Visualization of synchronization of the uterine contraction signals: Running cross-correlation and wavelet running cross-correlation methods

Performance comparison of coupling-evaluation methods in discriminating between pregnancy and labor EHG signals

BACKGROUND

Recent years have seen an increased interest in electrohysterogram (EHG) signals as a means to evaluate the synchronization of uterine contractions. Several studies have pointed out that the quality of signal processing - and hence the interpretation of measurement results - is affected significantly by the choice of measurement technique and the presence of non-stationary frequency content in EHG signals. To our knowledge, the effect of time variance on the quality of EHG signal processing has never been fully investigated. How best to process EHG signals with the goal of distinguishing labor-induced contractions from their harmless, pre-labor cousins, remains an open question.

METHOD

Our methodology is based on three pillars. The first consists of a new method for EHG preprocessing in which we apply a second-order Butterworth filter to retain only the EHG fast-wave, low-frequency band (FWL), then use a bivariate piecewise stationary pre-segmentation (bPSP) algorithm to segment the EHG signal into stationary parts. The second pillar addresses the estimation of connectivity and directionality using three methods: nonlinear correlation coefficient (h²), general synchronization (H), and Granger causality (GC). The third pillar is related to signal classification and discrimination between pregnancy and labor using receiver operating curves (ROC) and connectivity and direction maps. For this purpose, we analyze the impact of four factors on data processing efficiency: i) method of connectivity detection, ii) effect of piecewise stationary segmentation preprocessing, iii) retained frequency content and iv) electrode configuration used for EHG recording (bipolar vs. unipolar).

RESULTS

Our results show that piecewise signal segmentation and filtering considerably improves classification performance and statistical significance for some connectivity methods, in particular the h². To this end we propose a new approach (detailed below) for h² called Filtered-Windowed (FW) h² that better highlights the differences between pregnancy and labor in the connectivity matrix and directionality maps.

CONCLUSIONS

This is the first comparative study of the effects of multiple processing factors on connectivity measurement efficiency. Our results indicate that appropriate preprocessing can improve the differentiation of pregnancy and labor-induced contraction signals and may lead to innovative applications in the prevention of preterm labor.

The linear synchronization measures of uterine EMG signals: Evidence of synchronized action potentials during propagation

Evaluation of synchronization between myoelectric signals can give new insights into the functioning of the complex system of porcine myometrium. We propose a model of uterine contractions according to the hypothesis of action potentials similarity which is possible to detect during propagation in the uterine wall. We introduce similarity measures based on the concept of synchronization as used in matching linear signals such as electromyographic (EMG) time series data. The aim was to present linear measures to assess synchronization between contractions in different topographic regions of the uterus. We use the cross-correlation function (ƒx,y[l], ƒy,z[l]) and the cross-coherence function (Cxy[ƒ], Cyz[ƒ]) to assess synchronization between three data series of a diestral uterine EMG bundles in porcine reproductive tract. Spontaneous uterine activity was recorded using telemetry method directly by three-channel transmitter and three silver bipolar needle electrodes sutured on different topographic regions of the reproductive tract in the sow. The results show the usefulness of the cross-coherence function in that synchronization between uterine horn and corpus uteri for multiple action potentials (bundles) could be observed. The EMG bundles synchronization may be used to investigate the direction and velocity of EMG signals propagation in porcine reproductive tract.

Nonlinear estimation of coupling and directionality between signals: application to uterine EMG propagation

Understanding the direction and quantity of information flowing in a complex system is a fundamental task in signal processing. Several measures have been proposed to detect the quantity of synchronization and the directionality between time series and in physiological data. In this paper we use two methods that are widely used in synchronization and directionality analysis: Nonlinear correlation coefficient (h(2)) and the general synchronization (H). The performances of both methods were tested on four dimensional coupled synthetic nonlinear Rössler models. They were then applied to a single real labor contraction uterine EMG burst with the aim of using them to detect synchronization and to plot the map of direction of information flow between the whole signal channels. The results on synthetic signal show a slight superiority of H over h(2). The results obtained on a single contraction are encouraging for the future use of these tools for resolving the open question of the directionality of uterine contractions and may provide a way of finding their source loci.

Synchronization in the bivariate intrauterine pressure signals' nonlinear dynamics methods

It was shown earlier that nonlinear processes probably generate uterine contractions. In this study, the nonlinear synchronization measures (the mutual correlation dimension, the cross-approximate entropy, the mutual information and the nonlinear interdependencies) were employed to analyze the association between two time series representing the uterine contraction activity. Here the notion of synchronization is used in a loose sense as the synonym of correlation, the similarity of the signals or the similarity of their dynamics. The signals were recorded from the different topographic regions of the uterus: the cervix and the fundus. The results obtained by means of different algorithms are different but qualitatively similar for the checked methods.

Left hemisphere predominance of pilocarpine-induced rat epileptiform discharges

BACKGROUND

The left cerebral hemisphere predominance in human focal epilepsy has been observed in a few studies, however, there is no related systematic study in epileptic animal on hemisphere predominance. The main goal of this paper is to observe if the epileptiform discharges (EDs) of Pilocarpine-induced epileptic rats could present difference between left hemisphere and right hemisphere or not.

METHODS

The electrocorticogram (ECoG) and electrohippocampogram (EHG) from Pilocarpine-induced epileptic rats were recorded and analyzed using Synchronization likelihood (SL) in order to determine the synchronization relation between different brain regions, then visual check and cross-correlation analysis were adopted to evaluate if the EDs were originated more frequently from the left hemisphere than the right hemisphere.

RESULTS

The data show that the synchronization between left-EHG and right-EHG, left-ECoG and left-EHG, right-ECoG and right-EHG, left-ECoG and right-ECoG, are significantly strengthened after the brain functional state transforms from non-epileptiform discharges to continuous-epileptiform discharges(p < 0.05). When the state transforms from continuous EDs to periodic EDs, the synchronization is significantly weakened between left-ECoG and left-EHG, left-EHG and right-EHG (p < 0.05). Visual check and the time delay (tau) based cross-correlation analysis finds that 10 out of 13 EDs have a left predominance (77%) and 3 out of 13 EDs are right predominance (23%).

CONCLUSION

The results suggest that the left hemisphere may be more prone to EDs in the Pilocarpine-induced rat epilepsy model and implicate that the left hemisphere might play an important role in epilepsy states transition.

Towards understanding the myometrial physiome: approaches for the construction of a virtual physiological uterus

Premature labour (PTL) is the single most significant factor contributing to neonatal morbidity in Europe with enormous attendant healthcare and social costs. Consequently, it remains a major challenge to alleviate the cause and impact of this condition. Our ability to improve the diagnosis and treatment of women most at risk of PTL is, however, actually hampered by an incomplete understanding of the ways in which the functions of the uterine myocyte are integrated to effect an appropriate biological response at the multicellular whole organ system. The level of organization required to co-ordinate labouring uterine contractile effort in time and space can be considered immense. There is a multitude of what might be considered mini-systems involved, each with their own regulatory feedback cycles, yet they each, in turn, will influence the behaviour of a related system. These include, but are not exclusive to, gestational-dependent regulation of transcription, translation, post-translational modifications, intracellular signaling dynamics, cell morphology, intercellular communication and tissue level morphology.

We propose that in order to comprehend how these mini-systems integrate to facilitate uterine contraction during labour (preterm or term) we must, in concert with biological experimentation, construct detailed mathematical descriptions of our findings. This serves three purposes: firstly, providing a quantitative description of series of complex observations; secondly, proferring a database platform that informs further testable experimentation; thirdly, advancing towards the establishment of a virtual physiological uterus and in silico clinical diagnosis and treatment of PTL.

New research models and novel signal analysis in studies on preterm labor: a key to progress?

Preterm labor affects up to 20% of pregnancies, is considered a main cause of associated neonatal morbidity and mortality and is responsible for neonatal care costs of multimillion euros. In spite of that, the commercial market for this clinical indication is rather limited, which may be also related to high liability. Consequently, with only a few exceptions, preterm labor is not in the orbit of great interest of the pharmaceutical industry. Coordinated effort of research community may bring the change and help required to reduce the influence of this multifactorial syndrome on society. Between the novel techniques that are being explored in a SAFE (The Special Non-Invasive Advances in Fetal and Neonatal Evaluation Network) group, there are new research models of preterm labor as well as novel methodology of analysis of biological signals. In this article, we briefly describe new clinical and nonclinical human models of preterm labor as well as summarize some novel methods of data processing and analysis that may be used in the context of preterm labor.

Uterine Contractility: Visualization of Synchronization Measures in Two Simultaneously Recorded Signals

The analysis of the uterine contraction signals in nonpregnant states gives information about physiological changes during the menstrual cycle. Spontaneous uterine activity was recorded directly by a dual microtip catheter. The device consisted of two ultra-miniature pressure sensors. One sensor was placed in the fundus, the other in the cervix. It was important to identify time delays between contractions in two topographic locations, which may be of potential diagnostic significance in various pathologies: dysmenorrhea, endometriosis, and fecundity disorders. In this study the following synchronization measures-the cross-correlation, the semblance, the mutual information-were used to visualize the time delay changes over time. These measures were computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running synchronization functions were obtained. The running synchronization functions visualize changes in the propagation of the two simultaneously recorded signals. The propagation% parameter assessed from these functions allows for quantitative description of synchronization. Finally, we illustrate the use of running synchronization functions to investigate the effect of treatment with tamoxifen on primary dysmenorrhea.

Effect of short-term, low-dose treatment with tamoxifen in patients with primary dysmenorrhea

Current treatment of painful periods and other symptoms related to primary dysmenorrhea (PD) is usually commenced with non-steroidal anti-inflammatory drugs or oral contraceptives, which fails in about 10% of affected patients. Tamoxifen, a selective estrogen-receptor modulator (SERM), has been demonstrated to directly inhibit uterine contractions, causing improvement in uterine blood flow. It could be considered for application in selected groups of dysmenorrheic patients, for instance carriers of breast cancer-associated antigen (BRCA) genes, breast cancer survivors or women with advanced endometriosis. Thus the aim of the present study was to investigate the effect of short-term treatment with tamoxifen on PD and PD-related symptoms, as well as its direct effect on parameters of intrauterine pressure during the painful menstruation, in a group of dysmenorrheic patients. After two cycles of administration of tamoxifen we noted a significant decrease in bleeding together with reductions in the severity of menstrual cramps, diarrhea, headache, fatigue and anxiety. In intrauterine pressure assessments, tamoxifen significantly decreased propagation of uterine contractions. In conclusion, SERMs such as tamoxifen may constitute a therapeutic option in selected groups of patients, improving dysmenorrheic symptoms. Additionally to its receptor-mediated effects, tamoxifen was shown to exert a direct influence on uterine contractile activity that may explain the decrease of menstrual pain and cramps noted in the studied group.