Propagation of electrical activity in uterine muscle during pregnancy: a review

Three-dimensional virtual histology of the rat uterus musculature using micro-computed tomography

Contractions of the uterus play an important role in menstruation and fertility, and contractile dysfunction can lead to chronic diseases such as endometriosis. However, the structure and function of the uterus are difficult to interrogate in humans, and thus animal studies are often employed to understand its function. In rats, anatomical studies of the uterus have typically been based on histological assessment, have been limited to small segments of the uterine structure, and have been time-consuming to reconstruct at the organ scale. This study used micro-computed tomography imaging to visualise the muscle structures in the entire non-pregnant rat uterus and assess its use for 3D virtual histology. An assessment of the rodent uterus is presented to (i) quantify muscle thickness variations along the horns, (ii) identify predominant fibre orientations of the muscles and (iii) demonstrate how the anatomy of the uterus can be mapped to 3D volumetric meshes via virtual histology. Micro-computed tomography measurements were validated against measurements from histological sections. The average thickness of the myometrium was found to be 0.33 ± 0.11 mm and 0.31 ± 0.09 mm in the left and right horns, respectively. The micro-computed tomography and histology thickness calculations were found to correlate strongly at different locations in the uterus: at the cervix, r = 0.87, and along the horn from the cervical end to the ovarian end, respectively, r = 0.77, r = 0.89 and r = 0.54, with p < 0.001 in every location. This study shows that micro-computed tomography can be used to quantify the musculature in the whole non-pregnant uterus and can be used for 3D virtual histology.

A computationally efficient anisotropic electrophysiological multiscale uterus model: From cell to organ and myometrium to abdominal surface

BACKGROUND AND OBJECTIVE

Preterm labor is a global problem affecting the health of newborns. Despite numerous studies reporting electrophysiological changes throughout pregnancy, the underlying mechanism that triggers labor remains unclear. Electrophysiological modeling can provide additional information to better understand the physiological transition from pregnancy to labor. Previous uterine electrophysiological models do not consider either the tissue thickness or fiber structure, which have both been shown to significantly impact propagation patterns.

METHODS

This paper presents a parallel computational model of the uterus using the bioengineering modeling environment OpenCMISS. This model is a multiscale anisotropic model that spans different levels from cell to organ. At the cellular level, the model utilizes a mathematical representation of uterine myocytes based on multiple ion channels. In the 3D uterine model, fiber structures are added, ranging from horizontal rings in the inner layer to vertically downward fibers in the outer layer, to more accurately depict the electrophysiological activities of the uterus. Additionally, we have developed a multilayer volume conduction model based on the boundary element method to describe the propagation of electrical signals from the myometrium to the abdominal surface.

RESULTS

Our model can not only reproduce faithfully both local non-propagated and global propagated electrical activity, but also simulate the fast wave low and fast wave high components of the electrohysterogram (EHG) on the abdominal surface. The model results support the hypothesis that the fast wave high of the EHG signal is related to uterine excitability and fast wave low is related to signal propagation. The amplitude of the simulated signal on the abdominal surface falls in the ranges of real EHG data, which is inversely proportional to the abdominal subcutaneous fat thickness, and the signal waveform highly depends on electrode position and the relative distance to the pacemaker. In addition, the propagation velocity is highly dependent on the uterus geometry and falls in the real-world data range CONCLUSIONS: Our models facilitate a better understanding of the electrophysiological changes of the uterus during pregnancy and labor, and allow for an investigation of drug effects and/or structural or anatomical abnormalities.

Characteristics of phase synchronization in electrohysterography and tocodynamometry for preterm birth prediction

Preterm birth prediction is important in prenatal care; however, it remains a significant challenge due to the complex physiological mechanisms involved. This study aimed to explore the feasibility of phase synchronization of multiple oscillatory components across electrohysterography (EHG) and tocodynamometry (TOCO) signals to identify preterm births using advanced machine-learning techniques. Using an open-access EHG dataset, we first assessed the degree of phase synchronization of five specified frequency ranges from 0.08 to 5.0 Hz in three individual EHG signals by constructing two distinct sets of mean phase coherence: the inclusion or exclusion of TOCO signals. We then employed two machine-learning models, XGBoost and TabNet, to classify preterm and term delivery conditions and analyze the predictive potential of these features. The models' performance was evaluated by considering varying lengths of time windows and the use of overlapping windows. Our results demonstrate the importance of lower-frequency EHG signals and synchronization patterns across the horizontal plane of the abdomen, particularly synchronization between the upper and lower regions of the uterus. Furthermore, we observed a distinctive pattern in the high-frequency band (1.0-2.2 Hz), emphasizing the important role of the lower horizontal regions with other sites in the synchronization process. Interestingly, our findings indicated that TOCO signals, while not substantially enhancing the overall prediction performance, contributed to slightly improved accuracy rates when combined with EHG signals. This study suggests the critical role of EHG signals and their intricate spatiotemporal patterns in predicting preterm birth, providing insights for the development of more accurate and efficient prediction models.

Use of uterine electromyography in the prediction of preterm birth after transvaginal cervical cerclage

BACKGROUND

Preterm birth (PTB), complications of which account for approximately 35% of deaths among neonates, remains a crucial issue. Cervical insufficiency (CI) is defined as the inability of the utrine cervix to retain a pregnancy, leading to PTB. Cervical cerclage is an efficient surgery for CI patients by preventing the cervix from being further mechanically shortened. Unfortunately, a certain number of patients who had cerclage still delivered prematurely, raising the urgent need to accurately assess the risk of PTB in patients with cerclage. Uterine electromyography (uEMG) is an emerging technology that characterizes uterine contractions by describing the actual evolution process of uterine activity and has been used to predict PTB in recent years.

METHOD

In this single-center retrospective case-control study, singleton pregnancy women who received cervical cerclage and uEMG assessment between January 2018 and January 2022 at the Sun Yat-sen Memorial Hospital of Sun Yat-sen University were enrolled.

RESULTS

32 PTBs were observed of the 69 women who underwent assessment. Based on multivariate logistic regression analysis, PTB after cerclage was significantly associated with previous PTB history or mid-trimester pregnancy loss (OR: 2.87, 95%CI: 1.49-5.54) and contraction frequency detected by uEMG (OR: 2.24, 95%CI: 1.44-3.49). The AUC of contraction frequency (0.766, P<0.001) was observed, and the optimal cut-off value suggested by Youden Index was 1.75 times per hour. Combined with previous preterm history and cervical length, the AUC of contraction frequency reached 0.858. After stratification by contraction frequency, the median duration was 11 weeks in the high frequency group (> 1.75 times per hour) and 15 weeks in the low frequency group (≤ 1.75 times per hour) (P<0.001).

CONCLUSIONS

The uEMG effectively predicts PTB after transvaginal cervical cerclage and provides a new method for clinicians to evaluate the pregnancy outcome of CI patients.

Peak amplitude of the normalized power spectrum of the electromyogram of the uterus in the low frequency band is an effective predictor of premature birth

The current trends in the development of methods for non-invasive prediction of premature birth based on the electromyogram of the uterus, i.e., electrohysterogram (EHG), suggest an ever-increasing use of large number of features, complex models, and deep learning approaches. These "black-box" approaches rarely provide insights into the underlying physiological mechanisms and are not easily explainable, which may prevent their use in clinical practice. Alternatively, simple methods using meaningful features, preferably using a single feature (biomarker), are highly desirable for assessing the danger of premature birth. To identify suitable biomarker candidates, we performed feature selection using the stabilized sequential-forward feature-selection method employing learning and validation sets, and using multiple standard classifiers and multiple sets of the most widely used features derived from EHG signals. The most promising single feature to classify between premature EHG records and EHG records of all other term delivery modes evaluated on the test sets appears to be Peak Amplitude of the normalized power spectrum (PA) of the EHG signal in the low frequency band (0.125-0.575 Hz) which closely matches the known Fast Wave Low (FWL) frequency band. For classification of EHG records of the publicly available TPEHG DB, TPEHGT DS, and ICEHG DS databases, using the Partition-Synthesis evaluation technique, the proposed single feature, PA, achieved Classification Accuracy (CA) of 76.5% (AUC of 0.81). In combination with the second most promising feature, Median Frequency (MF) of the power spectrum in the frequency band above 1.0 Hz, which relates to the maternal resting heart rate, CA increased to 78.0% (AUC of 0.86). The developed method in this study for the prediction of premature birth outperforms single-feature and many multi-feature methods based on the EHG, and existing non-invasive chemical and molecular biomarkers. The developed method is fully automatic, simple, and the two proposed features are explainable.

Tissue Clearing and 3D Imaging of Gap Junctions in Rat Uterine Myometrium

The propagation patterns of electrical activity in the uterus are not well understood. However, the number and size of gap junctions between uterine smooth muscle cells towards the end of pregnancy increases, which may be a catalyst for the onset of the coordinated contractions required for successful labor. In non-pregnancy, there is some evidence that the number and distribution of gap junctions varies throughout the reproductive hormonal cycle. Gap junctions are hemichannel proteins in the cell membrane which allow fast electrical and ionic communication between cells. In this study, we outline the use of state-of-the-art tissue clearing, labelling, and imaging techniques in order to image connexin-43 gap junction in rat uterine tissue. We used stage-scanning line confocal microscopy to image a 3D volume of uterine tissue, and quantified the change in fluorescence of connexin-43 along the longitudinal length of the uterine horn. We observed an increased fluorescence signal at the cervical end of the uterine horn, compared with the ovarian end. This pilot study shows the efficacy of this approach for analyzing distributions of gap junctions in rat uterine smooth muscle.

Electrophysiological Modeling of Uterine Smooth Muscles Cells During Estrus

Uterine activity is regulated by sex hormones, notably progesterone and estrogen. Sex hormones play an important regulatory role in preparing the uterus for pregnancy, which includes an influence on contractile function. Computational models have previously been developed to simulate the electrical and contractile activity of pregnant smooth muscle cells. Here, a non-pregnant cell model which includes estrus stages was developed based on an existing pregnant cell model. The estrus cycle variations are modeled by including the effects of sex hormones on the different ionic currents. Root mean square error was used to quantify differences in the outputs of the pregnant and non-pregnant model at each estrus stage. The error of the membrane potential varied from 1.8 - 2.6 mV depending on the estrus stage, with the metestrus phase being the most similar to late pregnancy. A sensitivity analysis determined that the voltage-gated potassium channel was the most sensitive to sex hormones at each stage of estrus.

Localization of Catecholaminergic Neurofibers in Pregnant Cervix as a Possible Myometrial Pacemaker

In eutocic labor, the autonomic nervous system is dominated by the parasympathetic system, which ensures optimal blood flow to the uterus and placenta. This study is focused on the detection of the quantitative presence of catecholamine (C) neurofibers in the internal uterine orifice (IUO) and in the lower uterine segment (LUS) of the pregnant uterus, which could play a role in labor and delivery. A total of 102 women were enrolled before their submission to a scheduled cesarean section (CS); patients showed a singleton fetus in a cephalic presentation outside labor. During CS, surgeons sampled two serial consecutive full-thickness sections 5 mm in depth (including the myometrial layer) on the LUS and two randomly selected samples of 5 mm depth from the IUO of the cervix. All histological samples were studied to quantify the distribution of A nerve fibers. The authors demonstrated a significant and notably higher concentration of A fibers in the IUO (46 ± 4.8) than in the LUS (21 ± 2.6), showing that the pregnant cervix has a greater concentration of A neurofibers than the at-term LUS. Pregnant women's mechanosensitive pacemakers can operate normally when the body is in a physiological state, which permits normal uterine contractions and eutocic delivery. The increased frequency of C neurofibers in the cervix may influence the smooth muscle cell bundles' activation, which could cause an aberrant mechano-sensitive pacemaker activation-deactivation cycle. Stressful circumstances (anxiety, tension, fetal head position) cause the sympathetic nervous system to become more active, working through these nerve fibers in the gravid cervix. They might interfere with the mechano-sensitive pacemakers, slowing down the uterine contractions and cervix ripening, which could result in dystocic labor.

Directional Sensors for Recording Uterine EMG During Pregnancy

Multichannel uterine electromyography (uEMG) during pregnancy is traditionally performed with electrocardiography (ECG) sensors. Similar signals are often observed in two or more channels, suggesting the ECG sensors report activities originating from the same location on the uterus. To improve signal source localization, we designed a directional sensor or "Area Sensor". Here we compare Area Sensors with ECG sensors for source localization. Subjects were ≥ 38 wks experiencing regular contractions. 6 Area Sensors (n = 8) or 6 to 7 ECG sensors (n = 7) were used to record multichannel uEMG for 60 min. For each sensor type, the similarity of signals observed in pairs of channels during contractions was assessed by quantifying channel crosstalk. Since crosstalk depends on the separation between sensors, analyses were performed within distance groups: A 9-12 cm; B 13-16 cm; C 17-20 cm; D 21-24 cm; E ≥ 25 cm. For ECG sensors, crosstalk was 67.9 ± 14.4% in group A, decreasing to 27.8 ± 17.5% in group E. For Area Sensors, crosstalk was 24.6 ± 18.6% in Group A, decreasing to 12.5 ± 13.8% in group E. Area Sensors showed less crosstalk than ECG sensors in distance groups A, B, C and D, with all p < 0.002. Compared with ECG sensors, Area Sensors are more directional and report uterine activity from a smaller area of the uterine wall. Using 6 Area Sensors separated by at least 17 cm provides acceptably independent multichannel recording. This introduces the possibility of non-invasively evaluating uterine synchronization and the strength of individual uterine contractions in real time.

An open dataset with electrohysterogram records of pregnancies ending in induced and cesarean section delivery

The existing non-invasive automated preterm birth prediction methods rely on the use of uterine electrohysterogram (EHG) records coming from spontaneous preterm and term deliveries, and are indifferent to term induced and cesarean section deliveries. In order to enhance current publicly available pool of term EHG records, we developed a new EHG dataset, Induced Cesarean EHG DataSet (ICEHG DS), containing 126 30-minute EHG records, recorded early (23rd week), and/or later (31st week) during pregnancy, of those pregnancies that were expected to end in spontaneous term delivery, but ended in induced or cesarean section delivery. The records were collected at the University Medical Center Ljubljana, Ljubljana, Slovenia. The dataset includes 38 and 43, early and later, induced; 11 and 8, early and later, cesarean; and 13 and 13, early and later, induced and cesarean EHG records. This dataset enables better understanding of the underlying physiological mechanisms involved during pregnancies ending in induced and cesarean deliveries, and provides a robust and more realistic assessment of the performance of automated preterm birth prediction methods.

Upregulated TIMP1 facilitates and coordinates myometrial contraction by decreasing collagens and cell adhesive capacity during human labor

Myometrial contraction is one of the key events involved in parturition. Increasing evidence suggests the importance of the extracellular matrix (ECM) in this process, in addition to the functional role of myometrial smooth muscle cells, and our previous study identified an upregulated tissue inhibitor of metalloproteinase 1 (TIMP1) in human laboring myometrium compared to nonlabor samples. This study aimed to further explore the potential role of TIMP1 in myometrial contraction. First, we confirmed increased myometrial TIMP1 levels in labor and during labor with cervical dilation using transcriptomic and proteomic analyses, followed by real-time PCR, western blotting, and immunohistochemistry. Then, a cell contraction assay was performed to verify the decreased contractility after TIMP1 knockdown in vitro. To further understand the underlying mechanism, we used RNA-sequencing analysis to reveal the upregulated genes after TIMP1 knockdown; these genes were enriched in collagen fibril organization, cell adhesion, and ECM organization. Subsequently, a human matrix metalloproteinase (MMP) array and collagen staining were performed to determine the TIMPs, MMPs and collagens in laboring and nonlabor myometrium. A real-time cell adhesion assay was used to detect cell adhesive capacity. The results showed upregulated MMP8 and MMP9, downregulated collagens, and attenuated cell adhesive capacity in laboring myometrium, while lower MMP levels and higher collagen levels and cell adhesive capacity were observed in nonlabor. Moreover, TIMP1 knockdown led to restoration of cell adhesive capacity. Together, these results indicate that upregulated TIMP1 during labor facilitates and coordinates myometrial contraction by decreasing collagen and cell adhesive capacity, which may provide effective strategies for the regulation of myometrial contraction.

Noninvasive electromyometrial imaging of human uterine maturation during term labor

Electromyometrial imaging (EMMI) was recently developed to image the three-dimensional (3D) uterine electrical activation during contractions noninvasively and accurately in sheep. Herein we describe the development and application of a human EMMI system to image and evaluate 3D uterine electrical activation patterns at high spatial and temporal resolution during human term labor. We demonstrate the successful integration of the human EMMI system during subjects' clinical visits to generate noninvasively the uterine surface electrical potential maps, electrograms, and activation sequence through an inverse solution using up to 192 electrodes distributed around the abdomen surface. Quantitative indices, including the uterine activation curve, are developed and defined to characterize uterine surface contraction patterns. We thus show that the human EMMI system can provide detailed 3D images and quantification of uterine contractions as well as novel insights into the role of human uterine maturation during labor progression.

End-to-end learning with interpretation on electrohysterography data to predict preterm birth

Prediction of preterm birth is a difficult task for clinicians. By examining an electrohysterogram, electrical activity of the uterus that can lead to preterm birth can be detected. Since signals associated with uterine activity are difficult to interpret for clinicians without a background in signal processing, machine learning may be a viable solution. We are the first to employ Deep Learning models, a long-short term memory and temporal convolutional network model, on electrohysterography data using the Term-Preterm Electrohysterogram database. We show that end-to-end learning achieves an AUC score of 0.58, which is comparable to machine learning models that use handcrafted features. Moreover, we evaluate the effect of adding clinical data to the model and conclude that adding the available clinical data to electrohysterography data does not result in a gain in performance. Also, we propose an interpretability framework for time series classification that is well-suited to use in case of limited data, as opposed to existing methods that require large amounts of data. Clinicians with extensive work experience as gynaecologist used our framework to provide insights on how to link our results to clinical practice and stress that in order to decrease the number of false positives, a dataset with patients at high risk of preterm birth should be collected. All code is made publicly available.

Monitoring uterine contractions during labor: current challenges and future directions

Organ-level models are used to describe how cellular and tissue-level contractions coalesce into clinically observable uterine contractions. More importantly, these models provide a framework for evaluating the many different contraction patterns observed in laboring patients, ideally offering insight into the pitfalls of currently available recording modalities and suggesting new directions for improving recording and interpretation of uterine contractions. Early models proposed wave-like propagation of bioelectrical activity as the sole mechanism for recruiting the myometrium to participate in the contraction and increase contraction strength. However, as these models were tested, the results consistently revealed that sequentially propagating waves do not travel long distances and do not encompass the gravid uterus. To resolve this discrepancy, a model using 2 mechanisms, or a "dual model," for organ-level signaling has been proposed. In the dual model, the myometrium is recruited by action potentials that propagate wave-like as far as 10 cm. At longer distances, the myometrium is recruited by a mechanotransduction mechanism that is triggered by rising intrauterine pressure. In this review, we present the influential models of uterine function, highlighting their main features and inconsistencies, and detail the role of intrauterine pressure in signaling and cervical dilation. Clinical correlations demonstrate the application of organ-level models. The potential to improve the recording and clinical interpretation of uterine contractions when evaluating labor is discussed, with emphasis on uterine electromyography. Finally, 7 questions are posed to help guide future investigations on organ-level signaling mechanisms.

Assessment of uterine contractions in labor and delivery

Normal labor and delivery are dependent on the presence of regular and effective contractions of the uterine myometrium. The mechanisms responsible for the initiation and maintenance of adequate and synchronized uterine activity that are necessary for labor and delivery result from a complex interplay of hormonal, mechanical, and electrical factors that have not yet been fully elucidated. Monitoring uterine activity during term labor and in suspected preterm labor is an important component of obstetrical care because cases of inadequate and excessive uterine activity can be associated with substantial maternal and neonatal morbidity and mortality. Inadequate labor progress is a common challenge encountered in intrapartum care, with labor dystocia being the most common indication for cesarean deliveries performed during labor. Hereafter, an accurate assessment of uterine activity during labor can assist in the management of protracted labor by diagnosing inadequate uterine activity and facilitating the titration of uterotonic medications before a trial of labor is prematurely terminated. Conversely, the ability to diagnose unwanted or excessive uterine activity is also critical in cases of threatened preterm labor, tachysystole, or patients undergoing a trial of labor after cesarean delivery. Knowledge of uterine activity in these cases may guide the use of tocolytic medications or raise suspicion of uterine rupture. Current diagnostic capabilities are less than optimal, hindering the medical management of term and preterm labor. Currently, different methods exist for evaluating uterine activity during labor, including manual palpation, external tocodynamometry, intrauterine pressure monitoring, and electrical uterine myometrial activity tracing. Legacy uterine monitoring techniques have advantages and limitations. External tocodynamometry is the most widespread tool in clinical use owing to its noninvasive nature and its ability to time contractions against the fetal heart rate monitor. However, it does not provide information regarding the strength of uterine contractions and is limited by signal loss with maternal movements. Conversely, the intrauterine pressure catheter quantifies the strength of uterine contractions; however, its use is limited by its invasiveness, risk for complications, and limited additive value in all but few clinical scenarios. New monitoring methods are being used, such as electrical uterine monitoring, which is noninvasive and does not require ruptured membranes. Electrical uterine monitoring has yet to be incorporated into common clinical practice because of lack of access to this technology, its high cost, and the need for appropriate training of clinical staff. Further work needs to be done to increase the accessibility and implementation of this technique by experts, and further research is needed to implement new practical and useful methods. This review describes current clinical tools for uterine activity assessment during labor and discusses their advantages and shortcomings. The review also summarizes current knowledge regarding novel technologies for monitoring uterine contractions that are not yet in widespread use, but are promising and could help improve our understanding of the physiology of labor, delivery, and preterm labor, and ultimately enhance patient care.

Modeling and experimental approaches for elucidating multi-scale uterine smooth muscle electro- and mechano-physiology: A review

The uterus provides protection and nourishment (via its blood supply) to a developing fetus, and contracts to deliver the baby at an appropriate time, thereby having a critical contribution to the life of every human. However, despite this vital role, it is an under-investigated organ, and gaps remain in our understanding of how contractions are initiated or coordinated. The uterus is a smooth muscle organ that undergoes variations in its contractile function in response to hormonal fluctuations, the extreme instance of this being during pregnancy and labor. Researchers typically use various approaches to studying this organ, such as experiments on uterine muscle cells, tissue samples, or the intact organ, or the employment of mathematical models to simulate the electrical, mechanical and ionic activity. The complexity exhibited in the coordinated contractions of the uterus remains a challenge to understand, requiring coordinated solutions from different research fields. This review investigates differences in the underlying physiology between human and common animal models utilized in experiments, and the experimental interventions and computational models used to assess uterine function. We look to a future of hybrid experimental interventions and modeling techniques that could be employed to improve the understanding of the mechanisms enabling the healthy function of the uterus.

Uterine slow wave: directionality and changes with imminent delivery

OBJECTIVE

The slow wave (SW) of the electrohysterogram (EHG) may contain relevant information on the electrophysiological condition of the uterus throughout pregnancy and labor. Our aim was to assess differences in the SW as regards the imminence of labor and the directionality of uterine myoelectrical activity.

APPROACH

The SW of the EHG was extracted from the signals of the Icelandic 16-electrode EHG database in the bandwidth [5, 30] mHz and its power, spectral content, complexity and synchronization between the horizontal (X) and vertical (Y) directions were characterized by the root mean square (RMS), dominant frequency (domF), sample entropy (SampEn) and maximum cross-correlation (CCmax) of the signals, respectively. Significant differences between parameters at time-to-delivery (TTD) ≤7 vs. >7 days and between the horizontal vs. vertical directions were assessed.

MAIN RESULTS

The SW power significantly increased in both directions as labor approached (TTD≤7d vs. >7d (mean±SD): x= 0.12±0.10 vs. 0.08±0.06mV; y= 0.12±0.09 vs. 0.08±0.05mV), as well as the dominant frequency in the horizontal direction (= 9.1±1.3 vs. 8.5±1.2mHz) and the synchronization between both directions (= 0.44±0.16 vs. 0.36±0.14). Furthermore, its complexity decreased in the vertical direction (= 6.13·10-2±8.7·10-3 vs. 6.50·10-2±8.3·10-3), suggesting a higher cell-to-cell electrical coupling. Whereas there were no differences between the SW features in both directions in the general population, statistically significant differences were obtained between them in individuals in many cases.

SIGNIFICANCE

Our results suggest that the SW of the EHG is related to bioelectrical events in the uterus and could provide objective information to clinicians in challenging obstetric scenarios.

In vivo multi-channel measurement of electrical activity of the non-pregnant rat uterus

In the uterus, the characteristics of smooth muscle contraction and the electrical activity that drives this contraction depends on hormonal cycles, and pregnancy status. Smooth muscle contraction is initiated by a change in membrane electrical potential, due to the flux of ions in and out of the intracellular space. Chains of action potentials throughout a section of muscle can result in coordinated contraction events. In this study, flexible printed circuit electrode arrays were applied to measure the bioelectric signals on the surface of a rat uterus in vivo. Variations in the electrical activity were quantified, including intermittent periods of activity and inactivity, which contain both slow-wave type activity (0.039 Hz ±0.017 Hz) and faster, spike-like activity (3.26 Hz ±0.27 Hz). The spike activity initiated at the ovarian end of the uterine horn, spreading towards the cervical end with a propagation velocity of 5.34 ± 2.32 mm [Formula: see text]. In conclusion, this pilot study outlines a new method of in vivo measurement of uterine electrical activity in rats. Clinical Relevance- Measurement of bioelectrical data using in vivo techniques provides insight into the electromechanical function of uterine smooth muscle, which could provide insights into what drives coordinated contraction in the uterus.

Assessment of Features between Multichannel Electrohysterogram for Differentiation of Labors

Electrohysterogram (EHG) is a promising method for noninvasive monitoring of uterine electrical activity. The main purpose of this study was to characterize the multichannel EHG signals to distinguish between term delivery and preterm birth, as well as deliveries within and beyond 24 h. A total of 219 pregnant women were grouped in two ways: (1) term delivery (TD), threatened preterm labor (TPL) with the outcome of preterm birth (TPL_PB), and TPL with the outcome of term delivery (TPL_TD); (2) EHG recording time to delivery (TTD) ≤ 24 h and TTD > 24 h. Three bipolar EHG signals were analyzed for the 30 min recording. Six EHG features between multiple channels, including multivariate sample entropy, mutual information, correlation coefficient, coherence, direct partial Granger causality, and direct transfer entropy, were extracted to characterize the coupling and information flow between channels. Significant differences were found for these six features between TPL and TD, and between TTD ≤ 24 h and TTD > 24 h. No significant difference was found between TPL_PB and TPL_TD. The results indicated that EHG signals of TD were more regular and synchronized than TPL, and stronger coupling between multichannel EHG signals was exhibited as delivery approaches. In addition, EHG signals propagate downward for the majority of pregnant women regardless of different labors. In conclusion, the coupling and propagation features extracted from multichannel EHG signals could be used to differentiate term delivery and preterm birth and may predict delivery within and beyond 24 h.

Network theory based EHG signal analysis and its application in preterm prediction

OBJECTIVE

Preterm birth is the leading cause of neonatal morbidity and mortality. Early identification of high-risk patients followed by medical interventions is essential to the prevention of preterm birth. Based on the relationship between uterine contraction and the fundamental electrical activities of muscles, we extracted effective features from EHG signals recorded from pregnant women, and use them to train classifiers with the purpose of providing high precision in classifying term and preterm pregnancies.

METHODS

To characterize changes from irregularity to coherence of the uterine activity during the whole pregnancy, network representations of the original electrohysterogram (EHG) signals are established by applying the Horizontal Visibility Graph (HVG) algorithm, from which we extract network degree density and distribution, clustering coefficient and assortativity coefficient. Concerns on the interferences of different noise sources embedded in the EHG signal, we apply Short-Time Fourier Transform (STFT) to expand the original signal in the time-frequency domain. This allows a network representation and the extraction of related features on each frequency component. Feature selection algorithms are then used to filter out unrelated frequency components. We further apply the proposed feature extraction method to EHG signals available in the Term-Preterm EHG database (TPEHG), and use them to train classifiers. We adopt the Partition-Synthesis scheme which splits the original imbalanced dataset into two sets and synthesizes artificial samples separately within each subset to solve the problem of dataset imbalance.

RESULTS

The optimally selected network-based features, not only contribute to the identification of the essential frequency components of uterine activities related to preterm birth, but also to improved performance in classifying term/preterm pregnancies, i.e., the SVM (Support Vector Machine) classifier trained with the available samples in the TPEHG gives sensitivity, specificity, overall accuracy, and auc values as high as 0.89, 0.93, 0.91, and 0.97, respectively.

Automatic recognition of uterine contractions with electrohysterogram signals based on the zero-crossing rate

Uterine contraction (UC) is an essential clinical indicator in the progress of labour and delivery. Electrohysterogram (EHG) signals recorded on the abdomen of pregnant women reflect the uterine electrical activity. This study proposes a novel algorithm for automatic recognition of UCs with EHG signals to improve the accuracy of detecting UCs. EHG signals by electrodes, the tension of the abdominal wall by tocodynamometry (TOCO) and maternal perception were recorded simultaneously in 54 pregnant women. The zero-crossing rate (ZCR) of the EHG signal and its power were calculated to modulate the raw EHG signal and highlight the EHG bursts. Then the envelope was extracted from the modulated EHG for UC recognition. Besides, UC was also detected by the conventional TOCO signal. Taking maternal perception as a reference, the UCs recognized by EHG and TOCO were evaluated with the sensitivity, positive predictive value (PPV), and UC parameters. The results show that the sensitivity and PPV are 87.8% and 93.18% for EHG, and 84.04% and 90.89% for TOCO. EHG detected a larger number of UCs than TOCO, which is closer to maternal perception. The duration and frequency of UC obtained from EHG and TOCO were not significantly different (p > 0.05). In conclusion, the proposed UC recognition algorithm has high accuracy and simple calculation which could be used for real-time analysis of EHG signals and long-term monitoring of UCs.

Assessing Velocity and Directionality of Uterine Electrical Activity for Preterm Birth Prediction Using EHG Surface Records

The aim of the present study was to assess the capability of conduction velocity amplitudes and directions of propagation of electrohysterogram (EHG) waves to better distinguish between preterm and term EHG surface records. Using short-time cross-correlation between pairs of bipolar EHG signals (upper and lower, left and right), the conduction velocities and their directions were estimated using preterm and term EHG records of the publicly available Term–Preterm EHG DataSet with Tocogram (TPEHGT DS) and for different frequency bands below and above 1.0 Hz, where contractions and the influence of the maternal heart rate on the uterus, respectively, are expected. No significant or preferred continuous direction of propagation was found in any of the non-contraction (dummy) or contraction intervals; however, on average, a significantly lower percentage of velocity vectors was found in the vertical direction, and significantly higher in the horizontal direction, for preterm dummy intervals above 1.0 Hz. The newly defined features—the percentages of velocities in the vertical and horizontal directions, in combination with the sample entropy of the EHG signal recorded in the vertical direction, obtained from dummy intervals above 1.0 Hz—showed the highest classification accuracy of 86.8% (AUC=90.3%) in distinguishing between preterm and term EHG records of the TPEHGT DS.

Propagation of spontaneous electrical activity in the ex vivo human uterus

Contractions of the non-pregnant uterus play a key role in fertility. Yet, the electrophysiology underlying these contractions is poorly understood. In this paper, we investigate the presence of uterine electrical activity and characterize its propagation in unstimulated ex vivo human uteri. Multichannel electrohysterographic measurements were performed in five freshly resected human uteri starting immediately after hysterectomy. Using an electrode grid externally and an electrode array internally, measurements were performed up to 24 h after hysterectomy and compared with control. Up to 2 h after hysterectomy, we measured biopotentials in all included uteri. The median root mean squared (RMS) values of the external measurements ranged between 3.95 μV (interquartile range (IQR) 2.41–14.18 μV) and 39.4 μV (interquartile range (IQR) 10.84–105.64 μV) and were all significantly higher than control (median RMS of 1.69 μV, IQR 1.13–3.11 μV), consisting of chicken breast meat. The RMS values decreased significantly over time. After 24 h, the median RMS (1.27 μV, IQR 0.86–3.04 μV) was comparable with the control (1.69 μV, IQR 1.13–3.11 μV, p = 0.125). The internal measurements showed a comparable pattern over time, but overall lower amplitude. The measured biopotentials propagated over the uterine surface, following both a plane-wave as well as an erratic pattern. No clear pacemaker location nor a preferred propagation direction could be identified. These results show that ex vivo uteri can spontaneously generate propagating biopotentials and provide novel insight contributing to improving our understanding of the electrophysiology of the human non-pregnant uterus.

Open-source 128-channel bioamplifier module for ambulatory monitoring of gastrointestinal electrical activity

We present an open-source, low-cost, portable, 128-channel bioamplifier module designed specifically for ambulatory, long-term (≥24 hr) monitoring of gastrointestinal (GI) electrical activity. The electronics hardware integrates stateof-the-art, commercial-off-the-shelf components on a custom PCB. Features include on-board data logging, wireless data streaming, subject motion monitoring, and stable operation up to the maximum 2 kHz/channel sampling rate tested. The new device operates for ≈ 30 hr continuously powered by a single 3.7 V, 2500 mAh LiPo battery. The 3D-printed ABS mechanical enclosure is robust and small (13.1 × 8.8 × 2.5 cm), so that the device can be carried in a standard Holter monitor pouch. Results from initial 128-channel, high spatial resolution body surface colon mapping experiments demonstrate the utility of this new device for GI applications. The new bioamplifier module could also be used for multichannel recording experiments in a variety of biomedical domains to study electrical activity patterns of the neuromuscular system (EMG), uterus (EHG), heart (ECG), and brain (EEG).

Spatial-dependent regularization to solve the inverse problem in electromyometrial imaging

Recently, electromyometrial imaging (EMMI) was developed to non-invasively image uterine contractions in three dimensions. EMMI collects body surface electromyography (EMG) measurements and uses patient-specific body-uterus geometry generated from magnetic resonance images to reconstruct uterine electrical activity. Currently, EMMI uses the zero-order Tikhonov method with mean composite residual and smoothing operator (CRESO) to stabilize the underlying ill-posed inverse computation. However, this method is empirical and implements a global regularization parameter over all uterine sites, which is sub-optimal for EMMI given the severe eccentricity of body-uterus geometry. To address this limitation, we developed a spatial-dependent (SP) regularization method that considers both body-uterus eccentricity and EMG noise. We used electrical signals simulated with spherical and realistic geometry models to compare the reconstruction accuracy of the SP method to those of the CRESO and the L-Curve methods. The SP method reconstructed electrograms and potential maps more accurately than the other methods, especially in cases of high eccentricity and noise contamination. Thus, the SP method should facilitate clinical use of EMMI and can be used to improve the accuracy of other electrical imaging modalities, such as Electrocardiographic Imaging. Graphical abstract The spatial-dependent regularization (SP) technique was designed to improve the accuracy of Electromyometrial Imaging (EMMI). The top panel shows the eccentricity of body-uterus geometry and four representative body surface electrograms. The bottom panel shows boxplots of correlation coefficients and relative errors for the electrograms reconstructed with SP and two conventional methods, the L-Curve and mean CRESO methods.

Noninvasive high-resolution electromyometrial imaging of uterine contractions in a translational sheep model

In current clinical practice, uterine contractions are monitored via a tocodynamometer or an intrauterine pressure catheter, both of which provide crude information about contractions. Although electrohysterography/electromyography can measure uterine electrical activity, this method lacks spatial specificity and thus cannot accurately measure the exact location of electrical initiation and location-specific propagation patterns of uterine contractions. To comprehensively evaluate three-dimensional uterine electrical activation patterns, we describe here the development of electromyometrial imaging (EMMI) to display the three-dimensional uterine contractions at high spatial and temporal resolution. EMMI combines detailed body surface electrical recording with body-uterus geometry derived from magnetic resonance images. We used a sheep model to show that EMMI can reconstruct uterine electrical activation patterns from electrodes placed on the abdomen. These patterns closely match those measured with electrodes placed directly on the uterine surface. In addition, modeling experiments showed that EMMI reconstructions are minimally affected by noise and geometrical deformation. Last, we show that EMMI can be used to noninvasively measure uterine contractions in sheep in the same setup as would be used in humans. Our results indicate that EMMI can noninvasively, safely, accurately, robustly, and feasibly image three-dimensional uterine electrical activation during contractions in sheep and suggest that similar results might be obtained in clinical setting.

Accuracy of electromyometrial imaging of uterine contractions in clinical environment

Clinically, uterine contractions are monitored with tocodynamometers or intrauterine pressure catheters. In the research setting, electromyography (EMG), which detects electrical activity of the uterus from a few electrodes on the abdomen, is feasible, can provide more accurate data than these other methods, and may be useful for predicting preterm birth. However, EMG lacks sufficient spatial resolution and coverage to reveal where uterine contractions originate, how they propagate, and whether preterm contractions differ between women who do and do not progress to preterm delivery. To address those limitations, electromyometrial imaging (EMMI) was recently developed and validated to non-invasively assess three-dimensional (3D) electrical activation patterns on the entire uterine surface in pregnant sheep. EMMI uses magnetic resonance imaging to obtain subject-specific body-uterus geometry and collects uterine EMG data from up to 256 electrodes on the body surface. EMMI software then solves an ill-posed inverse computation to combine the two datasets and generate maps of electrical activity on the entire 3D uterine surface. Here, we assessed the feasibility to clinically translate EMMI by evaluating EMMI's accuracy under the unavoidable geometrical alterations and electrical noise contamination in a clinical environment. We developed a hybrid experimental-simulation platform to model the effects of fetal kicks, contractions, fetal/maternal movements, and noise contamination caused by maternal respiration and environmental electrical activity. Our data indicate that EMMI can accurately image uterine electrical activity in the presence of geometrical deformations and electrical noise, suggesting that EMMI can be reliably translated to non-invasively image 3D uterine electrical activation in pregnant women.

An Automatic Method for the Segmentation and Classification of Imminent Labor Contraction From Electrohysterograms

OBJECTIVE

Preterm birth is the first cause of perinatal morbidity and mortality. Despite continuous clinical routine improvements, the preterm rate remains steady. Moreover, the specificity of the early diagnosis stays poor as many hospitalized women for preterm delivery threat finally deliver at term. In this context, the use of electrohysterograms may increase the sensitivity and the specificity of early diagnosis of preterm labor.

METHODS

This paper proposes a clinical application of electrohysterogram processing for the classification of patients as prone to deliver within a week or later. The approach relies on non-linear correlation analysis for the contraction bursts extraction and uses computation of various features combined with the use of Gaussian mixture models for their classification. The method is tested on a new dataset of 68 records collected on women hospitalized for preterm delivery threat.

RESULTS

This paper presents promising results for the automatic segmentation of the contraction and a classification sensitivity, specificity, and accuracy of, respectively, 80.7%, 76.3%, and 76.2%.

CONCLUSION

These results are in accordance with the gold standards but have the advantage to be non-invasive and could be performed at home.

SIGNIFICANCE

Diagnosis of imminent labor is possible by electrohysterography recording and may help in avoiding over-medication and in providing better cares to at-risk pregnant women.

Potential use of electrohysterography in obstetrics: a review article

Monitoring the uterine contraction during pregnancy is necessary to monitor labor progress, fetal and maternal well-being, and uterine activity. The aim of this review was to evaluate the performance of electrohysterography and to analyze the nature of uterine contraction. A search was undertaken using PubMed, Embase, and ClinicalTrials.gov database from 1 January 1950 to 1 November 2018. Search terms include: "Uterine" or "Uterus" or "Labor" or "Labour" and "electrical activity" or "electrohysterogram" or "electrohysterograph". Reviewing the literature, electrohysterography showed a higher sensitivity for uterine contraction detection and was independent of body mass index, abdominal wall thickness, or maternal position enabling monitoring obese patients as well. Electrohysterography can enhance uterine monitoring throughout labor because of its noninvasiveness, adhesive properties, and reduced obesity sensitiveness. Electrohysterography should be available to safely improve intrapartum monitoring instead of the invasive intrauterine pressure catheter.

The Myometrium: From Excitation to Contractions and Labour

We start by describing the functions of the uterus, its structure, both gross and fine, innervation and blood supply. It is interesting to note the diversity of the female's reproductive tract between species and to remember it when working with different animal models. Myocytes are the overwhelming cell type of the uterus (>95%) and our focus. Their function is to contract, and they have an intrinsic pacemaker and rhythmicity, which is modified by hormones, stretch, paracrine factors and the extracellular environment. We discuss evidence or not for pacemaker cells in the uterus. We also describe the sarcoplasmic reticulum (SR) in some detail, as it is relevant to calcium signalling and excitability. Ion channels, including store-operated ones, their contributions to excitability and action potentials, are covered. The main pathway to excitation is from depolarisation opening voltage-gated Ca²⁺ channels. Much of what happens downstream of excitability is common to other smooth muscles, with force depending upon the balance of myosin light kinase and phosphatase. Mechanisms of maintaining Ca²⁺ balance within the myocytes are discussed. Metabolism, and how it is intertwined with activity, blood flow and pH, is covered. Growth of the myometrium and changes in contractile proteins with pregnancy and parturition are also detailed. We finish with a description of uterine activity and why it is important, covering progression to labour as well as preterm and dysfunctional labours. We conclude by highlighting progress made and where further efforts are required.

Effects of Ropivacaine in Patient-Controlled Epidural Analgesia on Uterine Electromyographic Activities during Labor

Epidural analgesia is effective in relieving pain during labor. However, concerns as to compromised labor progress and outcomes arise. This study aimed to assess the effect of patient-controlled epidural analgesia (PCEA) with ropivacaine on uterine electromyography (EMG) activities and outcomes in labor. A total of 213 pregnant women were divided into three groups: the PCEA with ropivacaine group (n = 78), the PCEA with levobupivacaine group (n = 66), and a control group that did not receive PCEA (n = 69). Uterine EMG activities were recorded during the first stage of labor. Maternal and fetal outcomes also were assessed. The primary outcomes of this study were EMG activities. No significant differences were observed in patient demographics or neonatal weight among the three groups. Compared to the PCEA with levobupivacaine group, the control and PCEA with ropivacaine groups had lower rates of oxytocin administration (P < 0.05) and shorter durations of the first stage of labor (P < 0.05). For the EMG activities, the PCEA with ropivacaine group showed a higher power (P < 0.01) and higher peak frequency (P < 0.05) than the PCEA with levobupivacaine group. With ropivacaine, the EMG activities remained stable 30–120 min. Compared with levobupivacaine, the use of ropivacaine in PCEA has no suppressive effect on uterine EMG activities during the first stage of labor. In addition, ropivacaine leads to labor progress and delivery outcomes similar to those in the control group, as well as similar and favorable analgesic satisfaction with the use of levobupivacaine.

An application of higher order multivariate cumulants in modelling of myoelectrical activity of porcine uterus during early pregnancy

The analysis of the uterine contraction have become a general practice in an effort to improve the clinical management of uterine contractions during pregnancy and labour in human beings. The fluctuations in uterine activity may occur without affecting progress of gestation, however the painful and fashion contractions may be the first threat of miscarriage. While pigs were considered as an referential preclinical model, the computational modelling of spontaneous myoelectrical activity of complex systems of porcine myometrium in peri-fertilization period has been proposed. The higher order statistic, multivariate cumulants and Joint Skewness Band Selection method, have been applied to study the dependence structure of electromyographic (EMG) signal with an effective EMG feature. Than the model of recognition of multivariate, myoelectricaly changes according to crucial stages for successful fertilization and early pregnancy maintenance has been estimated. We found that considering together time and frequency features of EMG signal was extremely non-Gaussian distributed and the higher order multivariate statistics such as cumulants, have to be used to determine the pattern of myoelectrical activity in reproductive tract. We confirmed the expectance that the probabilistic model changes on a daily base. We demonstrated the changes in proposed model at the crucial time points of in peri-fertilization period. We speculate the activity of the middle of uterine horn and the power (minimum and maximum) and pauses between myoelectrical burst features are essential for the functional role of uterine contractility in peri-fertilization period.

Clinical Use of Electrohysterography During Term Labor: A Systematic Review on Diagnostic Value, Advantages, and Limitations

Importance

Real-time electrohysterography (EHG)-based technologies have recently become available for uterine monitoring during term labor. Therefore, obstetricians need to be familiar with the diagnostic value, advantages, and limitations of using EHG.

Objective

The aims of this study were to determine the diagnostic value of EHG in comparison to (1) the intrauterine pressure catheter (IUPC), (2) the external tocodynamometer (TOCO), and (3) in case of maternal obesity; (4) to evaluate EHG from users' and patients' perspectives; and (5) to assess whether EHG can predict labor outcome.

Evidence Acquisition

A systematic review was performed in the MEDLINE, EMBASE, and Cochrane library in October 2017 resulting in 209 eligible records, of which 20 were included.

Results

A high sensitivity for contraction detection was achieved by EHG (range, 86.0%-98.0%), which was significantly better than TOCO (range, 46.0%-73.6%). Electrohysterography also enhanced external monitoring in case of maternal obesity. The contraction frequency detected by EHG was on average 0.3 to 0.9 per 10 minutes higher compared with IUPC, which resulted in a positive predictive value of 78.7% to 92.0%. When comparing EHG tocograms with IUPC traces, an underestimation of the amplitude existed despite that patient-specific EHG amplitudes have been mitigated by amplitude normalization. Obstetricians evaluated EHG tocograms as better interpretable and more adequate than TOCO. Finally, potential EHG parameters that could predict a vaginal delivery were a predominant fundal direction and a lower peak frequency.

Conclusions and Relevance

Electrohysterography enhances external uterine monitoring of both nonobese and obese women. Obstetricians consider EHG as better interpretable; however, they need to be aware of the higher contraction frequency detected by EHG and of the amplitude mismatch with intrauterine pressure measurements.

Characterization and automatic classification of preterm and term uterine records

Predicting preterm birth is uncertain, and numerous scientists are searching for non-invasive methods to improve its predictability. Current researches are based on the analysis of ElectroHysteroGram (EHG) records, which contain information about the electrophysiological properties of the uterine muscle and uterine contractions. Since pregnancy is a long process, we decided to also characterize, for the first time, non-contraction intervals (dummy intervals) of the uterine records, i.e., EHG signals accompanied by a simultaneously recorded external tocogram measuring mechanical uterine activity (TOCO signal). For this purpose, we developed a new set of uterine records, TPEHGT DS, containing preterm and term uterine records of pregnant women, and uterine records of non-pregnant women. We quantitatively characterized contraction intervals (contractions) and dummy intervals of the uterine records of the TPEHGT DS in terms of the normalized power spectra of the EHG and TOCO signals, and developed a new method for predicting preterm birth. The results on the characterization revealed that the peak amplitudes of the normalized power spectra of the EHG and TOCO signals of the contraction and dummy intervals in the frequency band 1.0-2.2 Hz, describing the electrical and mechanical activity of the uterus due to the maternal heart (maternal heart rate), are high only during term pregnancies, when the delivery is still far away; and they are low when the delivery is close. However, these peak amplitudes are also low during preterm pregnancies, when the delivery is still supposed to be far away (thus suggesting the danger of preterm birth); and they are also low or barely present for non-pregnant women. We propose the values of the peak amplitudes of the normalized power spectra due to the influence of the maternal heart, in an electro-mechanical sense, in the frequency band 1.0-2.2 Hz as a new biophysical marker for the preliminary, or early, assessment of the danger of preterm birth. The classification of preterm and term, contraction and dummy intervals of the TPEHGT DS, for the task of the automatic prediction of preterm birth, using sample entropy, the median frequency of the power spectra, and the peak amplitude of the normalized power spectra, revealed that the dummy intervals provide quite comparable and slightly higher classification performances than these features obtained from the contraction intervals. This result suggests a novel and simple clinical technique, not necessarily to seek contraction intervals but using the dummy intervals, for the early assessment of the danger of preterm birth. Using the publicly available TPEHG DB database to predict preterm birth in terms of classifying between preterm and term EHG records, the proposed method outperformed all currently existing methods. The achieved classification accuracy was 100% for early records, recorded around the 23rd week of pregnancy; and 96.33%, the area under the curve of 99.44%, for all records of the database. Since the proposed method is capable of using the dummy intervals with high classification accuracy, it is also suitable for clinical use very early during pregnancy, around the 23rd week of pregnancy, when contractions may or may not be present.

Estimating uterine source current during contractions using magnetomyography measurements

Understanding the uterine source of the electrophysiological activity of contractions during pregnancy is of scientific interest and potential clinical applications. In this work, we propose a method to estimate uterine source currents from magnetomyography (MMG) temporal course measurements on the abdominal surface. In particular, we develop a linear forward model, based on the quasistatic Maxwell’s equations and a realistic four-compartment volume conductor, relating the magnetic fields to the source currents on the uterine surface through a lead-field matrix. To compute the lead-field matrix, we use a finite element method that considers the anisotropic property of the myometrium. We estimate the source currents by minimizing a constrained least-squares problem to solve the non-uniqueness issue of the inverse problem. Because we lack the ground truth of the source current, we propose to predict the intrauterine pressure from our estimated source currents by using an absolute-value-based method and compare the result with real abdominal deflection recorded during contractile activity. We test the feasibility of the lead-field matrix by displaying the lead fields that are generated by putative source currents at different locations in the myometrium: cervix and fundus, left and right, front and back. We then illustrate our method by using three synthetic MMG data sets, which are generated using our previously developed multiscale model of uterine contractions, and three real MMG data sets, one of which has simultaneous real abdominal deflection measurements. The numerical results demonstrate the ability of our method to capture the local contractile activity of human uterus during pregnancy. Moreover, the predicted intrauterine pressure is in fair agreement with the real abdominal deflection with respect to the timing of uterine contractions.

Identification of uterine pacemaker regions at the myometrial-placental interface in the rat

KEY POINTS

Coordinated contraction of the uterine smooth muscle is essential to parturition. Histologically and physiologically defined pacemaker structures have not been identified in uterine smooth muscle. Here we report combined electrophysiological and histological evidence of zones associated with pacemaker activity in the rat myometrium. Our method relies crucially on the integration of histological and electrophysiological data in an in silico three-dimensional reconstruction of the rat myometrium at 10 μm resolution. We find that myometrial/placental pacemaking zones are closely related with placental sites and the area of disruptive myometrial remodelling surrounding such sites. If analogues of the myometrial/placental pacemaking zone are present in the human, defining their histology and physiology will be important steps towards treatment of pre-term birth, pre-eclampsia, and postpartum haemorrhage.

ABSTRACT

Coordinated uterine contractions are essential for delivering viable offspring in mammals. In contrast to other visceral smooth muscles, it is not known where excitation within the uterus is initiated, and no defined pacemaking region has hitherto been identified. Using multi-electrode array recordings and high-resolution computational reconstruction of the three-dimensional micro-structure of late pregnant rat uterus, we demonstrate that electrical potentials are initiated in distinct structures within the placental bed of individual implantation sites. These previously unidentified structures represent modified smooth muscle bundles that are derived from bridges between the longitudinal and circular layers. Coordinated implantation and encapsulation by invading trophoblast give rise to isolated placental/myometrial interface bundles that directly connect to the overlying longitudinal smooth muscle layer. Taken together, these observations imply that the anatomical structure of the uterus, combined with site-specific implantation, gives rise to emergent patterns of electrical activity that drive effective contractility during parturition.

The uterine pacemaker of labor

The laboring uterus is generally thought to initiate contractions much similar to the heart, with a single, dedicated pacemaker. Research on human and animal models over decades has failed to identify such pacemaker. On the contrary, data indicate that instead of being fixed at a site similar to the sinoatrial node of the heart, the initiation site for each uterine contraction changes during time, often with each contraction. The enigmatic uterine "pacemaker" does not seem to fit the standard definition of what a pacemaker should be. The uterine pacemaker must also mesh with the primary physiological function of the uterus - to generate intrauterine pressure. This requires that most areas of the uterine wall contract in a coordinated, or synchronized, manner for each contraction of labor. It is not clear whether the primary mechanism of the uterine pacemaker is a slow-wave generator or an impulse generator. Slow waves in the gut initiate localized smooth muscle contractions. Because the uterus and the gut have somewhat similar cellular and tissue structure, it is reasonable to consider if uterine contractions are paced by a similar mechanism. Unfortunately, there is no convincing experimental verification of uterine slow waves. Similarly, there is no convincing evidence of a cellular mechanism for impulse generation. The uterus appears to have multiple widely dispersed mechanically sensitive functional pacemakers. It is possible that the coordination of organ-level function occurs through intrauterine pressure, thus creating wall stress followed by activation of many mechanosensitive electrogenic pacemakers.

Feasibility of Transabdominal Electrohysterography for Analysis of Uterine Activity in Nonpregnant Women

PURPOSE

Uterine activity plays a key role in reproduction, and altered patterns of uterine contractility have been associated with important physiopathological conditions, such as subfertility, dysmenorrhea, and endometriosis. However, there is currently no method to objectively quantify uterine contractility outside pregnancy without interfering with the spontaneous contraction pattern. Transabdominal electrohysterography has great potential as a clinical tool to characterize noninvasively uterine activity, but results of this technique in nonpregnant women are poorly documented. The purpose of this study is to investigate the feasibility of transabdominal electrohysterography in nonpregnant women.

METHODS

Longitudinal measurements were performed on 22 healthy women in 4 representative phases of the menstrual cycle. Twelve electrohysterogram-based indicators previously validated in pregnancy have been estimated and compared in the 4 phases of the cycle. Using the Tukey honest significance test, significant differences were defined for P values below .05.

RESULTS

Half of the selected electrohysterogram-based indicators showed significant differences between menses and at least 1 of the other 3 phases, that is the luteal phase.

CONCLUSION

Our results suggest transabdominal electrohysterography to be feasible for analysis of uterine activity in nonpregnant women. Due to the lack of a golden standard, this feasibility study is indirectly validated based on physiological observations. However, these promising results motivate further research aiming at evaluating electrohysterography as a method to improve understanding and management of dysfunctions (possibly) related to altered uterine contractility, such as infertility, endometriosis, and dysmenorrhea.

Intsy: a low-cost, open-source, wireless multi-channel bioamplifier system

OBJECTIVE

Multi-channel electrical recordings of physiologically generated signals are common to a wide range of biomedical fields. The aim of this work was to develop, validate, and demonstrate the practical utility of a high-quality, low-cost 32/64-channel bioamplifier system with real-time wireless data streaming capability.

APPROACH

The new 'Intsy' system integrates three main off-the-shelf hardware components: (1) Intan RHD2132 bioamplifier; (2) Teensy 3.2 microcontroller; and (3) RN-42 Bluetooth 2.1 module with a custom LabView interface for real-time data streaming and visualization. Practical utility was validated by measuring serosal gastric slow waves and surface EMG on the forearm with various contraction force levels. Quantitative comparisons were made to a gold-standard commercial system (Biosemi ActiveTwo).

MAIN RESULTS

Intsy signal quality was quantitatively comparable to that of the ActiveTwo. Recorded slow wave signals had high SNR (24  ±  2.7 dB) and wavefront propagation was accurately mapped. EMG spike bursts were characterized by high SNR (⩾10 dB) and activation timing was readily identified. Stable data streaming rates achieved were 3.5 kS s^-1 for wireless and 64 kS s^-1 for USB-wired transmission.

SIGNIFICANCE

Intsy has the highest channel count of any existing open-source, wireless-enabled module. The flexibility, portability and low cost ($1300 for the 32-channel version, or $2500 for 64 channels) of this new hardware module reduce the entry barrier for a range of electrophysiological experiments, as are typical in the gastrointestinal (EGG), cardiac (ECG), neural (EEG), and neuromuscular (EMG) domains.

Electrohysterography in the diagnosis of preterm birth: a review

Preterm birth (PTB) is one of the most common and serious complications in pregnancy. About 15 million preterm neonates are born every year, with ratios of 10-15% of total births. In industrialized countries, preterm delivery is responsible for 70% of mortality and 75% of morbidity in the neonatal period. Diagnostic means for its timely risk assessment are lacking and the underlying physiological mechanisms are unclear. Surface recording of the uterine myoelectrical activity (electrohysterogram, EHG) has emerged as a better uterine dynamics monitoring technique than traditional surface pressure recordings and provides information on the condition of uterine muscle in different obstetrical scenarios with emphasis on predicting preterm deliveries.

OBJECTIVE

A comprehensive review of the literature was performed on studies related to the use of the electrohysterogram in the PTB context.

APPROACH

This review presents and discusses the results according to the different types of parameter (temporal and spectral, non-linear and bivariate) used for EHG characterization.

MAIN RESULTS

Electrohysterogram analysis reveals that the uterine electrophysiological changes that precede spontaneous preterm labor are associated with contractions of more intensity, higher frequency content, faster and more organized propagated activity and stronger coupling of different uterine areas. Temporal, spectral, non-linear and bivariate EHG analyses therefore provide useful and complementary information. Classificatory techniques of different types and varying complexity have been developed to diagnose PTB. The information derived from these different types of EHG parameters, either individually or in combination, is able to provide more accurate predictions of PTB than current clinical methods. However, in order to extend EHG to clinical applications, the recording set-up should be simplified, be less intrusive and more robust-and signal analysis should be automated without requiring much supervision and yield physiologically interpretable results.

SIGNIFICANCE

This review provides a general background to PTB and describes how EHG can be used to better understand its underlying physiological mechanisms and improve its prediction. The findings will help future research workers to decide the most appropriate EHG features to be used in their analyses and facilitate future clinical EHG applications in order to improve PTB prediction.

Dedicated Entropy Measures for Early Assessment of Pregnancy Progression From Single-Channel Electrohysterography

OBJECTIVE

Preterm birth is a large-scale clinical problem involving over 10% of infants. Diagnostic means for timely risk assessment are lacking and the underlying physiological mechanisms unclear. To improve the evaluation of pregnancy before term, we introduce dedicated entropy measures derived from a single-channel electrohysterogram (EHG).

METHODS

The estimation of approximate entropy (ApEn) and sample entropy (SampEn) is adjusted to monitor variations in the regularity of single-channel EHG recordings, reflecting myoelectrical changes due to pregnancy progression. In particular, modifications in the tolerance metrics are introduced for improving robustness to EHG amplitude fluctuations. An extensive database of 58 EHG recordings with 4 monopolar channels in women presenting with preterm contractions was manually annotated and used for validation. The methods were tested for their ability to recognize the onset of labor and the risk of preterm birth. Comparison with the best single-channel methods according to the literature was performed.

RESULTS

The reference methods were outperformed. SampEn and ApEn produced the best prediction of delivery, although only one channel showed a significant difference () between labor and nonlabor. The modified ApEn produced the best prediction of preterm delivery, showing statistical significance () in three channels. These results were also confirmed by the area under the receiver operating characteristic curve and fivefold cross validation.

CONCLUSION

The use of dedicated entropy estimators improves the diagnostic value of EHG analysis earlier in pregnancy.

SIGNIFICANCE

Our results suggest that changes in the EHG might manifest early in pregnancy, providing relevant prognostic opportunities for pregnancy monitoring by a practical single-channel solution.

Biomathematical pattern of EMG signal propagation in smooth muscle of the non-pregnant porcine uterus

Uterine contractions are generated by myometrial smooth muscle cells (SMCs) that comprise most of the myometrial layer of the uterine wall. Aberrant uterine motility (i.e., hypo- or hyper-contractility or asynchronous contractions) has been implicated in the pathogenesis of infertility due to the failure of implantation, endometriosis and abnormal estrous cycles. The mechanism whereby the non-pregnant uterus initiates spontaneous contractions remains poorly understood. The aim of the present study was to employ linear synchronization measures for analyzing the pattern of EMG signal propagation (direction and speed) in smooth muscles of the non-pregnant porcine uterus in vivo using telemetry recording system. It has been revealed that the EMG signal conduction in the uterine wall of the non-pregnant sow does not occur at random but it rather exhibits specific directions and speed. All detectable EMG signals moved along the uterine horn in both cervico-tubal and tubo-cervical directions. The signal migration speed could be divided into the three main types or categories: i. slow basic migration rhythm (SBMR); ii. rapid basic migration rhythm (RBMR); and iii. rapid accessory migration rhythm (RAMR). In conclusion, the EMG signal propagation in smooth muscles of the porcine uterus in vivo can be assessed using a linear synchronization model. Physiological pattern of the uterine contractile activity determined in this study provides a basis for future investigations of normal and pathologicall myogenic function of the uterus.

Uterine and Abdominal Muscle Electromyographic Activities in Control and PCEA-Treated Nulliparous Women During the Second Stage of Labor

OBJECTIVE

Patient-controlled epidural analgesia (PCEA), used to relieve pain during delivery, delays labor but the mechanism is unknown. The aim was to investigate the effects of PCEA on uterine and abdominal muscles electromyographic (EMG) activity during the second stage of labor.

METHODS

This study included 45 nulliparous pregnant women without PCEA, 42 women with standard PCEA treatment given during the first stage of labor and stopped near the end of the first stage, and 22 women with standard PCEA treatment with continued use throughout the first and second stages of labor. The EMG signals were recorded from the abdominal surface using PowerLab hardware and LabChart software (ADInstruments, New South Wales, Australia) and filtered to separate uterine and abdominal EMG. Various EMG burst parameters were obtained.

RESULTS

There are no differences ( P > .05) in the age, body mass index, fetal weight, and Apgar scores between the patients from the various groups. PCEA (both stopped and continued) inhibits ( P < .05) duration, number of bursts, and root mean square of uterine EMG. PCEA also produces statistically significant ( P < .001) reductions in abdominal EMG. The decrease in EMG activity is accompanied by a significant ( P < .001) prolongation of the second stage duration (PCEA continued = 95.08 ± 8.60 minutes, PCEA stopped = 79.39 ± 6.25 minutes, no PCEA = 61.00 ± 7.23 minutes).

CONCLUSION

PCEA suppresses uterine and abdominal muscle EMG during the second stage of labor but inhibition depends upon the treatment schedule. PCEA prolongs the duration of labor by inhibition of uterine and abdominal muscle and neural activity.