Why are congenital heart defects being missed?

Prenatally diagnosed congenital heart disease: the cost of maternal care

OBJECTIVE

Little is known regarding the effects of a prenatal diagnosis of congenital heart disease (CHD) on the cost of antenatal and delivery care. We sought to compare the maternal costs of care in pregnancies where the fetus or child was diagnosed prenatally vs. postnatally.

METHODS

Costs of maternal care were determined for pregnancies in which the fetus or child was diagnosed with CHD between 1997 and 2012 in the state of Utah. Cases of CHD were identified via a statewide birth defect surveillance program which included data on the timing of diagnosis, maternal demographic and clinical data, and linked to statewide inpatient maternal hospital discharge records. Antenatal testing costs were determined using Medicaid fee estimates and total facility costs were determined for all hospitalizations including delivery. The association of timing of diagnosis of CHD with costs was analyzed using univariable and multivariable models.

RESULTS

Of 2128 pregnancies included in the study, 36% had a fetus prenatally diagnosed with CHD. The prenatal diagnosis group was more likely to have a termination or stillbirth and were younger at delivery (gestational age 37.3 vs 38.0 weeks, p < .001). Labor induction and cesarean delivery rates were similar between groups. Antenatal testing and delivery hospitalization costs were higher in the prenatal diagnosis group: $5819 vs $4041 (p < .001) and $10,509 vs $7802 (p < .001), respectively. Patients in the prenatal diagnosis group had longer lengths of hospital stays (3.5 vs 2.4 d, p > .001). After controlling for significant differences between the groups, including lesion severity, the prenatal diagnosis remained directly associated with antenatal testing costs (+$1472), maternal hospitalization costs (+$2713), and maternal hospital length of stay (+1.0 d).

CONCLUSION

A prenatal diagnosis of fetal CHD was associated with increased prenatal costs, hospitalization costs, and hospital length of stay for affected pregnant patients.

Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes

Artificial intelligence (AI) is frequently used in non-medical fields to assist with automation and decision-making. The potential for AI in pediatric cardiology, especially in the echocardiography laboratory, is very high. There are multiple tasks AI is designed to do that could improve the quality, interpretation, and clinical application of echocardiographic data at the level of the sonographer, echocardiographer, and clinician. In this state-of-the-art review, we highlight the pertinent literature on machine learning in echocardiography and discuss its applications in the pediatric echocardiography lab with a focus on automation of the pediatric echocardiogram and the use of echo data to better understand physiology and outcomes in pediatric cardiology. We also discuss next steps in utilizing AI in pediatric echocardiography.

Impact of Socioeconomic Status and Residence Distance on Infant Heart Disease Outcomes in Canada

Background Socioeconomic status (SES) impacts clinical outcomes associated with severe congenital heart disease (sCHD). We examined the impact of SES and remoteness of residence (RoR) on congenital heart disease (CHD) outcomes in Canada, a jurisdiction with universal health insurance. Methods and Results All infants born in Canada (excluding Quebec) from 2008 to 2018 and hospitalized with CHD requiring intervention in the first year were identified. Neighborhood level SES income quintiles were calculated, and RoR was categorized as residing <100 km, 100 to 299 km, or >300 km from the closest of 7 cardiac surgical programs. In-hospital mortality at <1 year was the primary outcome, adjusted for preterm birth, low birth weight, and extracardiac pathology. Among 7711 infants, 4485 (58.2%) had moderate CHD (mCHD) and 3226 (41.8%) had sCHD. Overall mortality rate was 10.5%, with higher rates in sCHD than mCHD (13.3% versus 8.5%, respectively). More CHD infants were in the lowest compared with the highest SES category (27.1% versus 15.0%, respectively). The distribution of CHD across RoR categories was 52.3%, 21.3%, and 26.4% for <100 km, 100 to 299 km, and >300 km, respectively. Although SES and RoR had no impact on sCHD mortality, infants with mCHD living >300 km had a higher risk of mortality relative to those living <100 km (adjusted odds ratio [aOR], 1.43 [95% CI, 1.11-1.84]). Infants with mCHD within the lowest SES quintile and living farthest away had the highest risk for mortality (aOR, 1.74 [95% CI, 1.08-2.81]). Conclusions In Canada, neither RoR nor SES had an impact on outcomes of infants with sCHD. Greater RoR, however, may contribute to higher risk of mortality among infants with mCHD.

Circulating microRNA: Myocardium-derived prenatal biomarker of ventricular septal defects

Background: Recently, circulating microRNAs (miRNAs) from maternal blood and amniotic fluid have been used as biomarkers for ventricular septal defect (VSD) diagnosis. However, whether circulating miRNAs are associated with fetal myocardium remains unknown.

Methods: Dimethadione (DMO) induced a VSD rat model. The miRNA expression profiles of the myocardium, amniotic fluid and maternal serum were analyzed. Differentially expressed microRNAs (DE-microRNAs) were verified by qRT–PCR. The target gene of miR-1-3p was confirmed by dual luciferase reporter assays. Expression of amniotic fluid-derived DE-microRNAs was verified in clinical samples.

Results: MiRNAs were differentially expressed in VSD fetal rats and might be involved in cardiomyocyte differentiation and apoptosis. MiR-1-3p, miR-1b and miR-293-5p were downregulated in the myocardium and upregulated in amniotic fluid/maternal serum. The expression of amniotic fluid-derived DE-microRNAs (miR-1-3p, miR-206 and miR-184) was verified in clinical samples. Dual luciferase reporter assays confirmed that miR-1-3p directly targeted SLC8A1/NCX1.

Conclusion: MiR-1-3p, miR-1b and miR-293-5p are downregulated in VSD myocardium and upregulated in circulation and may be released into circulation by cardiomyocytes. MiR-1-3p targets SLC8A1/NCX1 and participates in myocardial apoptosis. MiR-1-3p upregulation in circulation is a direct and powerful indicator of fetal VSD and is expected to serve as a prenatal VSD diagnostic marker.

Artificial intelligence in perinatal diagnosis and management of congenital heart disease

Prenatal diagnosis and management of congenital heart disease (CHD) has progressed substantially in the past few decades. Fetal echocardiography can accurately detect and diagnose approximately 85% of cardiac anomalies. The prenatal diagnosis of CHD results in improved care, with improved risk stratification, perioperative status and survival. However, there is much work to be done. A minority of CHD is actually identified prenatally. This seemingly incongruous gap is due, in part, to diminished recognition of an anomaly even when present in the images and the need for increased training to obtain specialized cardiac views. Artificial intelligence (AI) is a field within computer science that focuses on the development of algorithms that "learn, reason, and self-correct" in a human-like fashion. When applied to fetal echocardiography, AI has the potential to improve image acquisition, image optimization, automated measurements, identification of outliers, classification of diagnoses, and prediction of outcomes. Adoption of AI in the field has been thus far limited by a paucity of data, limited resources to implement new technologies, and legal and ethical concerns. Despite these barriers, recognition of the potential benefits will push us to a future in which AI will become a routine part of clinical practice.

Disparities in surgical outcomes of neonates with congenital heart disease across regions, centers, and populations

OBJECTIVE

To summarize existing literature on neonatal disparities in congenital heart disease surgical outcomes and identify potential policies to address these disparities.

FINDING

Disparities in outcomes for neonatal congenital heart surgery were largely published under four domains: race/ethnicity, insurance type, neighborhood/socioeconomic status, and cardiac center characteristics. While existing research identifies associations between these domains and mortality, more nuanced analyses are emerging to understand the mediators between these domains and other non-mortality outcomes, as well as potential interventions and policies to reduce disparities. A broader look into social determinants of health (SDOH), prenatal diagnosis, proximity of birth to a cardiac surgical center, and post-surgical outpatient and neurodevelopmental follow-up may accelerate interventions to mitigate disparities in outcomes.

CONCLUSION

Understanding the mechanisms of how SDOH relate to neonatal surgical outcomes is paramount, as disparities research in neonatal congenital heart surgery continues to shift from identification and description, to intervention and policy.

Application of machine learning in screening for congenital heart diseases using fetal echocardiography

There is a growing body of literature supporting the utilization of machine learning (ML) to improve diagnosis and prognosis tools of cardiovascular disease. The current study was to investigate the impact that the ML framework may have on the sensitivity of predicting the presence or absence of congenital heart disease (CHD) using fetal echocardiography. A comprehensive fetal echocardiogram including 2D cardiac chamber quantification, valvar assessments, assessment of great vessel morphology, and Doppler-derived blood flow interrogation was recorded. The postnatal echocardiogram was used to ascertain the diagnosis of CHD. A random forest (RF) algorithm with a nested tenfold cross-validation was used to train models for assessing the presence of CHD. The study population was derived from a database of 3910 singleton fetuses with maternal age of 28.8 ± 5.2 years and gestational age at the time of fetal echocardiography of 22.0 weeks (IQR 21-24). The proportion of CHD was 14.1% for the studied cohort confirmed by post-natal echocardiograms. Our proposed RF-based framework provided a sensitivity of 0.85, a specificity of 0.88, a positive predictive value of 0.55 and a negative predictive value of 0.97 to detect the CHD with the mean of mean ROC curves of 0.94 and the mean of mean PR curves of 0.84. Additionally, six first features, including cardiac axis, peak velocity of blood flow across the pulmonic valve, cardiothoracic ratio, pulmonary valvar annulus diameter, right ventricular end-diastolic diameter, and aortic valvar annulus diameter, are essential features that play crucial roles in adding more predictive values to the model in detecting patients with CHD. ML using RF can provide increased sensitivity in prenatal CHD screening with very good performance. The incorporation of ML algorithms into fetal echocardiography may further standardize the assessment for CHD.

Incremental Detection of Severe Congenital Heart Disease by Fetal Echocardiography Following a Normal Second Trimester Ultrasound Scan in Québec, Canada

Background:

The benefit of fetal echocardiograms (FE) to detect severe congenital heart diseases (SCHD) in the setting of a normal second-trimester ultrasound is unclear. We aimed to assess whether the increase in SCHD detection rates when FE are performed for risk factors in the setting of a normal ultrasound was clinically significant to justify the resources needed.

Methods:

This is a multicenter, population-based, retrospective cohort study, including all singleton pregnancies and offspring in Quebec (Canada) between 2007 and 2015. Administrative health care data were linked with FE clinical data to gather information on prenatal diagnosis of CHD, indications for FE, outcomes of pregnancy and offspring, postnatal diagnosis of CHD, cardiac interventions, and causes of death. The difference between the sensitivity to detect SCHD with and without FE for risk factors was calculated using generalized estimating equations with a noninferiority margin of 5 percentage points.

Results:

A total of 688 247 singleton pregnancies were included, of which 30 263 had at least one FE. There were 1564 SCHD, including 1071 that were detected prenatally (68.5%). There were 12 210 FE performed for risk factors in the setting of a normal second-trimester ultrasound, which led to the detection of 49 additional cases of SCHD over 8 years. FE referrals for risk factors increased sensitivity by 3.1 percentage points (95% CI, 2.3–4.0; P<0.0001 for noninferiority).

Conclusions:

In the setting of a normal second-trimester ultrasound, adding a FE for risk factors offered low incremental value to the detection rate of SCHD in singleton pregnancies. The current ratio of clinical gains versus the FE resources needed to screen for SCHD in singleton pregnancies with isolated risk factors does not seem favorable. Further studies should evaluate whether these resources could be better allocated to increase SCHD sensitivity at the ultrasound level, and to help decrease heterogeneity between regions, institutions and operators.

Ventilatory management of critically ill children in the emergency setting, during transport and retrieval

Critical illness in children is uncommon. The acute stabilization and resuscitation of critically ill children remains challenging to even the most experienced operator. Cardiorespiratory illness represents the largest subgroup of diseases causing critical illness and, thus adds a layer of complexity and additional challenge to the safe intubation and establishment of effective ventilation of this group of children. Children have unique physiological and anatomical differences to adults, and present the team involved in their resuscitation and stabilization with challenges exaggerated by critical illness. The consideration of pathophysiological implications of disease and the equipment available during transport and retrieval from the roadside or nonspecialist setting to pediatric intensive care allows the clinician involved in resuscitation, stabilization, and establishment of ventilation to employ targeted strategies to optimize ventilatory success. This review focuses on the types of ventilatory challenges that must be addressed when managing critically ill children in the local settings in which they present, and the resources available to optimize the outcome prior to and during transfer to a higher level of care.

First-trimester ultrasound detection of fetal heart anomalies: systematic review and meta-analysis

OBJECTIVES

To determine the diagnostic accuracy of ultrasound at 11-14 weeks' gestation in the detection of fetal cardiac abnormalities and to evaluate factors that impact the detection rate.

METHODS

This was a systematic review of studies evaluating the diagnostic accuracy of ultrasound in the detection of fetal cardiac anomalies at 11-14 weeks' gestation, performed by two independent reviewers. An electronic search of four databases (MEDLINE, EMBASE, Web of Science Core Collection and The Cochrane Library) was conducted for studies published between January 1998 and July 2020. Prospective and retrospective studies evaluating pregnancies at any prior level of risk and in any healthcare setting were eligible for inclusion. The reference standard used was the detection of a cardiac abnormality on postnatal or postmortem examination. Data were extracted from the included studies to populate 2 × 2 tables. Meta-analysis was performed using a random-effects model in order to determine the performance of first-trimester ultrasound in the detection of major cardiac abnormalities overall and of individual types of cardiac abnormality. Data were analyzed separately for high-risk and non-high-risk populations. Preplanned secondary analyses were conducted in order to assess factors that may impact screening performance, including the imaging protocol used for cardiac assessment (including the use of color-flow Doppler), ultrasound modality, year of publication and the index of sonographer suspicion at the time of the scan. Risk of bias and quality assessment were undertaken for all included studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool.

RESULTS

The electronic search yielded 4108 citations. Following review of titles and abstracts, 223 publications underwent full-text review, of which 63 studies, reporting on 328 262 fetuses, were selected for inclusion in the meta-analysis. In the non-high-risk population (45 studies, 306 872 fetuses), 1445 major cardiac anomalies were identified (prevalence, 0.41% (95% CI, 0.39-0.43%)). Of these, 767 were detected on first-trimester ultrasound examination of the heart and 678 were not detected. First-trimester ultrasound had a pooled sensitivity of 55.80% (95% CI, 45.87-65.50%), specificity of 99.98% (95% CI, 99.97-99.99%) and positive predictive value of 94.85% (95% CI, 91.63-97.32%) in the non-high-risk population. The cases diagnosed in the first trimester represented 63.67% (95% CI, 54.35-72.49%) of all antenatally diagnosed major cardiac abnormalities in the non-high-risk population. In the high-risk population (18 studies, 21 390 fetuses), 480 major cardiac anomalies were identified (prevalence, 1.36% (95% CI, 1.20-1.52%)). Of these, 338 were detected on first-trimester ultrasound examination and 142 were not detected. First-trimester ultrasound had a pooled sensitivity of 67.74% (95% CI, 55.25-79.06%), specificity of 99.75% (95% CI, 99.47-99.92%) and positive predictive value of 94.22% (95% CI, 90.22-97.22%) in the high-risk population. The cases diagnosed in the first trimester represented 79.86% (95% CI, 69.89-88.25%) of all antenatally diagnosed major cardiac abnormalities in the high-risk population. The imaging protocol used for examination was found to have an important impact on screening performance in both populations (P < 0.0001), with a significantly higher detection rate observed in studies using at least one outflow-tract view or color-flow Doppler imaging (both P < 0.0001). Different types of cardiac anomaly were not equally amenable to detection on first-trimester ultrasound.

CONCLUSIONS

First-trimester ultrasound examination of the fetal heart allows identification of over half of fetuses affected by major cardiac pathology. Future first-trimester screening programs should follow structured anatomical assessment protocols and consider the introduction of outflow-tract views and color-flow Doppler imaging, as this would improve detection rates of fetal cardiac pathology. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Maternal serum-derived exosomal lactoferrin as a marker in detecting and predicting ventricular septal defect in fetuses

Among different types of congenital heart diseases, ventricular septal defect is the most frequently diagnosed type and is frequently missed in early prenatal screening programs. Herein, we explored the role of maternal serum-derived exosomes in detecting and predicting ventricular septal defect in fetuses in the early stage of pregnancy. A total of 104 pregnant women consisting of 52 ventricular septal defect cases and 52 healthy controls were recruited. TMT/iTRAQ proteomic analysis uncovered 15 maternal serum exosomal proteins, which showed differential expression between ventricular septal defect and control groups. Among these, four down-regulated proteins, lactoferrin, SBSN, DCD, and MBD3, were validated by Western blot. The protein lactoferrin was additionally verified by ELISA which was able to distinguish ventricular septal defects from controls with area under the ROC curve (AUC) 0.804 (p < 0.001). Our findings reveal that lactoferrin in maternal serum-derived exosomes may be a potential biomarker for non-invasive prenatal diagnosis of fetal ventricular septal defects.

Evaluation of Fetal Cardiac Size and Shape: A New Screening Tool to Identify Fetuses at Risk for Tetralogy of Fallot

OBJECTIVE

Prenatal detection rates for tetralogy of Fallot (TOF) vary between 23 and 85.7%, in part because of the absence of significant structural abnormalities of the 4-chamber view (4CV), as well as the relative difficulty in detection of abnormalities during the screening examination of the outflow tracts. The purpose of this study was to evaluate whether the 4CV and ventricles in fetuses with TOF may be characterized by abnormalities of size and shape of these structures.

METHODS

This study retrospectively evaluated 44 fetuses with the postnatal diagnosis of TOF. Measurements were made from the 4CV (end-diastolic length, width, area, global sphericity index, and cardiac axis) and the right (RV) and left (LV) ventricles (area, length, 24-segment transverse widths, sphericity index, and RV/LV ratios). Logistic regression analysis was performed to identify variables that might separate fetuses with TOF from normal controls.

RESULTS

The mean gestational age at the time of the last examination prior to delivery was 28 weeks 5 days (SD 4 weeks, 4 days). The mean z-scores were significantly lower in fetuses with TOF for the 4CV and RV and LV measurements of size and shape. Logistic regression analysis identified simple linear measurements of the 4CV, RV, and LV that had a sensitivity of 90.9 and specificity of 98.5% that outperformed the 4CV cardiac axis (sensitivity of 22.7%) as a screening tool for TOF.

CONCLUSIONS

Measurements of the 4CV, RV, and LV can be used as an adjunct to the outflow tract screening examination to identify fetuses with TOF.

The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics - an Assessment of the State of Play

The long-awaited progress in digitalisation is generating huge amounts of medical data every day, and manual analysis and targeted, patient-oriented evaluation of this data is becoming increasingly difficult or even infeasible. This state of affairs and the associated, increasingly complex requirements for individualised precision medicine underline the need for modern software solutions and algorithms across the entire healthcare system. The utilisation of state-of-the-art equipment and techniques in almost all areas of medicine over the past few years has now indeed enabled automation processes to enter - at least in part - into routine clinical practice. Such systems utilise a wide variety of artificial intelligence (AI) techniques, the majority of which have been developed to optimise medical image reconstruction, noise reduction, quality assurance, triage, segmentation, computer-aided detection and classification and, as an emerging field of research, radiogenomics. Tasks handled by AI are completed significantly faster and more precisely, clearly demonstrated by now in the annual findings of the ImageNet Large-Scale Visual Recognition Challenge (ILSVCR), first conducted in 2015, with error rates well below those of humans. This review article will discuss the potential capabilities and currently available applications of AI in gynaecological-obstetric diagnostics. The article will focus, in particular, on automated techniques in prenatal sonographic diagnostics.

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time

OBJECTIVE

Advances in artificial intelligence (AI) have demonstrated potential to improve medical diagnosis. We piloted the end-to-end automation of the mid-trimester screening ultrasound scan using AI-enabled tools.

METHODS

A prospective method comparison study was conducted. Participants had both standard and AI-assisted US scans performed. The AI tools automated image acquisition, biometric measurement, and report production. A feedback survey captured the sonographers' perceptions of scanning.

RESULTS

Twenty-three subjects were studied. The average time saving per scan was 7.62 min (34.7%) with the AI-assisted method (p < 0.0001). There was no difference in reporting time. There were no clinically significant differences in biometric measurements between the two methods. The AI tools saved a satisfactory view in 93% of the cases (four core views only), and 73% for the full 13 views, compared to 98% for both using the manual scan. Survey responses suggest that the AI tools helped sonographers to concentrate on image interpretation by removing disruptive tasks.

CONCLUSION

Separating freehand scanning from image capture and measurement resulted in a faster scan and altered workflow. Removing repetitive tasks may allow more attention to be directed identifying fetal malformation. Further work is required to improve the image plane detection algorithm for use in real time.

Prenatal diagnosis and planned peripartum care improve perinatal outcome of fetuses with transposition of the great arteries and intact ventricular septum in low-resource settings

OBJECTIVE

To report on the feasibility of establishing a regional prenatal referral network for critical congenital heart defects (CHDs) and its impact on perinatal outcome of fetuses with transposition of the great arteries and intact ventricular septum (TGA-IVS) in low-resource settings.

METHODS

This was a retrospective study of consecutive fetuses with a diagnosis of TGA-IVS between January 2011 and December 2019 in Kochi, Kerala, India. A regional network for prenatal diagnosis and referral of patients with critical CHDs was initiated in 2011. Pregnancy and early neonatal outcomes were reported. The impact of the timing of diagnosis (prenatal or after birth) on age at surgery, perinatal mortality and postoperative recovery was evaluated.

RESULTS

A total of 82 fetuses with TGA-IVS were included. Diagnosis typically occurred later on in gestation, at a median of 25 (interquartile range (IQR), 21-32) weeks. The majority (78.0%) of affected pregnancies resulted in live birth, most (84.4%) of which occurred in a specialist pediatric cardiac centers. Delivery in a specialist center, compared with delivery in a local maternity center, was associated with a significantly higher rate of surgical correction (98.1% vs 70.0%; P = 0.01) and overall lower neonatal mortality (3.7% vs 50%; P = 0.001). The proportion of cases undergoing arterial switch operation after prenatal diagnosis of TGA-IVS increased significantly, along with the prenatal detection rate, over the study period (2011-2015, 11.1% vs 2016-2019, 29.4%; P = 0.001). Median age at surgery was significantly lower in the prenatally diagnosed group than that in the postnatally diagnosed group (4 days (IQR, 1-23 days) vs 10 days (IQR, 1-91 days); P < 0.001). There was no significant difference in postoperative mortality (2.0% vs 3.6%; P = 0.49) between the two groups.

CONCLUSIONS

This study demonstrates the feasibility of creating a network for prenatal diagnosis and referral of patients with critical CHDs, such as TGA, in low-resource settings, that enables planned peripartum care in specialist pediatric cardiac centers and improved neonatal survival. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Prenatal detection of congenital heart disease - results of a Swedish screening program 2013-2017

Background

This report evaluates results of a screening program on prenatal detection of congenital heart defects in a geographical cohort of western Sweden between January 1st, 2013 and June 31st, 2017. During the study period 88,230 children were born in VGR.

Methods

Retrospective data on pregnant women from the Västra Götaland region that were referred to fetal cardiologists in Gothenburg were retrieved. To determine prenatal detection rate, all neonates who underwent surgery or catheter intervention for a critical congenital heart defect born between January 1st, 2014 and December 31st, 2016 were included. The four-chamber view was implemented into the routine scan in 2009 and implementation of the ISUOG guidelines, including the outflow tracts, started in the region in 2015.

Results

113 fetuses received a prenatal diagnosis of a major congenital heart defect. 89% of these were referred because of a suspected cardiac malformation and 88% were diagnosed before 22 completed weeks. 59% of the patients diagnosed before 22 completed weeks opted for termination of pregnancy. During 2014–2016, 61 fetuses had a prenatal diagnosis of a critical congenital heart defect and a further 47 were diagnosed after birth, hence 56% were diagnosed prenatally, 82% for those which had a combination with an extracardiac abnormality and/or chromosomal aberration compared to 50% if an isolated critical congenital heart defect was diagnosed. For single ventricle cardiac defects such as hypoplastic left heart syndrome, double inlet left ventricle and tricuspid atresia, the detection rate was 100%. The detection rate for transposition of the great arteries and coarctation of the aorta was 9 and 18% respectively.

Conclusions

56% of all fetuses with a critical congenital heart defect were diagnosed prenatally during 2014–2016 and approximately 53% of all major congenital heart defects 2013–2017 as compared to 13.8% in 2009 in the same region. An increased focus towards the fetal heart in the routine scan improved the prenatal detection rate of major congenital heart defects. The detection of congenital heart defects affecting the four-chamber view seems sufficient, but more training is needed to improve the quality of the examination of the outflow tracts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-04028-5.

A 'holistic' sonographic view on congenital heart disease - How automatic reconstruction using fetal intelligent navigation echocardiography (FINE) eases the unveiling of abnormal cardiac anatomy part I: Right heart anomalies

Attempting a comprehensive examination of the fetal heart remains challenging for unexperienced operators as it emphasizes the acquisition and documentation of sequential cross-sectional and sagittal views and inevitably results in diminished detection rates of fetuses affected by congenital heart disease. The introduction of four-dimensional spatio-temporal image correlation (4D STIC) technology facilitated a volumetric approach for thorough cardiac anatomic evaluation by the acquisition of cardiac 4D datasets. By analyzing and re-arranging of numerous frames according to their temporal event within the heart cycle, STIC allows visualization of cardiac structures as an endless cine loop sequence of a complete single cardiac cycle in motion. However, post-analysis with manipulation and repeated slicing of the volume usually requires experience and in-depth anatomic knowledge, which limits the widespread application of this advanced technique in clinical care and unfortunately leads to the underestimation of its diagnostic value to date. Fetal intelligent navigation echocardiography (FINE), a novel method that automatically generates and displays nine standard fetal echocardiographic views in normal hearts, has shown to be able to overcome these limitations. Very recent data on the detection of congenital heart defects (CHDs) using the FINE method revealed a high sensitivity and specificity of 98% and 93%, respectively. In this two-part manuscript, we focused on the performance of FINE in delineating abnormal anatomy of typical right and left heart lesions and thereby emphasized the educational potential of this technology for more than just teaching purposes. We further discussed recent findings in a pathophysiological and/or functional context.

Ventricular septal defect: diagnosis and treatments in the neonates: a systematic review

BACKGROUND

Medical advancements have encouraged minimally invasive surgical repair of congenital heart defects such as ventricular septal defects (VSDs), and the diagnostic process can now be carried out using non-traditional techniques such as pulse oximetry. This, in turn, has improved clinical outcomes with reduced complication rates post-surgery. However, the variations in type of VSDs, age of patient, comorbidities, and access to closure devices may limit the efficacy of surgical advancements.

METHODS

Articles were identified amongst Scopus, MEDLINE, and PubMed using various relevant search strings using PRISMA guidelines. Of the 115 articles initially extracted, 10 were eventually reviewed after duplicates and irrelevant studies were removed.

RESULTS

Of the 24 eligible articles, 10 papers were selected for analysis. Minimally invasive approaches to VSD repair was associated with satisfactory short-term outcomes when compared to open repair. For diagnosis of congenital VSD, whilst recent advances such as pulse oximetry method and genome analysis are more sensitive, the limited availability and access to such investigatory methods must be recognised.

CONCLUSION

Pulse oximetry and fetal echocardiography are established non-invasive diagnostic tools for VSD. The recent advances in minimally invasive treatment options including periventricular approach and transcatheter techniques have improved patient outcomes, yet at the expense of higher residual rates. Careful patient selection for each technique and follow-up should be planned through multidisciplinary team meetings.

A "holistic" sonographic view on congenital heart disease: How automatic reconstruction using fetal intelligent navigation echocardiography eases unveiling of abnormal cardiac anatomy part II-Left heart anomalies

Volume ultrasound has been shown to provide valid complementary information on fetal anatomy. Four-dimensional assessment (4D) of the fetal cardiovascular system using spatial-temporal image correlation (STIC) allows for detailed examination of a highly complex organ from the early second trimester onward. There is compelling evidence that this technique harbors quite a number of diagnostic opportunities, but manual navigation through STIC volume datasets is highly operator dependent. In fact, STIC is not incorporated yet into daily practice. Application of the novel fetal intelligent navigation echocardiography (FINE) considerably simplifies fetal cardiac volumetric examinations. This automatic technique applied on cardiac volume datasets reportedly has both high sensitivity and specificity for the detection of congenital heart defects (CHDs). Part I reviewed current data regarding detection rates of CHDs and illustrated the additional value of an automatic approach in delineating cardiac anatomy exemplified by congenital lesions of the right heart. In part II of this pictorial essay, we focused on left heart anomalies and aimed to tabulate recent findings on the quantification of normal and abnormal cardiac anatomy.

Prenatally detected isolated ventricular septum defects and the association with chromosomal aberrations-A nationwide register-based study from Denmark

OBJECTIVE

To evaluate the association between prenatally detected isolated ventricular septum defects (VSDs) and chromosomal aberrations in a nationwide study in Denmark.

METHOD

Nationwide, register-based study with prospectively collected data including all singleton pregnancies from 2014-2018. From the Danish Fetal Medicine Database, we retrieved data on maternal characteristics, first-trimester biomarkers, pre- and postnatal diagnoses, genetic test results, and pregnancy outcomes. VSDs were considered isolated in the absence of other malformations or soft markers, and with a low first-trimester risk assessment for trisomies 21, 18 and 13. All cases of an isolated VSD with a chromosomal anomaly were audited. The genetic tests included karyotyping and chromosomal microarray.

RESULTS

We retrieved data on 292 108 singleton pregnancies; 323 registered with a prenatally detected VSD and 697 with a VSD detected postnatally (incidence of 0.35%). Only 1/153 (0.7%, 95% CI 0.02;3.6%) of the isolated prenatally detected VSDs had an abnormal genetic test result (del (8)(q23.1)). Moreover, they had a lower free β-hCG MoM (0.9 MoM vs 0.99 MoM, P = 0.02), and were more likely born small for gestational age (SGA), defined as birthweight 2 or more SD below the mean, compared with the control population (5.2% vs 2.5%, P = 0.03).

CONCLUSION

We found a prevalence of chromosomal aberrations of 0.7% in fetuses with a prenatally detected isolated VSD. Moreover, we found an association between isolated VSDs and a larger proportion being born SGA.

Pränatalsonografie: Warum werden angeborene Herzfehler nicht erkannt?

Etwa die Hälfte der angeborenen Herzfehler wird bei der pränatalen Ultraschalldiagnostik nicht erkannt. Dies kann die Prognose der betroffenen Kinder erheblich verschlechtern. Warum so viele Fehlbildungen übersehen werden und wie man die Detektionsrate verbessern kann, untersuchte ein Team niederländischer Wissenschaftler.

Fetal cardiac evaluation services for low-risk pregnancies: how can we improve?

Linked Comment: Ultrasound Obstet Gynecol 2020; 55:747-757.