Cardiotocography and beyond: a review of one-dimensional Doppler ultrasound application in fetal monitoring

Abstract

One-dimensional Doppler ultrasound (1D-DUS) provides a low-cost and simple method for acquiring a rich signal for use in cardiovascular screening. However, despite the use of 1D-DUS in cardiotocography (CTG) for decades, there are still challenges that limit the effectiveness of its users in reducing fetal and neonatal morbidities and mortalities. This is partly due to the noisy, transient, complex and nonstationary nature of the 1D-DUS signals. Current challenges also include lack of efficient signal quality metrics, insufficient signal processing techniques for extraction of fetal heart rate and other vital parameters with adequate temporal resolution, and lack of appropriate clinical decision support for CTG and Doppler interpretation. Moreover, the almost complete lack of open research in both hardware and software in this field, as well as commercial pressures to market the much more expensive and difficult to use Doppler imaging devices, has hampered innovation. This paper reviews the basics of fetal cardiac function, 1D-DUS signal generation and processing, its application in fetal monitoring and assessment of fetal development and wellbeing. It also provides recommendations for future development of signal processing and modeling approaches, to improve the application of 1D-DUS in fetal monitoring, as well as the need for annotated open databases.

Data-Driven Modeling of Pregnancy-Related Complications

“…Time-Series Data Are a Promising Complex Modality Clinical time-series data are essential for monitoring patients and health assessments in real time [e.g., in the intensive care unit (ICU)] as well as in retrospective settings (e.g., for long-term monitoring and diagnoses). One example in the context of pregnancy is fetal heart rate analysis to identify pathological fetal conditions like perinatal hypoxia, FGR, or fetal arrhythmias and heart anomalies [129]. Here, a common practice is to extract various quantitative parameters associated with fetal conditions such as short-term variability (STV) and long-term irregularity (LTI) of fetal heart rate measurements, which are then directly interpreted or converted into a tabular format that can be used for machine learning [129,130].…”

“…One example in the context of pregnancy is fetal heart rate analysis to identify pathological fetal conditions like perinatal hypoxia, FGR, or fetal arrhythmias and heart anomalies [129]. Here, a common practice is to extract various quantitative parameters associated with fetal conditions such as short-term variability (STV) and long-term irregularity (LTI) of fetal heart rate measurements, which are then directly interpreted or converted into a tabular format that can be used for machine learning [129,130]. However, there is a wide variety of advanced machinelearning methods for time-series analyses and classifications, specifically deep learning and recurrent neural networks, that have the potential to directly model and predict pathological fetal conditions [131][132][133].…”

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

“…Some synchronised comparisons have been reported in the literature for the latter 45 ; however, no direct comparison between the two modalities has been reported, apart from the HR with 1D Doppler 71,72 . Given the complex and changing nature of the 1D Doppler signal 73 , 1D Doppler ultrasound is not adopted in clinical routines, except for cardiotocography 47 , which is mainly used in late pregnancy for continuous HR monitoring. However, this technique cannot provide a signal useful for the detailed analysis of atrial and ventricular activity, i.e.…”

Doppler Ultrasound Technology for Fetal Heart Rate Monitoring: A Review

“…While some reviews describe the state-of-the-art in CTG or Doppler signal analysis, with a focus on feature extraction and clinical interpretation [35], [36], limited information is available for understanding the role of US Doppler signal acquisition, along with the associated limitations, challenges, and opportunities. The focus of this article lies on the technical building blocks of a Doppler US-based fHR monitoring system and their relation to possible error sources, which may prevent a successful fHR recording.…”