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Longitudinal characterization of early brain growth in-utero has been limited by a number of challenges in fetal imaging, the rapid change in size, shape and volume of the developing brain, and the consequent lack of suitable algorithms for fetal brain image analysis. There is a need for an improved digital brain atlas of the spatiotemporal maturation of the fetal brain extending over the key developmental periods. We have developed an algorithm for construction of an unbiased four-dimensional atlas of the developing fetal brain by integrating symmetric diffeomorphic deformable registration in space with kernel regression in age. We applied this new algorithm to construct a spatiotemporal atlas from MRI of 81 normal fetuses scanned between 19 and 39 weeks of gestation and labeled the structures of the developing brain. We evaluated the use of this atlas and additional individual fetal brain MRI atlases for completely automatic multi-atlas segmentation of fetal brain MRI. The atlas is available online as a reference for anatomy and for registration and segmentation, to aid in connectivity analysis, and for groupwise and longitudinal analysis of early brain growth.

The recent development of motion robust super-resolution fetal brain MRI holds out the potential for dramatic new advances in volumetric and morphometric analysis. Volumetric analysis based on volumetric and morphometric biomarkers of the developing fetal brain must include segmentation. Automatic segmentation of fetal brain MRI is challenging, however, due to the highly variable size and shape of the developing brain; possible structural abnormalities; and the relatively poor resolution of fetal MRI scans. To overcome these limitations, we present a novel, constrained, multi-atlas, multi-shape automatic segmentation method that specifically addresses the challenge of segmenting multiple structures with similar intensity values in subjects with strong anatomic variability. Accordingly, we have applied this method to shape segmentation of normal, dilated, or fused lateral ventricles for quantitative analysis of ventriculomegaly (VM), which is a pivotal finding in the earliest stages of fetal brain development, and warrants further investigation. Utilizing these innovative techniques, we introduce novel volumetric and morphometric biomarkers of VM comparing these values to those that are generated by standard methods of VM analysis, i.e., by measuring the ventricular atrial diameter (AD) on manually selected sections of 2D ultrasound or 2D MRI. To this end, we studied 25 normal and abnormal fetuses in the gestation age (GA) range of 19 to 39weeks (mean=28.26, stdev=6.56). This heterogenous dataset was essentially used to 1) validate our segmentation method for normal and abnormal ventricles; and 2) show that the proposed biomarkers may provide improved detection of VM as compared to the AD measurement. ► We developed novel multi-atlas multi-shape fetal ventricular segmentation. ► The developed method accurately segmented normal and abnormal ventricles. ► Volumetric fetal brain MRI and automatic segmentation enabled volumetric analysis. ► We introduced novel volumetric and morphometric biomarkers of fetal ventriculomegaly. ► The new biomarkers show improvements to current analysis based on atrial diameter.

Diffusion weighted magnetic resonance imaging, or DWI, is one of the most promising tools for the analysis of neural microstructure and the structural connectome of the human brain. The application of DWI to map early development of the human connectome in-utero, however, is challenged by intermittent fetal and maternal motion that disrupts the spatial correspondence of data acquired in the relatively long DWI acquisitions. Fetuses move continuously during DWI scans. Reliable and accurate analysis of the fetal brain structural connectome requires careful compensation of motion effects and robust reconstruction to avoid introducing bias based on the degree of fetal motion. In this paper we introduce a novel robust algorithm to reconstruct in-vivo diffusion-tensor MRI (DTI) of the moving fetal brain and show its effect on structural connectivity analysis. The proposed algorithm involves multiple steps of image registration incorporating a dynamic registration-based motion tracking algorithm to restore the spatial correspondence of DWI data at the slice level and reconstruct DTI of the fetal brain in the standard (atlas) coordinate space. A weighted linear least squares approach is adapted to remove the effect of intra-slice motion and reconstruct DTI from motion-corrected data. The proposed algorithm was tested on data obtained from 21 healthy fetuses scanned in-utero at 22–38 weeks gestation. Significantly higher fractional anisotropy values in fiber-rich regions, and the analysis of whole-brain tractography and group structural connectivity, showed the efficacy of the proposed method compared to the analyses based on original data and previously proposed methods. The results of this study show that slice-level motion correction and robust reconstruction is necessary for reliable in-vivo structural connectivity analysis of the fetal brain. Connectivity analysis based on graph theoretic measures show high degree of modularity and clustering, and short average characteristic path lengths indicative of small-worldness property of the fetal brain network. These findings comply with previous findings in newborns and a recent study on fetuses. The proposed algorithm can provide valuable information from DWI of the fetal brain not available in the assessment of the original 2D slices and may be used to more reliably study the developing fetal brain connectome.

Elucidation of maternal immune correlates of protection against congenital cytomegalovirus (CMV) is necessary to inform future vaccine design. Here, we present a novel rhesus macaque model of placental rhesus CMV (rhCMV) transmission and use it to dissect determinants of protection against congenital transmission following primary maternal rhCMV infection. In this model, asymptomatic intrauterine infection was observed following i.v. rhCMV inoculation during the early second trimester in two of three rhCMV-seronegative pregnant females. In contrast, fetal loss or infant CMV-associated sequelae occurred in four rhCMV-seronegative pregnant macaques that were CD4⁺ T-cell depleted at the time of inoculation. Animals that received the CD4⁺ T-cell–depleting antibody also exhibited higher plasma and amniotic fluid viral loads, dampened virus-specific CD8⁺ T-cell responses, and delayed production of autologous neutralizing antibodies compared with immunocompetent monkeys. Thus, maternal CD4⁺ T-cell immunity during primary rhCMV infection is important for controlling maternal viremia and inducing protective immune responses that prevent severe CMV-associated fetal disease.

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

Abdominal ultrasound (AUS) is a promising adjunct to abdominal x-ray (AXR) for evaluating necrotizing enterocolitis (NEC). We developed a multivariable risk score incorporating AUS to predict surgical NEC. 83 patients were evaluated by AXR and AUS for suspected NEC. A subset had surgical NEC. Multivariate logistic regression determined predictors of surgical NEC, which were incorporated into a risk score. 14/83 patients (16.9%) had surgical NEC. 10/83 (12.0%) patients required acute intervention, while 4/83 (4.8%) patients only required delayed surgery. Four predictors of surgical NEC were identified: abdominal wall erythema (OR: 8.2, p = 0.048), portal venous gas on AXR (OR: 29.8, p = 0.014), and echogenic free fluid (OR: 17.2, p = 0.027) and bowel wall thickening (OR: 12.5, p = 0.030) on AUS. A multivariable risk score incorporating these predictors had excellent area-under-the-curve of 0.937 (95% CI: 0.879–0.994). AUS, as an adjunct to physical exam and AXR, has utility for predicting surgical NEC. [Display omitted] •This new multivariable risk score has excellent discrimination for surgical NEC.•Abdominal ultrasound has utility for predicting surgical NEC.•Abdominal wall erythema and x-ray portal venous gas are also predictors.

BackgroundLimb-length discrepancy (LLD) in children with congenital lower extremity shortening is constant in proportion from birth to skeletal maturity (known as constant inhibition), but its developmental pattern in utero is unknown. The popular prenatal multiplier method to predict LLD at birth assumes constant inhibition in utero to be true. Verifying the in utero developmental pattern of LLD, and thus confirming the validity of the prenatal multiplier method, is crucial for meaningful prenatal parental counseling.ObjectiveTo elucidate the in utero developmental pattern of LLD in fetuses with congenital lower extremity shortening.Materials and methodsClinical indications for 3,605 lower extremity radiographs performed on infants (<1 year old) at a large tertiary hospital over a 17-year period were reviewed. Inclusion criteria were (1) diagnosis of congenital lower extremity shortening, (2) bilateral lower limb postnatal radiographs documenting LLD and (3) fetal ultrasound (US) documenting LLD. Available measurements of femoral, tibial and fibular lengths on fetal US and postnatal radiographs were collected. Prenatal and postnatal length ratios of shorter-to-longer bones were calculated and compared.ResultsEighteen infants met inclusion criteria. Diagnoses were proximal focal femoral deficiency=4, congenital short femur=2, tibial hemimelia=3, posteromedial tibial bowing=6 and fibular hemimelia=3. The correlations between postnatal and prenatal length ratios were high for the femur, tibia and fibula (R>0.98, P<0.0001). The relative differences in the postnatal and prenatal length ratios of these bones were small (|average|<0.026, standard deviation <0.068).ConclusionOur data indicate that the postnatal and prenatal length ratios were equivalent, supporting the constant inhibition pattern of LLD in utero, thus validating the prenatal multiplier method for predicting LLD.

The Chiari II is a relatively common birth defect that is associated with open spinal abnormalities and is characterized by caudal migration of the posterior fossa contents through the foramen magnum. The pathophysiology of Chiari II is not entirely known, and the neurobiological substrate beyond posterior fossa findings remains unexplored. We aimed to identify brain regions altered in Chiari II fetuses between 17 and 26 GW. We used structural T2-weighted MRIs of 31 fetuses (6 controls and 25 cases with Chiari II). The results of our study indicated altered development of diencephalon and proliferative zones (ventricular and subventricular zones) in fetuses with a Chiari II malformation compared to controls. Specifically, fetuses with Chiari II showed significantly smaller volumes of the diencephalon and significantly larger volumes of lateral ventricles and proliferative zones. We conclude that regional brain development should be taken into consideration when evaluating prenatal brain development in fetuses with Chiari II.

Fetal health is critically dependent on placental function, especially placental transport of oxygen from mother to fetus. When fetal growth is compromised, placental insufficiency must be distinguished from modest genetic growth potential. If placental insufficiency is present, the physician must trade off the risk of prolonged fetal exposure to placental insufficiency against the risks of preterm delivery. Current ultrasound methods to evaluate the placenta are indirect and insensitive. We propose to use Blood-Oxygenation-Level-Dependent (BOLD) MRI with maternal hyperoxia to quantitatively assess mismatch in placental function in seven monozygotic twin pairs naturally matched for genetic growth potential. In-utero BOLD MRI time series were acquired at 29 to 34 weeks gestational age. Maps of oxygen Time-To-Plateau (TTP) were obtained in the placentas by voxel-wise fitting of the time series. Fetal brain and liver volumes were measured based on structural MR images. After delivery, birth weights were obtained and placental pathological evaluations were performed. Mean placental TTP negatively correlated with fetal liver and brain volumes at the time of MRI as well as with birth weights. Mean placental TTP positively correlated with placental pathology. This study demonstrates the potential of BOLD MRI with maternal hyperoxia to quantify regional placental function in vivo .

PurposeWe evaluated the diagnostic utility of abdominal ultrasound (AUS), an adjunct to abdominal X-ray (AXR), for necrotizing enterocolitis (NEC) in congenital heart disease (CHD) patients.Methods86 patients with suspected NEC from 2009 to 2018 were classified as with CHD (n = 18) if they required cardiac intervention versus without CHD (n = 68). Clinical and radiological data were collected, including AXR and AUS concordance. Wilcoxon rank-sum test and Fisher’s exact test were performed.ResultsCHD patients had higher birth weights (p < 0.001) and gestational ages (p < 0.001) than non-CHD patients. CHD patients presented more frequently with hypotension (p = 0.041) and less frequently with bilious emesis (p < 0.001). Overall, CHD patients were less likely to have AUS findings of pneumatosis (33.3 vs. 72.1%; p = 0.005) and decreased mural flow (0 vs. 20.6%; p = 0.035) compared to non-CHD patients. On concordance analysis, CHD patients had 3.9-fold more discordant studies with pneumatosis on AXR but not on AUS (33.3 vs. 8.8%; p = 0.016) compared to non-CHD patients. Urgent surgery was required in 5.6% of CHD patients versus 16.2% of non-CHD patients.ConclusionCHD patients with suspected NEC represent a distinct clinical population. AUS has particular utility in assessing findings of bowel viability in the CHD NEC population, reflecting reduced rates of surgical NEC.