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

Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease

INTRODUCTION

This study aims to investigate non-invasive electrocardiography as a method for the detection of congenital heart disease (CHD) with the help of artificial intelligence.

MATERIAL AND METHODS

An artificial neural network was trained for the identification of CHD using non-invasively obtained fetal electrocardiograms. With the help of a Bayesian updating rule, multiple electrocardiographs were used to increase the algorithm's performance.

RESULTS

Using 122 measurements containing 65 healthy and 57 CHD cases, the accuracy, sensitivity, and specificity were found to be 71%, 63%, and 77%, respectively. The sensitivity was however 75% and 69% for CHD cases requiring an intervention in the neonatal period and first year of life, respectively. Furthermore, a positive effect of measurement length on the detection performance was observed, reaching optimal performance when using 14 electrocardiography segments (37.5 min) or more. A small negative trend between gestational age and accuracy was found.

CONCLUSIONS

The proposed method combining recent advances in obtaining non-invasive fetal electrocardiography with artificial intelligence for the automatic detection of CHD achieved a detection rate of 63% for all CHD and 75% for critical CHD. This feasibility study shows that detection rates of CHD might improve by using electrocardiography-based screening complementary to the standard ultrasound-based screening. More research is required to improve performance and determine the benefits to clinical practice.

Adapting to a new environment: postnatal maturation of the human cardiomyocyte

The postnatal mammalian heart undergoes remarkable developmental changes, which are stimulated by the transition from the intrauterine to extrauterine environment. With birth, increased oxygen levels promote metabolic, structural and biophysical maturation of cardiomyocytes, resulting in mature muscle with increased efficiency, contractility and electrical conduction. In this Topical Review article, we highlight key studies that inform our current understanding of human cardiomyocyte maturation. Collectively, these studies suggest that human atrial and ventricular myocytes evolve quickly within the first year but might not reach a fully mature adult phenotype until nearly the first decade of life. However, it is important to note that fetal, neonatal and paediatric cardiac physiology studies are hindered by a number of limitations, including the scarcity of human tissue, small sample size and a heavy reliance on diseased tissue samples, often without age-matched healthy controls. Future developmental studies are warranted to expand our understanding of normal cardiac physiology/pathophysiology and inform age-appropriate treatment strategies for cardiac disease.

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.