symptoms. METHODS: We performed a retrospective review of patients with prenatal diagnosis of CLM treated at our institution between 2006-2020. Fetal ultrasound and magnetic resonance imaging (MRI) parameters including maximal congenital pulmonary airway malformation volume ratio (CVR), absolute cyst volume, and observed to expected normal fetal lung volume (O/E NFLV) were correlated with outcomes including postnatal respiratory symptoms, need for supplementary oxygen or mechanical ventilation, delay in tolerating full feeds, resection in the neonatal period. RESULTS: Our study included 111 patients, all of whom underwent fetal ultrasound with 64 patients additionally undergoing fetal MRI. Postnatal respiratory symptoms were noted in 22.5% of patients, 19.8% required supplemental oxygen, 2.7% mechanical ventilation and two patients requiring urgent resection. Ultrasound parameters including absolute cyst volume and maximal CVR correlated with need for mechanical ventilation (p=0.034 and p=0.024, respectively) and for urgent resection (p=0.018 and p=0.023, respectively) and had a marginal association with postnatal respiratory symptoms (p=0.050 and p=0.052). Absolute cyst volume became associated with postnatal respiratory symptoms (p=0.017) after multivariable analysis controlling for maternal steroid administration and gestational age. O/E NFLV did not correlate with perinatal outcomes. CONCLUSION: We have found that ultrasound-based measurements correlate with postnatal respiratory symptoms, while MRI derived O/E NFLV does not. Further studies are needed to elucidate the role of MRI in the prenatal workup of congenital lung malformations. TYPE OF STUDY: Study of Diagnostic Test. LEVEL OF EVIDENCE: Level I.

Approach to New-Onset Psychosis in Pediatrics: A Review of Current Practice and an Interdisciplinary Consensus-Driven Clinical Pathway at a Single-Center Institution.

New-onset psychosis in the pediatric population poses many diagnostic challenges. Given the diversity of underlying causes, which fall under the purview of multiple medical specialties, a timely, targeted, yet thorough workup requires a systematic and coordinated approach. A committee of expert pediatric physicians from the divisions of emergency medicine, psychiatry, neurology, hospitalist medicine, and radiology convened to create and implement a novel clinical pathway and approach to the pediatric patient presenting with new-onset psychosis. Here we provide background and review the evidence supporting the investigations recommended in our pathway to screen for a comprehensive range of etiologies of pediatric psychosis.

ID-Seg: an infant deep learning-based segmentation framework to improve limbic structure estimates.

Infant brain magnetic resonance imaging (MRI) is a promising approach for studying early neurodevelopment. However, segmenting small regions such as limbic structures is challenging due to their low inter-regional contrast and high curvature. MRI studies of the adult brain have successfully applied deep learning techniques to segment limbic structures, and similar deep learning models are being leveraged for infant studies. However, these deep learning-based infant MRI segmentation models have generally been derived from small datasets, and may suffer from generalization problems. Moreover, the accuracy of segmentations derived from these deep learning models relative to more standard Expectation-Maximization approaches has not been characterized. To address these challenges, we leveraged a large, public infant MRI dataset (n = 473) and the transfer-learning technique to first pre-train a deep convolutional neural network model on two limbic structures: amygdala and hippocampus. Then we used a leave-one-out cross-validation strategy to fine-tune the pre-trained model and evaluated it separately on two independent datasets with manual labels. We term this new approach the Infant Deep learning SEGmentation Framework (ID-Seg). ID-Seg performed well on both datasets with a mean dice similarity score (DSC) of 0.87, a mean intra-class correlation (ICC) of 0.93, and a mean average surface distance (ASD) of 0.31 mm. Compared to the Developmental Human Connectome pipeline (dHCP) pipeline, ID-Seg significantly improved segmentation accuracy. In a third infant MRI dataset (n = 50), we used ID-Seg and dHCP separately to estimate amygdala and hippocampus volumes and shapes. The estimates derived from ID-seg, relative to those from the dHCP, showed stronger associations with behavioral problems assessed in these infants at age 2. In sum, ID-Seg consistently performed well on two different datasets with an 0.87 DSC, however, multi-site testing and extension for brain regions beyond the amygdala and hippocampus are still needed.

Detailed Clinical and Psychological Phenotype of the X-linked HNRNPH2-Related Neurodevelopmental Disorder.

OBJECTIVE: To expand the clinical phenotype of the X-linked HNRNPH2-related neurodevelopmental disorder in 33 individuals. METHODS: Participants were diagnosed with pathogenic or likely pathogenic variants in HNRNPH2 using American College of Medical Genetics and Genomics/Association of Molecular Pathology criteria, largely identified via clinical exome sequencing. Genetic reports were reviewed. Clinical data were collected by retrospective chart review and caregiver report including standardized parent report measures. RESULTS: We expand our clinical characterization of HNRNPH2-related disorders to include 33 individuals, aged 2-38 years, both females and males, with 11 different de novo missense variants, most within the nuclear localization signal. The major features of the phenotype include developmental delay/intellectual disability, severe language impairment, motor problems, growth, and musculoskeletal disturbances. Minor features include dysmorphic features, epilepsy, neuropsychiatric diagnoses such as autism spectrum disorder, and cortical visual impairment. Although rare, we report early stroke and premature death with this condition. CONCLUSIONS: The spectrum of X-linked HNRNPH2-related disorders continues to expand as the allelic spectrum and identification of affected males increases.