Prenatal diagnosis of criss-cross heart - case series and review of the literature.

OBJECTIVE: This study aimed to improve the accuracy of prenatal diagnosis by analyzing fetal echocardiographic features of criss-cross heart (CCH), to provide an effective basis for the development of management strategies and improve the prognosis of patients. METHODS: A retrospective analysis was performed on CCH cases diagnosed prenatally at our center between July 2016 and June 2022. Clinical data and prenatal fetal echocardiographic images were reviewed. Literature on prenatal diagnosis of CCH was searched from January 2000 to December 2023 in the PubMed database. RESULTS: Fourteen (0.03%) CCH cases were diagnosed from a database of fetal echocardiograms of 41354 cases at our center. The prenatal genetic testing results were normal in 10 cases and 4 cases didn't check. All cases underwent termination of pregnancy. All cases showed crossed ventricular inflow tracts and combined with other cardiac structural abnormalities. A total of eight articles containing 25 cases were found in the literature review and all cases were associated with other cardiac structural abnormalities. CONCLUSION: Prenatal echocardiography is the primary tool for fetal diagnosis of CCH. Continuous scanning helps avoid missing data and misdiagnosis.

How automated techniques ease functional assessment of the fetal heart: Applicability of two-dimensional speckle-tracking echocardiography for comprehensive analysis of global and segmental cardiac deformation using fetalHQ®.

BACKGROUND: Prenatal echocardiographic assessment of fetal cardiac function has become increasingly important. Fetal two-dimensional speckle-tracking echocardiography (2D-STE) allows the determination of global and segmental functional cardiac parameters. Prenatal diagnostics is relying increasingly on artificial intelligence, whose algorithms transform the way clinicians use ultrasound in their daily workflow. The purpose of this study was to demonstrate the feasibility of whether less experienced operators can handle and might benefit from an automated tool of 2D-STE in the clinical routine. METHODS: A total of 136 unselected, normal, singleton, second- and third-trimester fetuses with normofrequent heart rates were examined by targeted ultrasound. 2D-STE was performed separately by beginner and expert semiautomatically using a GE Voluson E10 (FetalHQ®, GE Healthcare, Chicago, IL). Several fetal cardiac parameters were calculated (end-diastolic diameter [ED], sphericity index [SI], global longitudinal strain [EndoGLS], fractional shortening [FS]) and assigned to gestational age (GA). Bland-Altman plots were used to test agreement between both operators. RESULTS: The mean maternal age was 33 years, and the mean maternal body mass index prior to pregnancy was 24.78 kg/m2. The GA ranged from 16.4 to 32.0 weeks (average 22.9 weeks). Averaged endoGLS value of the beginner was -18.57% ± 6.59 percentage points (pp) for the right and -19.58% ± 5.63 pp for the left ventricle, that of the expert -14.33% ± 4.88 pp and -16.37% ± 5.42 pp. With increasing GA, right ventricular endoGLS decreased slightly while the left ventricular was almost constant. The statistical analysis for endoGLS showed a Bland-Altman-Bias of -4.24 pp ± 8.06 pp for the right and -3.21 pp ± 7.11 pp for the left ventricle. The Bland-Altman-Bias of the ED in both ventricles in all analyzed segments ranged from -.49 mm ± 1.54 mm to -.10 mm ± 1.28 mm, that for FS from -.33 pp ± 11.82 pp to 3.91 pp ± 15.56 pp and that for SI from -.38 ± .68 to -.15 ± .45. CONCLUSIONS: Between both operators, our data indicated that 2D-STE analysis showed excellent agreement for cardiac morphometry parameters (ED and SI), and good agreement for cardiac function parameters (EndoGLS and FS). Due to its complexity, the application of fetal 2D-STE remains the domain of scientific-academic perinatal ultrasound and should be placed preferably in the hands of skilled operators. At present, from our perspective, an implementation into clinical practice "on-the-fly" cannot be recommended.

Utility of the novel fetal heart quantification (fetal HQ) technique in diagnosing ventricular interdependence and biventricular dysfunction in a case of prenatally diagnosed Uhl's anomaly.

Uhl's anomaly is characterized by complete or partial absence of right ventricular myocardium. We describe a case of prenatally diagnosed Uhl's anomaly with biventricular dysfunction which was quantified with speckle tracking echocardiography using a novel fetal heart quantification (fetal HQ) technique.

Fetal Cardiovascular MR Imaging.

Prenatal diagnosis of congenital heart disease allows for appropriate planning of delivery and an opportunity to inform families about the prognosis of the cardiac malformation. On occasion, prenatal therapies may be offered to improve perinatal outcomes. While ultrasound is the primary diagnostic method, advances have led to interest in fetal MRI for its potential to aid in clinical decision-making. This review explores technical innovations and the clinical utility of fetal cardiovascular magnetic resonance (CMR), highlighting its role in diagnosing and planning interventions for complex heart conditions. Future directions include the prediction of perinatal physiology and guidance of delivery planning.

Clinical implementation of first trimester screening for congenital heart defects.

OBJECTIVE: To examine the feasibility and performance of implementing a standardized fetal cardiac scan at the time of a routine first-trimester ultrasound scan. METHOD: A retrospective, single-center study in an unselected population between March 2021 and July 2022. A standardized cardiac scan protocol consisting of a four-chamber and 3-vessel trachea view with color Doppler was implemented as part of the routine first-trimester scan. Sonographers were asked to categorize the fetal heart anatomy. Data were stratified into two groups based on the possibility of evaluating the fetal heart. The influence of maternal and fetal characteristics and the detection of major congenital heart disease were investigated. RESULTS: A total of 5083 fetuses were included. The fetal heart evaluation was completed in 84.9%. The proportion of successful scans increased throughout the study period from 76% in the first month to 92% in the last month. High maternal body mass index and early gestational age at scan significantly decreased the feasibility. The first-trimester detection of major congenital heart defects was 7/16, of which four cases were identified by the cardiac scan protocol with no false-positive cases. CONCLUSION: First-trimester evaluation of the fetal heart by a standardized scan protocol is feasible to implement in daily practice. It can contribute to the earlier detection of congenital heart defects at a very low false positive rate.

Transforming congenital heart disease management: Advances in fetal cardiac interventions.

This review addresses the transformative advancements in fetal cardiac interventions (FCI) for congenital heart diseases (CHD), with a particular focus on aortic stenosis with evolving hypoplastic left heart syndrome, pulmonary atresia with an intact ventricular septum, and HLHS with an intact atrial septum (HLHS-IAS). We outline the specific FCI techniques employed, the refined criteria for selecting appropriate fetal and maternal candidates, and the promising yet varied outcomes associated with these procedures. Procedural strategies and clinical decision-making are examined as we take into account the fetal pathophysiology and the benefits and risks of early intervention. We highlight the role of multidisciplinary teams in improving technical success and managing immediate procedural complications, which have led to significant improvements in procedural outcomes. Additionally, the review discusses the long-term outcomes, challenges, and future research directions in FCI, emphasizing the necessity for continuous innovation and collaboration across specialties to advance the management of CHD. The integration of new technologies and research findings holds the promise of further enhancing FCI success rates and patient outcomes.

Enhancing parental understanding of congenital heart disease through personalized prenatal counseling with 3D printed hearts.

OBJECTIVES: In addition to a correct prenatal diagnosis of congenital heart disease (CHD), comprehensive parental counseling is crucial to ensure that parents are well-informed about the condition of the fetus. This study aims to investigate whether there is a significant difference in the information acquired by parents through traditional counseling, utilizing 2-dimensional (2D) illustrations and images, compared to an advanced approach utilizing personalized three-dimensional (3D) printed models of the fetal heart developed from 3D ultrasound imaging. METHODS: This study, designed as a pilot randomized control trial, enrolled pregnant women with gestational ages greater than 18 weeks, whose fetuses were diagnosed with CHD and referred to our center between November, 2020 and June, 2021. Two groups of patients were included in the study. The first group received standard medical counseling with 2D images and illustrations, while the second group underwent advanced counseling with 3D-printed patient-specific heart models. Both groups were then required to complete the same survey in which the knowledge of the CHD was investigated. The 3D models were created from 3D ultrasound imaging and printed using resin materials in both 1:1 and 5:1 scale. RESULTS: A comparison of the scores obtained from the two groups revealed that 3D visualization of the fetus's heart has the potential to increase parental knowledge about CHD and the required surgical procedures. Furthermore, all couples expressed interest in receiving a 1:1 scale model of their baby's heart. CONCLUSION: Personalized prenatal counseling with 3D-ultrasound-based heart models positively impacts parents' understanding of CHD. The use of 3D models provides a more comprehensive and accessible representation of the condition, contributing to an increased knowledge gain, and potentially helping to support informed decisions regarding their child's care.

Automatic segmentation of 15 critical anatomical labels and measurements of cardiac axis and cardiothoracic ratio in fetal four chambers using nnU-NetV2.

BACKGROUND: Accurate segmentation of critical anatomical structures in fetal four-chamber view images is essential for the early detection of congenital heart defects. Current prenatal screening methods rely on manual measurements, which are time-consuming and prone to inter-observer variability. This study develops an AI-based model using the state-of-the-art nnU-NetV2 architecture for automatic segmentation and measurement of key anatomical structures in fetal four-chamber view images. METHODS: A dataset, consisting of 1,083 high-quality fetal four-chamber view images, was annotated with 15 critical anatomical labels and divided into training/validation (867 images) and test (216 images) sets. An AI-based model using the nnU-NetV2 architecture was trained on the annotated images and evaluated using the mean Dice coefficient (mDice) and mean intersection over union (mIoU) metrics. The model's performance in automatically computing the cardiac axis (CAx) and cardiothoracic ratio (CTR) was compared with measurements from sonographers with varying levels of experience. RESULTS: The AI-based model achieved a mDice coefficient of 87.11% and an mIoU of 77.68% for the segmentation of critical anatomical structures. The model's automated CAx and CTR measurements showed strong agreement with those of experienced sonographers, with respective intraclass correlation coefficients (ICCs) of 0.83 and 0.81. Bland-Altman analysis further confirmed the high agreement between the model and experienced sonographers. CONCLUSION: We developed an AI-based model using the nnU-NetV2 architecture for accurate segmentation and automated measurement of critical anatomical structures in fetal four-chamber view images. Our model demonstrated high segmentation accuracy and strong agreement with experienced sonographers in computing clinically relevant parameters. This approach has the potential to improve the efficiency and reliability of prenatal cardiac screening, ultimately contributing to the early detection of congenital heart defects.

Prenatal diagnosis of interrupted aortic arch using high-definition flow render mode and spatiotemporal image correlation.

OBJECTIVES: To evaluate the clinical utility of two dimensional (2D) ultrasound combined with spatiotemporal image correlation (STIC) in diagnosing interrupted aortic arch (IAA) in fetal life. METHODS: A total of 53 cases of fetal IAA were diagnosed using 2D ultrasound combined with STIC, and 53 normal fetuses of the same gestational week were selected. These cases were retrospectively analyzed to assess the utility of employing 2D ultrasound combined with STIC in the diagnosis of IAA. RESULTS: 2D ultrasound combined with STIC detected 22 cases of type A IAA, 24 cases of type B IAA, and seven cases of type C IAA. Furthermore, combining 2D ultrasound with STIC enabled dynamic visualization of the IAA, aiding in prenatal diagnosis. The diagnostic coincidence rate of IAA was found to be higher in the HD-flow combined with STIC than that in the 2D combined with HD-flow. CONCLUSION: HD-flow combined with STIC can assist in diagnosing fetal IAA, and this technique has important clinical value.

Investigation on ultrasound images for detection of fetal congenital heart defects.

Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The detection rate could be increased by supplementing ultrasound imaging with fetal ultrasound image evaluation (FUSI) using deep learning techniques. As a result, the non-invasive foetal ultrasound image has clear potential in the diagnosis of CHD and should be considered in addition to foetal echocardiography. This review paper highlights cutting-edge technologies for detecting CHD using ultrasound images, which involve pre-processing, localization, segmentation, and classification. Existing technique of preprocessing includes spatial domain filter, non-linear mean filter, transform domain filter, and denoising methods based on Convolutional Neural Network (CNN); segmentation includes thresholding-based techniques, region growing-based techniques, edge detection techniques, Artificial Neural Network (ANN) based segmentation methods, non-deep learning approaches and deep learning approaches. The paper also suggests future research directions for improving current methodologies.

Fetal cardiac screening: 1st trimester and beyond.

Congenital heart defects (CHD) are the most common birth defect and a leading cause of infant morbidity and mortality. CHD often occurs in low-risk pregnant patients, which underscores the importance of routine fetal cardiac screening at the time of the 2nd trimester ultrasound. Prenatal diagnosis of CHD is important for counseling and decision-making, focused diagnostic testing, and optimal perinatal and delivery management. As a result, prenatal diagnosis has led to improved neonatal and infant outcomes. Updated fetal cardiac screening guidelines, coupled with technological advancements and educational efforts, have resulted in increased prenatal detection of CHD in both low- and high-risk populations. However, room for improvement remains. In recent years, fetal cardiac screening for specific high-risk populations has started in the 1st trimester, which is a trend that is likely to expand over time. This review discusses fetal cardiac screening throughout pregnancy.

Fetal left and right ventricular strain parameters using speckle tracking in congenital heart diseases.

Assessment of fetal ventricular function is mostly subjective, and currently, for the objective assessment left ventricular shortening fraction is obtained. However, this by itself is not very reliable. Hence, more tools that can provide an objective assessment are needed to increase the confidence of functional assessment. Speckle tracking imaging can provide one such tool. In this study we sought to establish the normative value of global longitudinal and circumferential strain for our fetal patients and for two major forms of congenital heart diseases, namely atrioventricular canal defects (AVC) and uncorrected dextro-transposition of the great arteries (dTGA) to act as a benchmark. The study was completed via a single center retrospective analysis on 72 fetal echocardiograms (26 normal, 15 dTGA, and 31 AVC). Tomtec Arena™ echocardiography analysis software was used for analysis. In normal fetuses, mean left ventricular (LV) global longitudinal strain (GLS) was - 22.6% (95% CI -24, -21.1) and mean right ventricular (RV) GLS was - 22.1% (95% CI -23.6, -20.6). In AVC patients LV GLS was-26.6% (95% CI -28,-25.3) and mean RV GLS was - 26.5% (95% CI -27.9,-25.2). In dTGA patients LV GLS was - 22.9% (95% CI of -24.8, -21) and RV GLS was - 21.3% (95% CI was - 23.4, -20.8). There was good intra-rater reliability though poor to fair inter-rater reliability. Notwithstanding its current limitations, strain imaging can provide useful information that can increase confidence of cardiac functional assessment in fetal patients. However, to be reliable across the board, further automation and standardization is required.

Comparison of Left Ventricular Stroke Volume in 2nd- and 3rd-Trimester Fetuses Measured by the Product of VTI and Aortic Annular Area With That Assessed by Simpson's Single-Plane Rule Using the STE Technique.

OBJECTIVES: The aim of the study was to compare left ventricle stroke volume in healthy, eutrophic fetuses in the 2nd and 3rd trimesters evaluated using the velocity time integral and aortic annulus area with left ventricular stroke volume measured using Simpson's single-plane rule and to determine the discrepancy equation. METHODS: The study included 354 fetuses. In each fetus, during the same examination, simultaneous assessment of stroke volume was performed by pulsed-wave Doppler using the product of the velocity time integral and aortic annulus area and by the fetalHQ® software using Simpson's single-plane rule. The Mann-Whitney U test was used to compare the "product-derived" stroke volume and stroke volume using fetalHQ® software values in the 2nd and 3rd trimesters separately. The agreement between the two methods were verified using Bland-Altman analysis. A linear regression model was used to obtain the discrepancy equation. RESULTS: In the 2nd trimester, the mean percentage difference between both the techniques showed that the stroke volume values determined using pulsed-wave Doppler were, on average, 88% higher than the stroke volume values determined using fetalHQ®. The upper limit of agreement between the compared techniques was approximately 146% and the lower limit of agreement was equal to 29.6%. In the 3rd trimester, the results indicated that the stroke volume values determined using pulsed-wave Doppler were, on average, 76% higher than the stroke volume values determined using fetalHQ®. The upper limit of agreement between the compared techniques was approximately 129% and the lower limit of agreement was 23%. Based on the results of the linear regression models, discrepancy formulas of the stroke volume values were obtained. The equations to calculate the predicted mean and standard deviations were used to compute the reference intervals for the mean, 5th and 95th centiles. CONCLUSION: The calculation of left ventricular stroke volume using pulsed Doppler has higher result in relation to stroke volume determined using Simpson's rule significantly. The aortic annulus area showed a higher correlation regarding stroke volume than the velocity time integral in both the 2nd and 3rd trimesters. Stroke volume increased with the increase in aortic annulus area, whereas the velocity time integral remained relatively constant. The retrospective analysis of the collected material enabled the determination of the discrepancy equation.

Fetal transposition of the great arteries: 3D virtual and physical models from ultrasound datasets.

Transposition of the great arteries (TGA) is a cyanotic congenital heart disease characterized by ventriculoarterial discordance and atrioventricular concordance with the great arteries in a parallel relationship. Prenatal diagnosis of TGA has implications for postnatal outcomes, allowing for planned delivery and perinatal management. Three-dimensional virtual or physical models of fetal TGA allow better understanding of fetal cardiac anomalies by parents and interactive discussion among the multidisciplinary team (obstetricians, pediatricians, maternal-fetal specialists, pediatric cardiologists, and cardiovascular surgeons), as well as continuing medical education.

A Coarse-Fine Collaborative Learning Model for Three Vessel Segmentation in Fetal Cardiac Ultrasound Images.

Congenital heart disease (CHD) is the most frequent birth defect and a leading cause of infant mortality, emphasizing the crucial need for its early diagnosis. Ultrasound is the primary imaging modality for prenatal CHD screening. As a complement to the four-chamber view, the three-vessel view (3VV) plays a vital role in detecting anomalies in the great vessels. However, the interpretation of fetal cardiac ultrasound images is subjective and relies heavily on operator experience, leading to variability in CHD detection rates, particularly in resource-constrained regions. In this study, we propose an automated method for segmenting the pulmonary artery, ascending aorta, and superior vena cava in the 3VV using a novel deep learning network named CoFi-Net. Our network incorporates a coarse-fine collaborative strategy with two parallel branches dedicated to simultaneous global localization and fine segmentation of the vessels. The coarse branch employs a partial decoder to leverage high-level semantic features, enabling global localization of objects and suppression of irrelevant structures. The fine branch utilizes attention-parameterized skip connections to improve feature representations and improve boundary information. The outputs of the two branches are fused to generate accurate vessel segmentations. Extensive experiments conducted on a collected dataset demonstrate the superiority of CoFi-Net compared to state-of-the-art segmentation models for 3VV segmentation, indicating its great potential for enhancing CHD diagnostic efficiency in clinical practice. Furthermore, CoFi-Net outperforms other deep learning models in breast lesion segmentation on a public breast ultrasound dataset, despite not being specifically designed for this task, demonstrating its potential and robustness for various segmentation tasks.

Cardiac adaptation and malformation in twin-twin transfusion syndrome and selective fetal growth restriction: A systematic review.

OBJECTIVES: This systematic review explores cardiac adaptation in monochorionic (MC) twins with twin-twin transfusion syndrome (TTTS) or selective fetal growth restriction (sFGR) and assesses the risk of congenital heart defects (CHDs). METHODS: Adhering to PRISMA guidelines, 63 studies were reviewed (49 on cardiac adaptation, 13 on CHD, one on both). A narrative synthesis of cardiac adaptation patterns was performed. Additionally, a meta-analysis compared the livebirth prevalence of CHD in TTTS and sFGR against uncomplicated MC twins. RESULTS: In TTTS recipients, cardiac function may be impaired for diastolic, systolic, as well as global functions, while in donors, cardiac function is generally preserved. In sFGR, large twins may show hypertrophic cardiomyopathy, and small twins may show impaired systolic function. Co-occurrence of TTTS and sFGR magnifies cardiac impact but is often underreported. Meta-analysis for CHD prevalence revealed a relative risk ratio of 3.5 (95% CI: 2.5-4.9) for TTTS and 2.2 (95%CI: 1.3-3.5) for sFGR compared with uncomplicated MC twins. CONCLUSIONS: This study highlights the well-documented cardiac adaptation in TTTS, contrasting with limited understanding in sFGR. Elevated CHD risks were observed in both conditions. Enhanced cardiovascular surveillance is warranted in complicated MC twin pregnancies. Future research should explore cardiac adaptation in sFGR and its long-term consequences.