Total and Regional Brain Volumes in Fetuses With Congenital Heart Disease.

BACKGROUND: Congenital heart disease (CHD) is common and is associated with impaired early brain development and neurodevelopmental outcomes, yet the exact mechanisms underlying these associations are unclear. PURPOSE: To utilize MRI data from a cohort of fetuses with CHD as well as typically developing fetuses to test the hypothesis that expected cerebral substrate delivery is associated with total and regional fetal brain volumes. STUDY TYPE: Retrospective case-control study. POPULATION: Three hundred eighty fetuses (188 male), comprising 45 healthy controls and 335 with isolated CHD, scanned between 29 and 37 weeks gestation. Fetuses with CHD were assigned into one of four groups based on expected cerebral substrate delivery. FIELD STRENGTH/SEQUENCE: T2-weighted single-shot fast-spin-echo sequences and a balanced steady-state free precession gradient echo sequence were obtained on a 1.5 T scanner. ASSESSMENT: Images were motion-corrected and reconstructed using an automated slice-to-volume registration reconstruction technique, before undergoing segmentation using an automated pipeline and convolutional neural network that had undergone semi-supervised training. Differences in total, regional brain (cortical gray matter, white matter, deep gray matter, cerebellum, and brainstem) and brain:body volumes were compared between groups. STATISTICAL TESTS: ANOVA was used to test for differences in brain volumes between groups, after accounting for sex and gestational age at scan. PFDR -values <0.05 were considered statistically significant. RESULTS: Total and regional brain volumes were smaller in fetuses where cerebral substrate delivery is reduced. No significant differences were observed in total or regional brain volumes between control fetuses and fetuses with CHD but normal cerebral substrate delivery (all PFDR > 0.12). Severely reduced cerebral substrate delivery is associated with lower brain:body volume ratios. DATA CONCLUSION: Total and regional brain volumes are smaller in fetuses with CHD where there is a reduction in cerebral substrate delivery, but not in those where cerebral substrate delivery is expected to be normal. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta.

Neonatal coarctation of the aorta (CoA) is a common congenital heart defect. Its antenatal diagnosis remains challenging, and its pathophysiology is poorly understood. We present a novel statistical shape modeling (SSM) pipeline to study the role and predictive value of arch shape in CoA in utero. Cardiac magnetic resonance imaging (CMR) data of 112 fetuses with suspected CoA was acquired and motion-corrected to three-dimensional volumes. Centerlines from fetal arches were extracted and used to build a statistical shape model capturing relevant anatomical variations. A linear discriminant analysis was used to find the optimal axis between CoA and false positive cases. The CoA shape risk score classified cases with an area under the curve of 0.907. We demonstrate the feasibility of applying a SSM pipeline to three-dimensional fetal CMR data while providing novel insights into the anatomical determinants of CoA and the relevance of in utero arch anatomy for antenatal diagnosis of CoA.

3D black blood cardiovascular magnetic resonance atlases of congenital aortic arch anomalies and the normal fetal heart: application to automated multi-label segmentation.

BACKGROUND: Image-domain motion correction of black-blood contrast T2-weighted fetal cardiovascular magnetic resonance imaging (CMR) using slice-to-volume registration (SVR) provides high-resolution three-dimensional (3D) images of the fetal heart providing excellent 3D visualisation of vascular anomalies [1]. However, 3D segmentation of these datasets, important for both clinical reporting and the application of advanced analysis techniques is currently a time-consuming process requiring manual input with potential for inter-user variability. METHODS: In this work, we present novel 3D fetal CMR population-averaged atlases of normal and abnormal fetal cardiovascular anatomy. The atlases are created using motion-corrected 3D reconstructed volumes of 86 third trimester fetuses (gestational age range 29-34 weeks) including: 28 healthy controls, 20 cases with postnatally confirmed neonatal coarctation of the aorta (CoA) and 38 vascular rings (21 right aortic arch (RAA), 17 double aortic arch (DAA)). We used only high image quality datasets with isolated anomalies and without any other deviations in the cardiovascular anatomy.In addition, we implemented and evaluated atlas-guided registration and deep learning (UNETR) methods for automated 3D multi-label segmentation of fetal cardiac vessels. We used images from CoA, RAA and DAA cohorts including: 42 cases for training (14 from each cohort), 3 for validation and 6 for testing. In addition, the potential limitations of the network were investigated on unseen datasets including 3 early gestational age (22 weeks) and 3 low SNR cases. RESULTS: We created four atlases representing the average anatomy of the normal fetal heart, postnatally confirmed neonatal CoA, RAA and DAA. Visual inspection was undertaken to verify expected anatomy per subgroup. The results of the multi-label cardiac vessel UNETR segmentation showed 100[Formula: see text] per-vessel detection rate for both normal and abnormal aortic arch anatomy. CONCLUSIONS: This work introduces the first set of 3D black-blood T2-weighted CMR atlases of normal and abnormal fetal cardiovascular anatomy including detailed segmentation of the major cardiovascular structures. Additionally, we demonstrated the general feasibility of using deep learning for multi-label vessel segmentation of 3D fetal CMR images.

Dynamics of T2* and deformation in the placenta and myometrium during pre-labour contractions.

Pre-labour uterine contractions, occurring throughout pregnancy, are an important phenomenon involving the placenta in addition to the myometrium. They alter the uterine environment and thus potentially the blood supply to the fetus and may thus provide crucial insights into the processes of labour. Assessment in-vivo is however restricted due to their unpredictability and the inaccessible nature of the utero-placental compartment. While clinical cardiotocography (CTG) only allows global, pressure-based assessment, functional magnetic resonance imaging (MRI) provides an opportunity to study contractile activity and its effects on the placenta and the fetus in-vivo. This study aims to provide both descriptive and quantitative structural and functional MR assessments of pre-labour contractions in the human uterus. A total of 226 MRI scans (18-41 weeks gestation) from ongoing research studies were analysed, focusing on free-breathing dynamic quantitative whole uterus dynamic T2* maps. These provide an indirect measure of tissue properties such as oxygenation. 22 contractile events were noted visually and both descriptive and quantitative analysis of the myometrial and placental changes including volumetric and T2* variations were undertaken. Processing and analysis was successfully performed, qualitative analysis shows distinct and highly dynamic contraction related characteristics including; alterations in the thickness of the low T2* in the placental bed and other myometrial areas, high intensity vessel-like structures in the myometrium, low-intensity vessel structures within the placental parenchyma and close to the chorionic plate. Quantitative evaluation shows a significant negative correlation between T2* in both contractile and not-contractile regions with gestational age (p < 0.05) as well as a significant reduction in T2* during contractions. The T2* values in the myometrium were however not correlated to gestational age (p > 0.5). The quantitative and qualitative description of uterine pre-labour contractions including dynamic changes and key characteristics aims to contribute to the sparsely available in-vivo information and to provide an in-vivo tool to study this important phenomenon. Further work is required to analyse the origins of these subclinical contractions, their effects in high-risk pregnancies and their ability to determine the likelihood of a successful labour. Assessing T2* distribution as a marker for placental oxygenation could thus potentially complement clinically used cardiotocography measurements in the future.

Automated 3D reconstruction of the fetal thorax in the standard atlas space from motion-corrupted MRI stacks for 21-36 weeks GA range.

Slice-to-volume registration (SVR) methods allow reconstruction of high-resolution 3D images from multiple motion-corrupted stacks. SVR-based pipelines have been increasingly used for motion correction for T2-weighted structural fetal MRI since they allow more informed and detailed diagnosis of brain and body anomalies including congenital heart defects (Lloyd et al., 2019). Recently, fully automated rigid SVR reconstruction of the fetal brain in the atlas space was achieved in Salehi et al. (2019) that used convolutional neural networks (CNNs) for segmentation and pose estimation. However, these CNN-based methods have not yet been applied to the fetal trunk region. Meanwhile, the existing rigid and deformable SVR (DSVR) solutions (Uus et al., 2020) for the fetal trunk region are limited by the requirement of manual input as well the narrow capture range of the classical gradient descent based registration methods that cannot resolve severe fetal motion frequently occurring at the early gestational age (GA). Furthermore, in our experience, the conventional 2D slice-wise CNN-based brain masking solutions are reportedly prone to errors that require manual corrections when applied on a wide range of acquisition protocols or abnormal cases in clinical setting. In this work, we propose a fully automated pipeline for reconstruction of the fetal thorax region for 21-36 weeks GA range T2-weighted MRI datasets. It includes 3D CNN-based intra-uterine localisation of the fetal trunk and landmark-guided pose estimation steps that allow automated DSVR reconstruction in the standard radiological space irrespective of the fetal trunk position or the regional stack coverage. The additional step for generation of the common template space and rejection of outliers provides the means for automated exclusion of stacks affected by low image quality or extreme motion. The pipeline was quantitatively evaluated on a series of experiments including fetal MRI datasets and simulated rotation motion. Furthermore, we performed a qualitative assessment of the image reconstruction quality in terms of the definition of vascular structures on 100 early (median 23.14 weeks) and late (median 31.79 weeks) GA group MRI datasets covering 21 to 36 weeks GA range.

Structured analysis of the impact of fetal motion on phase-contrast MRI flow measurements with metric optimized gating.

The impact of fetal motion on phase contrast magnetic resonance imaging (PC-MRI) with metric optimized gating (MOG) remains unknown, despite being a known limitation to prenatal MRI. This study aims to describe the effect of motion on fetal flow-measurements using PC-MRI with MOG and to generate a scoring-system that could be used to predict motion-corrupted datasets at the time of acquisition. Ten adult volunteers underwent PC-MRI with MOG using a motion-device to simulate reproducible in-plane motion encountered in fetuses. PC-MRI data were acquired on ten fetuses. All ungated images were rated on their quality from 0 (no motion) to 2 (severe motion). There was no significant difference in measured flows with in-plane motion during the first and last third of sequence acquisition. Movement in the middle section of acquisition produced a significant difference while all referring ungated images were rated with a score of 2. Intra-Class-Correlation (ICC) for flow-measurements in adult and fetal datasets was lower for datasets with scores of 2. For fetal applications, the use of a simple three-point scoring system reliably identifies motion-corrupted sequences from unprocessed data at the time of acquisition, with a high score corresponding to significant underestimation of flow values and increased interobserver variability.

T2* placental MRI in pregnancies complicated with fetal congenital heart disease.

BACKGROUND: Congenital heart disease (CHD) is one of the most important and common group of congenital malformations in humans. Concurrent development and close functional links between the fetal heart and placenta emphasise the importance of understanding placental function and its influence in pregnancy outcomes. The aim of this study was to evaluate placental oxygenation by relaxometry (T2*) to assess differences in placental phenotype and function in CHD. METHODS: In this prospective cross-sectional observational study, 69 women with a fetus affected with CHD and 37 controls, whole placental T2* was acquired using a 1.5-Tesla MRI scanner. Gaussian Process Regression was used to assess differences in placental phenotype in CHD cohorts compared to our controls. RESULTS: Placental T2* maps demonstrated significant differences in CHD compared to controls at equivalent gestational age. Mean T2* values over the entire placental volume were lowest compared to predicted normal in right sided obstructive lesions (RSOL) (Z-Score 2.30). This cohort also showed highest lacunarity indices (Z-score -1.7), as a marker of lobule size. Distribution patterns of T2* values over the entire placental volume were positively skewed in RSOL (Z-score -4.69) and suspected, not confirmed coarctation of the aorta (CoA-) (Z-score -3.83). Deviations were also reflected in positive kurtosis in RSOL (Z-score -3.47) and CoA- (Z-score -2.86). CONCLUSION: Placental structure and function appear to deviate from normal development in pregnancies with fetal CHD. Specific patterns of altered placental function assessed by T2* deliver crucial complementary information to antenatal assessments in the presence of fetal CHD.

Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts.

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

Heterogeneity in Brain Microstructural Development Following Preterm Birth.

Preterm-born children are at increased risk of lifelong neurodevelopmental difficulties. Group-wise analyses of magnetic resonance imaging show many differences between preterm- and term-born infants but do not reliably predict neurocognitive prognosis for individual infants. This might be due to the unrecognized heterogeneity of cerebral injury within the preterm group. This study aimed to determine whether atypical brain microstructural development following preterm birth is significantly variable between infants. Using Gaussian process regression, a technique that allows a single-individual inference, we characterized typical variation of brain microstructure using maps of fractional anisotropy and mean diffusivity in a sample of 270 term-born neonates. Then, we compared 82 preterm infants to these normative values to identify brain regions with atypical microstructure and relate observed deviations to degree of prematurity and neurocognition at 18 months. Preterm infants showed strikingly heterogeneous deviations from typical development, with little spatial overlap between infants. Greater and more extensive deviations, captured by a whole brain atypicality index, were associated with more extreme prematurity and predicted poorer cognitive and language abilities at 18 months. Brain microstructural development after preterm birth is highly variable between individual infants. This poorly understood heterogeneity likely relates to both the etiology and prognosis of brain injury.

Modelling brain development to detect white matter injury in term and preterm born neonates.

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

Foetal lung volumes in pregnant women who deliver very preterm: a pilot study.

BACKGROUND: Infants born preterm are at increased risk of pulmonary morbidity. The contribution of antenatal factors to impairments in lung structure/function has not been fully elucidated. This study aimed to compare standardized lung volumes from foetuses that were delivered <32 weeks' gestation with foetuses that were delivered >37 weeks. METHODS: Fourteen women who delivered <32 weeks gestation and 56 women who delivered >37 underwent a foetal MRI. Slice-volume reconstruction was then used and the foetal lungs were then segmented using multi-atlas approaches. Body volumes were calculated by manual segmentation and lung:body volume ratios generated. RESULTS: Mean gestation at MRI of the preterm group was 27+2 weeks (SD 2.9, range 20+6-31+3) and control group 25+3 weeks (SD 4.7 range 20+5-31+6). Mean gestation at delivery of the preterm group was 29+2 weeks (SD 2.6, range 22+0-32+0). Lung:body volume ratios and foetal lung volumes were smaller in foetuses that were delivered preterm both with and without preterm premature rupture of membranes compared to those born at term (p < 0.001 in all cases). CONCLUSIONS: Foetuses that were delivered very preterm had reduced lung volumes when standardized for foetal size, irrespective of ruptured membranes. These are novel findings and suggest an antenatal aetiology of insult and possible focus for future preventative therapies.

Neuroimaging findings in newborns with congenital heart disease prior to surgery: an observational study.

OBJECTIVES: Neurodevelopmental impairment has become the most important comorbidity in infants with congenital heart disease (CHD). We aimed to (1) investigate the burden of brain lesions in infants with CHD prior to surgery and (2) explore clinical factors associated with injury. STUDY DESIGN: Prospective observational study. SETTING: Single centre UK tertiary neonatal intensive care unit. PATIENTS: 70 newborn infants with critical or serious CHD underwent brain MRI prior to surgery. MAIN OUTCOME MEASURES: Prevalence of cerebral injury including arterial ischaemic strokes (AIS), white matter injury (WMI) and intracranial haemorrhage. RESULTS: Brain lesions were observed in 39% of subjects (95% CI 28% to 50%). WMI was identified in 33% (95% CI 23% to 45%), subdural haemorrhage without mass effect in 33% (95% CI 23% to 45%), cerebellar haemorrhage in 9% (95% CI 4% to 18%) and AIS in 4% (95% CI 1.5% to 12%). WMI was distributed widely throughout the brain, particularly involving the frontal white matter, optic radiations and corona radiata. WMI exhibited restricted diffusion in 48% of cases. AIS was only observed in infants with transposition of the great arteries (TGA) who had previously undergone balloon atrial septostomy (BAS). AIS was identified in 23% (95% CI 8% to 50%) of infants with TGA who underwent BAS, compared with 0% (95% CI 0% to 20%) who did not. CONCLUSIONS: Cerebral injury in newborns with CHD prior to surgery is common.

Abnormal Microstructural Development of the Cerebral Cortex in Neonates With Congenital Heart Disease Is Associated With Impaired Cerebral Oxygen Delivery.

Background Abnormal macrostructural development of the cerebral cortex has been associated with hypoxia in infants with congenital heart disease ( CHD ). Animal studies have suggested that hypoxia results in cortical dysmaturation at the cellular level. New magnetic resonance imaging techniques offer the potential to investigate the relationship between cerebral oxygen delivery and cortical microstructural development in newborn infants with CHD . Methods and Results We measured cortical macrostructural and microstructural properties in 48 newborn infants with serious or critical CHD and 48 age-matched healthy controls. Cortical volume and gyrification index were calculated from high-resolution structural magnetic resonance imaging. Neurite density and orientation dispersion indices were modeled using high-angular-resolution diffusion magnetic resonance imaging. Cerebral oxygen delivery was estimated in infants with CHD using phase contrast magnetic resonance imaging and preductal pulse oximetry. We used gray matter-based spatial statistics to examine voxel-wise group differences in cortical microstructure. Microstructural development of the cortex was abnormal in 48 infants with CHD , with regions of increased fractional anisotropy and reduced orientation dispersion index compared with 48 healthy controls, correcting for gestational age at birth and scan (family-wise error corrected for multiple comparisons at P<0.05). Regions of reduced cortical orientation dispersion index in infants with CHD were related to impaired cerebral oxygen delivery ( R2=0.637; n=39). Cortical orientation dispersion index was associated with the gyrification index ( R2=0.589; P<0.001; n=48). Conclusions This study suggests that the primary component of cerebral cortex dysmaturation in CHD is impaired dendritic arborization, which may underlie abnormal macrostructural findings reported in this population, and that the degree of impairment is related to reduced cerebral oxygen delivery.

Impaired development of the cerebral cortex in infants with congenital heart disease is correlated to reduced cerebral oxygen delivery.

Neurodevelopmental impairment is the most common comorbidity associated with complex congenital heart disease (CHD), while the underlying biological mechanism remains unclear. We hypothesised that impaired cerebral oxygen delivery in infants with CHD is a cause of impaired cortical development, and predicted that cardiac lesions most associated with reduced cerebral oxygen delivery would demonstrate the greatest impairment of cortical development. We compared 30 newborns with complex CHD prior to surgery and 30 age-matched healthy controls using brain MRI. The cortex was assessed using high resolution, motion-corrected T2-weighted images in natural sleep, analysed using an automated pipeline. Cerebral oxygen delivery was calculated using phase contrast angiography and pre-ductal pulse oximetry, while regional cerebral oxygen saturation was estimated using near-infrared spectroscopy. We found that impaired cortical grey matter volume and gyrification index in newborns with complex CHD was linearly related to reduced cerebral oxygen delivery, and that cardiac lesions associated with the lowest cerebral oxygen delivery were associated with the greatest impairment of cortical development. These findings suggest that strategies to improve cerebral oxygen delivery may help reduce brain dysmaturation in newborns with CHD, and may be most relevant for children with CHD whose cardiac defects remain unrepaired for prolonged periods after birth.