A deep learning framework for identifying and segmenting three vessels in fetal heart ultrasound images.

BACKGROUND: Congenital heart disease (CHD) is one of the most common birth defects in the world. It is the leading cause of infant mortality, necessitating an early diagnosis for timely intervention. Prenatal screening using ultrasound is the primary method for CHD detection. However, its effectiveness is heavily reliant on the expertise of physicians, leading to subjective interpretations and potential underdiagnosis. Therefore, a method for automatic analysis of fetal cardiac ultrasound images is highly desired to assist an objective and effective CHD diagnosis. METHOD: In this study, we propose a deep learning-based framework for the identification and segmentation of the three vessels-the pulmonary artery, aorta, and superior vena cava-in the ultrasound three vessel view (3VV) of the fetal heart. In the first stage of the framework, the object detection model Yolov5 is employed to identify the three vessels and localize the Region of Interest (ROI) within the original full-sized ultrasound images. Subsequently, a modified Deeplabv3 equipped with our novel AMFF (Attentional Multi-scale Feature Fusion) module is applied in the second stage to segment the three vessels within the cropped ROI images. RESULTS: We evaluated our method with a dataset consisting of 511 fetal heart 3VV images. Compared to existing models, our framework exhibits superior performance in the segmentation of all the three vessels, demonstrating the Dice coefficients of 85.55%, 89.12%, and 77.54% for PA, Ao and SVC respectively. CONCLUSIONS: Our experimental results show that our proposed framework can automatically and accurately detect and segment the three vessels in fetal heart 3VV images. This method has the potential to assist sonographers in enhancing the precision of vessel assessment during fetal heart examinations.

Importance of Prenatal Diagnosis of Ileal Atresia in Gestational Diabetes Cases.

BACKGROUND Maldevelopment of the fetal bowel can result in the rare condition of intestinal atresia, which results in congenital bowel obstruction. This report describes a case of prenatal diagnosis of fetal ileal atresia at 22 weeks' gestation. CASE REPORT Here, we present a 24-year old woman who was 22 weeks into her first pregnancy when she underwent routine fetal ultrasound. She was diagnosed with gestational diabetes mellitus. Her body mass index was normal and she had normal weight gain. The ultrasonographic examination performed revealed a hyperechoic bowel and a small dilatation of the bowel. The couple was counselled for possible intestinal atresia and its postnatal implications. At 33 weeks of gestation, polyhydramnios appeared, and the intestinal distension was much more pronounced, with hyperechoic debris in the intestinal lumen (succus-entericus). After birth, surgery was performed and we concluded the patient had type II atresia, which was surgically treated. CONCLUSIONS This report has highlighted the importance of antenatal ultrasound in detecting fetal abnormalities, and has shown that rare conditions such as intestinal atresia can be accurately diagnosed and successfully managed. Surgical correction, if implemented promptly after stabilizing the general condition, can have a relatively good prognosis. Coexisting fetal ileal atresia and gestational diabetes mellitus are rare occurrences, which can make each condition even more difficult to treat.

Malformations of cortical development: Fetal imaging and genetics.

BACKGROUND: Malformations of cortical development (MCD) are a group of congenital disorders characterized by structural abnormalities in the brain cortex. The clinical manifestations include refractory epilepsy, mental retardation, and cognitive impairment. Genetic factors play a key role in the etiology of MCD. Currently, there is no curative treatment for MCD. Phenotypes such as epilepsy and cerebral palsy cannot be observed in the fetus. Therefore, the diagnosis of MCD is typically based on fetal brain magnetic resonance imaging (MRI), ultrasound, or genetic testing. The recent advances in neuroimaging have enabled the in-utero diagnosis of MCD using fetal ultrasound or MRI. METHODS: The present study retrospectively reviewed 32 cases of fetal MCD diagnosed by ultrasound or MRI. Then, the chromosome karyotype analysis, single nucleotide polymorphism array or copy number variation sequencing, and whole-exome sequencing (WES) findings were presented. RESULTS: Pathogenic copy number variants (CNVs) or single-nucleotide variants (SNVs) were detected in 22 fetuses (three pathogenic CNVs [9.4%, 3/32] and 19 SNVs [59.4%, 19/32]), corresponding to a total detection rate of 68.8% (22/32). CONCLUSION: The results suggest that genetic testing, especially WES, should be performed for fetal MCD, in order to evaluate the outcomes and prognosis, and predict the risk of recurrence in future pregnancies.

Comparing three cardiothoracic ratio measurement techniques and creating multivariable scoring system to predict Bart's hydrops fetalis at 17-22 weeks' gestation.

To assess the diagnostic performance of three cardiothoracic (CT) ratio techniques, including diameter, circumference, and area, for predicting hemoglobin (Hb) Bart's disease between 17 and 22 weeks' gestation, and to create a multivariable scoring system using multiple ultrasound markers. Before invasive testing, three CT ratio techniques and other ultrasound markers were obtained in 151 singleton pregnancies at risk of Hb Bart's disease. CT diameter ratio demonstrated the highest sensitivity among the other techniques. Significant predictors included CT diameter ratio > 0.5, middle cerebral artery-peak systolic velocity (MCA-PSV) > 1.5 multiples of the median, and placental thickness > 3 cm. MCA-PSV exhibited the highest sensitivity (97.8%) in predicting affected fetuses. A multivariable scoring achieved excellent sensitivity (100%) and specificity (84.9%) for disease prediction. CT diameter ratio exhibited slightly outperforming the other techniques. Increased MCA-PSV was the most valuable ultrasound marker. Multivariable scoring surpassed single-parameter analysis in predictive capabilities.

Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.

Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularly in the field of medical imaging. In this study, we investigated the application of deep learning models in early detection of fetal kidney anomalies. To provide an enhanced interpretation of those models' predictions, we proposed an adapted two-class representation and developed a multi-class model interpretation approach for problems with more than two labels and variable hierarchical grouping of labels. Additionally, we employed the explainable AI (XAI) visualization tools Grad-CAM and HiResCAM, to gain insights into model predictions and identify reasons for misclassifications. The study dataset consisted of 969 ultrasound images from unique patients; 646 control images and 323 cases of kidney anomalies, including 259 cases of unilateral urinary tract dilation and 64 cases of unilateral multicystic dysplastic kidney. The best performing model achieved a cross-validated area under the ROC curve of 91.28% ± 0.52%, with an overall accuracy of 84.03% ± 0.76%, sensitivity of 77.39% ± 1.99%, and specificity of 87.35% ± 1.28%. Our findings emphasize the potential of deep learning models in predicting kidney anomalies from limited prenatal ultrasound imagery. The proposed adaptations in model representation and interpretation represent a novel solution to multi-class prediction problems.

Pulmonary vascular reactivity in growth restricted fetuses using computational modelling and machine learning analysis of fetal Doppler waveforms.

The aim of this study was to investigate the pulmonary vasculature in baseline conditions and after maternal hyperoxygenation in growth restricted fetuses (FGR). A prospective cohort study of singleton pregnancies including 97 FGR and 111 normally grown fetuses was carried out. Ultrasound Doppler of the pulmonary vessels was obtained at 24-37 weeks of gestation and data were acquired before and after oxygen administration. After, Machine Learning (ML) and a computational model were used on the Doppler waveforms to classify individuals and estimate pulmonary vascular resistance (PVR). Our results showed lower mean velocity time integral (VTI) in the main pulmonary and intrapulmonary arteries in baseline conditions in FGR individuals. Delta changes of the main pulmonary artery VTI and intrapulmonary artery pulsatility index before and after hyperoxygenation were significantly greater in FGR when compared with controls. Also, ML identified two clusters: A (including 66% controls and 34% FGR) with similar Doppler traces over time and B (including 33% controls and 67% FGR) with changes after hyperoxygenation. The computational model estimated the ratio of PVR before and after maternal hyperoxygenation which was closer to 1 in cluster A (cluster A 0.98 ± 0.33 vs cluster B 0.78 ± 0.28, p = 0.0156). Doppler ultrasound allows the detection of significant changes in pulmonary vasculature in most FGR at baseline, and distinct responses to hyperoxygenation. Future studies are warranted to assess its potential applicability in the clinical management of FGR.

Two-dimensional (2D) placental ultrasound measurements - The correlation with placental volume measured by magnetic resonance imaging (MRI).

INTRODUCTION: Information about placental size in ongoing pregnancies may aid the identification of pregnancies with increased risk of adverse outcome. Placental volume can be measured using magnetic resonance imaging (MRI). However, this method is not universally available in antenatal care. Ultrasound is the diagnostic tool of choice in pregnancy. Therefore, we studied whether simple two-dimensional (2D) ultrasound placental measurements were correlated with placental volume measured by MRI. METHODS: We examined a convenience sample of 104 ongoing pregnancies at gestational week 27, using both ultrasound and MRI. The ultrasound measurements included placental length, width and thickness. Placental volume was measured using MRI. The correlation between each 2D placental ultrasound measurement and placental volume was estimated by applying Pearson's correlation coefficient (r). RESULTS: Mean placental length was 17.2 cm (SD 2.1 cm), mean width was 14.7 cm (SD 2.1 cm), and mean thickness was 3.2 cm (SD 0.6 cm). Mean placental volume was 536 cm3 (SD 137 cm3). The 2D ultrasound measurements showed poor correlation with placental volume (placental length; r = 0.27, width; r = 0.37, and thickness r = 0.13). DISCUSSION: Simple 2D ultrasound measurements of the placenta were poorly correlated with placental volume and cannot be used as proximate measures of placental volume. Our finding may be explained by the large variation between pregnancies in intrauterine placental shape.

Predicting High-Risk Fetal Cardiac Disease Anticipated to Need Immediate Postnatal Stabilization and Intervention with Planned Pediatric Cardiac Operating Room Delivery.

BACKGROUND: Distances between delivery and cardiac services can make the care of fetuses with cardiac disease at risk of acute cardiorespiratory instability at birth a challenge. In 2013 we implemented a fetal echocardiography-based algorithm targeting fetuses considered high risk for acute cardiorespiratory instability at ≤2 hours of birth for delivery in our pediatric cardiac operating room of our children's hospital, and, herein, examine our experience. METHODS AND RESULTS: We reviewed maternal and postnatal medical records of all fetuses with cardiac disease encountered January 2013 to March 2022 considered high risk for acute cardiorespiratory instability. Secondary analysis was performed including all fetuses with diagnoses of d-transposition of the great arteries/intact ventricular septum (d-TGA/IVS) and hypoplastic left heart syndrome (HLHS) encountered over the study period. Forty fetuses were considered high risk for acute cardiorespiratory instability: 15 with d-TGA/IVS and 7 with HLHS with restrictive atrial septum, 4 with absent pulmonary valve syndrome, 3 with obstructed anomalous pulmonary veins, 2 with severe Ebstein anomaly, 2 with thoracic/intracardiac tumors, and 7 others. Pediatric cardiac operating room delivery occurred for 33 but not for 7 (5 with d-TGA/IVS, 2 with HLHS with restrictive atrial septum). For high-risk cases, fetal echocardiography had a positive predictive value of 50% for intervention/extracorporeal membrane oxygenation/death at ≤2 hours and 70% at ≤24 hours. Of "low-risk" cases, 6/46 with d-TGA/IVS and 0/45 with HLHS required intervention at ≤2 hours. Fetal echocardiography for predicting intervention/extracorporeal membrane oxygenation/death at ≤2 hours had a sensitivity of 67%, specificity 93%, and positive and negative predictive values of 80% and 87%, respectively, for d-TGA/IVS, and 100%, 95%, 71%, and 100% for HLHS, respectively. CONCLUSIONS: Fetal echocardiography can predict the need for urgent intervention in a majority with d-TGA/IVS and HLHS and in half of the entire spectrum of high-risk cardiac disease.

Predictive value of placental real-time shear wave elastography combined with 3-dimensional power Doppler index for preeclampsia.

This study aimed to investigate the value of placental real-time shear wave elastography combined with three-dimensional power Doppler index (3D-PDI) in the prediction of preeclampsia. We conducted a retrospective study selecting 60 pregnant women diagnosed with preeclampsia as the experimental group and 60 normal pregnant women as the control group from January 2021 to December 2022. The elastic modulus values of different regions of the placenta and placental 3D-PDI were detected and compared between the two groups. The ROC curve was used to evaluate the diagnostic value of each parameter, alone or in combination, for preeclampsia. The study findings demonstrated that the elastic modulus values of different regions of the placenta and 3D-PDI of the two groups have statistical significance. The values of SWE, VI, FI, and VFI are different in prediction of preeclampsia, and the combination of various parameters can improve the prediction value. Overall, our study provides a valuable method for the prediction of preeclampsia with the advantages of non-invasiveness, efficiency, and simplicity.

Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection.

INTRODUCTION: Congenital anomalies are the most encountered cause of fetal death, infant mortality and morbidity. 7.9 million infants are born with congenital anomalies yearly. Early detection of congenital anomalies facilitates life-saving treatments and stops the progression of disabilities. Congenital anomalies can be diagnosed prenatally through morphology scans. A correct interpretation of the morphology scan allows a detailed discussion with the parents regarding the prognosis. The central feature of this project is the development of a specialised intelligent system that uses two-dimensional ultrasound movies obtained during the standard second trimester morphology scan to identify congenital anomalies in fetuses. METHODS AND ANALYSIS: The project focuses on three pillars: committee of deep learning and statistical learning algorithms, statistical analysis, and operational research through learning curves. The cross-sectional study is divided into a training phase where the system learns to detect congenital anomalies using fetal morphology ultrasound scan, and then it is tested on previously unseen scans. In the training phase, the intelligent system will learn to answer the following specific objectives: (a) the system will learn to guide the sonographer's probe for better acquisition; (b) the fetal planes will be automatically detected, measured and stored and (c) unusual findings will be signalled. During the testing phase, the system will automatically perform the above tasks on previously unseen videos.Pregnant patients in their second trimester admitted for their routine scan will be consecutively included in a 32-month study (4 May 2022-31 December 2024). The number of patients is 4000, enrolled by 10 doctors/sonographers. We will develop an intelligent system that uses multiple artificial intelligence algorithms that interact between themselves, in bulk or individual. For each anatomical part, there will be an algorithm in charge of detecting it, followed by another algorithm that will detect whether anomalies are present or not. The sonographers will validate the findings at each intermediate step. ETHICS AND DISSEMINATION: All protocols and the informed consent form comply with the Health Ministry and professional society ethics guidelines. The University of Craiova Ethics Committee has approved this study protocol as well as the Romanian Ministry of Research Innovation and Digitization that funded this research. The study will be implemented and reported in line with the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) statement. TRIAL REGISTRATION NUMBER: The study is registered under the name 'Pattern recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical Learning', project number 101PCE/2022, project code PN-III-P4-PCE-2021-0057. TRIAL REGISTRATION: ClinicalTrials.gov, unique identifying number NCT05738954, date of registration: 2 November 2023.

Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.

BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists. MATERIALS AND METHODS: This prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments. RESULTS: There were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively. CONCLUSIONS: CUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.

Ultrasonographic assessment of abnormal fetal growth related to uteroplacental-fetal biometrics and Doppler (U-AID) indices: Protocol for multicenter retrospective cohort study trial.

Fetal growth restriction (FGR) is one of the leading causes of perinatal morbidity and mortality. Many studies have reported an association between FGR and fetal Doppler indices focusing on umbilical artery (UA), middle cerebral artery (MCA), and ductus venosus (DV). The uteroplacental-fetal circulation which affects the fetal growth consists of not only UA, MCA, and DV, but also umbilical vein (UV), placenta and uterus itself. Nevertheless, there is a paucity of large-scale cohort studies that have assessed the association between UV, uterine wall, and placental thickness with perinatal outcomes in FGR, in conjunction with all components of the uteroplacental-fetal circulation. Therefore, this multicenter study will evaluate the association among UV absolute flow, placental thickness, and uterine wall thickness and adverse perinatal outcome in FGR fetuses. This multicenter retrospective cohort study will include singleton pregnant women who undergo at least one routine fetal ultrasound scan during routine antepartum care. Pregnant women with fetuses having structural or chromosomal abnormalities will be excluded. The U-AID indices (UtA, UA, MCA, and UV flow, placental and uterine wall thickness, and estimated fetal body weight) will be measured during each trimester of pregnancy. The study population will be divided into two groups: (1) FGR group (pregnant women with FGR fetuses) and (2) control group (those with normal growth fetus). We will assess the association between U-AID indices and adverse perinatal outcomes in the FGR group and the difference in U-AID indices between the two groups.

Prenatal Diagnosis and Postnatal Outcomes of Persistent Left Superior Vena Cava Associated With Mild Narrow Aorta: A Cohort Study.

PURPOSE: To explore prenatal ultrasonic features and prognosis of the persistent left superior vena cava (PLSVC) complicated with mild narrow aorta. MATERIALS AND METHODS: A retrospective study was conducted involving 1348 fetuses diagnosed with PLSVC prenatally between January 2016 and December 2019. Forty-five fetuses with PLSVC associated with mild narrow aorta were selected from the cohort as the study group and 79 fetuses with isolated PLSCV were recruited randomly as the control group. All clinical and ultrasound results, including images and parameters of cardiac structures, were reviewed retrospectively. General conditions, ultrasound (US) measurements, and fetal prognosis were compared between the groups. RESULTS: Aorta valve diameter (AOD), Z-score of aorta valve (AODz-score), aortic isthmus diameter (AOIsD), and pulmonary diameter (PAD)/AOD were significantly different in study group than control group no matter in the second or third trimester. Thirty-eight fetuses in study group were born with favorable outcomes after long-term follow-up. A total of 13.16% (5/38) remain mild narrow aorta and 3 of them showed smaller left ventricle after 3 years follow up. Prenatal AODz-score in infants remains mild narrow aorta after 2 years aged was higher than ones' aorta return to normal (P = .01), especially when AODz-score >1.725. Moreover, when prenatal ratio of AOIsD/left subclavian artery was <1.12, it was more likely that the aorta would remain mildly narrow at age 2. CONCLUSION: Fetuses diagnosed with PLSVC with mild narrow aorta had favorable prognosis. AODz-score and AOIsD/left subclavian artery may be two predictors that reveal the risk of a mildly narrowed aorta remaining after birth.

FUSC: Fetal Ultrasound Semantic Clustering of Second-Trimester Scans Using Deep Self-Supervised Learning.

OBJECTIVE: The aim of this study was address the challenges posed by the manual labeling of fetal ultrasound images by introducing an unsupervised approach, the fetal ultrasound semantic clustering (FUSC) method. The primary objective was to automatically cluster a large volume of ultrasound images into various fetal views, reducing or eliminating the need for labor-intensive manual labeling. METHODS: The FUSC method was developed by using a substantial data set comprising 88,063 images. The methodology involves an unsupervised clustering approach to categorize ultrasound images into diverse fetal views. The method's effectiveness was further evaluated on an additional, unseen data set consisting of 8187 images. The evaluation included assessment of the clustering purity, and the entire process is detailed to provide insights into the method's performance. RESULTS: The FUSC method exhibited notable success, achieving >92% clustering purity on the evaluation data set of 8187 images. The results signify the feasibility of automatically clustering fetal ultrasound images without relying on manual labeling. The study showcases the potential of this approach in handling a large volume of ultrasound scans encountered in clinical practice, with implications for improving efficiency and accuracy in fetal ultrasound imaging. CONCLUSION: The findings of this investigation suggest that the FUSC method holds significant promise for the field of fetal ultrasound imaging. By automating the clustering of ultrasound images, this approach has the potential to reduce the manual labeling burden, making the process more efficient. The results pave the way for advanced automated labeling solutions, contributing to the enhancement of clinical practices in fetal ultrasound imaging. Our code is available at https://github.com/BioMedIA-MBZUAI/FUSC.

Association of Prenatally Diagnosed Isolated Single Left Superior Vena Cava and Postnatal Development of Coarctation of the Aorta.

To report the prevalence of coarctation of the aorta (CoA) in fetuses with single left superior vena cava (SL-SVC) and to evaluate changes in echocardiographic measurements. Additionally, to report the prevalence of associated malformations. Retrospective observational study of fetuses diagnosed with SL-SVC between 2012 and 2021 at a tertiary fetal cardiology unit. In fetuses without intracardiac abnormalities, Z-scores of the ventricles, great arteries, and Doppler flow patterns are reported. We identified 47 fetuses with SL-SVC of which 8/47 (17%) had abnormal intracardiac anatomy. One fetus was lost to follow-up. Of those with normal intracardiac anatomy and postnatal follow-up (38), karyotype abnormalities were confirmed in 2/38 (5%) and ECA in 8/38 (21%). 33/38 were live-born. None developed CoA postnatally. Paired analysis of Z-scores between early and late scans of 24 fetuses showed that diameters of the right heart structures and Doppler flows of tricuspid valve increased significantly during pregnancy, while the left heart structures and flow patterns did not change. The median risk of CoA did not change between the early and the late scan. We did not observe CoA in this cohort. A degree of ventricular asymmetry was present, but this was due to right heart dominance rather than hypoplasia of left heart structures. This likely reflects redistribution of blood and does not appear to confer increased risk of CoA. Predictive models of the postnatal development of CoA which set the dimensions of right and left heart structures in relation might not be applicable in this situation.

Quantitative Analysis of Morphology and Function in the Fetal Heart with Severe Tricuspid Regurgitation by Speckle Tracking Imaging.

Morphology and function in a fetal heart with severe tricuspid regurgitation remains challenging. The aim of this study was to assess cardiac morphology and function in fetuses with severe tricuspid regurgitation by fetal heart quantification (HQ) and to assess the practical value of fetal HQ. Clinical information was analyzed for 63 pregnant women who underwent fetal cardiac ultrasonography. The women were divided into those who had a fetus with severe tricuspid regurgitation (n = 20) and those with a normal fetus (n = 40). The global sphericity index (GSI), fractional area change (FAC), and global longitudinal strain (GLS) of both ventricles and the sphericity index (SI) and fractional shortening (FS) of 24 segments were quantified by fetal HQ using speckle tracking imaging. Fetuses with severe tricuspid regurgitation had a significantly lower GSI (1.14 ± 0.10 vs. 1.26 ± 0.08, p < 0.001) and a higher GSI Z-score (-0.98 ± 1.01 vs. 0.25 ± 0.87, p < 0.001) as well as a significantly lower right ventricular FAC (36.50 ± 7.34% vs. 45.19 ± 3.39%, p < 0.001), FAC Z-score (-1.02 ± 1.41 vs. 0.49 ± 0.74, p < 0.001), and GLS (-21.01 ± 5.66% vs. 45.19 ± 3.49%, p < 0.001). The SI and SI Z-score were significantly lower in segments 1-18 of the right ventricle in fetuses with severe tricuspid regurgitation (p < 0.05); furthermore, FS of segments 1-12 and 19-24 and the FS Z-score of segments 18-24 were significantly lower in fetuses with severe tricuspid regurgitation (p < 0.05). Fetal HQ is useful for evaluation of cardiac morphology and function in fetuses with severe tricuspid regurgitation and can provide important reference information for both clinical diagnosis and treatment.

Magnetic Resonance Imaging of Dural Sinus Malformation in a Fetus: A Case Report.

BACKGROUND: Dural sinus malformation (DSM) is a rather rare congenital condition that can be encountered in the fetus and infants. The cause and etiology of DSM remain unclear. Obstetric ultrasound plays a key role in screening fetal brain malformations, and MRI is frequently used as a complementary method to confirm the diagnosis and provide more details. OBJECTIVE: Here, we present a fetus with DSM by multiple imaging methods to help better understand the imaging characteristics of this malformation. CASE PRESENTATION: A 22-year-old primipara was referred to our hospital at 25 weeks of gestation following the detection of a fetal intracranial mass without any symptoms. A prenatal ultrasound performed in our hospital at 25 + 2 gestational weeks showed a large anechoic mass with liquid dark space, while no blood flow was detected. After the initial evaluation, this primipara received a prenatal MRI in our hospital. This examination at 25 + 5 gestational weeks delineated a fan-shaped mass in the torcular herophili, which was iso-to hyperintense on T1WI and hypointense on T2WI. At the lower part of this lesion, a quasi-circular hyperintense on T1WI and a signal slightly hyperintense on T2WI could be seen. Meanwhile, the adjacent brain parenchyma was compressed by the mass. CONCLUSION: We reviewed the current literature to obtain a better understanding of the mechanisms, imaging characteristics, and survival status of DSM. Although the primipara of the present study regretfully opted for elective termination of pregnancy, the reevaluation of DSM survival deserves more attention because of the better survival data from recent studies.

A case report of single umbilical artery combined with fetal bladder exstrophy in singleton pregnancy and related literature review.

BACKGROUND: According to prenatal ultrasonographic studies, single umbilical artery may be present alone or in association with other fetal abnormalities. So far, the exact pathogenesis of bladder exstrophy is unclear. Some scholars believe that bladder exstrophy and cloacal exstrophy should be regarded as a disease spectrum to explore their pathogenesis. If bladder exstrophy and cloacal exstrophy are regarded as the same disease spectrum, then we can speculate that the single umbilical artery should have the probability of being accompanied by bladder exstrophy at the same time. CASE PRESENTATION: For the first time, we report a rare case of fetal bladder exstrophy with single umbilical artery in single pregnancy. This patient underwent targeted color Doppler ultrasound at 26 weeks of pregnancy which first suspected bladder exstrophy with single umbilical artery and fetal MRI for diagnosis at 38 + 3 weeks of pregnancy which confirmed the suspicion. After the diagnosis was confirmed, the patient was scheduled for a multidisciplinary discussion. Ultimately the patient opted for induced fetal demise at 38 + 5 weeks of pregnancy and the physical appearance of the fetal demise affirmed previous ultrasound and MRI examination results. CONCLUSIONS: Our report is the first finding of single umbilical artery combined with bladder exstrophy in a singleton pregnancy. Accordingly, our case enhances the evidence that cloacal exstrophy and bladder exstrophy should be treated as the same disease spectrum. In addition, we conducted a literature review on the diagnostic progress of single umbilical artery combined with bladder exstrophy, hoping to provide useful references for the diagnosis of this disease.

Fetal face shape analysis from prenatal 3D ultrasound images.

3D ultrasound imaging of fetal faces has been predominantly confined to qualitative assessment. Many genetic conditions evade diagnosis and identification could assist with parental counselling, pregnancy management and neonatal care planning. We describe a methodology to build a shape model of the third trimester fetal face from 3D ultrasound and show how it can objectively describe morphological features and gestational-age related changes of normal fetal faces. 135 fetal face 3D ultrasound volumes (117 appropriately grown, 18 growth-restricted) of 24-34 weeks gestation were included. A 3D surface model of each face was obtained using a semi-automatic segmentation workflow. Size normalisation and rescaling was performed using a growth model giving the average size at every gestation. The model demonstrated a similar growth rate to standard head circumference reference charts. A landmark-free morphometry model was estimated to characterize shape differences using non-linear deformations of an idealized template face. Advancing gestation is associated with widening/fullness of the cheeks, contraction of the chin and deepening of the eyes. Fetal growth restriction is associated with a smaller average facial size but no morphological differences. This model may eventually be used as a reference to assist in the prenatal diagnosis of congenital anomalies with characteristic facial dysmorphisms.

Clinical significance of three-dimensional power Doppler combined with two-dimensional Doppler ultrasonography for evaluating fetal growth restriction.

OBJECTIVES: To assess the predictive accuracy of three-dimensional (3D) power Doppler combined with two-dimensional (2D) Doppler ultrasonography in detecting fetal growth restriction (FGR). METHODS: The study was conducted on singleton pregnancies presenting for growth ultrasound examinations between 20 and 40 weeks of gestation. 63 patients with FGR were enrolled and matched 1:1.8 for gestational age with normal fetuses. Both groups were further divided into subgroups, with 32 weeks as the threshold-early-onset and late-onset FGR groups, and corresponding control groups. Conventional 2D Doppler parameters and standardized 3D power Doppler measurements of the placenta, including vascularization index (VI), flow index (FI), and vascularization-flow index (VFI) were obtained for each patient. RESULTS: (1) The average gestational weeks of delivery and birth weight of newborns in early-onset and late-onset FGR case groups were lower than those in control groups, while the incidence of placenta previa and adverse pregnancy outcomes were higher than those in control groups. (2) The biparietal diameter, head circumference, abdominal circumference, femur length, estimated fetal weight, middle cerebral artery systolic/diastolic velocity ratio (S/D), pulsatility index (PI), resistance index (RI), and placental blood perfusion indices of vascular index (VI), flow index (FI), vascular flow index (VFI), and cerebro-placental ratio (CPR) of the early-onset and late-onset FGR case groups were all lower than those of the control group. Moreover, the S/D, PI, and RI of the umbilical and uterine arteries were higher than those of the corresponding control group. (3) For early-onset FGR, the area under the curve (AUC) of the umbilical artery PI was the largest (0.861), exhibiting the highest predictive value. When combined with the placental blood perfusion index, the AUC was 0.789. For late-onset FGR, the AUC of the CPR was 0.861. After integrating the placental blood perfusion index, the AUC increased to 0.877. The positive likelihood ratio (PLR) of combined 2D Doppler indexes (21.938) and negative likelihood ratio (NLR) of VFI (0.565) were the highest in the early-onset FGR group. The PLR of combined 3D Doppler indexes (8.536) and NLR of VFI (0.557) were the highest in the late-onset FGR group. CONCLUSIONS: The combination of 3D Doppler indices with 2D Doppler ultrasonography demonstrated superior predictive value in diagnosing late-onset FGR compared to other conventional indicators. The 3D Dower index, VFI, has a good true-negative predictive value for both early- and late-onset FGR.