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OBJECTIVE: Fetal venous system malformations frequently coincide with cardiac or extracardiac anomalies. This study explores our experience with an integrated fetal echocardiography approach and analyzes the characteristics and outcomes of fetal venous system disorders. MATERIALS AND METHODS: We conducted a retrospective study with 7048 pregnant women (7255 fetuses) who underwent complete two-dimensional (2D) fetal echocardiographic examinations. We primarily employed an integrated 2D approach. Three-/four-dimensional (3D/4D) spatiotemporal image correlation was supplemental. Fetal venous disorders were classified into 3 groups: cardinal (Group 1), umbilical and vitelline (Group 2), and pulmonary (Group 3) systems, based on embryological-anatomical considerations. Maternofetal data were recorded alongside imaging diagnoses. RESULTS: Congenital venous malformations were identified in 98 fetuses, yielding a prevalence of 1.35% (98/7255). Six participants had coexisting venous disorders from different groups. Group 1 included 48 fetuses with persistent left superior vena cava (LSVC) and 3 others (unidentified brachiocephalic vein, left inferior vena cava (IVC), and interrupted IVC with azygous continuation to SVC). Group 2 had 39 fetuses with persistent right umbilical vein and 7 with umbilical-portal-ductus venosus disorders. Group 3 had 7 fetuses with pulmonary venous return disorders. Group 2 showed the most favorable outcomes (alive and without neonatal death), while Group 3 exhibited the poorest. Associated cardiac defects were observed in 43.1% of Group 1, 8.7% of Group 2, and 57.1% of Group 3 (P < 0.001), displaying a broad spectrum of non-specific anomalies. Meanwhile, Group 2 had a greater occurrence of a single venous disorder (93.5%) compared to Group 1 (88.2%) and Group 3 (57.1%) (P = 0.020). CONCLUSION: Our approach offers an integrated strategy for assessing the fetal venous system during fetal echocardiography, providing multiple views to characterize venous anomalies. The presence of a fetal venous disorder may indicate the coexistence of more severe abnormalities, and the prognosis depends on associated anomalies or the venous disorders per se.

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PURPOSE OF REVIEW: Speckle tracking echocardiography (STE)-derived measures of myocardial mechanics, referred to herewithin as strain measurements, directly assess myocardial contractility and provide a nuanced assessment of ventricular function. This review provides an overview of strain measurements and their current clinical value and utility in decision making in pediatric cardiology. RECENT FINDINGS: Strain measurements are advancing understanding of how cardiac dysfunction occurs in children with acquired and congenital heart disease (CHD). Global strain measurements can detect early changes in cardiac function and are reliable methods of serially monitoring systolic function in children. Global strain measurements are increasingly reported in echocardiographic assessment of ventricular function alongside ejection fraction. Research is increasingly focused on how strain measurements can help improve clinical management, risk stratification, and prognostic insight. Although more research is needed, preliminary studies provide hope that there will be clinical benefit for strain in pediatric cardiology management. SUMMARY: Strain measurements provide a more detailed assessment of ventricular function than conventional measures of echocardiographic functional assessment. Strain measurements are increasingly being used to advance understanding of normal and abnormal myocardial contractility, to increase sensitivity to detect early cardiac dysfunction, and to improve prognostic management in children with acquired and CHD.

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BACKGROUND: High-fidelity cardiac magnetic resonance (MR) imaging plays a pivotal role in the surveillance of congenital heart disease (CHD) and aortopathy. OBJECTIVE: We aimed to evaluate the quality and accuracy of free breathing, ECG-gated noncontrast three-dimensional (3D) balanced steady-state free precession (bSSFP) in cases of CHDs and aortopathies using contrast-enhanced 3D bSSFP as a reference. We also used one of our routinely used non-ECG-gated 2D-single-shot (SSh) bSSFP sequence as an adjunct to noncontrast 3D bSSFP. MATERIALS AND METHODS: Institutional review board approval was obtained to perform a systematic retrospective analysis of image quality and vascular measurements. Patients with CHD and aortopathy, who were undergoing clinically indicated contrast-enhanced 3D bSSFP, were prospectively identified to also undergo additional noncontrast 3D bSSFP and 2D SSh bSSFP imaging as part of a clinical quality improvement initiative aimed at reducing the use of contrast when feasible. Two readers, blinded to each other's evaluations, graded image quality on a 5-point Likert scale and performed vascular measurements in separate sessions for both 3D bSSFP images. They also reported the visibility of various mediastinal great vessels on 2D SSh bSSFP images. Raw agreement, the weighted kappa statistic, and intra-class correlation coefficients (ICCs) were computed to assess the consistency and agreement between the two readers. Comparative analysis of noncontrast and contrast-enhanced 3D bSSFP imaging was performed in adult and pediatric patients using a two-sided paired t-test and Bland-Altman analysis. A P-value < 0.05 was considered significant for all inference testing. RESULTS: A total of 29 patients (17 males, median age 20.3 years, interquartile range (IQR) 12.5, age range 7-39 years), including 11 pediatric patients under the age of 18 years (6 males, median age 14.5 years, IQR 4.0, age range 7-17 years), underwent retrospective analysis. The overall image quality score for contrast-enhanced 3D bSSFP was significantly higher (P < 0.0001) than that of noncontrast 3D bSSFP for both all subjects (4.4 ± 0.2, range 4.0-4.9 vs 3.7 ± 0.4, range 3.1-4.7) and only pediatric subjects (4.3 ± 0.3, range 4.0-4.9 vs 3.6 ± 0.5, range 3.1-4.4). By combining noncontrast 3D bSSFP and 2D bSSFP, reader 1 and reader 2 rated 423 and 420 vessels diagnostic, respectively, in a total of 435 vessel segments. All landmarks showed similar mean vessel diameters without significant differences between noncontrast and contrast-enhanced 3D bSSFP MR angiography (r = 0.99, bias -0.31 mm, 95% limits of agreement -2.04 mm to 1.43 mm). CONCLUSIONS: Although contrast-enhanced images had better overall image quality, an imaging protocol consisting of noncontrast 2D SSh bSSFP and 3D bSSFP whole-chest images provides diagnostically adequate image quality, and accurate vascular measurements, comparable to free-breathing contrast-enhanced 3D bSSFP in both children and adults with CHD and aortopathies.

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INTRODUCTION: Understanding the variations of abdominal vascular structures is important for preventing complications of abdominal surgical procedures for gastrointestinal disease such as necrotizing enterocolitis or others that may arise in patients with congenital cardiac disease. We analysed the coeliac trunk and its branches in children with congenital heart disease to determine whether there is a greater prevalence of associated vascular abnormalities. METHODS: We retrospectively analysed thoracic computed tomography (CT) angiograms performed in our hospital in paediatric patients with congenital heart disease. We documented the anatomical variations observed in abdominal sections in which the coeliac trunk and hepatic arteries were included in the field of view. We used the Uflacker classification to describe anatomical variants of the coeliac trunk, and the Michels classification and its modified version (Hiatt classification) to describe the anatomy of the hepatic artery system. RESULTS: Our study included 178 patients with congenital heart disease. We identified coeliac trunk variants in 10.7% of the patients. Gastrosplenic trunk was to the most prevalent variant, amounting to 5.6% of total cases. We found hepatic artery variations in 19.1% of the patients. According to the Michels classification, the prevalence of accessory left hepatic artery arising from the left gastric artery as 4.5%, compared to 6.7% based on the Hiatt classification. CONCLUSION: The prevalence of coeliac trunk and hepatic artery variations in patients with congenital heart disease was not greater in our study compared to other series in the literature. Clinicians must be vigilant about the variations detected in multislice CT scans to avoid complications resulting from vascular abnormalities, especially in patients who undergo abdominal surgery.

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Echocardiography is one the most commonly used imaging modalities for the diagnosis of congenital heart disease. Echocardiographic image analysis is crucial to obtaining accurate cardiac anatomy information. Semantic segmentation models can be used to precisely delimit the borders of the left ventricle, and allow an accurate and automatic identification of the region of interest, which can be extremely useful for cardiologists. In the field of computer vision, convolutional neural network (CNN) architectures remain dominant. Existing CNN approaches have proved highly efficient for the segmentation of various medical images over the past decade. However, these solutions usually struggle to capture long-range dependencies, especially when it comes to images with objects of different scales and complex structures. In this study, we present an efficient method for semantic segmentation of echocardiographic images that overcomes these challenges by leveraging the self-attention mechanism of the Transformer architecture. The proposed solution extracts long-range dependencies and efficiently processes objects at different scales, improving performance in a variety of tasks. We introduce Shifted Windows Transformer models (Swin Transformers), which encode both the content of anatomical structures and the relationship between them. Our solution combines the Swin Transformer and U-Net architectures, producing a U-shaped variant. The validation of the proposed method is performed with the EchoNet-Dynamic dataset used to train our model. The results show an accuracy of 0.97, a Dice coefficient of 0.87, and an Intersection over union (IoU) of 0.78. Swin Transformer models are promising for semantically segmenting echocardiographic images and may help assist cardiologists in automatically analyzing and measuring complex echocardiographic images.

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Congenital heart disease (CHD) encompasses a spectrum of cardiovascular structural abnormalities, often requiring customized treatment plans for individual patients. Computational modeling and analysis of these unique cardiac anatomies can improve diagnosis and treatment planning and may ultimately lead to improved outcomes. Deep learning (DL) methods have demonstrated the potential to enable efficient treatment planning by automating cardiac segmentation and mesh construction for patients with normal cardiac anatomies. However, CHDs are often rare, making it challenging to acquire sufficiently large patient cohorts for training such DL models. Generative modeling of cardiac anatomies has the potential to fill this gap via the generation of virtual cohorts; however, prior approaches were largely designed for normal anatomies and cannot readily capture the significant topological variations seen in CHD patients. Therefore, we propose a type- and shape-disentangled generative approach suitable to capture the wide spectrum of cardiac anatomies observed in different CHD types and synthesize differently shaped cardiac anatomies that preserve the unique topology for specific CHD types. Our DL approach represents generic whole heart anatomies with CHD type-specific abnormalities implicitly using signed distance fields (SDF) based on CHD type diagnosis. To capture the shape-specific variations, we then learn invertible deformations to morph the learned CHD type-specific anatomies and reconstruct patient-specific shapes. After training with a dataset containing the cardiac anatomies of 67 patients spanning 6 CHD types and 14 combinations of CHD types, our method successfully captures divergent anatomical variations across different types and the meaningful intermediate CHD states across the spectrum of related CHD diagnoses. Additionally, our method demonstrates superior performance in CHD anatomy generation in terms of CHD-type correctness and shape plausibility. It also exhibits comparable generalization performance when reconstructing unseen cardiac anatomies. Moreover, our approach shows potential in augmenting image-segmentation pairs for rarer CHD types to significantly enhance cardiac segmentation accuracy for CHDs. Furthermore, it enables the generation of CHD cardiac meshes for computational simulation, facilitating a systematic examination of the impact of CHDs on cardiac functions.

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A girl in middle childhood presented with glaucoma in her right eye along with segmental haemangiomas on the right side of the face and neck. Magnetic resonance angiography of the brain showed hypoplasia of the right internal carotid artery, leading to the diagnosis of posterior fossa malformations, haemangioma, arterial anomalies, cardiac defects and eye abnormalities (PHACE) syndrome. High-definition anterior segment ocular coherence tomography (AS-OCT) of the right eye showed an absence of Schlemm's canal and a hyperreflective membrane over the trabecular meshwork. The presence of this angle dysgenesis on AS-OCT, a novel finding in this disease, explained the elevated intraocular pressure in the right eye. The embryological basis for the development of angle dysgenesis might help better understand the pathogenesis of PHACE syndrome.

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Shone's syndrome (SS) is a rare congenital cardiac anomaly characterized by a spectrum of developmental abnormalities. It predominantly presents as consisting of a variety of left ventricular inflow and outflow tract lesions, with inflow tract lesions typically including parachute mitral valve and supravalvular mitral ring. However, reports of SS involving double-orifice mitral valve are scarce.

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Congenital heart disease (CHD) represents a significant challenge in prenatal care due to low prenatal detection rates. Artificial Intelligence (AI) offers promising avenues for precise CHD prediction. In this study we conducted a systematic review according to the PRISMA guidelines, investigating the landscape of AI applications in prenatal CHD detection. Through searches on PubMed, Embase, and Web of Science, 621 articles were screened, yielding 28 relevant studies for analysis. Deep Learning (DL) emerged as the predominant AI approach. Data types were limited to ultrasound and MRI sequences mainly. This comprehensive analysis provides valuable insights for future research and clinical practice in CHD detection using AI applications.

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We describe the safe and effective percutaneous pulmonary thrombectomy in an 18-year-old female with a Fontan circulation using the FlowTriever® device (Inari Medical®, Irvine, US). Aspiration thrombectomy of both pulmonary arteries was performed using 24 and 16 F FlowTriever® catheters retrieving large amounts of thrombus material resulting in near total angiographic recanalization.

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Patients with functionally univentricular hearts are usually palliated surgically. There have been several reports of successful attempts to complete the Fontan procedure without surgery. The pathways created at the time of the preconditioning were largely reminiscent of the lateral tunnel Fontan. However, this approach is still confidentially limited to a small number of centers. In 2013, we designed a circuit that mimics the actual surgical technique of extracardiac total cavopulmonary connection to allow for transcatheter completion in an animal study. A polytetrafluoroethylene conduit was connected between the pulmonary artery and the inferior vena cava (IVC). The superior anastomosis was occluded to avoid flow between IVC and superior vena cava (SVC). The conduit was connected to the right atrium (RA) and a large fenestration was created to allow free flow from the IVC to the RA. Extrapolating our approach, a center reported the successful transcatheter completion of an extracardiac Fontan in a 6-year-old child. However, this technique is not directly transposable to our population of patients who require preconditioning in infancy. We report here an innovative extension of this technique that may allow preparing patients in infancy, ideally at the time of the Glenn in the future, to receive an extracardiac Fontan at 2 years/11 kg without additional surgery.

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Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

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BACKGROUND: Liver fibrosis has been recognized as a long-term morbidity associated with Fontan circulation (Fontan-associated liver disease, FALD). The pathophysiology of FALD is not completely understood and abnormal flow dynamics may be associated with this condition. Liver hemodynamics can be quantitatively evaluated with four-dimensional phase-contrast flow magnetic resonance imaging (4D PC flow MRI). The study aimed to evaluate suitability of liver 4D PC flow MRI in Fontan patients and relate flow measurements to normal values and FALD severity. PATIENTS AND METHODS: Twenty-two Fontan patients were examined by 4D PC flow MRI at 1.5 Tesla to assess mesenteric, portal, splenic, and hepatic venous blood flow. Severity of FALD was graded based on routine screening, including abdominal ultrasound and laboratory tests. RESULTS: Median age was 18.5 (interquartile range, IQR 15.5-20.2) years. FALD was graded as "none or mild" in 16 and as "moderate to severe" in six cases. Ten patients presented at least one feature of portal hypertension (ascites, splenomegaly, or thrombocytopenia). For the entire cohort, blood flow in the superior mesenteric, splenic, and portal vein was lower than reported in the literature. No significant differences were observed in relation to FALD severity. Features of portal hypertension were associated with a higher splenic vein blood flow (0.34 ± 0.17 vs. 0.20 ± 0.07 l/min, p = 0.046). Splenic vein blood flow was negatively correlated to platelet count (r = -0.590, p = 0.005). CONCLUSIONS: 4D PC flow MRI appears suitable to assess liver hemodynamics in Fontan patients and integration into clinical follow-up might help to improve our understanding of FALD.

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PURPOSE: The detection of congenital heart disease (CHD) before neonatal surgery is crucial for anaesthetic and perioperative management. There are no established criteria for pre-operative echocardiography in neonates. We aimed to survey current practice in the United Kingdom and evaluate the reliability of antenatal screening and postnatal clinical assessment in detecting CHD before surgery. METHOD: A 9-point questionnaire was sent to all paediatric surgical centres in the United Kingdom to assess their practice. Subsequently, a single-centre retrospective review of all neonatal surgery over 5 years (2015-2020) was conducted in our tertiary paediatric/neonatal hospital. Data included pre-operative clinical assessment, performance of chest radiograph and echocardiography. Indications for echocardiography were categorised and assessed using sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: All 26 paediatric surgical centres responded to our survey. 23/26 (88.5%) did not have established criteria or guidelines for pre-operative echocardiography. There was a large variation in which surgical conditions required a pre-operative scan and whether a normal clinical examination was considered sufficient to not require one. For the retrospective review, 454 patients were identified. There were 40 cases with CHDs (8.8%), 13 were classed as major or moderate. Indications for echocardiography were categorised into abnormal foetal cardiac screening, medical/surgical conditions associated with CHD and an abnormal cardiorespiratory examination. Sensitivity, specificity, positive predictive value and negative predictive value for major and moderate CHD were 46%, 99%, 67%, 98% for abnormal foetal screening, 46%, 97%, 35%, 98% for associated medical conditions, 62%, 66%, 6%, 98% for associated surgical conditions, and 100%, 66%, 9%, 100% for abnormal clinical examination. CONCLUSION: The use of pre-operative echocardiography in neonates is not standardised across the UK. The results from our cohort demonstrate that foetal echocardiography is not sufficient to capture all major and moderate CHDs, but the absence of abnormal clinical examination is highly reliable in ruling out them out. Specifying a list of medical/surgical of conditions associated with CHD warranting pre-operative echocardiography may improve yield, but this depends on the availability of resources and expertise.

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Evaluation of the fetal heart involves two approaches. The first describes a screening protocol in which the heart is imaged in transverse planes that includes the four-chamber view (4CV), left and right outflow tracts, and the 3-vessel-tracheal view. The second approach is a fetal echocardiogram that requires additional cardiac images as well as evaluating ventricular function using diagnostic tools such as M-mode and pulsed Doppler ultrasound. Speckle tracking analysis of the ventricular and atrial endocardium of the fetal heart has focused primarily on computing longitudinal global strain. However, the technology enabling this measurement to occur has recently been adapted to enable the clinician to obtain numerous additional measurements of the size, shape, and contractility of the ventricles and atrial chambers. By using the increased number of measurements derived from speckle tracking analysis, we have reported the ability to screen for tetralogy of Fallot, D-transposition of the great arteries (D-TGA), and coarctation of the aorta by only imaging the 4CV. In addition, we have found that measurements derived from speckle tracking analysis of the ventricular and atrial chambers can be used to compute the risk for emergent neonatal balloon atrial septostomy in fetuses with D-TGA. The purpose of this review is to consolidate our experience in one source to provide perspective on the benefits of speckle tracking analysis to measure the size, shape, and contractility of the ventricles and atria imaged in the 4CV in fetuses with congenital heart defects.

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Patients with congenital heart disease often have cardiac anatomy that deviates significantly from normal, frequently requiring multiple heart surgeries. Image segmentation from a preoperative cardiovascular magnetic resonance (CMR) scan would enable creation of patient-specific 3D surface models of the heart, which have potential to improve surgical planning, enable surgical simulation, and allow automatic computation of quantitative metrics of heart function. However, there is no publicly available CMR dataset for whole-heart segmentation in patients with congenital heart disease. Here, we release the HVSMR-2.0 dataset, comprising 60 CMR scans alongside manual segmentation masks of the 4 cardiac chambers and 4 great vessels. The images showcase a wide range of heart defects and prior surgical interventions. The dataset also includes masks of required and optional extents of the great vessels, enabling fairer comparisons across algorithms. Detailed diagnoses for each subject are also provided. By releasing HVSMR-2.0, we aim to encourage development of robust segmentation algorithms and clinically relevant tools for congenital heart disease.

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