Hydrocephalus associated with a molar tooth sign: A distinct subtype of Joubert syndrome.

Hydrocephalus is rarely described in Joubert-Boltshauser syndrome (JBTS). The aim of this study was to investigate whether this association is a chance occurrence or potentially signifies a new phenotypic subtype. The databases of Wolfson Medical Center, Sourasky Medical Center, and EB's personal collection were reviewed. Records from an additional family were obtained from RG. The patients' medical records, prenatal ultrasounds, and magnetic resonance imaging were assessed. In addition, we reviewed the medical literature for the association of ventriculomegaly/hydrocephalus (VM/HC) in JBTS. Only seven cases (from five families) were found with prenatal onset of VM/HC, diagnosed during the second trimester; three pregnancies were terminated, one was stillborn and three were born, of which one died within a week, and another died at the age of 6 years. Additional central nervous system findings included dysgenesis of the corpus callosum, delayed sulcation, polymicrogyria, and pachygyria. We found 16 publications describing 54 patients with JBTS and VM/HC: only five were diagnosed at birth and three were diagnosed prenatally. Hydrocephalus is extremely rare in JBTS. The recurrence of this association, reported in several publications in multiple family members, suggests that it might represent a new phenotypic subtype of JBTS possibly associated with specific genes or variants. Further genetic studies are needed to confirm this hypothesis.

Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.

OBJECTIVES: To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity to detect fetuses with growth restriction (FGR). METHODS: Retrospective data of 348 fetuses with gestational age (GA) of 19-39 weeks were included: 249 normal appropriate for GA (AGA), 19 FGR, and 80 Other (having various imaging abnormalities). A fetal whole-body segmentation model with a quality estimation module was developed and evaluated in 169 cases. The method was evaluated for its repeatability (repeated scans within the same scanner, n = 22), reproducibility (different scanners, n = 6), and accuracy (compared with birth weight, n = 7). A normal MRI-based growth chart was derived. RESULTS: The method achieved a Dice = 0.973, absolute volume difference ratio (VDR) = 1.8% and VDR mean difference = 0.75% ([Formula: see text]: - 3.95%, 5.46), and high agreement with the gold standard. The method achieved a repeatability coefficient = 4.01%, ICC = 0.99, high reproducibility with a mean difference = 2.21% ([Formula: see text]: - 1.92%, 6.35%), and high accuracy with a mean difference between estimated fetal weight (EFW) and birth weight of - 0.39% ([Formula: see text]: - 8.23%, 7.45%). A normal growth chart (n = 246) was consistent with four ultrasound charts. EFW based on MRI correctly predicted birth-weight percentiles for all 18 fetuses ≤ 10thpercentile and for 14 out of 17 FGR fetuses below the 3rd percentile. Six fetuses referred to MRI as AGA were found to be < 3rd percentile. CONCLUSIONS: The proposed method for automatic MRI-based EFW demonstrated high performance and sensitivity to identify FGR fetuses. CLINICAL RELEVANCE STATEMENT: Results from this study support the use of the automatic fetal weight estimation method based on MRI for the assessment of fetal development and to detect fetuses at risk for growth restriction. KEY POINTS: • An AI-based segmentation method with a quality assessment module for fetal weight estimation based on MRI was developed, achieving high repeatability, reproducibility, and accuracy. • An MRI-based fetal weight growth chart constructed from a large cohort of normal and appropriate gestational-age fetuses is proposed. • The method showed a high sensitivity for the diagnosis of small fetuses suspected of growth restriction.

Automatic Quantification of Normal Brain Gyrification Patterns and Changes in Fetuses with Polymicrogyria and Lissencephaly Based on MRI.

BACKGROUND AND PURPOSE: The current imaging assessment of fetal brain gyrification is performed qualitatively and subjectively using sonography and MR imaging. A few previous studies have suggested methods for quantification of fetal gyrification based on 3D reconstructed MR imaging, which requires unique data and is time-consuming. In this study, we aimed to develop an automatic pipeline for gyrification assessment based on routinely acquired fetal 2D MR imaging data, to quantify normal changes with gestation, and to measure differences in fetuses with lissencephaly and polymicrogyria compared with controls. MATERIALS AND METHODS: We included coronal T2-weighted MR imaging data of 162 fetuses retrospectively collected from 2 clinical sites: 134 controls, 12 with lissencephaly, 13 with polymicrogyria, and 3 with suspected lissencephaly based on sonography, yet with normal MR imaging diagnoses. Following brain segmentation, 5 gyrification parameters were calculated separately for each hemisphere on the basis of the area and ratio between the contours of the cerebrum and its convex hull. Seven machine learning classifiers were evaluated to differentiate control fetuses and fetuses with lissencephaly or polymicrogyria. RESULTS: In control fetuses, all parameters changed significantly with gestational age (P < .05). Compared with controls, fetuses with lissencephaly showed significant reductions in all gyrification parameters (P ≤ .02). Similarly, significant reductions were detected for fetuses with polymicrogyria in several parameters (P ≤ .001). The 3 suspected fetuses showed normal gyrification values, supporting the MR imaging diagnosis. An XGBoost-linear algorithm achieved the best results for classification between fetuses with lissencephaly and control fetuses (n = 32), with an area under the curve of 0.90 and a recall of 0.83. Similarly, a random forest classifier showed the best performance for classification of fetuses with polymicrogyria and control fetuses (n = 33), with an area under the curve of 0.84 and a recall of 0.62. CONCLUSIONS: This study presents a pipeline for automatic quantification of fetal brain gyrification and provides normal developmental curves from a large cohort. Our method significantly differentiated fetuses with lissencephaly and polymicrogyria, demonstrating lower gyrification values. The method can aid radiologic assessment, highlight fetuses at risk, and may improve early identification of fetuses with cortical malformations.

Fetal MRI-Based Body and Adiposity Quantification for Small for Gestational Age Perinatal Risk Stratification.

BACKGROUND: Small for gestational age (SGA) fetuses are at risk for perinatal adverse outcomes. Fetal body composition reflects the fetal nutrition status and hold promise as potential prognostic indicator. MRI quantification of fetal anthropometrics may enhance SGA risk stratification. HYPOTHESIS: Smaller, leaner fetuses are malnourished and will experience unfavorable outcomes. STUDY TYPE: Prospective. POPULATION: 40 SGA fetuses, 26 (61.9%) females: 10/40 (25%) had obstetric interventions due to non-reassuring fetal status (NRFS), and 17/40 (42.5%) experienced adverse neonatal events (CANO). Participants underwent MRI between gestational ages 30 + 2 and 37 + 2. FIELD STRENGTH/SEQUENCE: 3-T, True Fast Imaging with Steady State Free Precession (TruFISP) and T1 -weighted two-point Dixon (T1 W Dixon) sequences. ASSESSMENT: Total body volume (TBV), fat signal fraction (FSF), and the fat-to-body volumes ratio (FBVR) were extracted from TruFISP and T1 W Dixon images, and computed from automatic fetal body and subcutaneous fat segmentations by deep learning. Subjects were followed until hospital discharge, and obstetric interventions and neonatal adverse events were recorded. STATISTICAL TESTS: Univariate and multivariate logistic regressions for the association between TBV, FBVR, and FSF and interventions for NRFS and CANO. Fisher's exact test was used to measure the association between sonographic FGR criteria and perinatal outcomes. Sensitivity, specificity, positive and negative predictive values, and accuracy were calculated. A P-value <0.05 was considered statistically significant. RESULTS: FBVR (odds ratio [OR] 0.39, 95% confidence interval [CI] 0.2-0.76) and FSF (OR 0.95, CI 0.91-0.99) were linked with NRFS interventions. Furthermore, TBV (OR 0.69, CI 0.56-0.86) and FSF (OR 0.96, CI 0.93-0.99) were linked to CANO. The FBVR sensitivity/specificity for obstetric interventions was 85.7%/87.5%, and the TBV sensitivity/specificity for CANO was 82.35%/86.4%. The sonographic criteria sensitivity/specificity for obstetric interventions was 100%/33.3% and insignificant for CANO (P = 0.145). DATA CONCLUSION: Reduced TBV and FBVR may be associated with higher rates of obstetric interventions for NRFS and CANO. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 5.

Utility of genetic testing in children with leukodystrophy.

BACKGROUND: Leukodystrophies are monogenic disorders primarily affecting the white matter. We aimed to evaluate the utility of genetic testing and time-to-diagnosis in a retrospective cohort of children with suspected leukodystrophy. METHODS: Medical records of patients who attended the leukodystrophy clinic at the Dana-Dwek Children's Hospital between June 2019 and December 2021 were retrieved. Clinical, molecular, and neuroimaging data were reviewed, and the diagnostic yield was compared across genetic tests. RESULTS: Sixty-seven patients (Female/Male ratio 35/32) were included. Median age at symptom onset was 9 months (interquartile range (IQR) 3-18 months), and median length of follow-up was 4.75 years (IQR 3-8.5). Time from symptom onset to a confirmed genetic diagnosis was 15months (IQR 11-30). Pathogenic variants were identified in 60/67 (89.6%) patients; classic leukodystrophy (55/67, 82.1%), leukodystrophy mimics (5/67, 7.5%). Seven patients (10.4%) remained undiagnosed. Exome sequencing showed the highest diagnostic yield (34/41, 82.9%), followed by single-gene sequencing (13/24, 54%), targeted panels (3/9, 33.3%) and chromosomal microarray (2/25, 8%). Familial pathogenic variant testing confirmed the diagnosis in 7/7 patients. A comparison between patients who presented before (n = 31) and after (n = 21) next-generation sequencing (NGS) became clinically available in Israel revealed that the time-to-diagnosis was shorter in the latter group with a median of 12months (IQR 3.5-18.5) vs. a median of 19 months (IQR 13-51) (p = 0.005). CONCLUSIONS: NGS carries the highest diagnostic yield in children with suspected leukodystrophy. Access to advanced sequencing technologies accelerates speed to diagnosis, which is increasingly crucial as targeted treatments become available.

Reduced adipose tissue in growth-restricted fetuses using quantitative analysis of magnetic resonance images.

OBJECTIVES: Fat-water MRI can be used to quantify tissues' lipid content. We aimed to quantify fetal third trimester normal whole-body subcutaneous lipid deposition and explore differences between appropriate for gestational age (AGA), fetal growth restriction (FGR), and small for gestational age fetuses (SGAs). METHODS: We prospectively recruited women with FGR and SGA-complicated pregnancies and retrospectively recruited the AGA cohort (sonographic estimated fetal weight [EFW] ≥ 10th centile). FGR was defined using the accepted Delphi criteria, and fetuses with an EFW < 10th centile that did not meet the Delphi criteria were defined as SGA. Fat-water and anatomical images were acquired in 3 T MRI scanners. The entire fetal subcutaneous fat was semi-automatically segmented. Three adiposity parameters were calculated: fat signal fraction (FSF) and two novel parameters, i.e., fat-to-body volume ratio (FBVR) and estimated total lipid content (ETLC = FSF*FBVR). Normal lipid deposition with gestation and differences between groups were assessed. RESULTS: Thirty-seven AGA, 18 FGR, and 9 SGA pregnancies were included. All three adiposity parameters increased between 30 and 39 weeks (p < 0.001). All three adiposity parameters were significantly lower in FGR compared with AGA (p ≤ 0.001). Only ETLC and FSF were significantly lower in SGA compared with AGA using regression analysis (p = 0.018-0.036, respectively). Compared with SGA, FGR had a significantly lower FBVR (p = 0.011) with no significant differences in FSF and ETLC (p ≥ 0.053). CONCLUSIONS: Whole-body subcutaneous lipid accretion increased throughout the third trimester. Reduced lipid deposition is predominant in FGR and may be used to differentiate FGR from SGA, assess FGR severity, and study other malnourishment pathologies. CLINICAL RELEVANCE STATEMENT: Fetuses with growth restriction have reduced lipid deposition than appropriately developing fetuses measured using MRI. Reduced fat accretion is linked with worse outcomes and may be used for growth restriction risk stratification. KEY POINTS: • Fat-water MRI can be used to assess the fetal nutritional status quantitatively. • Lipid deposition increased throughout the third trimester in AGA fetuses. • FGR and SGA have reduced lipid deposition compared with AGA fetuses, more predominant in FGR.

Pediatric low-dose head CT: Image quality improvement using iterative model reconstruction.

PURPOSE: To evaluate the differences in pediatric non-contrast low-dose head computed tomography (CT) between filtered-back projection and iterative model reconstruction using objective and subjective image quality evaluation. METHODS: A retrospective study evaluated children undergoing low-dose non-contrast head CT. All CT scans were reconstructed using both filtered-back projection and iterative model reconstruction. Objective image quality analysis was performed using contrast and signal-to-noise ratios for the supra- and infratentorial brain regions of identical regions of interest on the two reconstruction methods. Two experienced pediatric neuroradiologists evaluated subjective image quality, visibility of structures, and artifacts. RESULTS: We evaluated 233 low-dose brain CT scans of 148 pediatric patients. There was a ∼2-fold improvement in the contrast-to-noise ratio between gray and white matter in the infra- and supratentorial regions (p < 0.001) using iterative model reconstruction compared to filtered-back projection. The white and gray matter signal-to-noise ratio improved more than 2-fold using iterative model reconstruction (p < 0.001). Furthermore, radiologists graded anatomical details, gray-white matter differentiation, beam hardening artifacts, and image quality using iterative model reconstructions as superior to filtered-back projection reconstructions. CONCLUSION: Iterative model reconstructions had better contrast-to-noise and signal-to-noise ratios with fewer artifacts in pediatric CT brain scans using low-dose radiation protocols. This image quality improvement was demonstrated in the supra- and infratentorial regions. This method thus comprises an important tool for reducing children's exposure while maintaining diagnostic capability.

Bi-allelic variants in the ESAM tight-junction gene cause a neurodevelopmental disorder associated with fetal intracranial hemorrhage.

The blood-brain barrier (BBB) is an essential gatekeeper for the central nervous system and incidence of neurodevelopmental disorders (NDDs) is higher in infants with a history of intracerebral hemorrhage (ICH). We discovered a rare disease trait in thirteen individuals, including four fetuses, from eight unrelated families associated with homozygous loss-of-function variant alleles of ESAM which encodes an endothelial cell adhesion molecule. The c.115del (p.Arg39Glyfs∗33) variant, identified in six individuals from four independent families of Southeastern Anatolia, severely impaired the in vitro tubulogenic process of endothelial colony-forming cells, recapitulating previous evidence in null mice, and caused lack of ESAM expression in the capillary endothelial cells of damaged brain. Affected individuals with bi-allelic ESAM variants showed profound global developmental delay/unspecified intellectual disability, epilepsy, absent or severely delayed speech, varying degrees of spasticity, ventriculomegaly, and ICH/cerebral calcifications, the latter being also observed in the fetuses. Phenotypic traits observed in individuals with bi-allelic ESAM variants overlap very closely with other known conditions characterized by endothelial dysfunction due to mutation of genes encoding tight junction molecules. Our findings emphasize the role of brain endothelial dysfunction in NDDs and contribute to the expansion of an emerging group of diseases that we propose to rename as "tightjunctionopathies."

Improved differentiation between hypo/hypertelorism and normal fetuses based on MRI using automatic ocular biometric measurements, ocular ratios, and machine learning multi-parametric classification.

OBJECTIVES: To differentiate hypo-/hypertelorism (abnormal) from normal fetuses using automatic biometric measurements and machine learning (ML) classification based on MRI. METHODS: MRI data of normal (n = 244) and abnormal (n = 52) fetuses of 22-40 weeks' gestational age (GA), scanned between March 2008 and June 2020 on 1.5/3T systems with various T2-weighted sequences and image resolutions, were included. A fully automatic method including deep learning and geometric algorithms was developed to measure the binocular (BOD), inter-ocular (IOD), ocular (OD) diameters, and ocular volume (OV). Two new parameters, BOD-ratio and IOD-ratio, were defined as the ratio between BOD/IOD relative to the sum of both globes' OD, respectively. Eight ML classifiers were evaluated to detect abnormalities using measured and computed parameters. RESULTS: The automatic method yielded a mean difference of BOD = 0.70 mm, IOD = 0.81 mm, OD = 1.00 mm, and a 3D-Dice score of OV = 93.7%. In normal fetuses, all four measurements increased with GA. Constant values were detected for BOD-ratio = 1.56 ± 0.05 and IOD-ratio = 0.60 ± 0.05 across all GA and when calculated from previously published reference data of both MRI and ultrasound. A random forest classifier yielded the best results on an independent test set (n = 58): AUC-ROC = 0.941 and F1-Score = 0.711 in comparison to AUC-ROC = 0.650 and F1-Score = 0.385 achieved based on the accepted criteria that define hypo/hypertelorism based on IOD (< 5th or > 95th percentiles). Using the explainable ML method, the two computed ratios were found as the most contributing parameters. CONCLUSIONS: The developed fully automatic method demonstrates high performance on varied clinical imaging data. The new BOD and IOD ratios and ML multi-parametric classifier are suggested to improve the differentiation of hypo-/hypertelorism from normal fetuses. KEY POINTS: • A fully automatic method for computing fetal ocular biometry from MRI is proposed, achieving high performance, comparable to that of an expert fetal neuro-radiologist. • Two new parameters, IOD-ratio and BOD-ratio, are proposed for routine clinical use in ultrasound and MRI. These two ratios are constant across gestational age in normal fetuses, consistent across studies, and differentiate between fetuses with and without hypo/hypertelorism. • Multi-parametric machine learning classification based on automatic measurements and the two new ratios improves the identification of fetal ocular anomalies beyond the accepted criteria (<5th or >95th IOD percentiles).

Radiologically isolated aquaporin-4 antibody neuromyelitis optica spectrum disorder.

Aquaporin-4 antibody (AQP4-Ab) Neuromyelitis Optica Spectrum Disorder (NMOSD) is a rare neuroinflammatory syndrome presenting predominantly with optic neuritis and transverse myelitis. We report a case of radiologically isolated longitudinally extensive optic neuritis in an asymptomatic 12-year-old female with positive serum AQP4-Ab, with resolution of imaging changes after immune therapy. By contrast to patients with radiologically isolated syndrome, of which some will never convert to multiple sclerosis, the pathogenicity of AQP4-Ab in the context of sub-clinical disease, supported treatment in our patient. Given the severe morbidity in AQP4-Ab NMOSD, prognostic biomarkers for disease severity are required to guide optimal therapy for patients.

Short and thick corpus callosum - the thin border between a minor anatomical variant to very poor outcome.

The corpus callosum (CC) is the largest commissure connecting the cerebral hemispheres. Its components are recognized sonographically at 18-20 GW and from that point forward, its growth can be assessed using nomograms for CC length and thickness according to gestational week. Prenatal diagnosis of agenesis of the CC has been reported comprehensively. On the contrary, information regarding findings as short or thick CC is very rare. Is short CC an expression of callosal dysgenesis or could it be a variant of the normal development when all its parts exist? We discuss this issue through this case report.

Prenatal diagnosis of a likely pathogenic variant in ZBTB18: Natural evolution of fetal phenotype including the long bones and corpus callosum.

Pathogenic variants in ZBTB18 gene have been described only postnatally with a variable phenotypic spectrum that includes intellectual disability, microcephaly, hypotonia, poor growth, corpus callosum abnormalities, seizures, and dysmorphic facial features. These features overlap with the phenotype of 1q43-q44 deletion syndrome (OMIM #612337). There are several genes within the 1q43-q44 deletion region, and ZBTB18 is of particular interest due to its known involvement in neuronal differentiation and migration. We describe here a fetus presenting with an intrauterine growth restriction, diminished long bones growth, single umbilical artery, and a short corpus callosum. On mid pregnancy ultrasound, all biometric parameters including the corpus callosum were relatively small but still within the normal range. Only a targeted follow-up during the third trimester, including neurosonographic and MRI exams, revealed the full extent of the malformation, leading to amniocentesis and a genetic workup that led to the identification of a de novo likely pathogenic variant in ZBTB18 gene. This is the first description of the evolving phenotype of a ZBTB18-related disorder in a fetus, which emphasizes the challenging diagnosis of subtle findings, that mandates a high level of clinical suspicion and a targeted follow-up throughout pregnancy.

Ex-Vivo MRI of the Normal Human Placenta: Structural-Functional Interplay and the Association With Birth Weight.

BACKGROUND: Advanced magnetic resonance imaging (MRI) methods are increasingly being used to assess the human placenta. Yet, the structure-function interplay in normal placentas and their associations with pregnancy risks are not fully understood. PURPOSE: To characterize the normal human placental structure (volume and umbilical cord centricity index (CI)) and function (perfusion) ex-vivo using MRI, to assess their association with birth weight (BW), and identify imaging-markers for placentas at risk for dysfunction. STUDY TYPE: Prospective. POPULATION: Twenty normal term ex-vivo placentas. FIELD STRENGTH/SEQUENCE: 3 T/ T1 and T2 weighted (T1 W, T2 W) turbo spin-echo, three-dimensional susceptibility-weighted image, and time-resolved angiography with interleaved stochastic trajectories (TWIST), during passage of a contrast agent using MRI compatible perfusion system that mimics placental flow. ASSESSMENT: Placental volume and CI were manually extracted from the T1 W images by a fetal-placental MRI scientist (D.L., 7 years of experience). Perfusion maps including bolus arrival-time and full-width at half maximum were calculated from the TWIST data. Mean values, entropy, and asymmetries were calculated from each perfusion map, relating to both the whole placenta and volumes of interest (VOIs) within the umbilical cord and its daughter blood vessels. STATISTICAL TESTS: Pearson correlations with correction for multiple comparisons using false discovery rate were performed between structural and functional parameters, and with BW, with P < 0.05 considered significant. RESULTS: All placentas were successfully perfused and scanned. Significant correlations were found between whole placenta and VOIs perfusion parameters (mean R = 0.76 ± 0.06, range = 0.67-0.89), which were also significantly correlated with CI (mean R = 0.72 ± 0.05, range = 0.65-0.79). BW was correlated with placental volume (R = 0.62), but not with CI (P = 0.40). BW was also correlated with local perfusion asymmetry (R = -0.71). DATA CONCLUSION: Results demonstrate a gradient of placental function, associated with CI and suggest several ex-vivo imaging-markers that might indicate an increased risk for placental dysfunction. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 1.

L1CAM variants cause two distinct imaging phenotypes on fetal MRI.

Data on fetal MRI in L1 syndrome are scarce with relevant implications for parental counseling and surgical planning. We identified two fetal MR imaging patterns in 10 fetuses harboring L1CAM mutations: the first, observed in 9 fetuses was characterized by callosal anomalies, diencephalosynapsis, and a distinct brainstem malformation with diencephalic-mesencephalic junction dysplasia and brainstem kinking. Cerebellar vermis hypoplasia, aqueductal stenosis, obstructive hydrocephalus, and pontine hypoplasia were variably associated. The second pattern observed in one fetus was characterized by callosal dysgenesis, reduced white matter, and pontine hypoplasia. The identification of these features should alert clinicians to offer a prenatal L1CAM testing.

Fetal and Perinatal Outcome Following First and Second Trimester COVID-19 Infection: Evidence from a Prospective Cohort Study.

A novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of coronavirus causing coronavirus disease 2019 (COVID-19) disease, which emerged as a global pandemic. Data regarding the implications of COVID-19 disease at early gestation on fetal and obstetric outcomes is scarce. Thus, our aim was to investigate the effect of first and second trimester maternal COVID-19 disease on fetal and perinatal outcomes. This was a prospective cohort study of pregnant women with a laboratory-proven SARS-COV-2 infection contracted prior to 26 weeks gestation. Women were followed at a single tertiary medical center by serial sonographic examinations every 4-6 weeks to assess fetal well-being, growth, placental function, anatomic evaluation and signs of fetal infection. Amniocentesis was offered to assess amniotic fluid SARS-COV-2-PCR (polymerase chain reaction) and fetal brain magnetic resonance imaging (MRI) was offered at 30-32 weeks gestation. Demographic, obstetric and neonatal data were collected from history intake, medical charts or by telephone survey. Perinatal outcomes were compared between women infected at first vs. second trimester. 55 women with documented COVID-19 disease at early gestation were included and followed at our center. The mean maternal age was 29.6 ± 6.2 years and the mean gestational age at viral infection was 14.2 ± 6.7 weeks with 28 (51%) women infected at the first trimester and 27 (49%) at the second trimester. All patients but one experienced asymptomatic to mild symptoms. Of 22 patients who underwent amniocentesis, none had evidence of vertical transmission. None of the fetuses exhibited signs of central nervous system (CNS) disease, growth restriction and placental dysfunction on serial ultrasound examinations and fetal MRI. Pregnancies resulted in perinatal survival of 100% to date with mean gestational age at delivery of 38.6 ± 3.0 weeks and preterm birth <37 weeks rate of 3.4%. The mean birthweight was 3260 ± 411 g with no cases of small for gestational age infants. The obstetric and neonatal outcomes were similar among first vs. second trimester infection groups. We conclude SARS-CoV-2 infection at early gestation was not associated with vertical transmission and resulted in favorable obstetric and neonatal outcomes.

Automatic linear measurements of the fetal brain on MRI with deep neural networks.

PURPOSE: Timely, accurate and reliable assessment of fetal brain development is essential to reduce short and long-term risks to fetus and mother. Fetal MRI is increasingly used for fetal brain assessment. Three key biometric linear measurements important for fetal brain evaluation are cerebral biparietal diameter (CBD), bone biparietal diameter (BBD), and trans-cerebellum diameter (TCD), obtained manually by expert radiologists on reference slices, which is time consuming and prone to human error. The aim of this study was to develop a fully automatic method computing the CBD, BBD and TCD measurements from fetal brain MRI. METHODS: The input is fetal brain MRI volumes which may include the fetal body and the mother's abdomen. The outputs are the measurement values and reference slices on which the measurements were computed. The method, which follows the manual measurements principle, consists of five stages: (1) computation of a region of interest that includes the fetal brain with an anisotropic 3D U-Net classifier; (2) reference slice selection with a convolutional neural network; (3) slice-wise fetal brain structures segmentation with a multi-class U-Net classifier; (4) computation of the fetal brain midsagittal line and fetal brain orientation, and; (5) computation of the measurements. RESULTS: Experimental results on 214 volumes for CBD, BBD and TCD measurements yielded a mean [Formula: see text] difference of 1.55 mm, 1.45 mm and 1.23 mm, respectively, and a Bland-Altman 95% confidence interval ([Formula: see text] of 3.92 mm, 3.98 mm and 2.25 mm, respectively. These results are similar to the manual inter-observer variability, and are consistent across gestational ages and brain conditions. CONCLUSIONS: The proposed automatic method for computing biometric linear measurements of the fetal brain from MR imaging achieves human-level performance. It has the potential of being a useful method for the assessment of fetal brain biometry in normal and pathological cases, and of improving routine clinical practice.

Utility of three-dimensional modeling of the fetal airway for ex utero intrapartum treatment.

Recent technological developments in three-dimensional (3D) printing have created new opportunities for applications in clinical medicine. 3D printing has been adopted for teaching and planning complicated surgeries, including maxillofacial, orthopedic reconstructions, and airway manipulation for one-lung ventilation or airway stenting. We present here the first use of such technology to print a model from in utero imaging for intrapartum treatment planning. A 32-week fetus presented with congenital high airway obstruction syndrome (CHAOS) due to a large cervical lymphatic malformation. An ex utero intrapartum treatment (EXIT) procedure was planned to allow delivery of a viable infant. We printed a 3D model of the fetal airway by printing separate elements: mandible, tongue, mass, larynx, and trachea from the fetal MRI. The elements were stuck together maintaining correct anatomical relationships. Airway planning was then performed in consultation with a pediatric ear nose and throat (ENT) surgeon. 3D modeling in utero presents many challenges: the resolution of the 3D model generated from a fetal MRI is less crisp than from CT images, fetal position may be variable and not in a defined anatomical plane, movement artifact occurs. Nevertheless, pre-procedure simulations with the aid of 3D modeling promoted team cooperation and well-prepared management of the fetus during EXIT.

White matter abnormalities and iron deposition in prenatal mucolipidosis IV- fetal imaging and pathology.

Mucolipidosis type IV (MLIV; OMIM 252,650) is an autosomal recessive lysosomal disorder caused by mutations in MCOLN1. MLIV causes psychomotor impairment and progressive vision loss. The major hallmarks of postnatal brain MRI are hypomyelination and thin corpus callosum. Human brain pathology data is scarce and demonstrates storage of various inclusion bodies in all neuronal cell types. The current study describes novel fetal brain MRI and neuropathology findings in a fetus with MLIV. Fetal MRI was performed at 32 and 35 weeks of gestation due to an older sibling with spastic quadriparesis, visual impairment and hypomyelination. Following abnormal fetal MRI results, the parents requested termination of pregnancy according to Israeli regulations. Fetal autopsy was performed after approval of the high committee for pregnancy termination. A genetic diagnosis of MLIV was established in the fetus and sibling. Sequential fetal brain MRI showed progressive curvilinear hypointensities on T2-weighted images in the frontal deep white matter and a thin corpus callosum. Fetal brain pathology exhibited a thin corpus callosum and hypercellular white matter composed of reactive astrocytes and microglia, multifocal white matter abnormalities with mineralized deposits, and numerous aggregates of microglia with focal intracellular iron accumulation most prominent in the frontal lobes. This is the first description in the literature of brain MRI and neuropathology in a fetus with MLIV. The findings demonstrate prenatal white matter involvement with significant activation of microglia and astrocytes and impaired iron metabolism.

Deletion in COL4A2 is associated with a three-generation variable phenotype: from fetal to adult manifestations.

Genetic alterations in COL4A2 are less common than those of COL4A1 and their fetal phenotype has not been described to date. We describe a three-generation family with an intragenic deletion in COL4A2 associated with a prenatal diagnosis of recurrent fetal intracerebral hemorrhage (ICH), and a myriad of cerebrovascular manifestations. Exome sequencing, co-segregation analysis, and imaging studies were conducted on eight family members including two fetuses with antenatal ICH. Histopathological evaluation was performed on the terminated fetuses. An intragenic heterozygous pathogenic in-frame deletion; COL4A2, c.4151_4168del, (p.Thr1384_Gly1389del) was identified in both fetuses, their father with hemiplegic cerebral palsy (CP), as well as other family members. Postmortem histopathological examination identified microscopic foci of heterotopias and polymicrogyria. The variant segregated in affected individuals demonstrating varying degrees of penetrance and a wide phenotypic spectrum including periventricular venous hemorrhagic infarction causing hemiplegic CP, polymicrogyria, leukoencephalopathy, and lacunar stroke. We present radiographic, pathological, and genetic evidence of prenatal ICH and show, for what we believe to be the first time, a human pathological proof of polymicrogyria and heterotopias in association with a COL4A2 disease-causing variant, while illustrating the variable phenotype and partial penetrance of this disease. We highlight the importance of genetic analysis in fetal ICH and hemiplegic CP.

MRI-based diagnosis and treatment of pediatric brain tumors: is tissue sample always needed?

Traditional management of newly diagnosed pediatric brain tumors (PBTs) consists of cranial imaging, typically magnetic resonance imaging (MRI), and is frequently followed by tissue diagnosis, through either surgical biopsy or tumor resection. Therapy regimes are typically dependent on histological diagnosis. To date, many treatment regimens are based on molecular biology. The scope of this article is to discuss the role of diagnosis and further treatment of PBTs based solely on MRI features, in light of the latest treatment protocols. Typical MRI findings and indications for surgical biopsy of these lesions are described.