Systematic Review of Intrapartum Fetal Heart Rate Spectral Analysis and an Application in the Detection of Fetal Acidemia

Abstract

It is fundamental to diagnose fetal acidemia as early as possible, allowing adequate obstetrical interventions to prevent brain damage or perinatal death. The visual analysis of cardiotocography traces has been complemented by computerized methods in order to overcome some of its limitations in the screening of fetal hypoxia/acidemia. Spectral analysis has been proposed by several studies exploring fetal heart rate recordings while referring to a great variety of frequency bands for integrating the power spectrum. In this paper, the main goal was to systematically review the spectral bands reported in intrapartum fetal heart rate studies and to evaluate their performance in detecting fetal acidemia/hypoxia. A total of 176 articles were reviewed, from MEDLINE, and 26 were included for the extraction of frequency bands and other relevant methodological information. An open-access fetal heart rate database was used, with recordings of the last half an hour of labor of 246 fetuses. Four different umbilical artery pH cutoffs were considered for fetuses' classification into acidemic or non-acidemic: 7.05, 7.10, 7.15, and 7.20. The area under the receiver operating characteristic curve (AUROC) was used to quantify the frequency bands' ability to distinguish acidemic fetuses. Bands referring to low frequencies, mainly associated with neural sympathetic activity, were the best at detecting acidemic fetuses, with the more severe definition (pH ≤ 7.05) attaining the highest values for the AUROC. This study shows that the power spectrum analysis of the fetal heart rate is a simple and powerful tool that may become an adjunctive method to CTG, helping healthcare professionals to accurately identify fetuses at risk of intrapartum hypoxia and to implement timely obstetrical interventions to reduce the incidence of related adverse perinatal outcomes.

Fetal heart rate variability is a biomarker of rapid but not progressive exacerbation of inflammation in preterm fetal sheep

“…In this study, we chose to utilize the standard adult VLF, LF and HF bands, and included an additional VHF band to interrogate higher frequency activity in view of evidence that FHRV includes higher frequency rhythms than the adult heart rate, at least in part due to the high frequency of fetal breathing movements 35 – 37 . Our rationale for the inclusion of an additional VHF band instead of adopting the proposed extended ‘fetal’ HF band is that this approach provides greater granularity of information, and allows better comparison to adult data 38 , 39 .…”

Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals

“…The principal components resulting from the application of the bwPCA, together with the two global features that were kept unchanged (pregnancy week and FHR mean), represent a subset of eight meaningful features, i.e., features that can be related to peculiar and interpretable information brought by the examined signals. Indeed, the following characteristics of the signals are represented in the obtained subset: one time-domain information (LIN_time), which represents a statistical description of the variability of the signal [ 44 , 45 , 61 , 62 ]; three types of frequency-domain information, i.e., LIN_VLF_power, LIN_LF_HF, and LIN_SVB, respectively, reflecting long period events like thermoregulation (LIN_VLF_power), neural sympathetic activity and fetal breathing (LIN_LF_HF), and the autonomic balance derived from sympathetic and parasympathetic control mechanisms (LIN_SVB) [ 23 , 45 , 63 , 64 , 65 ]; two types of indicators of nonlinear dynamics, the former, NL_variability, mainly related to the intrinsic variability of the FHRV, while the second one, NL_complexity, mainly revealing complex behavior and self-similarities in the time series. Finally, there are two general descriptors of the development and growth of the fetus, indicated by the pregnancy week and the mean FHR.…”

“…The efforts towards the establishment of a standard technique for the processing and analysis of FHR signals brought the development of different software solutions, methodological approaches, and indicators that could assist the clinical examination of CTG recordings, with particular regard to the FHR signals [ 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. As also happened in the analysis of adult and newborn heart rate signals [ 25 , 26 , 27 , 28 ], most of the newer computerized tools for FHR processing and analysis are based on Artificial Intelligence (AI) algorithms aimed at extracting novel features from the FHR signals, and achieve a more accurate classification of the traces according to the fetal health status [ 29 , 30 , 31 , 32 ].…”

Physiological control of fetal heart rate variability during labour: implications and controversies

“…2008; Castro et al . 2021) calculate measures of FHRV on relatively long intervals that include FHR decelerations, including clinical studies that have assessed frequency‐domain measures (van Laar et al . 2008; Castro et al .…”

“…2008; Castro et al . 2021). Although there are clear merits to this approach, FHR decelerations and FHRV are governed by distinct physiological and autonomic processes and so these analyses cannot be used to describe the dynamics of interdeceleration FHRV per se .…”