Time-scale analysis of antepartum fetal heart rate variability

Reliable evaluation of fetal condition and early detection of fetal distress is one of the largest challenges in modern obstetrics. Safely protected within the maternal womb, the fetus is rather inaccessible for physiological measurements. One of few physiological phenomena that can be measured antenatal, is fetal heart activity. The heart plays an essential role in the transportation of oxygen to the tissues, but is only one of multiple factors that influence oxygen supply. Consequently, fetal heart activity provides direct, but rather limited information for the evaluation of fetal condition. Cardiotocography, the simultaneous recording of fetal heart rate and uterine activity, has been the standard in fetal monitoring for more than 30 years. Nevertheless, cardiotocography is insufficiently capable of predicting bad fetal outcome and therefore its value in clinical practice is limited. As a result, any additional information that can contribute to reliably evaluating fetal condition, is highly appreciated. The beat-to-beat variability of the fetal heart rate is an expression of cardiovascular control by the autonomic part of the fetal central nervous system. As this cardiovascular control will respond to changes in fetal condition, fetal heart rate variability will indirectly reflect fetal condition. Fetal heart rate activity therefore contains potentially useful information that cardiotocography does not reveal. As modulation by different parts of the autonomic nervous system occurs on characteristic timescales, timefrequency analysis of fetal heart rate variability might provide additional information that can be used to more reliably assess fetal well-being. However, interpretation of this information is complicated by the complexity of the physiological mechanisms for cardiovascular control. Additionally, to obtain accurate spectral information, the beat-to-beat fetal heart rate is required, which can only be obtained in clinical practice by measuring the fetal electrocardiogram directly from the fetal scalp. This currently limits the application of the method to intrapartum measurements. To further explore the potential of time-frequency analysis of fetal heart rate variability for monitoring fetal condition, application of the analysis technique to antepartum measurements is highly appreciated. The first goal of this doctoral dissertation therefore is to: 1. Obtain the beat-to-beat fetal heart rate throughout pregnancy Given the limited successes in literature, it is expected that the obtained fetal heart rate will contain considerably more artifacts than the fetal heart rate obtained from scalp ECG measurements during labor does. Standard techniques for time-frequency analysis, such as the fast Fourier transform, will then fail to provide accurate spectral information. The second goal of this dissertation therefore is to: 2. Obtain accurate spectral information on antepartum fetal heart rate variability To measure fetal heart activity antepartum, a dedicated data-acquisition system has been developed for electrophysiological measurements on the abdomen of a pregnant woman (chapter 2). A novel method developed by a coworker was chosen to remove the dominating maternal electrocardiogram from the recorded signals. An online software implementation of this method has been realized to process the recorded signals real-time. To achieve the first goal of the dissertation, chapter 3 presents an algorithm that uses a priori knowledge on the physiology of the fetal heart to enhance the fetal ECG components in multi-lead abdominal fetal ECG recordings, before QRS-detection. Evaluation of the method on generated fetal ECG recordings with controlled signal-to-noise ratios showed excellent results. However, for actual recordings, evaluation of the results by experts learned that fine-tuning of the algorithm is necessary. In chapter 4, a more theoretical approach has been used to exploit the spatial correlation of multi-channel fetal ECG recordings for increasing the signal-to-noise ratio of the retrieved fetal electrocardiogram. A threedimensional representation of the fetal vectorcardiogram is constructed by erse Dower matrix. An ellipse is fitted to the QRS loop of several overlayed heartbeats and the axes of the ellipse are calculated to determine the source signals of the fetal electrocardiogram. In future work, this technique could be used for calculating the linear combinations that are used in the algorithm of chapter 3, which will increase the accuracy of the heart rate detection. The suitability of non-invasive fetal ECG recordings for fetal monitoring in clinical practice was evaluated by using the developed technology in a longitudinal patient study (chapter 5). Repeated measurements on pregnant patients learned that the performance of the method for removing the maternal electrocardiogram was good and remained more or less constant throughout pregnancy. Between 20 and 25 weeks of gestational age, the quality of the retrieved fetal ECG waveforms generally was very high, and the beat-to-beat fetal heart rate could be accurately detected. For this stage of pregnancy, abdominal measurement of the fetal electrocardiogram offers an opportunity to obtain unique cardiac information on the fetus. However, to increase the performance of the technology throughout pregnancy, the noise in the electrophysiological recordings must be significantly reduced. Still, it remains uncertain whether this will be adequate when isolating sections of the vernix caseosa reduce the amplitude of the fetal electrocardiogram that is measured on the maternal abdomen. For stages of pregnancy in which abdominal recording of the fetal electrocardiogram fails to provide the beat-to-beat heart rate, chapter 6 offers an alternative. By processing Doppler waveforms of ultrasound signals reflected at the fetal heart, the beat-to-beat fetal heart rate can be obtained. However, the measurement requires a skilled operator and is very sensitive to fetal movement. The presence of artifacts in the beat-to-beat fetal heart rate obtained from either abdominal recordings of the fetal electrocardiogram or Doppler ultrasound recordings, is common and cannot be prevented. To obtain the second goal of the dissertation, a continuous wavelet based analysis method has been developed to reliably calculate the power within the scales of interest (chapter 7). This method provides accurate results when up to 20 % of the dataset is missing due to artifacts. In chapter 8, the continuous wavelet based method has been applied for time-scale analysis of the recordings from chapter 5. The results of this analysis correspond with literature on the development of the fetal autonomic nervous system. In addition, the results suggest that functional development of the sympathetic nervous system takes place around 22 weeks of gestational age. The final chapter reflects on the realization of the goals of this dissertation and provides specific directions for future work. Although additional clinical research might contribute to obtaining clinically relevant information from time-scale analysis of fetal heart rate variability, focus should be on solving the technical limitations of the used instrumentation for abdominal recording of the fetal electrocardiogram

Bayesian approach to patient-tailored vectorcardiography

For assessment of specific cardiac pathologies, vectorcardiography is generally considered superior with respect to electrocardiography. Existing vectorcardiography methods operate by calculating the vectorcardiogram (VCG) as a fixed linear combination of ECG signals. These methods, with the inverse Dower matrix method the current standard, are therefore not flexible with respect to different body compositions and geometries. Hence, they cannot be applied with accuracy on patients that do not conform to the fixed standard. Typical examples of such patients are obese patients or fetuses. For the latter category, when recording the fetal ECG from the maternal abdomen the distance of the fetal heart with respect to the electrodes is unknown. Consequently, also the signal attenuation/transformation per electrode is not known. In this paper, a Bayesian method is developed that estimates the VCG and, to some extent, also the signal attenuation in multichannel ECG recordings from either the adult 12-lead ECG or the maternal abdomen. This is done by determining for which VCG and signal attenuation the joint probability over both these variables is maximal given the observed ECG signals. The underlying joint probability distribution is determined by assuming the ECG signals to originate from scaled VCG projections and additive noise. With this method, a VCG, tailored to each specific patient, is determined. The method is compared to the inverse Dower matrix method by applying both methods on standard 12-lead ECG recordings and evaluating the performance in predicting ECG signals from the determined VCG. In addition, to model nonstandard patients, the 12-lead ECG signals are randomly scaled and, once more, the performance in predicting ECG signals from the VCG is compared between both methods. Finally, both methods are also compared on fetal ECG signals that are obtained from the maternal abdomen. For patients conforming to the standard, both methods perform similarly, with the developed method performing marginally better. For scaled ECG signals and fetal ECG signals, the developed method significantly outperforms the inverse Dower matrix method

Fetal movement quantification by fetal vectrocardiography: a preliminary study.

Fetal movement is a valuable source of information to monitor the neurological development of the fetus and assess fetal health. Currently, fetal movement can be assessed by the mother or detected by analysis of ultrasound images. Long-term monitoring of movement is complicated with both these methods as maternal self-assessment has a relatively poor sensitivity and specificity and automatic analysis of ultrasound images is not available. Moreover, ultrasound transducers transmit energy into the body, potentially endangering fetal health. In this paper, an alternative method for fetal movement monitoring is presented. This method operates by estimating and analyzing the fetal vectorcardiogram (VCG) from non-invasive recordings on the maternal abdomen. The determined fetal movement is compared with that assessed from a simultaneously performed ultrasound recording; the results of the presented method are consistent with the ultrasound images. In addition, the presented method enables quantification of the rotation angles by means of analysis of the rotation matrix between consecutive fetal VCGs, providing a tool for long-term monitoring of fetal movement with increased specificity

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria

Time-scale analysis of antepartum fetal heart rate variability

Reliable evaluation of fetal condition and early detection of fetal distress is one of the largest challenges in modern obstetrics. Safely protected within the maternal womb, the fetus is rather inaccessible for physiological measurements. One of few physiological phenomena that can be measured antenatal, is fetal heart activity. The heart plays an essential role in the transportation of oxygen to the tissues, but is only one of multiple factors that influence oxygen supply. Consequently, fetal heart activity provides direct, but rather limited information for the evaluation of fetal condition. Cardiotocography, the simultaneous recording of fetal heart rate and uterine activity, has been the standard in fetal monitoring for more than 30 years. Nevertheless, cardiotocography is insufficiently capable of predicting bad fetal outcome and therefore its value in clinical practice is limited. As a result, any additional information that can contribute to reliably evaluating fetal condition, is highly appreciated. The beat-to-beat variability of the fetal heart rate is an expression of cardiovascular control by the autonomic part of the fetal central nervous system. As this cardiovascular control will respond to changes in fetal condition, fetal heart rate variability will indirectly reflect fetal condition. Fetal heart rate activity therefore contains potentially useful information that cardiotocography does not reveal. As modulation by different parts of the autonomic nervous system occurs on characteristic timescales, timefrequency analysis of fetal heart rate variability might provide additional information that can be used to more reliably assess fetal well-being. However, interpretation of this information is complicated by the complexity of the physiological mechanisms for cardiovascular control. Additionally, to obtain accurate spectral information, the beat-to-beat fetal heart rate is required, which can only be obtained in clinical practice by measuring the fetal electrocardiogram directly from the fetal scalp. This currently limits the application of the method to intrapartum measurements. To further explore the potential of time-frequency analysis of fetal heart rate variability for monitoring fetal condition, application of the analysis technique to antepartum measurements is highly appreciated. The first goal of this doctoral dissertation therefore is to: 1. Obtain the beat-to-beat fetal heart rate throughout pregnancy Given the limited successes in literature, it is expected that the obtained fetal heart rate will contain considerably more artifacts than the fetal heart rate obtained from scalp ECG measurements during labor does. Standard techniques for time-frequency analysis, such as the fast Fourier transform, will then fail to provide accurate spectral information. The second goal of this dissertation therefore is to: 2. Obtain accurate spectral information on antepartum fetal heart rate variability To measure fetal heart activity antepartum, a dedicated data-acquisition system has been developed for electrophysiological measurements on the abdomen of a pregnant woman (chapter 2). A novel method developed by a coworker was chosen to remove the dominating maternal electrocardiogram from the recorded signals. An online software implementation of this method has been realized to process the recorded signals real-time. To achieve the first goal of the dissertation, chapter 3 presents an algorithm that uses a priori knowledge on the physiology of the fetal heart to enhance the fetal ECG components in multi-lead abdominal fetal ECG recordings, before QRS-detection. Evaluation of the method on generated fetal ECG recordings with controlled signal-to-noise ratios showed excellent results. However, for actual recordings, evaluation of the results by experts learned that fine-tuning of the algorithm is necessary. In chapter 4, a more theoretical approach has been used to exploit the spatial correlation of multi-channel fetal ECG recordings for increasing the signal-to-noise ratio of the retrieved fetal electrocardiogram. A threedimensional representation of the fetal vectorcardiogram is constructed by erse Dower matrix. An ellipse is fitted to the QRS loop of several overlayed heartbeats and the axes of the ellipse are calculated to determine the source signals of the fetal electrocardiogram. In future work, this technique could be used for calculating the linear combinations that are used in the algorithm of chapter 3, which will increase the accuracy of the heart rate detection. The suitability of non-invasive fetal ECG recordings for fetal monitoring in clinical practice was evaluated by using the developed technology in a longitudinal patient study (chapter 5). Repeated measurements on pregnant patients learned that the performance of the method for removing the maternal electrocardiogram was good and remained more or less constant throughout pregnancy. Between 20 and 25 weeks of gestational age, the quality of the retrieved fetal ECG waveforms generally was very high, and the beat-to-beat fetal heart rate could be accurately detected. For this stage of pregnancy, abdominal measurement of the fetal electrocardiogram offers an opportunity to obtain unique cardiac information on the fetus. However, to increase the performance of the technology throughout pregnancy, the noise in the electrophysiological recordings must be significantly reduced. Still, it remains uncertain whether this will be adequate when isolating sections of the vernix caseosa reduce the amplitude of the fetal electrocardiogram that is measured on the maternal abdomen. For stages of pregnancy in which abdominal recording of the fetal electrocardiogram fails to provide the beat-to-beat heart rate, chapter 6 offers an alternative. By processing Doppler waveforms of ultrasound signals reflected at the fetal heart, the beat-to-beat fetal heart rate can be obtained. However, the measurement requires a skilled operator and is very sensitive to fetal movement. The presence of artifacts in the beat-to-beat fetal heart rate obtained from either abdominal recordings of the fetal electrocardiogram or Doppler ultrasound recordings, is common and cannot be prevented. To obtain the second goal of the dissertation, a continuous wavelet based analysis method has been developed to reliably calculate the power within the scales of interest (chapter 7). This method provides accurate results when up to 20 % of the dataset is missing due to artifacts. In chapter 8, the continuous wavelet based method has been applied for time-scale analysis of the recordings from chapter 5. The results of this analysis correspond with literature on the development of the fetal autonomic nervous system. In addition, the results suggest that functional development of the sympathetic nervous system takes place around 22 weeks of gestational age. The final chapter reflects on the realization of the goals of this dissertation and provides specific directions for future work. Although additional clinical research might contribute to obtaining clinically relevant information from time-scale analysis of fetal heart rate variability, focus should be on solving the technical limitations of the used instrumentation for abdominal recording of the fetal electrocardiogram