Fetal MRI: An approach to practice: A review

Examining Craniofacial and Velopharyngeal Structures in Premature Infants: A Window Into the Womb

BACKGROUND

Very little is known about how the velopharynx and levator veli palatini muscle develop in utero. The purpose of this study was to describe craniofacial, velopharyngeal, and levator veli palatini dimensions in a group of infants born prematurely and imaged before 40 weeks gestation.

METHODS

A retrospective, descriptive study design was utilized to examine the MRI scans of 6 infants less than 40 weeks' gestation. Imaging was initially completed for medically necessity and pulled from patients' charts retrospectively for the purpose of this study. Craniofacial, velopharyngeal, and levator veli palatini dimensions were analyzed.

RESULTS

All linear measures were consistently shorter across all variable categories. While effective VP ratio was less favorable for speech in infants under 40 weeks' gestation, angle measures such as LVP angle of origin, NSB angle, SNA angle, and SNB angle were relatively unchanged.

CONCLUSIONS

Linear craniofacial, VP, and LVP variables tend to be smaller in infants under 40 weeks' gestation than those reported within the first 6 months of life while angulation is relatively similar. Future research in this area may be relevant to better diagnosis of craniofacial conditions in utero.

Diagnostic magnetic resonance imaging characteristics of congenital mesoblastic nephroma: a retrospective multi-center International Society of Pediatric Oncology-Renal Tumor Study Group (SIOP-RTSG) radiology panel study

BACKGROUND

Congenital mesoblastic nephroma is the most common solid renal tumor in neonates. Therefore, patients <3 months of age are advised to undergo upfront nephrectomy, whereas invasive procedures at diagnosis in patients ≥3 months of age are discouraged by the International Society of Pediatric Oncology-Renal Tumor Study Group (SIOP-RTSG). Nevertheless, discriminating congenital mesoblastic nephroma, especially from the more common Wilms tumor, solely based on imaging remains difficult. Recently, magnetic resonance imaging (MRI) has become the preferred modality. Studies focusing on MRI characteristics of congenital mesoblastic nephroma are limited.

OBJECTIVE

This study aims to identify diagnostic MRI characteristics of congenital mesoblastic nephroma in the largest series of patients to date.

MATERIALS AND METHODS

In this retrospective multicenter study, five SIOP-RTSG national review radiologists identified 52 diagnostic MRIs of histologically proven congenital mesoblastic nephromas. MRI was performed following SIOP-RTSG protocols, while radiologists assessed their national cases using a validated case report form.

RESULTS

Patients (24/52 classic, 11/52 cellular, and 15/52 mixed type congenital mesoblastic nephroma, 2/52 unknown) had a median age of 1 month (range 1 day-3 months). Classic type congenital mesoblastic nephroma appeared homogeneous with a lack of hemorrhage, necrosis and/or cysts, showing a concentric ring sign in 14 (58.3%) patients. Cellular and mixed type congenital mesoblastic nephroma appeared more heterogeneous and were larger (311.6 and 174.2 cm3, respectively, versus 41.0 cm3 for the classic type (P<0.001)). All cases were predominantly T2-weighted isointense and T1-weighted hypointense, and mean overall apparent diffusion coefficient values ranged from 1.05-1.10×10-3 mm2/s.

CONCLUSION

This retrospective international collaborative study showed classic type congenital mesoblastic nephroma predominantly presented as a homogeneous T2-weighted isointense mass with a typical concentric ring sign, whereas the cellular type appeared more heterogeneous. Future studies may use identified MRI characteristic of congenital mesoblastic nephroma for validation and for exploring the discriminative non-invasive value of MRI, especially from Wilms tumor.

PDFF-CNN: An attention-guided dynamic multi-orientation feature fusion method for gestational age prediction on imbalanced fetal brain MRI dataset

BACKGROUND

Fetal brain magnetic resonance imaging (MRI)-based gestational age prediction has been widely used to characterize normal fetal brain development and diagnose congenital brain malformations.

PURPOSE

The uncertainty of fetal position and external interference leads to variable localization and direction of the fetal brain. In addition, pregnant women typically concentrate on receiving MRI scans during the fetal anomaly scanning week, leading to an imbalanced distribution of fetal brain MRI data. The above-mentioned problems pose great challenges for deep learning-based fetal brain MRI gestational age prediction.

METHODS

In this study, a pyramid squeeze attention (PSA)-guided dynamic feature fusion CNN (PDFF-CNN) is proposed to robustly predict gestational ages from fetal brain MRI images on an imbalanced dataset. PDFF-CNN contains four components: transformation module, feature extraction module, dynamic feature fusion module, and balanced mean square error (MSE) loss. The transformation and feature extraction modules are employed by using the PSA to learn multiscale and multi-orientation feature representations in a parallel weight-sharing Siamese network. The dynamic feature fusion module automatically learns the weights of feature vectors generated in the feature extraction module to dynamically fuse multiscale and multi-orientation brain sulci and gyri features. Considering the fact of the imbalanced dataset, the balanced MSE loss is used to mitigate the negative impact of imbalanced data distribution on gestational age prediction performance.

RESULTS

Evaluated on an imbalanced fetal brain MRI dataset of 1327 routine clinical T2-weighted MRI images from 157 subjects, PDFF-CNN achieved promising gestational age prediction performance with an overall mean absolute error of 0.848 weeks and anR 2 $R^2$ of 0.904. Furthermore, the attention activation maps of PDFF-CNN were derived, which revealed regional features that contributed to gestational age prediction at each gestational stage.

CONCLUSIONS

These results suggest that the proposed PDFF-CNN might have broad clinical applicability in guiding treatment interventions and delivery planning, which has the potential to be helpful with prenatal diagnosis.

A joint brain extraction and image quality assessment framework for fetal brain MRI slices

Brain extraction and image quality assessment are two fundamental steps in fetal brain magnetic resonance imaging (MRI) 3D reconstruction and quantification. However, the randomness of fetal position and orientation, the variability of fetal brain morphology, maternal organs around the fetus, and the scarcity of data samples, all add excessive noise and impose a great challenge to automated brain extraction and quality assessment of fetal MRI slices. Conventionally, brain extraction and quality assessment are typically performed independently. However, both of them focus on the brain image representation, so they can be jointly optimized to ensure the network learns more effective features and avoid overfitting. To this end, we propose a novel two-stage dual-task deep learning framework with a brain localization stage and a dual-task stage for joint brain extraction and quality assessment of fetal MRI slices. Specifically, the dual-task module compactly contains a feature extraction module, a quality assessment head and a segmentation head with feature fusion for simultaneous brain extraction and quality assessment. Besides, a transformer architecture is introduced into the feature extraction module and the segmentation head. We utilize a multi-step training strategy to guarantee a stable and successful training of all modules. Finally, we validate our method by a 5-fold cross-validation and ablation study on a dataset with fetal brain MRI slices in different qualities, and perform a cross-dataset validation in addition. Experiments show that the proposed framework achieves very promising performance.

Navigating the path of TOF- A Literature review unveiling maternal-fetal dynamics, treatment strategies and psychological dimensions

Tetralogy of Fallot (TOF) is a complex congenital heart defect that poses unique challenges for both mothers and their unborn children. This comprehensive review, aims to provide a holistic exploration of the maternal-fetal dynamics, treatment strategies, and psychological dimensions involved in navigating the path of TOF during pregnancy. It delves into the physiological changes that occur during pregnancy in TOF patients, including pulmonary regurgitation, right ventricular hypertrophy, and the overriding aorta. By understanding these dynamics, healthcare professionals can tailor treatment strategies to optimize maternal and fetal outcomes. The review further investigates the treatment strategies employed in managing TOF during pregnancy, encompassing medical interventions, cardiac monitoring, and multidisciplinary care. It explores the role of advanced imaging techniques, such as echocardiography and cardiac magnetic resonance imaging, in assessing TOF severity and guiding treatment decisions. The psychological factors influencing maternal adaptation, coping strategies, and the long-term implications on the child's psychological development are also examined. The integration of multidisciplinary approaches, including cardiac care, psychosocial support, and mental health interventions, can orchestrate a harmonious symphony of maternal-fetal well-being in the challenging journey of TOF pregnancies. Future research endeavours should continue to explore these dimensions, further refining treatment strategies and enhancing the understanding of TOF pregnancies for improved outcomes.

Fetal monitoring technologies for the detection of intrapartum hypoxia - challenges and opportunities

Intrapartum fetal hypoxia is related to long-term morbidity and mortality of the fetus and the mother. Fetal surveillance is extremely important to minimize the adverse outcomes arising from fetal hypoxia during labour. Several methods have been used in current clinical practice to monitor fetal well-being. For instance, biophysical technologies including cardiotocography, ST-analysis adjunct to cardiotocography, and Doppler ultrasound are used for intrapartum fetal monitoring. However, these technologies result in a high false-positive rate and increased obstetric interventions during labour. Alternatively, biochemical-based technologies including fetal scalp blood sampling and fetal pulse oximetry are used to identify metabolic acidosis and oxygen deprivation resulting from fetal hypoxia. These technologies neither improve clinical outcomes nor reduce unnecessary interventions during labour. Also, there is a need to link the physiological changes during fetal hypoxia to fetal monitoring technologies. The objective of this article is to assess the clinical background of fetal hypoxia and to review existing monitoring technologies for the detection and monitoring of fetal hypoxia. A comprehensive review has been made to predict fetal hypoxia using computational and machine-learning algorithms. The detection of more specific biomarkers or new sensing technologies is also reviewed which may help in the enhancement of the reliability of continuous fetal monitoring and may result in the accurate detection of intrapartum fetal hypoxia.

Safety of Magnetic Resonance Imaging in Pregnancy

Magnetic resonance imaging is being increasingly used to diagnose and follow up a variety of medical conditions in pregnancy, both for maternal and fetal indications. However, limited data regarding its safe use in pregnancy may be a source of anxiety and avoidance for both patients and their healthcare providers. In this review, we critically discuss the main safety concerns of Magnetic Resonance Imaging (MRI) in pregnancy including energy deposition, acoustic noise, and use of contrast agents, supported by data from animal and human studies. Use of maternal sedatives and concerns related to occupational exposure in pregnant personnel are also addressed. Exposure to gadolinium-based contrast agents and sedation for MRI during pregnancy should be avoided whenever feasible.

Automatic Ventriculomegaly Detection in Fetal Brain MRI: A Step-by-Step Deep Learning Model for Novel 2D-3D Linear Measurements

In this study, we developed an automated workflow using a deep learning model (DL) to measure the lateral ventricle linearly in fetal brain MRI, which are subsequently classified into normal or ventriculomegaly, defined as a diameter wider than 10 mm at the level of the thalamus and choroid plexus. To accomplish this, we first trained a UNet-based deep learning model to segment the brain of a fetus into seven different tissue categories using a public dataset (FeTA 2022) consisting of fetal T2-weighted images. Then, an automatic workflow was developed to perform lateral ventricle measurement at the level of the thalamus and choroid plexus. The test dataset included 22 cases of normal and abnormal T2-weighted fetal brain MRIs. Measurements performed by our AI model were compared with manual measurements performed by a general radiologist and a neuroradiologist. The AI model correctly classified 95% of fetal brain MRI cases into normal or ventriculomegaly. It could measure the lateral ventricle diameter in 95% of cases with less than a 1.7 mm error. The average difference between measurements was 0.90 mm in AI vs. general radiologists and 0.82 mm in AI vs. neuroradiologists, which are comparable to the difference between the two radiologists, 0.51 mm. In addition, the AI model also enabled the researchers to create 3D-reconstructed images, which better represent real anatomy than 2D images. When a manual measurement is performed, it could also provide both the right and left ventricles in just one cut, instead of two. The measurement difference between the general radiologist and the algorithm (p = 0.9827), and between the neuroradiologist and the algorithm (p = 0.2378), was not statistically significant. In contrast, the difference between general radiologists vs. neuroradiologists was statistically significant (p = 0.0043). To the best of our knowledge, this is the first study that performs 2D linear measurement of ventriculomegaly with a 3D model based on an artificial intelligence approach. The paper presents a step-by-step approach for designing an AI model based on several radiological criteria. Overall, this study showed that AI can automatically calculate the lateral ventricle in fetal brain MRIs and accurately classify them as abnormal or normal.

Establishing and Comparing the Normal apparent Diffusion Coefficient Values of Fetal Organs and Placenta Using 1.5 Tesla and 3.0 T MRI at Various Gestational Age

Background

Diffusion-weighted imaging (DWI) is the random Brownian motion of water molecules within a tissue voxel. The apparent diffusion coefficient (ADC) is a quantitative parameter calculated from the DWI that directly reflects the mobility of water molecules in biological tissues. The objective of this study was to establish and compare the normal reference ADC values of fetal organs and the placenta using 1.5 T and 3.0 T MRI at various gestational ages.

Methods

This was a retrospective and prospective observational study. This study included one hundred and three (103) singleton pregnancies for each magnetic field strength. Diffusion-weighted imaging was performed using single-shot spin-echo-planar imaging (EPI) in the axial plane of the fetal head-trunk with a slice thickness of 4mm and diffusion gradient values of b = 0 and b = 700-800 s/mm2.

Results

The mean ADC values of cerebral WM areas were significantly higher than the deep grey areas in the brain. The white-matter regions, lung, and placenta showed a positive and significant correlation with increasing gestational age in both field strengths. A statistically weak negative correlation was observed between increasing gestational age and ADC measurements obtained in the thalamus, cerebellum, pons, and kidney.

Conclusion

This study gives the reference values for both 1.5T and 3T MRI of vital organs. The current study shows that diffusion-weighted MRI can offer a promising technique to evaluate the structural development of fetal organs and can potentially act as a biomarker for predicting the functionality of the fetal organs in abnormalities.

Low-field 0.55 T MRI evaluation of the fetus

Fetal magnetic resonance imaging (MRI) is an important adjunct modality for the evaluation of fetal abnormalities. Recently, low-field MRI systems at 0.55 Tesla have become available which can produce images on par with 1.5 Tesla systems but with lower power deposition, acoustic noise, and artifact. In this article, we describe a technical innovation using low-field MRI to perform diagnostic quality fetal MRI.

Focused Abbreviated Survey MRI Protocols for Brain and Spine Imaging

There has been extensive growth in both the technical development and the clinical applications of MRI, establishing this modality as one of the most powerful diagnostic imaging tools. However, long examination and image interpretation times still limit the application of MRI, especially in emergent clinical settings. Rapid and abbreviated MRI protocols have been developed as alternatives to standard MRI, with reduced imaging times, and in some cases limited numbers of sequences, to more efficiently answer specific clinical questions. A group of rapid MRI protocols used at the authors' institution, referred to as FAST (focused abbreviated survey techniques), are designed to include or exclude emergent or urgent conditions or screen for specific entities. These FAST protocols provide adequate diagnostic image quality with use of accelerated approaches to produce imaging studies faster than traditional methods. FAST protocols have become critical diagnostic screening tools at the authors' institution, allowing confident and efficient confirmation or exclusion of actionable findings. The techniques commonly used to reduce imaging times, the imaging protocols used at the authors' institution, and future directions in FAST imaging are reviewed to provide a practical and comprehensive overview of FAST MRI for practicing neuroradiologists. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

NeSVoR: Implicit Neural Representation for Slice-to-Volume Reconstruction in MRI

Reconstructing 3D MR volumes from multiple motion-corrupted stacks of 2D slices has shown promise in imaging of moving subjects, e. g., fetal MRI. However, existing slice-to-volume reconstruction methods are time-consuming, especially when a high-resolution volume is desired. Moreover, they are still vulnerable to severe subject motion and when image artifacts are present in acquired slices. In this work, we present NeSVoR, a resolution-agnostic slice-to-volume reconstruction method, which models the underlying volume as a continuous function of spatial coordinates with implicit neural representation. To improve robustness to subject motion and other image artifacts, we adopt a continuous and comprehensive slice acquisition model that takes into account rigid inter-slice motion, point spread function, and bias fields. NeSVoR also estimates pixel-wise and slice-wise variances of image noise and enables removal of outliers during reconstruction and visualization of uncertainty. Extensive experiments are performed on both simulated and in vivo data to evaluate the proposed method. Results show that NeSVoR achieves state-of-the-art reconstruction quality while providing two to ten-fold acceleration in reconstruction times over the state-of-the-art algorithms.

Quantitative measurements and morphological evaluation of fetal cardiovascular structures with fetal cardiac MRI

PURPOSE

Fetal cardiac magnetic resonance imaging (FCMR) can be used as an imaging modality in fetal cardiovascular evaluation as studied in recent years. We aimed to evaluate cardiovascular morphology using FCMR and to observe the development of cardiovascular structures according to gestational age (GA) in pregnant women.

METHOD

In our prospective study, 120 pregnant women between 19 and 37 weeks of gestation in whom absence of cardiac anomaly could not be excluded by ultrasonography (US) or, who were referred to us for magnetic resonance imaging (MRI) for suspected non-cardiovascular system pathology, were included. According to the axis of the fetal heart, axial, coronal, and sagittal multiplanar steady-state free precession (SSFP) and 'real time' untriggered SSFP sequence, respectively, were obtained. The morphology of the cardiovascular structures and their relationships with each other were evaluated, and their sizes were measured.

RESULTS

Seven cases (6.3%) contained motion artefacts that did not allow the assessment and measurement of cardiovascular morphology, and three (2.9%) cases with cardiac pathology in the analysed images were excluded from the study. The study included a total of 100 cases. Cardiac chamber diameter, heart diameter, heart length, heart area, thoracic diameter, and thoracic area were measured in all fetuses. The diameters of the aorta ascendens (Aa), aortic isthmus (Ai), aorta descendens (Ad), main pulmonary artery (MPA), ductus arteriosus (DA, superior vena cava (SVC), and inferior vena cava (IVC) were measured in all fetuses. The left pulmonary artery (LPA) was visualised in 89 patients (89%). The right PA (RPA) was visualised in 99 (99%) cases. Four pulmonary veins (PVs) were seen in 49 (49%) cases, three in 33 (33%), and two in 18 (18%). High correlation values were found for all diameter measurements performed with GW.

CONCLUSION

In cases where US cannot achieve adequate image quality, FCMR can contribute to diagnosis. The very short acquisition time and parallel imaging technique with the SSFP sequence allow for adequate image quality without maternal or fetal sedation.

Longitudinal MRI Evaluation of Brain Development in Fetuses with Congenital Diaphragmatic Hernia around the Time of Fetal Endotracheal Occlusion

BACKGROUND AND PURPOSE

Congenital diaphragmatic hernia is associated with high mortality and morbidity, including evidence suggesting neurodevelopmental comorbidities after birth. The aim of this study was to document longitudinal changes in brain biometry and the cortical folding pattern in fetuses with congenital diaphragmatic hernia compared with healthy fetuses.

MATERIALS AND METHODS

This is a retrospective cohort study including fetuses with isolated congenital diaphragmatic hernia between January 2007 and May 2019, with at least 2 MR imaging examinations. For controls, we used images from fetuses who underwent MR imaging for an unrelated condition that did not compromise fetal brain development and fetuses from healthy pregnant women. Biometric measurements and 3D segmentations of brain structures were used as well as qualitative and quantitative grading of the supratentorial brain. Brain development was correlated with disease-severity markers.

RESULTS

Forty-two fetuses were included, with a mean gestational age at first MR imaging of 28.0 (SD, 2.1) weeks and 33.2 (SD, 1.3) weeks at the second imaging. The mean gestational age in controls was 30.7 (SD, 4.2) weeks. At 28 weeks, fetuses with congenital diaphragmatic hernia had abnormal qualitative and quantitative maturation, more extra-axial fluid, and larger total skull volume. By 33 weeks, qualitative grading scores were still abnormal, but quantitative scoring was in the normal range. In contrast, the extra-axial fluid volume remained abnormal with increased ventricular volume. Normal brain parenchymal volumes were found.

CONCLUSIONS

Brain development in fetuses with congenital diaphragmatic hernia around 28 weeks appears to be delayed. This feature is less prominent at 33 weeks. At this stage, there was also an increase in ventricular and extra-axial space volume.

Fet-Net Algorithm for Automatic Detection of Fetal Orientation in Fetal MRI

Identifying fetal orientation is essential for determining the mode of delivery and for sequence planning in fetal magnetic resonance imaging (MRI). This manuscript describes a deep learning algorithm named Fet-Net, composed of convolutional neural networks (CNNs), which allows for the automatic detection of fetal orientation from a two-dimensional (2D) MRI slice. The architecture consists of four convolutional layers, which feed into a simple artificial neural network. Compared with eleven other prominent CNNs (different versions of ResNet, VGG, Xception, and Inception), Fet-Net has fewer architectural layers and parameters. From 144 3D MRI datasets indicative of vertex, breech, oblique and transverse fetal orientations, 6120 2D MRI slices were extracted to train, validate and test Fet-Net. Despite its simpler architecture, Fet-Net demonstrated an average accuracy and F1 score of 97.68% and a loss of 0.06828 on the 6120 2D MRI slices during a 5-fold cross-validation experiment. This architecture outperformed all eleven prominent architectures (p < 0.05). An ablation study proved each component's statistical significance and contribution to Fet-Net's performance. Fet-Net demonstrated robustness in classification accuracy even when noise was introduced to the images, outperforming eight of the 11 prominent architectures. Fet-Net's ability to automatically detect fetal orientation can profoundly decrease the time required for fetal MRI acquisition.

Imaging fetal anatomy

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.

A comparison of the accuracy of fetal magnetic resonance imaging and ultrasonography for the diagnosis of fetal congenital malformations of the spine and spinal cord

PURPOSE

To determine the diagnostic value of fetal magnetic resonance imaging (MRI) for congenital spine/spinal cord malformations.

METHODS

This single-center retrospective study included 120 cases of fetal spine/spinal cord abnormalities detected using fetal ultrasonography (US) and further examined by fetal MRI between 2016 and 2020. Cases were divided into three groups (congenital spine, spinal cord, and spine + spinal cord malformations) based on US assessment. We analyzed the accuracy of fetal US and MRI relative to postnatal imaging.

RESULTS

The diagnostic accuracy of fetal MRI for fetal spinal cord, spine, and spine + spinal cord malformations was 86.2% (25/29), 89.4% (42/47), and 86.3% (38/44), respectively, and the corresponding rates for fetal US were 51.7% (15/29), 87.2% (41/47), and 68.2% (30/44). The diagnostic accuracy did not differ between fetal MRI and US for congenital spine malformations (P > 0.05); for congenital spinal cord malformations and congenital spine+spinal cord malformations, the diagnostic accuracy was significantly higher for fetal MRI than for fetal US (P < 0.05).

CONCLUSIONS

Fetal MRI is effective in the assessment of congenital spine/spinal cord malformations. It can yield information that supplements US findings, especially for congenital spinal cord malformations, and can improve the accuracy of fetal diagnosis. This article is protected by copyright. All rights reserved.

Attention-guided deep learning for gestational age prediction using fetal brain MRI

Magnetic resonance imaging offers unrivaled visualization of the fetal brain, forming the basis for establishing age-specific morphologic milestones. However, gauging age-appropriate neural development remains a difficult task due to the constantly changing appearance of the fetal brain, variable image quality, and frequent motion artifacts. Here we present an end-to-end, attention-guided deep learning model that predicts gestational age with R² score of 0.945, mean absolute error of 6.7 days, and concordance correlation coefficient of 0.970. The convolutional neural network was trained on a heterogeneous dataset of 741 developmentally normal fetal brain images ranging from 19 to 39 weeks in gestational age. We also demonstrate model performance and generalizability using independent datasets from four academic institutions across the U.S. and Turkey with R² scores of 0.81–0.90 after minimal fine-tuning. The proposed regression algorithm provides an automated machine-enabled tool with the potential to better characterize in utero neurodevelopment and guide real-time gestational age estimation after the first trimester.

Optimization of the image contrast for the developing fetal brain using 3D radial VIBE sequence in 3 T magnetic resonance imaging

Background

Faster and motion robust magnetic resonance imaging (MRI) sequences are desirable in fetal brain MRI. T1-weighted images are essential for evaluating fetal brain development. We optimized the radial volumetric interpolated breath-hold examination (VIBE) sequence for qualitative T1-weighted images of the fetal brain with improved image contrast and reduced motion sensitivity.

Materials and methods

This was an institutional review board-approved prospective study. Thirty-five pregnant subjects underwent fetal brain scan at 3 Tesla MRI. T1-weighted images were acquired using a 3D radial VIBE sequence with flip angles of 6º, 9º, 12º, and 15º. T1-weighted images of Cartesian VIBE sequence were acquired in three of the subjects. Qualitative assessments including image quality and motion artifact severity were evaluated. The image contrast ratio between gray and white matter were measured. Interobserver reliability and intraobserver repeatability were assessed using intraclass correlation coefficient (ICC).

Results

Interobserver reliability and intraobserver repeatability universally revealed almost perfect agreement (ICC > 0.800). Significant differences in image quality were detected in basal ganglia (P = 0.023), central sulcus (P = 0.028), myelination (P = 0.007) and gray matter (P = 0.023) among radial VIBE with flip angles 6º, 9º, 12º, 15º. Image quality at the 9º flip angle in radial VIBE was generally better than flip angle of 15º. Radial VIBE sequence with 9º flip angle of gray matter was significantly different by gestational age (GA) before and after 28 weeks (P = 0.036). Quantified image contrast was significantly different among different flip angles, consistent with qualitative analysis of image quality.

Conclusions

Three-dimensional radial VIBE with 9º flip angle provides optimal, stable T1-weighted images of the fetal brain. Fetal brain structure and development can be evaluated using high-quality images obtained using this angle. However, different scanners will achieve different TRs and so the FA should be re-optimized each time a new protocol is employed.

Cellular congenital mesoblastic nephroma detected by prenatal MRI: a case report and literature review

Congenital mesoblastic nephroma (CMN) is a rare tumor, yet it is the most frequently diagnosed renal neoplasm in the first 3 months of life. CMN reports with prenatal magnetic resonance imaging (MRI) are scarce. Our aims were to describe a case with fetal MR imaging along with other findings, and to review the literature concerned with prenatal MRI detection of CMN. Upon routine ultrasound (US) examination of a 36-week pregnant woman, a fetal abdominal mass was disclosed. Prenatal MRI revealed a large, well-circumscribed renal mass of solid and cystic components, not invading the adjacent tissues, but compressing normal renal parenchyma of the lower pole of the left kidney. Thus, a low malignant renal tumor was considered. After Cesarean delivery, imaging including US and computerized tomography (CT) scan was performed on the apparently healthy boy and verified the prenatal MRI finding. Accordingly, left nephrectomy was performed at the age of 12 days. The pathology confirmed CT results of the solid and cystic components of the mass, in addition to the necrotic and hemorrhagic constitution. Cellular CMN was diagnosed, and ETV6 gene rearrangement was demonstrated by FISH analysis. No recurrence was detected within the 40 months follow-up after the operation. Our report described a rare and seldomly detected renal tumor in utero with the aid of MRI and reviewed the few related reports in the literature in which MRI was performed prenatally. This report also highlights the need for prenatal MRI as a complementary tool to US in cases with suspected fetal renal mass and recommends its use for carefully managing the possible risks during the perinatal period.

The role of magnetic resonance imaging in the diagnosis and prognostic evaluation of fetuses with congenital diaphragmatic hernia

In recent years, magnetic resonance imaging (MRI) has largely increased our knowledge and predictive accuracy of congenital diaphragmatic hernia (CDH) in the fetus. Thanks to its technical advantages, better anatomical definition, and superiority in fetal lung volume estimation, fetal MRI has been demonstrated to be superior to 2D and 3D ultrasound alone in CDH diagnosis and outcome prediction. This is of crucial importance for prenatal counseling, risk stratification, and decision-making approach. Furthermore, several quantitative and qualitative parameters can be evaluated simultaneously, which have been associated with survival, postnatal course severity, and long-term morbidity.

CONCLUSION

Fetal MRI will further strengthen its role in the near future, but it is necessary to reach a consensus on indications, methodology, and data interpretation. In addition, it is required data integration from different imaging modalities and clinical courses, especially for predicting postnatal pulmonary hypertension. This would lead to a comprehensive prognostic assessment.

WHAT IS KNOWN

• MRI plays a key role in evaluating the fetal lung in patients with CDH. • Prognostic assessment of CDH is challenging, and advanced imaging is crucial for a complete prenatal assessment and counseling.

WHAT IS NEW

• Fetal MRI has strengthened its role over ultrasound due to its technical advantages, better anatomical definition, superior fetal lung volume estimation, and outcome prediction. • Imaging and clinical data integration is the most desirable strategy and may provide new MRI applications and future research opportunities.

Ex utero intrapartum technique (EXIT): Indications, procedure methods and materno-fetal complications - A literature review

A congenital malformation of the head, neck or thorax can lead to upper airway compression with a risk of asphyxia or neonatal death. To secure and protect the upper airway, the Ex Utero Intrapartum Therapy (EXIT) procedure has been developed. The procedure allows delivery of the fetus via a hysterotomy while relying on the placenta as the organ of respiration for the fetus prior to clamping of the umbilical cord. A high level of expertise is necessary for successful completion of the EXIT procedure, which is not void of maternal and fetal risks. In this literature review, we present the indications, procedure methods and materno-fetal complications associated with the EXIT procedure.

STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning

Fetal motion is unpredictable and rapid on the scale of conventional MR scan times. Therefore, dynamic fetal MRI, which aims at capturing fetal motion and dynamics of fetal function, is limited to fast imaging techniques with compromises in image quality and resolution. Super-resolution for dynamic fetal MRI is still a challenge, especially when multi-oriented stacks of image slices for oversampling are not available and high temporal resolution for recording the dynamics of the fetus or placenta is desired. Further, fetal motion makes it difficult to acquire high-resolution images for supervised learning methods. To address this problem, in this work, we propose STRESS (Spatio-Temporal Resolution Enhancement with Simulated Scans), a self-supervised super-resolution framework for dynamic fetal MRI with interleaved slice acquisitions. Our proposed method simulates an interleaved slice acquisition along the high-resolution axis on the originally acquired data to generate pairs of low- and high-resolution images. Then, it trains a super-resolution network by exploiting both spatial and temporal correlations in the MR time series, which is used to enhance the resolution of the original data. Evaluations on both simulated and in utero data show that our proposed method outperforms other self-supervised super-resolution methods and improves image quality, which is beneficial to other downstream tasks and evaluations.

Rapid head-pose detection for automated slice prescription of fetal-brain MRI

In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical assessment. As motion limits acquisitions to thick slices that preclude retrospective resampling, technologists repeat ~55-second stack-of-slices scans (HASTE) with incrementally reoriented field of view numerous times, deducing the head pose from previous stacks. To address this inefficient workflow, we propose a robust head-pose detection algorithm using full-uterus scout scans (EPI) which take ~5 seconds to acquire. Our ~2-second procedure automatically locates the fetal brain and eyes, which we derive from maximally stable extremal regions (MSERs). The success rate of the method exceeds 94% in the third trimester, outperforming a trained technologist by up to 20%. The pipeline may be used to automatically orient the anatomical sequence, removing the need to estimate the head pose from 2D views and reducing delays during which motion can occur.

Fetal brain issues in congenital heart disease

Following the improvements in the clinical management of patients with congenital heart disease (CHD) and their increased survival, neurodevelopmental outcome has become an emerging priority in pediatric cardiology. Large-scale efforts have been made to protect the brain during the postnatal, surgical, and postoperative period; however, the presence of brain immaturity and injury at birth suggests in utero and peripartum disturbances. Over the past decade, there has been considerable interest and investigations on fetal brain growth in the setting of CHD. Advancements in fetal brain imaging have identified abnormal brain development in fetuses with CHD from the macrostructural (brain volumes and cortical folding) down to the microstructural (biochemistry and water diffusivity) scale, with more severe forms of CHD showing worse disturbances and brain abnormalities starting as early as the first trimester. Anomalies in common genetic developmental pathways and diminished cerebral substrate delivery secondary to altered cardiovascular physiology are the forefront hypotheses, but other factors such as impaired placental function and maternal psychological stress have surfaced as important contributors to fetal brain immaturity in CHD. The characterization and timing of fetal brain disturbances and their associated mechanisms are important steps for determining preventative prenatal interventions, which may provide a stronger foundation for the developing brain during childhood.

T2*-weighted MRI produces viable fetal "Black-Bone" contrast with significant benefits when compared to current sequences

OBJECTIVES

Fetal "black bone" MRI could be useful in the diagnosis of various skeletal conditions during pregnancy without exposure to ionizing radiation. Previously suggested susceptibility-weighted imaging (SWI) is not available in the suggested form on all scanners leading to long imaging times that are susceptible to motion artefacts. We aimed to assess if an optimized T2*-weighted GRE sequence can provide viable "black bone" contrast and compared it to other sequences in the literature.

METHODS

A retrospective study was conducted on 17 patients who underwent fetal MRI. Patients were imaged with an optimized T2*-weighted GRE sequence, as well as at least one other "black-bone" sequence. Image quality was scored by four blinded observers on a five-point scale.

RESULTS

The T2*-weighted GRE sequence offered adequate to excellent image quality in 63% of cases and scored consistently higher than the three other comparison sequences when comparing images from the same patient. Image quality was found to be dependent on gestational age with good image quality achieved on almost all patients after 26 weeks.

CONCLUSIONS

T2*-weighted GRE imaging can provide adequate fetal "black bone" contrast and performs at least as well as other sequences in the literature due to good bone to soft tissue contrast and minimal motion artefacts.

ADVANCES IN KNOWLEDGE

T2*-weighted fetal "black-bone" imaging can provide excellent bone to soft tissue contrast without using ionizing radiation. It is as good as other "black bone" sequences and may be simpler and more widely implemented, with less motion artefacts.

Data Quality Assessment for Super-Resolution Fetal Brain MR Imaging: A Retrospective 1.5 T Study

BACKGROUND

Super-resolution is a promising technique to create isotropic image volumes from stacks of two-dimensional (2D) motion-corrupted images in fetal magnetic resonance imaging (MRI).

PURPOSE

To determine an acquisition quality metric and correlate that metric with radiologist perception of three-dimensional (3D) image quality.

STUDY TYPE

Retrospective.

SUBJECTS

Eighty-seven patients, mean gestational age 29 ± 6 weeks.

FIELD STRENGTH/SEQUENCE

1.5 T/2D fast spin-echo.

ASSESSMENT

Four radiologists (L.G., D.M.E.B., P.C., and J.V.; 31, 21, 7, and 7 years' experience, respectively) graded reconstructions on a 0 to 4 scale for overall appearance and visibility of specific anatomy. During reconstruction, slices were labeled as inliers based on correlation between a simulated vs. actual acquisition. The fraction of brain voxels in inlier slicers vs. total brain voxels was measured for each acquisition.

STATISTICAL TESTS

Paired sample t test, Pearson's correlation, intra-class correlation.

RESULTS

The average brain mask inlier fraction for all acquisitions was 0.8. There was a statistically significant correlation (0.71) between overall reconstruction appearance and number of acquisitions with inlier fraction above 0.73. There was low correlation (0.21, P = 0.05) between the number of acquisitions used in the reconstruction and overall score when no data quality measure was considered. Similar results were found for ratings of specific anatomy. Statistically significant differences in overall perception of image quality were found when using three vs. four, four vs. five, and three vs. five high-quality acquisitions in the reconstruction. Five high-quality acquisitions were sufficient to yield an average radiologist rating of 3.59 out of 4.0 for overall image quality.

DATA CONCLUSION

Reconstruction quality can be reliably predicted using the brain mask inlier fraction. Real-time super-resolution protocols could exploit this to terminate acquisition when enough high-quality acquisitions have been collected. To achieve consistent 3D image quality it may be necessary to acquire more than five scans to compensate for severely motion-corrupted acquisitions.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: 1.

Image Quality Assessment of Fetal Brain MRI Using Multi-Instance Deep Learning Methods

BACKGROUND

Due to random motion of fetuses and maternal respirations, image quality of fetal brain MRIs varies considerably. To address this issue, visual inspection of the images is performed during acquisition phase and after 3D-reconstruction, and the images are re-acquired if they are deemed to be of insufficient quality. However, this process is time-consuming and subjective. Multi-instance (MI) deep learning methods (DLMs) may perform this task automatically.

PURPOSE

To propose an MI count-based DLM (MI-CB-DLM), an MI vote-based DLM (MI-VB-DLM), and an MI feature-embedding DLM (MI-FE-DLM) for automatic assessment of 3D fetal-brain MR image quality. To quantify influence of fetal gestational age (GA) on DLM performance.

STUDY TYPE

Retrospective.

SUBJECTS

Two hundred and seventy-one MR exams from 211 fetuses (mean GA ± SD = 30.9 ± 5.5 weeks).

FIELD STRENGTH/SEQUENCE

T₂ -weighted single-shot fast spin-echo acquired at 1.5 T.

ASSESSMENT

The T₂ -weighted images were reconstructed in 3D. Then, two fetal neuroradiologists, a clinical neuroscientist, and a fetal MRI technician independently labeled the reconstructed images as 1 or 0 based on image quality (1 = high; 0 = low). These labels were fused and served as ground truth. The proposed DLMs were trained and evaluated using three repeated 10-fold cross-validations (training and validation sets of 244 and 27 scans). To quantify GA influence, this variable was included as an input of the DLMs.

STATISTICAL TESTS

DLM performance was evaluated using precision, recall, F-score, accuracy, and AUC values.

RESULTS

Precision, recall, F-score, accuracy, and AUC averaged over the three cross validations were 0.85 ± 0.01, 0.85 ± 0.01, 0.85 ± 0.01, 0.85 ± 0.01, 0.93 ± 0.01, for MI-CB-DLM (without GA); 0.75 ± 0.03, 0.75 ± 0.03, 0.75 ± 0.03, 0.75 ± 0.03, 0.81 ± 0.03, for MI-VB-DLM (without GA); 0.81 ± 0.01, 0.81 ± 0.01, 0.81 ± 0.01, 0.81 ± 0.01, 0.89 ± 0.01, for MI-FE-DLM (without GA); and 0.86 ± 0.01, 0.86 ± 0.01, 0.86 ± 0.01, 0.86 ± 0.01, 0.93 ± 0.01, for MI-CB-DLM with GA.

DATA CONCLUSION

MI-CB-DLM performed better than other DLMs. Including GA as an input of MI-CB-DLM improved its performance. MI-CB-DLM may potentially be used to objectively and rapidly assess fetal MR image quality.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 3.

Fetal Hepatomegaly: Causes and Associations

Fetal hepatomegaly is associated with significant fetal morbidity and mortality. However, hepatomegaly might be overlooked when numerous other fetal anomalies are present, or it might not be noticed when it is an isolated entity. As the largest solid organ in the abdomen, the liver can be seen well with US or MRI, and the normal imaging characteristics are well described. The length of the fetal liver, which can be used to identify hepatomegaly, can be determined by measuring the liver from the diaphragm to the tip of the right lobe in the sagittal plane. Fetal hepatomegaly is seen with infection, transient abnormal myelopoiesis, liver storage and deposition diseases, some syndromes, large liver tumors, biliary atresia, and anemia. Some of these diagnoses are treatable during the fetal period. Attention to the associated findings and specific hepatic and nonhepatic imaging characteristics can help facilitate more accurate diagnoses and appropriate patient counseling.^©RSNA, 2020.

Update on fetal cardiovascular magnetic resonance and utility in congenital heart disease

Background

Congenital heart disease (CHD) is the most common birth defect, affecting approximately eight per thousand newborns. Between one and two neonates per thousand have congenital cardiac lesions that require immediate post-natal treatment to stabilize the circulation, and the management of these patients in particular has been greatly enhanced by prenatal detection. The antenatal diagnosis of CHD has been made possible through the development of fetal echocardiography, which provides excellent visualization of cardiac anatomy and physiology and is widely available. However, late gestational fetal echocardiographic imaging can be hampered by suboptimal sonographic windows, particularly in the setting of oligohydramnios or adverse maternal body habitus.

Main body

Recent advances in fetal cardiovascular magnetic resonance (CMR) technology now provide a feasible alternative that could be helpful when echocardiography is inconclusive or limited. Fetal CMR has also been used to study fetal circulatory physiology in human fetuses with CHD, providing new insights into how these common anatomical abnormalities impact the distribution of blood flow and oxygen across the fetal circulation. In combination with conventional fetal and neonatal magnetic resonance imaging (MRI) techniques, fetal CMR can be used to explore the relationship between abnormal cardiovascular physiology and fetal development. Similarly, fetal CMR has been successfully applied in large animal models of the human fetal circulation, aiding in the evaluation of experimental interventions aimed at improving in utero development. With the advent of accelerated image acquisition techniques, post-processing approaches to correcting motion artifacts and commercial MRI compatible cardiotocography units for acquiring gated fetal cardiac imaging, an increasing number of CMR methods including angiography, ventricular volumetry, and the quantification of vessel blood flow and oxygen content are now possible.

Conclusion

Fetal CMR has reached an exciting stage whereby it may now be used to enhance the assessment of cardiac morphology and fetal hemodynamics in the setting of prenatal CHD.

The use of FIESTA sequence MRI in successful management of abdominal pregnancy

Identification of fetal location and its relations to abdominal organs is extremely important in reducing fetal and maternal morbidity in rare cases of abdominal pregnancy. Ultrasound examination is inadequate for helping to successfully manage such cases. In this case report, FIESTA sequence MRI is used to provide high-resolution, better contrast, and higher signal-to-noise ratio fetal and abdominal images. A case of advanced abdominal pregnancy with a live fetus is reported. The surgery was conducted successfully on 34 weeks of gestation.

Current ideas about the roles of rapid eye movement and non-rapid eye movement sleep in brain development

Understanding the links between sleep and brain development is important, as rapid eye movement (REM) sleep and non-REM (NREM) sleep seem to contribute to different aspects of brain maturation. If children have sleep problems, REM sleep and NREM sleep are likely to have different consequences for their developing brain, depending on their age. We highlight important discoveries from human and animal research on the role sleep plays in brain development. A hypothetical model is presented to explain the dynamic relationship of REM sleep and NREM sleep with different processes of brain maturation, with implications for current neonatal care and future research.

How to read a fetal magnetic resonance image 101

Accurate antenatal diagnosis is essential for planning appropriate pregnancy management and improving perinatal outcomes. The provision of information vital for prognostication is a crucial component of prenatal imaging, and this can be enhanced by the use of fetal MRI. Image acquisition, interpretation and reporting of a fetal MR study can be daunting to the individual who has encountered few or none of these examinations. This article provides the radiology trainee with a general approach to interpreting a fetal MRI. The authors review the added value of prenatal MRI in the overall assessment of fetal wellbeing, discuss MRI protocols and techniques, and review the normal appearance of maternal and fetal anatomy. The paper concludes with a sample template for structured reporting, to serve as a checklist and guideline for reporting radiologists.

Neuroimaging in tuberous sclerosis complex

INTRODUCTION

Tuberous sclerosis complex (TSC) is a rare autosomal dominant disorder affecting multiple systems, due to inactivating mutations of TSC1 or TSC2 mTOR pathway genes. Neurological manifestations are observed in about 95% cases, representing the most frequent cause of morbidity and one of the most common causes of mortality.

BACKGROUND

Neuroimaging is crucial for early diagnosis, monitoring, and management of these patients. While computed tomography is generally used as first-line investigation at emergency department, magnetic resonance imaging is the reference method to define central nervous system involvement and investigate subtle pathophysiological alterations in TSC patients.

PURPOSE

Here, we review the state-of-the-art knowledge in TSC brain imaging, describing conventional findings and depicting the role of advanced techniques in providing new insights on the disease, also offering an overview on future perspectives of neuroimaging applications for a better understanding of disease pathophysiology.

Spotlight on the pediatric eye: a pictorial review of orbital anatomy and congenital orbital pathologies

Orbital lesions in the pediatric population vary from adults in terms of their presentation, unique pathology, and imaging characteristics. The prompt and accurate diagnosis of these lesions is imperative to prevent serious consequences in terms of visual impairment and disfigurement. Along with dedicated ophthalmologic examination, imaging is instrumental in characterizing these lesions, both for accurate diagnosis and subsequent management. In our pictorial essay, we provide a basic review of orbital embryology, anatomy, and congenital orbital pathologies, with emphasis on radiological findings.

Prenatal diagnosis of congenital anomalies of genito-urinary system on fetal magnetic resonance imaging

Background

The aim of this study is to elucidate the spectrum of commonly encountered anomalies affecting fetal genito-urinary system (GUS) on fetal MRI and examine its utility in providing better morphological information resulting in improved diagnostic accuracy and in detecting additional malformations. The study also aims to highlight the promising role of fetal MRI in the detection and characterization of renal fusion anomalies like the horseshoe kidney or developmental abnormalities such as renal agenesis/ectopia.

Results

The mean age of study participants was 29 years ± 3 years. The gestation age of pregnant mothers ranged from 18 weeks and 1 day to 39 weeks and 0 day. Amniotic fluid was reduced or absent in 41% (N = 13) and normal in 59% (N = 18) of participating mothers. Overall, urinary obstruction was the commonest anomaly encountered (29%) followed by the multicystic dysplastic kidney (MCDK) (22%). Bilateral renal disease was seen in all mothers having features of anhydramnios {B/L MCDK (N = 3), autosomal recessive polycystic kidney disease (ARPKD) (N = 2), posterior urethral valves (PUV) (N = 2), B/L renal agenesis (N = 3), and megacystis (N = 1)}. Fusion anomalies (horseshoe kidney) and rotation anomaly (malrotation) were detected in one case each. Additional extrarenal findings were seen on fetal MRI in 35% (N = 11) cases.

Conclusions

Fetal MRI improves diagnostic accuracy in anomalies affecting the fetal kidney and genito-urinary systems by better morphological delineation. It has the ability to detect additional extra-renal malformations and perform a more accurate assessment of associated pulmonary hypoplasia. The diffusion-weighted sequence is particularly useful in confirming the diagnosis of renal agenesis/ectopia.

Fetal cardiac MRI: a single center experience over 14-years on the potential utility as an adjunct to fetal technically inadequate echocardiography

Unlike ultrasound (US) imaging, foetal magnetic resonance imaging (MRI) is not significantly limited by maternal obesity, oligohydramnios, uterine myoma, twins, and foetal lie, which impair US visualization of the foetus. The present study aimed to introduce our foetal cardiac MRI scanning technology and over 14-years of experience on the potential utility of foetal cardiac MRI examination as an adjunct to foetal technically inadequate echocardiography (Echo). This retrospective review included 1,573 pregnant women [1,619 foetuses (46 twins)] referred for a foetal cardiac MRI because of technically limited Echo. Foetal cardiac MRI was performed using two 1.5 T units. Among the 1,619 foetuses referred for cardiac MRI, 1,379 (85.2%) cases were followed up using postnatal imaging and/or surgery, 240 (14.8%), including three twins, had no follow-up confirmation because of pregnancy termination without autopsy or loss to follow-up. The results of the present study indicated that foetal cardiac MRI examinations can be a useful adjunct to foetal echocardiography when the technical limitations of echocardiography make it inadequate for diagnosis.

Genetic diagnoses and associated anomalies in fetuses prenatally diagnosed with esophageal atresia

Esophageal atresia (EA) is a congenital anomaly occurring in 2.3 per 10,000 live births. Due to advances in prenatal imaging, EA is more readily diagnosed, but data on the associated genetic diagnoses, other anomalies, and postnatal outcome for fetuses diagnosed prenatally with EA are scarce. We collected data from two academic medical centers (n = 61). Our data included fetuses with suspected EA on prenatal imaging that was confirmed postnatally and had at least one genetic test. In our cohort of 61 cases, 29 (49%) were born prematurely and 19% of those born alive died in the first 9 years of life. The most commonly associated birth defects were cardiac anomalies (67%) and spine anomalies (50%). A diagnosis was made in 61% of the cases; the most common diagnoses were vertebral defects, anal atresia, cardiac anomalies, tracheoesophageal fistula with esophageal atresia, radial or renal dysplasia, and limb anomalies association (43%, although 12% met only 2 of the criteria), trisomy 21 (5%), and CHARGE syndrome (5%). Our findings suggest that most fetuses with prenatally diagnosed EA have one or more additional major anomaly that warrants a more comprehensive clinical genetics evaluation. Fetuses diagnosed prenatally appear to represent a cohort with a worse outcome.

Preoperative Evaluation of Craniopagus Twins: Anatomy, Imaging Techniques, and Surgical Management

Craniopagus twins are a rare congenital malformation in which twins are conjoined at the head. Although there is high prenatal and postnatal mortality for craniopagus twins, successful separation has become more common due to advances in neuroimaging, neuroanesthesia, and neurosurgical techniques. Joined brain tissue, shared arteries and veins, and defects in the skull and dura make surgery technically challenging, and neuroimaging plays an important role in preoperative planning. Drawing on our experience from consultation for multiple successful separations of craniopagus twins, we discuss what radiologists need to know about the anatomy, classification, imaging techniques, and surgical management of craniopagus twins.

Prenatal diagnosis of central nervous system abnormalities: Neurosonography versus fetal magnetic resonance imaging

OBJECTIVE

To share our experience in diagnosis of congenital central nervous system (CNS) abnormalities by fetal magnetic resonance imaging (MRI).

STUDY DESIGN

This study consisted of 110 pregnancies. Neurosonography (NS) findings were compared with MRI results. Anomalies were categorized into 10 groups: 1) Corpus callosum (CC) and cavum septum pellucidum (CSP) anomalies, 2) Neural tube defects (NTD), 3) Posterior fossa anomalies (PFA), 4) Primary ventriculomegaly (PVM), 5) Microcephaly, 6) Macrocephaly, 7) Periventricular leukomalacia (PVL), 8) Craniosynostosis, 9) Intracranial hemorrhage (ICH) and 10) Lumbosacral teratoma. Demographic features, clinical characteristics and perinatal outcomes of the study subjects were evaluated.

RESULTS

Gestational weeks for NS and for MRI were 25.5 and 26.5 weeks, respectively. Fourteen (12.7%) pregnancies were terminated. PVM (n = 36, 32.7%), CC and CSP anomalies (n = 29, 26.3%), PFA (n = 11, 10%) and NTD (n = 11, 10%) were the most common fetal MRI indications. There were no statistically significant differences between the accuracy of fetal NS and fetal MRI for CC and CSP anomalies, NTDs, PFA and PVM (p = 0.09, 0.43, 0.45 and 0.23, respectively). However, fetal MRI was more accurate for the detection of normal anatomic findings in cases with suspected microcephaly, macrocephaly and craniosynostosis in NS when pooled together (p = 0.007). Furthermore, MRI also seemed to be advantageous in CC & CSP anomalies though it was not validated by statistical measures. No statistically significant difference was found for diagnostic performance of NS and MRI according to gestational week (p = 0.27).

CONCLUSION

Fetal MRI in addition to NS may improve diagnostic accuracy in pregnancies with congenital CNS abnormalities.

The prevalence and the adding value of fetal MRI imaging in midline cerebral anomalies

Background

Foetal MR imaging is widely accepted as an adjunct to foetal ultrasonography; however, there are many controversies regarding its importance and indications. Therefore, this study aimed to evaluate foetuses with different midline cerebral abnormalities, to determine the prevalence of these anomalies, to define the role of foetal MRI, and to compare MRI and ultrasound (US) result with postnatal MRI findings. Seventy-eight pregnant women who had foetuses with CNS abnormalities detected by sonogram were included. Foetuses with midline anomalies were selected and evaluated by anomaly scan foetal US, pre- and postnatal MRI.

Results

Midline brain anomalies were found in 47.4% of foetuses with brain anomalies. Holoprosencephaly was found in 24.3% of midline anomaly foetuses, corpus callosum abnormalities (ACC) were detected in 40.5%, midline intracranial mass lesions in 2.7%, and midline posterior fossa anomalies in 32.4%. An agreement between MRI and US in the main diagnosis was in 56.76% of cases; MRI added information to US findings in 43.2% of cases, and US added information to MRI findings in 8.1% of cases.

Conclusion

In evaluating midline cerebral anomalies, US and MRI are complementary techniques. US is the primary survey, and MRI can add additional information and/or change the main diagnosis.

An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI

High-resolution volume reconstruction from multiple motion-corrupted stacks of 2D slices plays an increasing role for fetal brain Magnetic Resonance Imaging (MRI) studies. Currently existing reconstruction methods are time-consuming and often require user interactions to localize and extract the brain from several stacks of 2D slices. We propose a fully automatic framework for fetal brain reconstruction that consists of four stages: 1) fetal brain localization based on a coarse segmentation by a Convolutional Neural Network (CNN), 2) fine segmentation by another CNN trained with a multi-scale loss function, 3) novel, single-parameter outlier-robust super-resolution reconstruction, and 4) fast and automatic high-resolution visualization in standard anatomical space suitable for pathological brains. We validated our framework with images from fetuses with normal brains and with variable degrees of ventriculomegaly associated with open spina bifida, a congenital malformation affecting also the brain. Experiments show that each step of our proposed pipeline outperforms state-of-the-art methods in both segmentation and reconstruction comparisons including expert-reader quality assessments. The reconstruction results of our proposed method compare favorably with those obtained by manual, labor-intensive brain segmentation, which unlocks the potential use of automatic fetal brain reconstruction studies in clinical practice.

Preliminary Experience Using Motion Compensated CINE Magnetic Resonance Imaging to Visualise Fetal Congenital Heart Disease

BACKGROUND

Recent advances in cardiovascular magnetic resonance (CMR) imaging have facilitated CINE imaging of the fetal heart. In this work, a preliminary investigation of the utility of multislice CINE CMR for assessing fetal congenital heart disease is performed and compared with echocardiography.

METHODS AND RESULTS

Multislice CINE CMR and echocardiography images were acquired in 25 pregnant women wherein the fetus had a suspected congenital heart defect based on routine obstetric ultrasound. Pathognomonic images were identified for each subject for qualitative comparison of CMR and echocardiography. Quantitative comparison of CMR and echocardiography was then performed by 2 reviewers using a binary scoring of 9 fetal cardiac anatomic features (identifiable/not-identifiable). Pathognomonic images demonstrated the ability of CMR to visualize a variety of congenital heart defects. Overall CMR was able to identify the majority of the 9 assessed fetal cardiac anatomic features (reviewer 1, 7.1±2.1; reviewer 2, 6.7±2.3). Although both reviewers identified more anatomic features with echocardiography (reviewer 1, 7.8±2.3; reviewer 2, 7.5±2.4; P=0.01), combining information from both modalities enabled identification of additional anatomic features across subjects (reviewer 1, 8.4±1.3; reviewer 2, 8.4±1.2). The primary limiting factor for CMR was inadequate coverage of the fetal cardiac anatomy or noncontiguous slices because of gross fetal movement.

CONCLUSIONS

CINE CMR enables visualization of fetal congenital heart disease. This work demonstrates the potential of CMR for diagnosing congenital heart disease in utero in conjunction with echocardiography during late gestation.

A simulation study on the effect of optimized high permittivity materials on fetal imaging at 3T

PURPOSE

One of the main concerns in fetal MRI is the radiofrequency power that is absorbed both by the mother and the fetus. Passive shimming using high permittivity materials in the form of "dielectric pads" has previously been shown to increase the B 1 + efficiency and homogeneity in different applications, while reducing the specific absorption rate (SAR). In this work, we study the effect of optimized dielectric pads for 3 pregnant models.

METHODS

Pregnant models in the 3rd, 7th, and 9th months of gestation were used for simulations in a birdcage coil at 3T. Dielectric pads were optimized regions of interest (ROI) using previously developed methods for B 1 + efficiency and homogeneity and were designed for 2 ROIs: the entire fetus and the brain of the fetus. The SAR was evaluated in terms of the whole-body SAR, average SAR in the fetus and amniotic fluid, and maximum 10 g-averaged SAR in the mother, fetus, and amniotic fluid.

RESULTS

The optimized dielectric pads increased the transmit efficiency up to 55% and increased the B 1 + homogeneity in almost every tested configuration. The B 1 + -normalized whole-body SAR was reduced by more than 31% for all body models. The B 1 + -normalized local SAR was reduced in most scenarios by up to 62%.

CONCLUSION

Simulations have shown that optimized high permittivity pads can reduce SAR in pregnant subjects at the 3rd, 7th, and 9th month of gestation, while improving the transmit field homogeneity in the fetus. However, significantly more work is required to demonstrate that fetal imaging is safe under standard operating conditions.