A systematic review of prenatal screening for congenital heart disease by fetal electrocardiography

Verdurmen, Kmj Kim; Eijsvoogel, Noortje; Lempersz, Carlijn; Vullings, Rik; Schroer, Christian; Laar, Joeh Judith van; Oei, S.G.

doi:10.1016/j.ijgo.2016.05.010

Cited by 25 publications

(15 citation statements)

References 34 publications

(59 reference statements)

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“…Therefore, fetal heart rate (FHR) measurement is integral to fetal surveillance throughout pregnancy, as it is of significant clinical importance. Fetal electrocardiography [ 3 , 4 ] can be used for the detection of the FHR before birth and thus makes it possible to administer faster medical or surgical interventions once the baby is born, if required. Noninvasive fetal electrocardiogram (FECG) monitoring methods [ 5 , 6 ] measure the abdominal electrocardiogram (AECG) through skin electrodes on the expecting mother’s abdomen.…”

Section: Introductionmentioning

confidence: 99%

A clustering-based method for single-channel fetal heart rate monitoring

et al. 2018

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Non-invasive fetal electrocardiography (ECG) is based on the acquisition of signals from abdominal surface electrodes. The composite abdominal signal consists of the maternal electrocardiogram along with the fetal electrocardiogram and other electrical interferences. These recordings allow for the acquisition of valuable and reliable information that helps ensure fetal well-being during pregnancy. This paper introduces a procedure for fetal heart rate extraction from a single-channel abdominal ECG signal. The procedure is composed of three main stages: a method based on wavelet for signal denoising, a new clustering-based methodology for detecting fetal QRS complexes, and a final stage to correct false positives and false negatives. The novelty of the procedure thus relies on using clustering techniques to classify singularities from the abdominal ECG into three types: maternal QRS complexes, fetal QRS complexes, and noise. The amplitude and time distance of all the local maxima followed by a local minimum were selected as features for the clustering classification. A wide set of real abdominal ECG recordings from two different databases, providing a large range of different characteristics, was used to illustrate the efficiency of the proposed method. The accuracy achieved shows that the proposed technique exhibits a competitve performance when compared to other recent works in the literature and a better performance over threshold-based techniques.

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Section: Introductionmentioning

confidence: 99%

A clustering-based method for single-channel fetal heart rate monitoring

et al. 2018

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“…Both fetuses with AVSD and HRHS may be expected to have a left-oriented electrical heart axis. We chose to include these CHD where the most overt differences in electrical heart axis can be expected compared to the healthy control group, since literature on the electrical heart axis in fetuses with CHD is scarce [ 16 , 33 , 34 ].…”

Section: Methodsmentioning

confidence: 99%

“…Prenatal detection of CHD allows for deliberate management to optimize the preoperative neonatal condition and therefore improve neonatal outcome. Furthermore, it keeps the option of pregnancy termination open if the diagnosis is made before the legal limit for pregnancy termination in the said country [11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

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

Noben

Lempersz²,

Heuvel³

et al. 2022

PLoS ONE

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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.

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“…Congenital heart disease (CHD) includes abnormalities in the heart structure that occur before birth [ 1 ]. It is the most common congenital anomaly, accounting for approximately 0.8% of live births [ 2 , 3 ], and ranks first among birth defects [ 4 ]. Despite significant advances in diagnosis and treatment in recent years, CHD remains the most common cause of death in newborns.…”

Section: Introductionmentioning

confidence: 99%

Development of Digital Fetal Heart Models with Virtual Ultrasound Function Based on Cardiovascular Casting and Computed Tomography Scan

et al. 2022

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Despite recent breakthroughs in diagnosis and treatment, congenital heart defects (CHDs) continue to be the leading cause of death among newborns. Fetal echocardiography is the most effective and non-invasive method for the prenatal diagnosis of CHDs. However, the challenge of obtaining standard views can lead to a low diagnostic accuracy. To explore new methods for training, the combined use of cardiovascular casting, computed tomography (CT) scanning, and virtual ultrasound generation methods was studied to preserve the cardiac structures of a fetus in digital form. The feasibility of the proposed workflow was verified by testing three fetal heart specimens collected after the termination of pregnancy. As a result, the anatomical structures were imaged clearly by a CT scan after cardiovascular casting, and the virtually generated ultrasound images based on the use of the Public software Library for UltraSound imaging research (PLUS) toolkit successfully demonstrated both the standard views and the views with diagnostic values for the visualization of the cardiovascular structures. This solution provides great data extensibility while being simple and cost-effective for end users. Therefore, the proposed method could provide a promising educational system for trainees to understand standard views of fetal echocardiography and the corresponding anatomical correlations.

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A systematic review of prenatal screening for congenital heart disease by fetal electrocardiography

Abstract: Fetal ECG might be a promising clinical tool to complement ultrasonography in the screening program for CHD.

Cited by 25 publications

References 34 publications

A clustering-based method for single-channel fetal heart rate monitoring

A clustering-based method for single-channel fetal heart rate monitoring

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

Development of Digital Fetal Heart Models with Virtual Ultrasound Function Based on Cardiovascular Casting and Computed Tomography Scan

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