Barriers to prenatal detection of congenital heart disease: a population-based study

Adult-Trained Cardiac Sonographers: Essential Team Members in the Evaluation and Management of Unexpected Neonatal Critical Congenital Heart Disease

Early identification of critical congenital heart disease (CCHD) is essential in the management of neonates without a prenatal diagnosis. Adult-trained cardiac sonographers often perform initial neonatal transthoracic echocardiograms for outside interpretation. We sought to critically evaluate the accuracy and quality of these echocardiograms. Neonates treated at our center for postnatally diagnosed CCHD, who had an initial echocardiogram performed by an adult-trained sonographer at an outside birthing center were included. Each initial echocardiogram was evaluated using a 4-point Likert scale for diagnostic accuracy and quality, and a 3-point Likert scale assessing 5 standard echocardiogram views. Six paired graders independently assessed an equal distribution of echocardiograms. 52 echocardiograms from 4 states met all inclusion criteria. The most common diagnoses were aortic arch abnormalities (37%), followed by dTGA (19%), and TAPVR (17%). Ninety-eight percent of the original interpretations provided the correct primary diagnosis or high enough suspicion of the primary diagnosis to warrant appropriate escalation in care. Average scores of the echocardiograms were 3.13 ± 0.66 for diagnostic accuracy and 3.09 ± 0.54 for overall image quality. Average scores were highest for parasternal long-axis view (2.74 ± 0.31) and lowest for suprasternal notch (2.18 ± 0.46) and subcostal (2.07 ± 0.34) views. The average intraclass correlation between raters was > 0.9. Postnatal CCHD is discoverable by adult-trained sonographers with remote interpretation by pediatric cardiologists. Suprasternal notch and subcostal views are areas of educational opportunity. With appropriate support systems, adult-trained sonographers can be an invaluable asset in the early diagnosis and management of unexpected CCHD.

Fetal cardiac diagnostics in Indonesia: a study of screening and echocardiography

INTRODUCTION

Congenital heart defects (CHDs) are a leading cause of neonatal morbidity and mortality globally. Accurate prenatal detection is crucial to improving neonatal outcomes. In Indonesia, two primary methods are used: fetal cardiac screening (FCS), which is accessible but limited in sensitivity (40-60 %), and fetal echocardiography (FE), the gold standard with over 90 % sensitivity but limited access due to infrastructural and financial challenges.

CONTENT

This review analyzes Indonesia's diagnostic disparities, highlighting how rural regions rely heavily on FCS, while FE remains restricted to urban centers. Emerging technologies, such as AI-enhanced diagnostics and telemedicine, show promise in bridging gaps by increasing FCS accuracy and extending access to FE through remote consultations.

SUMMARY

AI has the potential to boost FCS sensitivity by up to 30 %, making it an effective preliminary screening tool, while telemedicine platforms connect rural practitioners to urban specialists. However, barriers like insufficient infrastructure, regulatory issues, and limited training hinder widespread adoption.

OUTLOOK

Addressing these gaps requires standardized national protocols, capacity-building initiatives, and public-private partnerships to finance infrastructure and reduce costs. With technology integration and systemic reforms, Indonesia can achieve equitable CHD diagnostics, improving maternal and neonatal outcomes and aligning with global standards.

Suboptimal Imaging on Obstetric Ultrasound Should Prompt Early Referral for Fetal Echocardiography

Recent studies suggest that suboptimal cardiac imaging on routine obstetric anatomy ultrasound (OB-scan) is not associated with a higher risk for congenital heart disease (CHD) and, therefore, should not be an indication for fetal echocardiography (F-echo). We aim to determine the incidence of CHD in patients referred for suboptimal imaging in a large catchment area, including regions that are geographically distant from a tertiary care center. We conducted a retrospective chart review of patients referred to Seattle Children's Hospital (SCH) and SCH Regional Cardiology sites (SCH-RC) from 2011 to 2021 for F-echo with the indication of suboptimal cardiac imaging by OB-scan. Of 454 patients referred for suboptimal imaging, 21 (5%) of patients were diagnosed with CHD confirmed on postnatal echo. 10 patients (2%) required intervention by age one. Mean GA at F-echo was significantly later for suboptimal imaging compared to all other referral indications (27.5 ± 3.9 vs 25.2 ± 5.2 weeks, p < 0.01). Mean GA at F-echo was also significantly later at SCH-RC compared to SCH (29.2 ± 4.6 vs 24.2 ± 2.9 weeks; p < 0.01). In our experience, CHD in patients referred for suboptimal imaging is higher (5%) than previously described, suggesting that routine referral for is warranted. Furthermore, while suboptimal imaging was associated with a delayed F-echo compared to other indications, this delay was most striking for those seen at regional sites. This demonstrates a potential disparity for these patients and highlights opportunities for targeted education in cardiac assessment for primary providers in these regions.

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence

Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detection of cyanotic CHD (CCHD) can have disastrous consequences. We therefore sought to use a Precision Fetal Cardiology based approach combining metabolomic profiling of maternal saliva and machine learning, a major branch of artificial intelligence (AI), for the prenatal detection of isolated, non-syndromic cyanotic CHD. Metabolomic analyses using Ultra-High Performance Liquid Chromatography/Mass Spectrometry identified 468 metabolites in the saliva. Six different AI platforms were utilized for the detection of CCHD and CHD overall. AI achieved excellent accuracy for the CCHD detection: Area Under the ROC curve: AUC (95% CI) = 0.819 (0.635-1.00) with a sensitivity and specificity of 92.5% and 87.0%, and for CHD overall: AUC (95% CI) = 0.828 (0.635-1.00) with a sensitivity of 90.5% and specificity of 88.0%. Similarly high accuracies were achieved for the detection of CHD overall: AUC (95% CI) = 0.8488 (0.635-1.00) with a sensitivity of 92.5% and specificity of 91.0%. Pathway analysis showed significant alterations in Arachidonic Acid, Alpha-linoleic acid, and Tryptophan metabolism indicating significant lipid dysfunction in cyanotic CHD. In summary, we report for the first time, the accurate detection of non-syndromic cyanotic CHD using maternal salivary metabolomics. Further, analysis revealed significant alteration of lipid metabolism.

Factors affecting the accuracy of fetal cardiac ultrasound screening in the first trimester of pregnancy

PURPOSE

Most studies on the performance of first-trimester cardiac screening have concentrated on comparing the detection rate between different protocols and not on the actual reason for false-negative results. Herein, we report the performance of first-trimester congenital heart disease (CHD) screening and factors that may affect the detection rate of CHDs.

METHODS

This retrospective observational study included patients who underwent first-trimester screening and subsequently gave birth at our facility. We analyzed the performance of first-trimester screening for CHD and major CHD (CHD requiring cardiac surgery or interventional catheterization within 12 months of birth).

RESULTS

Of the 6614 fetuses included, 53 had CHD and 35 had major CHD. For the prenatal diagnosis of CHD, the detection rate, specificity, positive predictive value, negative predictive value, and first-trimester detection rate for CHD were 64.1%, 99.9%, 94.4%, 99.7%, and 82.9%, respectively; the respective values for major CHD were 85.7%, 99.96%, 93.75%, 99.92%, and 85.7%. The detection rate was not significantly different when classified by crown-rump length or number of fetuses. A weak correlation was observed between low detection rate of major CHD and lower maternal body mass index (BMI) (correlation ratio: 0.17). The detection rate was significantly higher when the fetus was scanned with its spine at the 5-7 o'clock position (posterior spine) than at other positions (odds ratio: 3.82, 95% confidence interval: 1.16-12.5, p = 0.02).

CONCLUSION

Posterior spine contributes to an improved diagnostic rate in first-trimester CHD screening. In addition, sonographers must recognize that low maternal BMI is a risk factor of false-negative results.

Geospatial Distribution of Prenatally and Postnatally Diagnosed Congenital Heart Disease: Implications for Equitable Care from a Fetal Heart Society Research Collaborative Study

OBJECTIVE

To characterize patterns in the geospatial distribution of pre- and postnatally diagnosed congenital heart disease (CHD) across 6 surgical centers.

STUDY DESIGN

A retrospective, multicenter case series from the Fetal Heart Society identified patients at 6 centers from 2012 through 2016 with prenatally (PrND) or postnatally (PoND) diagnosed hypoplastic left heart syndrome (HLHS) or d-transposition of the great arteries (TGA). Geospatial analysis for clustering was done by the average nearest neighbor (ANN) tool or optimized hot spot tool, depending on spatial unit and data type. Both point location and county case rate per 10 000 live births were assessed for geographic clustering or dispersion.

RESULTS

Of the 453 CHD cases, 26% were PoND (n = 117), and 74% were PrND (n = 336). PrND cases, in all but one center, displayed significant geographic clustering by the ANN. Conversely, PoND cases tended toward geographic dispersion. Dispersion of PoND HLHS occurred in 2 centers (ANN = 1.59, P < .001; and 1.47, P = .016), and PoND TGA occurred in 2 centers (ANN = 1.22, P < .05; and ANN = 1.73, P < .001). Hot spot analysis of all CHD cases (TGA and HLHS combined) revealed clustering near areas of high population density and the tertiary surgical center. Hot spot analysis of county-level case rate, accounting for population density, found variable clustering patterns.

CONCLUSION

Geographic dispersion among postnatally detected CHD highlights the need for a wider reach of prenatal cardiac diagnosis tailored to the specific needs of a community. Geospatial analysis can support centers in improving the equitable delivery of prenatal care.

The Role of Social Determinants in Diagnosis Timing for Fetal Care Center-Eligible Conditions: A Scoping Review

Timely identification of fetal conditions enables comprehensive evaluation, counseling, postnatal planning, and prenatal treatments. This study assessed the existing evidence on how social determinants of health (SDOH) influence diagnosis timing of fetal conditions appropriate for care in fetal care centers (FCCs). Eligible studies were conducted in the U.S. and published in English after 1999. We employed the Healthy People 2020 SDOH framework to categorize and analyze data from 16 studies, where 86% focused solely on congenital heart disease (CHD). Studies primarily focused on individual-level SDOH, with only 36% addressing structural-level factors. A total of 31 distinct indicators of SDOH were identified, with 68% being unique to individual studies. Indicators often varied in definition and specificity. Three studies covered all five SDOH categories in the Healthy People 2020 Framework. Studies revealed varying and often conflicting associations with SDOH indicators, with race and ethnicity being the most explored (100%), followed by socioeconomic status (69%), maternal age (57%), residence (43%), and structural factors (29%). Our findings highlight the need for more comprehensive research, including conditions beyond CHD, and the establishment of consensus on indicators of SDOH. Such efforts are necessary to gain a deeper understanding of the underlying factors driving disparities in fetal diagnosis and treatment.

Ethical Considerations in Fetal Cardiology

Fetal cardiology has evolved over the last 40 years and changed the timing of diagnosis and counseling of congenital heart disease, decision-making, planning for treatment at birth, and predicting future surgery from the postnatal to the prenatal period. Ethical issues in fetal cardiology transect multiple aspects of biomedical ethics including improvement in prenatal detection and diagnostic capabilities, access to equitable comprehensive care that preserves a pregnant person's right to make decisions, access to all reproductive options, informed consent, complexity in shared decision-making, and appropriate use of fetal cardiac interventions. This paper first reviews the literature and then provides an ethical analysis of accurate and timely diagnosis, equitable delivery of care, prenatal counseling and shared decision-making, and innovation through in utero intervention.

Update on Prenatal Detection Rate of Critical Congenital Heart Disease Before and During the COVID-19 Pandemic

Prenatal diagnosis of critical congenital heart disease (CCHD) has improved over time, and previous studies have identified CCHD subtype and socioeconomic status as factors influencing rates of prenatal diagnosis. Our objective of this single-center study was to compare prenatal diagnosis rates of newborns with CCHD admitted for cardiac intervention from the COVID-19 pandemic period (March 2020 to March 2021) to the pre-pandemic period and identify factors associated with the lack of CCHD prenatal diagnosis. The overall rate of CCHD and rates of the various CCHD diagnoses were calculated and compared with historical data collection periods (2009-2012 and 2013-2016). Compared with the 2009-2012 pre-pandemic period, patients had 2.17 times higher odds of having a prenatal diagnosis of CCHD during the pandemic period controlling for lesion type (aOR = 2.17, 95% CI 1.36-3.48, p = 0.001). Single ventricle lesions (aOR 6.74 [4.64-9.80], p < 0.001) and outflow tract anomalies (aOR 2.20 [1.56-3.12], p < 0.001) had the highest odds of prenatal diagnosis compared with the remaining lesions. Patients with outflow tract anomalies had higher odds for prenatal detection in the pandemic period compared with during the 2009-2012 pre-pandemic period (aOR 2.01 [1.06-3.78], p = 0.031). In conclusion, prenatal detection of CCHD among newborns presenting for cardiac intervention appeared to have improved during the pandemic period.

Obstetric imaging practice characteristics associated with prenatal detection of critical congenital heart disease in a rural US region over 20 years

OBJECTIVE

To identify clinical practice characteristics associated with the frequency of prenatal critical congenital heart disease (CCHD) detection (i.e., the number of liveborn infants with postnatally confirmed CCHD identified on prenatal sonography) over 20 years in a rural setting comprised of 11 primarily low-volume obstetric hospitals and the single tertiary academic hospital to which they refer.

METHODS

This was a retrospective cohort study of all patients in the referral region with an initial prenatal and/or postnatal diagnosis of CCHD from 01/01/2002 to 12/31/2021. The frequency of prenatal CCHD detection at the time of an obstetric ultrasound was reported, as was the change in detection over time. Critical congenital heart disease detection was assessed as a function of cardiac lesion type, practice setting, and practice characteristics.

RESULTS

There were 271 cases with a confirmed postnatal CCHD diagnosis, of which 49% were identified prenatally. The majority of community practices each averaged <10 CCHD cases in total over the study period. Prenatal detection at the tertiary academic hospital's obstetric ultrasound unit was 64%, compared to 22% at the combined referring community practices (p < 0.001), though CCHD detection improved over time in both settings. Professional accreditation by the American Institute of Ultrasound in Medicine, image interpretation by radiology or Maternal Fetal Medicine, and use of video clips of ventricular outflow tracts were associated with improved prenatal CCHD detection.

CONCLUSIONS

Our data demonstrate the infrequency of CCHD cases at small-volume, rural hospitals and the substantial variation in prenatal CCHD detection across practice settings. Our methods allowed for the identification of practice characteristics associated with prenatal CCHD detection.

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.

Clinical Risk Assessment and Prediction in Congenital Heart Disease Across the Lifespan: JACC Scientific Statement

Congenital heart disease (CHD) comprises a range of structural anomalies, each with a unique natural history, evolving treatment strategies, and distinct long-term consequences. Current prediction models are challenged by generalizability, limited validation, and questionable application to extended follow-up periods. In this JACC Scientific Statement, we tackle the difficulty of risk measurement across the lifespan. We appraise current and future risk measurement frameworks and describe domains of risk specific to CHD. Risk of adverse outcomes varies with age, sex, genetics, era, socioeconomic status, behavior, and comorbidities as they evolve through the lifespan and across care settings. Emerging technologies and approaches promise to improve risk assessment, but there is also need for large, longitudinal, representative, prospective CHD cohorts with multidimensional data and consensus-driven methodologies to provide insight into time-varying risk. Communication of risk, particularly with patients and their families, poses a separate and equally important challenge, and best practices are reviewed.

Cost-utility analysis of prenatal diagnosis of congenital cardiac diseases using deep learning

BACKGROUND

Deep learning (DL) is a new technology that can assist prenatal ultrasound (US) in the detection of congenital heart disease (CHD) at the prenatal stage. Hence, an economic-epidemiologic evaluation (aka Cost-Utility Analysis) is required to assist policymakers in deciding whether to adopt the new technology.

METHODS

The incremental cost-utility ratios (CUR), of adding DL assisted ultrasound (DL-US) to the current provision of US plus pulse oximetry (POX), was calculated by building a spreadsheet model that integrated demographic, economic epidemiological, health service utilization, screening performance, survival and lifetime quality of life data based on the standard formula: CUR = Increase in Intervention Costs - Decrease in Treatment costs Averted QALY losses of adding DL to US & POX US screening data were based on real-world operational routine reports (as opposed to research studies). The DL screening cost of 145 USD was based on Israeli US costs plus 20.54 USD for reading and recording screens.

RESULTS

The addition of DL assisted US, which is associated with increased sensitivity (95% vs 58.1%), resulted in far fewer undiagnosed infants (16 vs 102 [or 2.9% vs 15.4%] of the 560 and 659 births, respectively). Adoption of DL-US will add 1,204 QALYs. with increased screening costs 22.5 million USD largely offset by decreased treatment costs (20.4 million USD). Therefore, the new DL-US technology is considered "very cost-effective", costing only 1,720 USD per QALY. For most performance combinations (sensitivity > 80%, specificity > 90%), the adoption of DL-US is either cost effective or very cost effective. For specificities greater than 98% (with sensitivities above 94%), DL-US (& POX) is said to "dominate" US (& POX) by providing more QALYs at a lower cost.

CONCLUSION

Our exploratory CUA calculations indicate the feasibility of DL-US as being at least cost-effective.

Untangling the Complex Associations between Socioeconomic and Demographic Characteristics and Prenatal Detection and Outcomes in Congenital Heart Disease

Recent literature has established a strong foundation examining the associations between socioeconomic/demographic characteristics and outcomes for congenital heart disease. These associations are found beginning in fetal life and influence rates of prenatal detection, access to timely and appropriate delivery room and neonatal interventions, and surgical and other early childhood outcomes. This review takes a broad look at the existing literature and identifies gaps in the current body of research, particularly as it pertains to disparities in the prenatal detection of congenital heart disease within the United States. It also proposes further research and interventions to address these health disparities.

Feasibility of neurosonography in CHD-fetuses and controls in a clinical tertiary setting

Objective

Ultrasonographic examination is the first-tier test to detect abnormal development of central nervous system (CNS). In optimal conditions, neurosonography can detect all important hallmarks of CNS development. It is, however, not known how the performance of this modality is in a routine setting. We aimed to evaluate the feasibility of neurosonography in a time-limited routine setting.

Study design

We have performed a prospective study in which we have included a group of pregnant women carrying a fetus with an isolated congenital heart defect (CHD), and a control group of fetuses without structural anomalies. We have performed basic neurosonography examination according to the guideline 'how to perform a basic screening examination of the CNS', published by the international society of ultrasound in obstetrics and gynecology in both groups. In all these examinations, 9 brain structures were scored in 3 different planes, by researchers that were blinded for group allocation. A sufficient neurosonogram was performed when 7 or more out of 9 CNS structures were clearly visible during the off-line scoring of the examination.

Results

A total of 574 neurosonographic examinations were performed in 151 fetuses, 90 in the CHD-group and 61 in the control group. A sufficient neurosonogram could be performed in 79% (234/294) of cases in a clinical setting (CHD cases) and in 90% (253/280) of control pregnancies. Higher maternal BMI (>30), maternal age, fetal cephalic position, fetal gender and placental position did not significantly influence neurosonography scores.

Conclusion

In clinical setting, basic fetal neurosonography can be sufficiently performed in the majority of cases. This was not significantly influenced by maternal or fetal factors. The optimal gestational age for neurosonography is between 22 and 34 weeks.

Prevalence and detection rate of major congenital heart disease in twin pregnancies in Denmark

OBJECTIVE

To investigate the national prevalence and prenatal detection rate (DR) of major congenital heart disease (mCHD) in twin pregnancies without twin-to-twin transfusion syndrome (TTTS)-associated CHD in a Danish population following a standardized prenatal screening program.

METHODS

This was a national registry-based study of data collected prospectively over a 10-year period. In Denmark, all women with a twin pregnancy are offered standardized screening and surveillance programs in addition to first- and second-trimester screening for aneuploidies and malformation, respectively: monochorionic (MC) twins every 2 weeks from gestational week 15 and dichorionic (DC) twins every 4 weeks from week 18. The data were retrieved from the Danish Fetal Medicine Database and included all twin pregnancies from 2009-2018, in which at least one fetus had a pre- and/or postnatal mCHD diagnosis. mCHD was defined as CHD requiring surgery within the first year of life, excluding ventricular septal defects. All pregnancy data were pre- and postnatally validated in the local patient files at the four tertiary centers covering the entire country.

RESULTS

A total of 60 cases from 59 twin pregnancies were included. The prevalence of mCHD was 4.6 (95% CI, 3.5-6.0) per 1000 twin pregnancies (1.9 (95% CI, 1.3-2.5) per 1000 live births). The prevalences for DC and MC were 3.6 (95% CI, 2.6-5.0) and 9.2 (95% CI, 5.8-13.7) per 1000 twin pregnancies, respectively. The national prenatal DR of mCHD in twin pregnancies for the entire period was 68.3%. The highest DRs were in cases with univentricular hearts (100%) and the lowest with aortopulmonary window, total anomalous pulmonary venous return, Ebstein's anomaly, aortic valve stenosis and coarctation of the aorta (0-25%). Mothers of children with prenatally undetected mCHD had a significantly higher body mass index (BMI) compared to mothers of children with a prenatally detected mCHD (median, 27 kg/m2 and 23 kg/m2 , respectively; P = 0.02).

CONCLUSIONS

The prevalence of mCHD in twins was 4.6 per 1000 pregnancies and was higher in MC than DC pregnancies. The prenatal DR of mCHD in twin pregnancies was 68.3%. Maternal BMI was higher in cases of prenatally undetected mCHD. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Role of autopsy in diagnosing asplenia and right bilobed lung in a fetus with dextrocardia

We present a unique case of a fetus with dextrocardia, asplenia and a right bilobed lung in a primigravida woman in her 20s at 21 weeks' gestation. Prenatal ultrasound examination revealed dextrocardia and other anomalies such as atrioventricular septal defect and situs ambiguous with the gallbladder on the left, leading to termination of the pregnancy. Fetal autopsy confirmed the diagnosis, detected additional findings such as asplenia and right bilobed lung missed on ultrasound and highlighted the importance of autopsy in prenatal diagnosis. This rare case emphasises the value of a comprehensive prenatal assessment, fetal autopsy and a multidisciplinary approach in diagnosing, managing and counselling families affected by congenital anomalies. Timely detection and appropriate genetic counselling can guide affected families in making informed decisions regarding future pregnancies while providing closure and support in their grieving process.

Prenatal detection of congenital heart disease: Recent experience across the state of Arizona

OBJECTIVE

To determine the prenatal detection rate (PDR) of congenital heart disease (CHD) in Arizona as well as describe various factors that may influence detection rates.

METHODS

This was a retrospective chart review using the Society of Thoracic Surgeons and Phoenix Children's Fetal Cardiology databases. We included all cases of CHD requiring surgery <1 year of age between 2013 and 2018. A total of 1137 patients met the criteria, and various demographic, socioeconomic, and patient outcome data were collected.

RESULTS

The overall PDR was 58% with an improving detection rate over the course of our study, with the final year having a PDR of 67%. Over time, PDR improved in urban communities, but this was not seen in rural communities. Rural address, public insurance, and Native American ethnicity were associated with lower PDR. Postnatal outcomes, including Apgars, initial pH, and lactate, did not differ with the presence of a prenatal diagnosis. Diagnoses typically identified with the outflow tract and 3-vessel views on the fetal echocardiogram were less likely to be detected prenatally.

CONCLUSIONS

The PDR of CHD continues to improve with evolving technologies and guidelines. We highlight a discrepancy between urban, rural, and Native American populations. Additionally, by supplying descriptors of missed diagnosis and associated echocardiography views, we hope to provide data for future interventions.

Use of artificial intelligence and deep learning in fetal ultrasound imaging

Deep learning is considered the leading artificial intelligence tool in image analysis in general. Deep-learning algorithms excel at image recognition, which makes them valuable in medical imaging. Obstetric ultrasound has become the gold standard imaging modality for detection and diagnosis of fetal malformations. However, ultrasound relies heavily on the operator's experience, making it unreliable in inexperienced hands. Several studies have proposed the use of deep-learning models as a tool to support sonographers, in an attempt to overcome these problems inherent to ultrasound. Deep learning has many clinical applications in the field of fetal imaging, including identification of normal and abnormal fetal anatomy and measurement of fetal biometry. In this Review, we provide a comprehensive explanation of the fundamentals of deep learning in fetal imaging, with particular focus on its clinical applicability. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Confirmation of Heart Malformations in Fetuses in the First Trimester Using Three-Dimensional Histologic Autopsy

BACKGROUND

We aimed to evaluate the usefulness of three-dimensional (3D) reconstruction of histology slides to confirm congenital heart disease (CHD) detected by first-trimester fetal cardiac ultrasonography. Conventional autopsy is hindered by the small size of the first-trimester fetal heart, and current CHD confirmation studies employ the use of highly specialized and expensive methods.

TECHNIQUE

An extended first-trimester ultrasound examination protocol was used to diagnose fetal heart anomalies. Medical termination of pregnancies was followed by fetal heart extraction. The specimens were sliced, and the histology slides were stained and scanned. The resulting images were processed, and volume rendering was performed using 3D reconstruction software. The volumes were analyzed by a multidisciplinary team of maternal-fetal medicine subspecialists and pathologists and compared with ultrasound examination findings.

EXPERIENCE

Six fetuses with heart malformations were evaluated using histologic 3D imaging: two with hypoplastic left heart syndrome, two with atrioventricular septal defects, one with an isolated ventricular septal defect, and one with transposition of the great arteries. The technique allowed us to confirm ultrasound-detected anomalies and also identified additional malformations.

CONCLUSION

After pregnancy termination or loss, histologic 3D imaging can be used to confirm the presence of fetal cardiac malformations detected during first-trimester ultrasound examination. Additionally, this technique has the potential to refine the diagnosis for counseling regarding recurrence risk and retains the advantages of standard histology.

Application of Semiautomatic Fetal Intelligent Navigation Echocardiography (FINE) in Twin Pregnancies: Half the Work or Twice the Effort?

OBJECTIVE

To assess the performance of fetal intelligent navigation echocardiography (FINE, 5D Heart™) for automated volumetric investigation of the fetal heart in twin pregnancies.

METHODS

Three hundred twenty-eight twin fetuses underwent fetal echocardiography in the second and third trimesters. Spatiotemporal image correlation (STIC) volumes were obtained for a volumetric investigation. The volumes were analyzed using the FINE software, and the data were investigated regarding image quality and many properly reconstructed planes.

RESULTS

Three hundred and eight volumes underwent final analysis. 55.8% of the included pregnancies were dichorionic twin pregnancies, and 44.2% were monochorionic twin pregnancies. The mean gestational age (GA) was 22.1 weeks, and the mean maternal BMI was 27.3 kg/m². The STIC-volume acquisition was successful in 100.0% and 95.5% of cases. The overall depiction rates of FINE were 96.5% (twin 1) and 94.7% (twin 2), respectively (p = 0.0849, not significant). In 95.9% (twin 1) and 93.9% (twin 2), at least 7 planes were reconstructed properly (p = 0.6056, not significant).

CONCLUSION

Our results indicate that the FINE technique used in twin pregnancies is reliable. No significant difference between the depiction rates of twin 1 and twin 2 could be detected. In addition, the depiction rates are as high as those derived from singleton pregnancies. Due to the challenges of fetal echocardiography in twin pregnancies (i.e., greater rates of cardiac anomaly and more difficult scans), the FINE technique might be a valuable tool to improve the quality of medical care in those pregnancies.

Cell-free DNA in maternal blood and artificial intelligence: accurate prenatal detection of fetal congenital heart defects

BACKGROUND

DNA cytosine nucleotide methylation (epigenomics and epigenetics) is an important mechanism for controlling gene expression in cardiac development. Combined artificial intelligence and whole-genome epigenomic analysis of circulating cell-free DNA in maternal blood has the potential for the detection of fetal congenital heart defects.

OBJECTIVE

This study aimed to use genome-wide DNA cytosine methylation and artificial intelligence analyses of circulating cell-free DNA for the minimally invasive detection of fetal congenital heart defects.

STUDY DESIGN

In this prospective study, whole-genome cytosine nucleotide methylation analysis was performed on circulating cell-free DNA using the Illumina Infinium MethylationEPIC BeadChip array. Multiple artificial intelligence approaches were evaluated for the detection of congenital hearts. The Ingenuity Pathway Analysis program was used to identify gene pathways that were epigenetically altered and important in congenital heart defect pathogenesis to further elucidate the pathogenesis of isolated congenital heart defects.

RESULTS

There were 12 cases of isolated nonsyndromic congenital heart defects and 26 matched controls. A total of 5918 cytosine nucleotides involving 4976 genes had significantly altered methylation, that is, a P value of <.05 along with ≥5% whole-genome cytosine nucleotide methylation difference, in congenital heart defect cases vs controls. Artificial intelligence analysis of the methylation data achieved excellent congenital heart defect predictive accuracy (areas under the receiver operating characteristic curve, ≥0.92). For example, an artificial intelligence model using a combination of 5 whole-genome cytosine nucleotide markers achieved an area under the receiver operating characteristic curve of 0.97 (95% confidence interval, 0.87-1.0) with 98% sensitivity and 94% specificity. We found epigenetic changes in genes and gene pathways involved in the following important cardiac developmental processes: "cardiovascular system development and function," "cardiac hypertrophy," "congenital heart anomaly," and "cardiovascular disease." This lends biologic plausibility to our findings.

CONCLUSION

This study reported the feasibility of minimally invasive detection of fetal congenital heart defect using artificial intelligence and DNA methylation analysis of circulating cell-free DNA for the prediction of fetal congenital heart defect. Furthermore, the findings supported an important role of epigenetic changes in congenital heart defect development.

The electrical heart axis in fetuses with congenital heart disease, measured with non-invasive fetal electrocardiography

OBJECTIVES

To determine if the electrical heart axis in different types of congenital heart defects (CHD) differs from that of a healthy cohort at mid-gestation.

METHODS

Non-invasive fetal electrocardiography (NI-fECG) was performed in singleton pregnancies with suspected CHD between 16 and 30 weeks of gestation. The mean electrical heart axis (MEHA) was determined from the fetal vectorcardiogram after correction for fetal orientation. Descriptive statistics were used to determine the MEHA with corresponding 95% confidence intervals (CI) in the frontal plane of all fetuses with CHD and the following subgroups: conotruncal anomalies (CTA), atrioventricular septal defects (AVSD) and hypoplastic right heart syndrome (HRHS). The MEHA of the CHD fetuses as well as the subgroups was compared to the healthy control group using a spherically projected multivariate linear regression analysis. Discriminant analysis was applied to calculate the sensitivity and specificity of the electrical heart axis for CHD detection.

RESULTS

The MEHA was determined in 127 fetuses. The MEHA was 83.0° (95% CI: 6.7°; 159.3°) in the total CHD group, and not significantly different from the control group (122.7° (95% CI: 101.7°; 143.6°). The MEHA was 105.6° (95% CI: 46.8°; 164.4°) in the CTA group (n = 54), -27.4° (95% CI: -118.6°; 63.9°) in the AVSD group (n = 9) and 26.0° (95% CI: -34.1°; 86.1°) in the HRHS group (n = 5). The MEHA of the AVSD and the HRHS subgroups were significantly different from the control group (resp. p = 0.04 and p = 0.02). The sensitivity and specificity of the MEHA for the diagnosis of CHD was 50.6% (95% CI 47.5% - 53.7%) and 60.1% (95% CI 57.1% - 63.1%) respectively.

CONCLUSION

The MEHA alone does not discriminate between healthy fetuses and fetuses with CHD. However, the left-oriented electrical heart axis in fetuses with AVSD and HRHS was significantly different from the control group suggesting altered cardiac conduction along with the structural defect.

TRIAL REGISTRATION

Clinical trial registration number: NL48535.015.14.

Health Care Disparities in Congenital Cardiology: Considerations Through the Lens of an Interventional Cardiologist

When resources in a society are dispersed unevenly, generally through allocation standards, distinct patterns emerge along lines of socially defined categories of people. Power, religion, kinship, prestige, race, ethnicity, gender, age, sexual orientation, and class all play a role in determining who has access to social goods in society. In most cases, social inequality refers to a lack of equality of outcome, but it can also refer to a lack of equality of access to opportunity. Unfortunately, health care is not immune to these social disparities and/or inequalities. These health care disparities in interventional cardiology were recently brought to the forefront by the Society for Cardiovascular Angiography and Interventions (SCAI) as a major focus of 2020-2021. In a recent publication, unique factors leading to disparities were reported to exist among the subsections of interventional cardiology. The congenital heart disease council of SCAI created a task force to further investigate the unique challenges and disparities impacting the practice of congenital heart disease and pediatric cardiology.

Impact of rural residence and low socioeconomic status on rate and timing of prenatal detection of major congenital heart disease in a jurisdiction of universal health coverage

OBJECTIVE

Socioeconomic status (SES) and distance of residence from tertiary care may impact fetal detection of congenital heart disease (CHD), partly through reduced access to and quality of obstetric ultrasound screening. It is unknown whether SES and remoteness of residence (RoR) affect prenatal detection of CHD in jurisdictions with universal health coverage. We examined the impact of SES and RoR on the rate and timing of prenatal diagnosis of major CHD within the province of Alberta in Canada.

METHODS

In this retrospective study, we identified all fetuses and infants diagnosed with major CHD in Alberta, from 2008 to 2018, that underwent cardiac surgical intervention within the first year after birth, died preoperatively, were stillborn or underwent termination. Using maternal residence postal code and geocoding, Chan SES index quintile, geographic distance from a tertiary-care fetal cardiology center and the Canadian Index of Remoteness (IoR) were calculated. Outcome measures included rates of prenatal diagnosis and diagnosis after 22 weeks' gestation. Risk ratios (RR) were calculated using log-binomial regression and stratified by rural (≥ 100 km from tertiary care) or metropolitan (< 100 km from tertiary care) residence, adjusting for year of birth and the obstetric ultrasound screening view in which CHD would most likely be detected (four-chamber view; outflow-tract view; three-vessel or three-vessels-and-trachea or non-standard view; septal view).

RESULTS

Of 1405 fetuses/infants with major CHD, prenatal diagnosis occurred in 814 (57.9%). Residence ≥ 100 km from tertiary care (adjusted RR, 1.19; 95% CI, 1.05-1.34) and higher IoR (adjusted RR, 1.9; 95% CI, 1.1-3.3) were associated with missed prenatal diagnosis of major CHD. Similarly, residence ≥ 100 km from tertiary care (adjusted RR, 1.41; 95% CI, 1.22-1.62) and higher IoR (adjusted RR, 3.6; 95% CI, 2.2-8.2) were associated with prenatal diagnosis after 22 weeks. Although adjusted and unadjusted analyses showed no association between Chan SES index quintile and prenatal-diagnosis rate overall nor for residence in rural areas, in metropolitan regions, lower SES quintiles were associated with missed prenatal diagnosis (quintile 1: RR, 1.24; 95% CI, 1.02-1.50) and higher risk of diagnosis after 22 weeks' gestation (quintile 1: RR, 1.46; 95% CI, 1.10-1.93; quintile 2: RR, 1.66; 95% CI, 1.24-2.23).

CONCLUSIONS

Despite universal healthcare, rural residence in Alberta is associated with lower rate of prenatal diagnosis of major CHD and higher risk of late prenatal diagnosis (≥ 22 weeks). Within metropolitan regions, lower SES impacts negatively prenatal-diagnosis rate and timing. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Associations of congenital heart disease with deprivation index by rural-urban maternal residence: a population-based retrospective cohort study in Ontario, Canada

BACKGROUND

The risk of congenital heart disease (CHD) has been found to vary by maternal socioeconomic status (SES) and rural-urban residence. In this study, we examined associations of CHD with two maternal SES indicators and stratified the analysis by maternal rural-urban residence.

METHODS

This was a population-based retrospective cohort study. We included all singleton stillbirths and live hospital births from April 1, 2012 to March 31, 2018 in Ontario, Canada. We linked the BORN Information System and Canadian Institute for Health Information databases. Multivariable logistic regression models were used to examine associations of CHD with material deprivation index (MDI), social deprivation index (SDI), and maternal residence while adjusting for maternal age at birth, assisted reproductive technology, obesity, pre-pregnancy maternal health conditions, mental health illness before and during pregnancy, substance use during pregnancy, and infant's sex. MDI and SDI were estimated at a dissemination area level in Ontario and were categorized into quintiles (Q1-Q5).

RESULTS

This cohort study included 798,173 singletons. In maternal urban residence, the p trend (Cochran-Armitage test) was less than 0.0001 for both MDI and SDI; while for rural residence, it was 0.002 and 0.98, respectively. Infants living in the most materially deprived neighbourhoods (MDI Q5) had higher odds of CHD (aOR: 1.21, 95% CI: 1.12-1.29) compared to Q1. Similarly, infants living in the most socially deprived neighbourhoods (SDI Q5) had an 18% increase in the odds of CHD (aOR: 1.18, 95% CI: 1.1-1.26) compared to Q1. Rural infants had a 13% increase in the odds of CHD compared to their urban counterparts. After stratifying by maternal rural-urban residence, we still detected higher odds of CHD with two indices in urban residence but only MDI in rural residence.

CONCLUSION

Higher material and social deprivation and rural residence were associated with higher odds of CHD. Health interventions and policies should reinforce the need for optimal care for all families, particularly underprivileged families in both rural and urban regions. Future studies should further investigate the effect of social deprivation on the risk of CHD development.

Maximal Reduction of STIC Acquisition Time for Volumetric Assessment of the Fetal Heart—Benefits and Limitations of Semiautomatic Fetal Intelligent Navigation Echocardiography (FINE) Static Mode

(1) Objective: To scrutinize the reliability and the clinical value of routinely used fetal intelligent navigation echocardiography (FINE) static mode (5DHeartStatic™) for accelerated semiautomatic volumetric assessment of the normal fetal heart. (2) Methods: In this study, a total of 296 second and third trimester fetuses were examined by targeted ultrasound. Spatiotemporal image correlation (STIC) volumes of the fetal heart were acquired for further volumetric assessment. In addition, all fetal hearts were scanned by a fast acquisition time volume (1 s). The volumes were analyzed using the FINE software. The data were investigated regarding the number of properly reconstructed planes and cardiac axis. (3) Results: A total of 257 volumes were included for final analysis. The mean gestational age (GA) was 23.9 weeks (14.3 to 37.7 weeks). In 96.9 (standard acquisition time, FINE standard mode) and 94.2% (fast acquisition time, FINE static mode) at least seven planes were reconstructed properly (p = 0.0961, not significant). Regarding the overall depiction rate, the standard mode was able to reconstruct 96.9% of the planes properly, whereas the static mode showed 95.2% of the planes (p = 0.0098). Moreover, there was no significant difference between the automatic measurement of the cardiac axis (37.95 + 9.14 vs. 38.00 + 8.92 degrees, p = 0.8827, not significant). (4) Conclusions: Based on our results, the FINE static mode technique is a reliable method. It provides similar information of the cardiac anatomy compared to conventional STIC volumes assessed by the FINE method. The FINE static mode has the potential to minimize the influence of motion artifacts during volume acquisition and might therefore be helpful concerning volumetric cardiac assessment in daily routine.

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.

Fifteen-minute consultation: How to spot serious heart disease in the newborn

Congenital heart disease (CHD) is common and important as it remains a leading cause of neonatal morbidity and appreciable mortality. Prenatal diagnosis, the presence of a murmur, cyanosis, tachypnoea and/or poor or differential peripheral pulses raise the suspicion of CHD aided by differential pre/postductal saturations. Yet even serious CHD may not be considered when such clues are absent. Nevertheless, there are clinical cues which may alert the clinician to the possibility of a significant CHD which may lead to an early and accurate diagnosis and appropriate intervention to achieve best results. This paper addresses these issues which become especially difficult if caring for infants away from facilities provided by tertiary centres. Tachypnoea on the first postnatal day is generally non-cardiac in origin. Exceptions include large arteriovenous fistulae and/or 'pump' (ventricular) failure. In addition, attention is drawn to two important confounding factors in the newborn, namely the patency of the ductus arteriosus and the initially high pulmonary vascular resistance, both of which alter and may mask the clinical findings of a serious cardiac abnormality. An appreciation of the physiological changes that occur in early infancy will aid the clinician's understanding of CHD as it affects the newborn.

New and advanced features of fetal intelligent navigation echocardiography (FINE) or 5D heart

Congenital heart disease (CHD) is the leading organ-specific birth defect, as well as the leading cause of infant morbidity and mortality from congenital malformations. Therefore, a comprehensive screening examination of the fetal heart should be performed in all women to maximize the detection of CHD. Four-dimensional sonography with spatiotemporal image correlation (STIC) technology displays a cine loop of a complete single cardiac cycle in motion. A novel method known as Fetal Intelligent Navigation Echocardiography (or FINE) was previously developed to interrogate STIC volume datasets using "intelligent navigation" technology. Such method allows the automatic display of nine standard fetal echocardiography views required to diagnose most cardiac defects. FINE considerably simplifies fetal cardiac examinations and reduces operator dependency. It has both high sensitivity and specificity for the detection of CHD. Indeed, FINE has been integrated into several commercially available ultrasound platforms.Recently, eight novel and advanced features have been developed for the FINE method and they will be described herein. Such features can be categorized based upon their broad goals. The first goal is to simplify FINE further, and consists of the following features: (1) Auto fetal positioning (or FINE align); (2) Skip points; (3) Predictive cursor; (4) Static mode volume; and (5) Breech sweep. The second goal is to allow quantitative measurements to be performed on the cardiac views generated by FINE: (6) Automatic cardiac axis; and (7) Cardiac biometry. Finally, the last goal is to improve the success of obtaining fetal echocardiography view(s); and consists of (8) Maestro planar navigation.

Perinatal outcomes of pregnancies with prenatally diagnosed foetal congenital heart disease

We aimed to assess the types of prenatally diagnosed congenital heart disease (CHD) and their association with structural and chromosomal abnormalities and to evaluate the perinatal outcomes according to the type of the heart defect. We retrospectively reviewed 377 pregnancies with prenatally diagnosed CHD. The main outcome measure was to evaluate the pregnancy outcomes of CHD according to the type of the heart defect and associated structural or chromosomal abnormalities. Of 377 foetuses with major structural CHD, 214 (56.8%) were isolated, 49 (13%) had additional cardiac anomalies, 58 (15.4%) had extracardiac malformations with normal karyotype and 56 (14.9%) had chromosomal abnormalities. The most common chromosomal abnormality was trisomy 21 (55.4%). Prenatal detection of CHD allows early workup to identify chromosomal abnormalities and detailed anatomic evaluation of extracardiac malformations. Prognostication of each heart defect at diagnosis and facilitating patients with isolated surgically correctable CHD for targeted postnatal care is essential.IMPACT STATEMENTWhat is already known on this subject? CHD is the most common structural anomaly and is strongly associated with chromosomal anomalies and genetic syndromes.What do the results of this study add? Survival of the prenatally diagnosed CHD depends on the type and severity of the condition and coexisting extracardiac structural or chromosomal abnormalities.What are the implications of these findings for clinical practice and/or further research? Prenatal detection of CHD allows early workup to identify chromosomal abnormalities, detailed anatomic evaluation of extracardiac malformations and time to refer the parents to tertiary cardiac care centres and prepare for planned delivery, as well as to establish an appropriate perinatal and postnatal therapeutic plan.

Transition in cardiology 2: Maternal and fetal congenital heart disease

The number of women with congenital heart disease (CHD) reaching reproductive age has been increasing. Many women with CHDs are desirous of pregnancy, but they face issues regarding preconception, antepartum, and postpartum management. On the other hand, the fetal diagnosis of CHD has improved with advances in the technique and equipment for fetal echocardiography. Recently, experiences with fetal intervention have been reported in patients with severe CHD, such as critical aortic stenosis. Nevertheless, some types of CHD are challenge to diagnose prenatally, resulting in adverse outcomes. Medical care is part of the transitional care for women and fetuses with CHD during the perinatal period. Pre-conceptional and prenatal counseling play an important role in transitional care. Sex and reproductive education need to be performed as early as possible. We herein review the current status, important issues to be resolved, and the future of maternal and fetal CHD to relevant caregivers.

The electrical heart axis of the fetus between 18 and 24 weeks of gestation: A cohort study

Introduction

A fetal anomaly scan in mid-pregnancy is performed, to check for the presence of congenital anomalies, including congenital heart disease (CHD). Unfortunately, 40% of CHD is still missed. The combined use of ultrasound and electrocardiography might boost detection rates. The electrical heart axis is one of the characteristics which can be deduced from an electrocardiogram (ECG). The aim of this study was to determine reference values for the electrical heart axis in healthy fetuses around 20 weeks of gestation.

Material and methods

Non-invasive fetal electrocardiography was performed subsequent to the fetal anomaly scan in pregnant women carrying a healthy singleton fetus between 18 and 24 weeks of gestation. Eight adhesive electrodes were applied on the maternal abdomen including one ground and one reference electrode, yielding six channels of bipolar electrophysiological measurements. After removal of interferences, a fetal vectorcardiogram was calculated and then corrected for fetal orientation. The orientation of the electrical heart axis was determined from this normalized fetal vectorcardiogram. Descriptive statistics were used on normalized cartesian coordinates to determine the average electrical heart axis in the frontal plane. Furthermore, 90% prediction intervals (PI) for abnormality were calculated.

Results

Of the 328 fetal ECGs performed, 281 were included in the analysis. The average electrical heart axis in the frontal plane was determined at 122.7° (90% PI: -25.6°; 270.9°).

Discussion

The average electrical heart axis of healthy fetuses around mid-gestation is oriented to the right, which is, due to the unique fetal circulation, in line with muscle distribution in the fetal heart.

Newborn Pulse Oximetry for Infants Born Out-of-Hospital

BACKGROUND AND OBJECTIVES

Conventional timing of newborn pulse oximetry screening is not ideal for infants born out-of-hospital. We implemented a newborn pulse oximetry screen to align with typical midwifery care and measure its efficacy at detecting critical congenital heart disease.

METHODS

Cohort study of expectant mothers and infants mainly from the Amish and Mennonite (Plain) communities with limited prenatal ultrasound use. Newborns were screened at 1 to 4 hours of life ("early screen") and 24 to 48 hours of life ("late screen"). Newborns were followed up to 6 weeks after delivery to report outcomes. Early screen, late screen, and combined results were analyzed on the basis of strict algorithm interpretation ("algorithm") and the midwife's interpretation in the field ("field") because these did not correspond in all cases.

RESULTS

Pulse oximetry screening in 3019 newborns (85% Plain; 50% male; 43% with a prenatal ultrasound) detected critical congenital heart disease in 3 infants. Sensitivity of combined early and late screen was 66.7% (95% confidence interval [CI] 9.4% to 99.2%) for algorithm interpretation and 100% (95% CI 29.2% to 100%) for field interpretation. Positive predictive value was similar for the field interpretation (8.8%; 95% CI 1.9% to 23.7%) and algorithm interpretation (5.4%; 95% CI 0.7% to 18.2%). False-positive rates were ≤1.2% for both algorithm and field interpretations. Other pathologies (noncritical congenital heart disease, pulmonary issues, or infection) were reported in 12 of the false-positive cases.

CONCLUSIONS

Newborn pulse oximetry can be adapted to the out-of-hospital setting without compromising sensitivity or prohibitively increasing false-positive rates.

The current state of prenatal detection of genetic conditions in congenital heart defects

The incidence of congenital heart defect (CHD) has increased over the past fifty years, partly attributed to routine fetal anatomical examination by sonography during obstetric care and improvements in ultrasound technology and technique. Fetal findings on ultrasound in addition to maternal biomarkers are the backbone of first- and second-trimester screening for common genetic conditions, namely aneuploidy. Since the introduction of non-invasive prenatal testing (NIPT) using next-generation sequencing to sequence cell-free fetal DNA, the detection rate of common trisomies as well as sex chromosomal aneuploidies have markedly increased. As the use of NIPT continues to broaden, the best means of incorporating NIPT into prenatal care is less clear and complicated by misunderstanding of the limitations and non-diagnostic role of NIPT by clinicians and families. In other advancements in prenatal genetic testing, recommendations on the role of chromosomal microarray (CMA) for prenatal diagnosis has led to its increasing use to identify genetic conditions in fetuses diagnosed with CHD. Lastly, as whole exome sequencing (WES) becomes more available and affordable, the next clinical application of next-generation sequencing in prenatal diagnostic testing is on the horizon. While newer genetic tests may provide answers in terms of genetic diagnosis, even more questions will likely ensue for clinicians, researchers, and parents. The objective of this review is to provide the perspective of the evolution of maternal and fetal obstetric care against the backdrop of advancing genetic technology and its impact on families and clinicians.

Ethical issues after pre-natal diagnosis

Following pre-natal diagnosis of congenital heart defect parents and family face a dramatic psychological crisis because of their state of shock, contradictory information available on potential outcomes, limited availability of time for decisions and for autonomous choices. Counselling the parents can present additional difficulties due to influence of education, cultural and religious background, individual cognitive and emotional processes, and cross-cultural patient care is a challenging issue for the caregivers. Type and quality of messages transmitted by the caregivers determine the counselling process, with the risk of misunderstandings particularly high with reduced available evidence, or with different outcomes accordingly with the various alternatives of treatment. Since the introduction of pre-natal diagnosis for congenital abnormality, interruption of pregnancy became available on these grounds in many Western countries, and the numbers of babies born with congenital heart defects has declined significantly despite concomitant advances in treatment options and outcomes. Detailed and objective information, with all available options, should be provided after pre-natal diagnosis of congenital heart defect. One of the major achievements of pediatric medicine in the last 50 years is the increased understanding of the pathogenetic causal mechanisms of congenital heart defects as well as its treatment. For congenital heart defects the progress of surgical treatments allowed a huge proportion of these children to reach adult life with a decent quality of life and social integration. Therefore, must be a considerable concern that universal pre-natal diagnosis widespread pregnancy interruption may obviate those gains. A reduction in the post-natal population undergoing treatment may have a significantly deleterious effect on the expertise of the caregivers, producing a reduction in outcome quality. With all respect for the parental choices and the obligations to follow the national laws, is necessary to remark that our society is genuinely ambivalent.

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.

Analysis of Biomarkers for Congenital Heart Disease Based on Maternal Amniotic Fluid Metabolomics

Congenital heart disease (CHD) is the most common birth defect. The prenatal diagnosis of fetal CHD is completely dependent on ultrasound testing, but only ~40% of CHD can be detected. The purpose of this study is to find good biomarkers in amniotic fluid (AF) to detect CHD in the second trimester, so as to better manage this group of people and reduce the harm of CHD to the fetus. Metabolites analysis were performed in two separate sets. The discovery set consisted of 18 CHD fetal maternal AF samples and 35 control samples, and the validation set consisted of 53 CHD fetal maternal AF samples and 114 control samples. Untargeted metabolite profiles were analyzed by gas chromatography/time-of-flight-mass spectrometry (GC-TOF/MS). Orthogonal partial least square discrimination analysis (OPLS-DA) demonstrated that CHD and control samples had significantly different metabolic profiles. Two metabolites, uric acid and proline, were significantly elevated in CHD and verified in two data sets. Uric acid was associated with CHD [odds ratio (OR): 7.69 (95% CI: 1.18-50.13) in the discovery set and 3.24 (95% CI:1.62-6.48) in the validation set]. Additionally, uric acid showed moderate predictive power; the area under curve (AUC) was 0.890 in the discovery set and 0.741 in the validation set. The sensitivity and specificity of uric acid to detect CHD was, respectively, 94.4 and 74.3% in the discovery set and 67.9 and 71.9% in the validation set. The identification of uric acid as a biomarker for CHD has the potential to stimulate research on the pathological mechanism of CHD and the development of a diagnostic test for clinical applications.

Racial and ethnic disparities in coronary, vascular, structural, and congenital heart disease

Cardiovascular disease (CVD) remains the leading cause of death in the United States. However, percutaneous interventional cardiovascular therapies are often underutilized in Blacks, Hispanics, and women and may contribute to excess morbidity and mortality in these vulnerable populations. The Society for Cardiovascular Angiography and Interventions (SCAI) is committed to reducing racial, ethnic, and sex-based treatment disparities in interventional cardiology patients. Accordingly, each of the SCAI Clinical Interest Councils (coronary, peripheral, structural, and congenital heart disease [CHD]) participated in the development of this whitepaper addressing disparities in diagnosis, treatment, and outcomes in underserved populations. The councils were charged with summarizing the available data on prevalence, treatment, and outcomes and elucidating potential reasons for any disparities. Given the huge changes in racial and ethnic composition by age in the United States (Figure 1), it was difficult to determine disparities in rates of diagnosis and we expected to find some racial differences in prevalence of disease. For example, since the average age of patients undergoing transcatheter aortic valve replacement (TAVR) is 80 years, one may expect 80% of TAVR patients to be non-Hispanic White. Conversely, only 50% of congenital heart interventions would be expected to be performed in non-Hispanic Whites. Finally, we identified opportunities for SCAI to advance clinical care and equity for our patients, regardless of sex, ethnicity, or race.

Impact of Socioeconomic Status, Race and Ethnicity, and Geography on Prenatal Detection of Hypoplastic Left Heart Syndrome and Transposition of the Great Arteries

BACKGROUND

Prenatal detection (PND) has benefits for infants with hypoplastic left heart syndrome (HLHS) and transposition of the great arteries (TGA), but associations between sociodemographic and geographic factors with PND have not been sufficiently explored. This study evaluated whether socioeconomic quartile (SEQ), public insurance, race and ethnicity, rural residence, and distance of residence (distance and driving time from a cardiac surgical center) are associated with the PND or timing of PND, with a secondary aim to analyze differences between the United States and Canada.

METHODS

In this retrospective cohort study, fetuses and infants <2 months of age with HLHS or TGA admitted between 2012 and 2016 to participating Fetal Heart Society Research Collaborative institutions in the United States and Canada were included. SEQ, rural residence, and distance of residence were derived using maternal census tract from the maternal address at first visit. Subjects were assigned a SEQ z score using the neighborhood summary score or Canadian Chan index and separated into quartiles. Insurance type and self-reported race and ethnicity were obtained from medical charts. We evaluated associations among SEQ, insurance type, race and ethnicity, rural residence, and distance of residence with PND of HLHS and TGA (aggregate and individually) using bivariate analysis with adjusted associations for confounding variables and cluster analysis for centers.

RESULTS

Data on 1862 subjects (HLHS: n=1171, 92% PND; TGA: n=691, 58% PND) were submitted by 21 centers (19 in the United States). In the United States, lower SEQ was associated with lower PND in HLHS and TGA, with the strongest association in the lower SEQ of pregnancies with fetal TGA (quartile 1, 0.78 [95% CI, 0.64-0.85], quartile 2, 0.77 [95% CI, 0.64-0.93], quartile 3, 0.83 [95% CI, 0.69-1.00], quartile 4, reference). Hispanic ethnicity (relative risk, 0.85 [95% CI, 0.72-0.99]) and rural residence (relative risk, 0.78 [95% CI, 0.64-0.95]) were also associated with lower PND in TGA. Lower SEQ was associated with later PND overall; in the United States, rural residence and public insurance were also associated with later PND.

CONCLUSIONS

We demonstrate that lower SEQ, Hispanic ethnicity, and rural residence are associated with decreased PND for TGA, with lower SEQ also being associated with decreased PND for HLHS. Future work to increase PND should be considered in these specific populations.

Examining ultrasound diagnostic performance improvement with utilization of maternal-fetal medicine tele-interpretation

BACKGROUND

Telemedicine can extend essential health services to under-resourced settings and improve the quality of obstetrical care. Specifically, the evaluation and management of fetal anomalies require perinatal subspecialists, rendering prenatal diagnosis essential, and may benefit from telemedicine platforms to improve access to care.

OBJECTIVE

This study aimed to evaluate the impact of a maternal-fetal medicine telemedicine ultrasound program on the diagnostic accuracy of fetal anomalies when used within practices where ultrasounds are interpreted by general obstetricians or family medicine physicians.

STUDY DESIGN

This was a cross-sectional study of all patients receiving care at 11 private obstetrical practices and imaging centers who had obstetrical ultrasounds performed from January 1, 2020, to July 6, 2020. All ultrasounds were performed by sonographers remotely trained under a standardized protocol and interpreted by maternal-fetal medicine physicians via telemedicine. Ultrasound characteristics and interpretation were extracted from ultrasound reports. Before the introduction of maternal-fetal medicine telemedicine, all ultrasound interpretations were reviewed by general obstetricians and family medicine physicians with reliance predominantly on the sonographer's impression. The primary outcome was potential missed diagnosis of a fetal anomaly, defined as an ultrasound designated as normal by a sonographer but diagnosed with an anomaly by a maternal-fetal medicine physician via telemedicine. This outcome serves as a proxy measure for anomaly diagnoses that would likely be missed without the supervision of a maternal-fetal medicine physician. The characteristics of the potential missed diagnoses were compared by type of scan and fetal organ system in univariable analysis. Moreover, a survey was conducted for sonographers and obstetrical providers to assess their perceptions of ultrasound interpretation via telemedicine.

RESULTS

Overall, 6403 ultrasound examinations were evaluated, 310 of which had a diagnosis of fetal anomaly by a maternal-fetal medicine physician (4.8%). Of the fetal anomalies, 43 were diagnosed on an anatomic survey (13.9%), and 89 were diagnosed as cardiac anomalies (28.7%). The overall rate of the potential missed diagnoses was 34.5% and varied significantly by type of ultrasound (anatomy scans vs other first-, second-, and third-trimester ultrasounds) (P<.01). Moreover, there were significant differences in the rate of the potential missed diagnoses by organ system, with the highest rate for cardiac anomalies (P<.01).

CONCLUSION

Expertise in maternal-fetal medicine telemedicine improves the diagnostic performance of antenatal ultrasound throughout pregnancy. However, there are implications for improving the quality of antenatal care, such as ensuring appropriate referrals and site of delivery, particularly for cardiac anomalies.

Urine metabolomic biomarkers for prediction of isolated fetal congenital heart defect

OBJECTIVE

To identify maternal second and third trimester urine metabolomic biomarkers for the detection of fetal congenital heart defects (CHDs).

STUDY DESIGN

This was a prospective study. Metabolomic analysis of randomly collected maternal urine was performed, comparing pregnancies with isolated, non-syndromic CHDs versus unaffected controls. Mass spectrometry (liquid chromatography and direct injection and tandem mass spectrometry, LC-MS-MS) as well as nuclear magnetic resonance spectrometry, ¹H NMR, were used to perform the analyses between 14 0/7 and 37 0/7 weeks gestation. A total of 36 CHD cases and 41 controls were compared. Predictive algorithms using urine markers alone or combined with, clinical and ultrasound (US) (four-chamber view) predictors were developed and compared.

RESULTS

A total of 222 metabolites were identified, of which 16 were overlapping between the two platforms. Twenty-three metabolite concentrations were found in significantly altered in CHD gestations on univariate analysis. The concentration of methionine was most significantly altered. A predictive algorithm combining metabolites (histamine, choline, glucose, formate, methionine, and carnitine) plus US four-chamber view achieved an AUC = 0.894; 95% CI, 0814-0.973 with a sensitivity of 83.8% and specificity of 87.8%. Enrichment pathway analysis identified several lipid related pathways that are dysregulated in CHD, including phospholipid biosynthesis, phosphatidylcholine biosynthesis, phosphatidylethanolamine biosynthesis, and fatty acid metabolism. This could be consistent with the increased risk of CHD in diabetic pregnancies.

CONCLUSIONS

We report a novel, noninvasive approach, based on the analysis of maternal urine for isolated CHD detection. Further, the dysregulation of lipid- and folate metabolism appears to support prior data on the mechanism of CHD.

Reliability of Sonography-based Volume Computer Aided Diagnosis in the Normal Fetal Heart

OBJECTIVES

To explore the inter- and intra-observer reliability of Sonography-based Volume Computer Aided Diagnosis (SonoVCAD) in the display of 8 diagnostic planes of fetal echocardiography and to evaluate its efficiency.

METHODS

Three-dimensional volume data sets of the 56 normal singleton fetuses were acquired from a 4-chamber view by using a volume probe. After processing the data sets by using SonoVCAD, 8 cardiac diagnostic planes were displayed automatically. Three doctors with different experiences of performing fetal echocardiography evaluated each diagnostic plane and the success rates of 8 diagnostic planes were calculated. Inter-observer and intra-observer reliabilities were estimated by Cohen's kappa statistics.

RESULTS

A total of 276 volume data sets acquired from the 56 normal fetuses were used for SonoVCAD analysis and display. The success rate of each diagnostic section was more than 90%, ranging from 90.6% to 99.6%. Among 276 volumes, 81.5% (225/276) of volumes were able to generate all 8 diagnostic views successfully. Moderate to substantial agreement (kappa, 0.509-0.794) was found between 2 less experienced operators. Moderate to near-perfect agreement (kappa, 0.439-0.933) was found between an expert and 2 less experienced sonographers. Intra-observer reliability was substantial to near-perfect (kappa, 0.602-0.903). The efficiency of SonoVCAD was assessed. The expert spent less time than 2 less experienced examiners (P < 0.001) but no significant difference was found between 2 less experienced examiners (P = 0.176). Besides, SonoVCAD consumed significantly less time than 2-dimensional ultrasound (P < 0.001).

CONCLUSIONS

SonoVCAD can significantly improve the success rates of 8 diagnostic planes in fetal echocardiography with low operator dependency, good reproducibility and high efficiency.

Ultrasound screening for fetal anomalies in a single center: diagnostic performances twenty years after the Eurofetus Study

PURPOSE

To establish the accuracy of ultrasound in detecting fetal anomalies looking at the concordance between prenatal and postnatal diagnosis.

MATERIALS AND METHODS

Retrospective analysis of concordance between prenatal and postnatal/autoptic diagnosis of fetuses with congenital abnormalities. Data are from a single center (Policlinico di Modena); all fetuses included were born between 2017 and 2018 and with a follow-up of at least 6 months. We included all deliveries (including perinatal deaths) and termination of pregnancy (TOP) for fetal indication. We calculated sensibility, sensitivity, Positive and Negative Likelihood Ratio, positive and negative predictive value of ultrasound.

RESULTS

During the study period 5920 deliveries, including perinatal deaths, and 28 TOP for fetal indication were registered at our center. The prevalence of congenital malformations was 2.6% (153/5920). At least one ultrasound was performed in our center in 1250 women delivering in our unit. All 28 TOP had the anomaly scan performed in our center. Among the total 1278 women scanned in our unit, there were 128 (10%) suspicious scans. In 5/128 (3.9%) cases we diagnosed a false alarm; in 8/128 (6.2%) cases an evolutive malformation with in-utero regression. The prenatal diagnosis was confirmed in 77 (60.2%) cases at birth and in 28/128 (21.9%) at postmortem analysis while there were 10/128 false positive (7.8%). Among the 153 congenital malformations diagnosed at birth, the anomaly scan was performed in our Prenatal Medicine Unit in 92 (60.1%) fetuses. Among these, there were 15 false negatives (9.8%) while in 77/92 (83.7%) the malformation at birth agreed with the sonographic diagnosis. Sensitivity and specificity of ultrasound were 87.5% (IC95 80.2-92.8%) and 99.1% (IC95 98.4-99.6%) respectively with a Positive Likelihood Ratio and Negative Likelihood Ratio of 101.3 (IC95 54.5-188.5) and 0.13 (IC95 0.08-0.2); Positive Predictive Value and Negative Predictive Value were 91.3% (IC95 85-95.1%) and 98.7(IC95 98-99.2%).

CONCLUSION

Anomaly scan in pregnancy allows the diagnosis of congenital malformations with a sensibility of 87.5% and specificity of 99.1%. The main limitations of this study are its retrospective design and that it was conducted in a single referral center.

Early detection of significant congenital heart disease: The contribution of fetal cardiac ultrasound and newborn pulse oximetry screening

Fetal cardiac and newborn pulse oximetry screening has greatly facilitated the detection of cardiac abnormalities, which may be serious with potentially dire neonatal consequences. The prenatal diagnosis of a serious cardiac abnormality allows the attending obstetrician to organise the much safer in-utero transfer of the fetus for delivery at a tertiary centre, particularly if there is evidence of a duct-dependent lesion that may require the infusion of Prostaglandin E1 to maintain duct patency pending surgical intervention. Newborn pulse oximetry alerts the paediatrician that the baby may have a significant cardiac abnormality, which warrants further elucidation prior to discharge, rather than for the baby to represent unwell a few days later. Despite these advances, serious cardiac abnormalities may be missed on screening. Their detection then falls back onto the clinical acumen of the attending paediatrician/family physician to review the history, carefully elicit and evaluate the clinical signs further aided by whatever investigations that may be available at the birthing hospital, frequently less resourced than the tertiary centres. At the outset, a brief synopsis is provided of the clinical findings that may point to a cardiac abnormality. That is followed by a critical review of the accuracy of prenatal and newborn pulse oximetry screening with emphasis on the lesions that may be missed. Suggestions are made as to how to improve the diagnostic accuracy.

A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

The current diagnosis of Congenital Heart Disease (CHD) in neonates relies on echocardiography. Its limited availability requires alternative screening procedures to prioritise newborns awaiting ultrasound. The routine screening for CHD is performed using a multidimensional clinical examination including (but not limited to) auscultation and pulse oximetry. While auscultation might be subjective with some heart abnormalities not always audible it increases the ability to detect heart defects. This work aims at developing an objective clinical decision support tool based on machine learning (ML) to facilitate differentiation of sounds with signatures of Patent Ductus Arteriosus (PDA)/CHDs, in clinical settings. The heart sounds are pre-processed and segmented, followed by feature extraction. The features are fed into a boosted decision tree classifier to estimate the probability of PDA or CHDs. Several mechanisms to combine information from different auscultation points, as well as consecutive sound cycles, are presented. The system is evaluated on a large clinical dataset of heart sounds from 265 term and late-preterm newborns recorded within the first six days of life. The developed system reaches an area under the curve (AUC) of 78% at detecting CHD and 77% at detecting PDA. The obtained results for PDA detection compare favourably with the level of accuracy achieved by an experienced neonatologist when assessed on the same cohort.

Comparison of the 1-year survival rate in infants with congenital heart disease diagnosed by prenatal and postnatal ultrasound: A retrospective study

The impact of prenatal diagnosis on the survival outcome of infants with congenital heart disease (CHD) is still unclear. This study aimed to compare the 1-year survival rate between the prenatally and postnatally diagnosed infants with CHDs.A single-center population-based retrospective cohort study was performed on data from all infants diagnosed with CHD born between January 1998 and December 2017. Among infants with isolated CHDs, the 1-year Kaplan-Meier survival probabilities for prenatal and postnatal diagnosis were estimated. Cox proportional hazard ratios were adjusted for critical CHD (CCHD) status and gestational age.A total of 424 (40 prenatally and 384 postnatally) diagnosed infants with CHDs were analyzed. Compared with non-CCHDs, infants with CCHDs were more likely to be prenatally diagnosed (55.0% vs 18.0%; P < .001). Among the 312 infants with isolated CHDs, the 1-year survival rate for the prenatally diagnosed was significantly lower than postnatally diagnosed (77.1% vs 96.1%; P < .001). For isolated CCHDs, the 1-year survival rate for the prenatally diagnosed was significantly lower than postnatally diagnosed (73.4% vs 90.0%; P < .001). The 1-year survival rate was increased with the increase of age at diagnosis. Among infants with isolated CHDs and CCHDs, the adjusted hazard ratios for 1-year mortality rates for the prenatally versus postnatally diagnosed were 2.554 (95% confidence interval [CI], 1.790, 3.654; P < .001) and 2.538 (95% CI: 1.796, 3.699; P < .001), respectively.Prenatal diagnosis is associated with lower 1-year survival rate for infants with isolated CCHDs. This could probably due to variation in the disease severity among the CCHD subtypes.

Feasibility of Semiautomatic Fetal Intelligent Navigation Echocardiography for Different Fetal Spine Positions: A Matter of "Time"?

OBJECTIVES

We investigated the feasibility of a semiautomatic approach for assessments of the fetal heart (fetal intelligent navigation echocardiography [FINE]) in cases of optimal and unfavorable fetal spine positions.

METHODS

In this study, a total of 1693 spatiotemporal image correlation volumes of first-, second-, and third-trimester fetuses were evaluated by experts using the FINE approach. The data were analyzed regarding proper reconstruction of the diagnostic cardiac planes depending on the fetal spine position.

RESULTS

A total of 1531 volumes were included. The volumes were divided into 4 groups depending on the fetal spine position: 5-7 o'clock, 4 + 8 o'clock, 3 + 9 o'clock, and 2 + 10 o'clock. In total, 93.2% of the diagnostic planes were displayed properly. Between 5 and 7 o'clock, 94.9% of the diagnostic planes were displayed properly. The correct depiction rates in the other groups were 92.4% (4 + 8 o'clock; n = 538; P = 0.0027), 88.3% (3 + 9 o'clock; n = 156; P < .0001), and 87.3% (2 + 10 o'clock; n = 41; P = .0139). In total, the highest dropout rates were found in the sagittal planes: ductal arch, 13.9%; aortic arch, 10.5%; and venae cavae, 12.0%.

CONCLUSIONS

Based on our results, the FINE technique is an effective method, but its feasibility depends on the fetal position. The use of this semiautomatic work flow-based approach supports evaluation of the fetal heart in a standardized manner. Semiautomatic evaluation of the fetal heart might be useful in facilitating the detection of fetal cardiac anomalies.