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

Characterization of the effects of Atosiban on uterine electromyograms recorded in women with threatened preterm labor

[EN] Although research studies using electrohysterography on women without tocolytic therapy have shown its potential for preterm birth diagnosis, tocolytics are usually administered in emergency rooms at the first sign of threatened preterm labor (TPL). Information on the uterine response during tocolytic treatment could prove useful for the development of tools able to predict true preterm deliveries under normal clinical conditions. The aim of this study was thus to analyze the effects of Atosiban on Electrohysterogram (EHG) parameters and to compare its effects on women who delivered preterm (WDP) and at term (WDT). Electrohysterograms recorded in different Atosiban therapy stages (before, during and after drug administration) on 40 WDT and 27 WDP were analyzed by computing linear, and non-linear EHG parameters. Results reveal that Atosiban does not greatly affect the EHG signal amplitude, but does modify its spectral content and reduces the energy associated with the fast wave high component in both WDP and WDT, with a faster response in the latter. EHG signal complexity remained constant in WDT, while it increased in WDP until it reached similar values to WDT during Atosiban treatment. The spectral and complexity parameters were able to separate (p < 0.05) WDT and WDP prior to and during tocolytic treatment and before and after treatment, respectively. The results pave the way for developing better and more reliable medical decision support systems based on EHG for preterm delivery prediction in TPL women in clinical scenarios.This work received financial support from the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (DPI2015-68397-R), VLC/Campus (UPV-FE-2018-B03) and by Conselleria de Educación, Investigación, Cultura y Deporte, Generalitat Valenciana (GV/2018/104).Mas-Cabo, J.; Prats-Boluda, G.; Ye Lin, Y.; Alberola Rubio, J.; Perales, A.; Garcia-Casado, J. (2019). Characterization of the effects of Atosiban on uterine electromyograms recorded in women with threatened preterm labor. Biomedical Signal Processing and Control. 52:198-205. https://doi.org/10.1016/j.bspc.2019.04.001S1982055

Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode

The conduction velocity and propagation patterns of Electrohysterogram (EHG) provide fundamental information about uterine electrophysiological condition. The accuracy of these measurements can be impaired by both the poor spatial selectivity and sensitivity to the relative direction of the contraction propagation associated with conventional disc electrodes. Concentric ring electrodes could overcome these limitations the aim of this study was to examine the feasibility of picking up surface EHG signals using a new flexible tripolar concentric ring electrode (TCRE), and to compare it with conventional bipolar recordings. Simultaneous recording of conventional bipolar signals and bipolar concentric EHG (BC-EHG) were carried out on 22 pregnant women. Signal bursts were characterized and compared. No significant differences among channels in either duration or dominant frequency in the Fast Wave High frequency range were found. Nonetheless, the high pass filtering effect of the BC-EHG records resulted in lower frequency content within the range 0.1 to 0.2 Hz than the bipolar ones. Although the BC-EHG signal amplitude was about 5-7 times smaller than that of bipolar recordings, similar signal-to-noise ratio was obtained. These results suggest that the flexible TCRE is able to pick up uterine electrical activity and could provide additional information for deducing uterine electrophysiological condition.The authors are grateful to the Obstetrics Unit of the Hospital Universitario La Fe de Valencia (Valencia, Spain), where the recording sessions were carried out. The work was supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC2010-16945), by the Universitat Politecnica de Valencia (PAID SP20120490) and Generalitat Valenciana (GV/2014/029) and by General Electric Healthcare.Ye Lin, Y.; Alberola Rubio, J.; Prats Boluda, G.; Perales Marin, AJ.; Desantes, D.; Garcia Casado, FJ. (2015). Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode. Annals of Biomedical Engineering. 43(4):968-976. https://doi.org/10.1007/s10439-014-1130-5S968976434Alberola-Rubio, J., G. Prats-Boluda, Y. Ye-Lin, J. Valero, A. Perales, and J. Garcia-Casado. Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. Med. Eng. Phys. 35(12):1736–1743, 2013.Besio, W. G., K. Koka, R. Aakula, and W. Dai. Tri-polar concentric ring electrode development for laplacian electroencephalography. IEEE Trans. Biomed. Eng. 53(5):926–933, 2006.Devasahayam, S. R. Signals and Systems in Biomedical Engineering. Berlin: Springer, 2013.Devedeux, D., C. Marque, S. Mansour, G. Germain, and J. Duchene. Uterine electromyography: a critical review. Am. J. Obstet. Gynecol. 169(6):1636–1653, 1993.Estrada, L., A. Torres, J. Garcia-Casado, G. Prats-Boluda, and R. Jane. Characterization of laplacian surface electromyographic signals during isometric contraction in biceps brachii. Conf. Proc. IEEE Eng Med. Biol. Soc. 2013:535–538, 2013.Euliano, T. Y., D. Marossero, M. T. Nguyen, N. R. Euliano, J. Principe, and R. K. Edwards. Spatiotemporal electrohysterography patterns in normal and arrested labor. Am. J. Obstet. Gynecol. 200(1):54–57, 2009.Farina, D., and C. Cescon. Concentric-ring electrode systems for noninvasive detection of single motor unit activity. IEEE Trans. Biomed. Eng. 48(11):1326–1334, 2001.Fele-Zorz, G., G. Kavsek, Z. Novak-Antolic, and F. Jager. A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Med. Biol. Eng Comput. 46(9):911–922, 2008.Garfield, R. E., and W. L. Maner. Physiology and electrical activity of uterine contractions. Semin. Cell Dev. Biol. 18(3):289–295, 2007.Garfield, R. E., W. L. Maner, L. B. Mackay, D. Schlembach, and G. R. Saade. Comparing uterine electromyography activity of antepartum patients vs. term labor patients. Am. J. Obstet. Gynecol. 193(1):23–29, 2005.Garfield, R. E., H. Maul, L. Shi, W. Maner, C. Fittkow, G. Olsen, and G. R. Saade. Methods and devices for the management of term and preterm labor. Ann. N. Y. Acad. Sci. 943(1):203–224, 2001.Hassan, M., J. Terrien, C. Muszynski, A. Alexandersson, C. Marque, and B. Karlsson. Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans. Biomed. Eng. 60(4):1160–1166, 2013.Kaufer, M., L. Rasquinha, and P. Tarjan. Optimization of multi-ring sensing electrode set, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 1990, pp. 612–613.Koka, K., and W. G. Besio. Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. J. Neurosci. Methods 165(2):216–222, 2007.Lu, C.-C., and P. P. Tarjan. Pasteless, active, concentric ring sensors for directly obtained laplacian cardiac electrograms. J. Med. Biol. Eng. 22(4):199–203, 2002.Lucovnik, M., W. L. Maner, L. R. Chambliss, R. Blumrick, J. Balducci, Z. Novak-Antolic, and R. E. Garfield. Noninvasive uterine electromyography for prediction of preterm delivery. Am. J. Obstet. Gynecol. 204(3):228.e1–228.e10, 2011.Maner, W. L., and R. E. Garfield. Identification of human term and preterm labor using artificial neural networks on uterine electromyography data. Ann. Biomed. Eng. 35(3):465–473, 2007.Maner, W. L., R. E. Garfield, H. Maul, G. Olson, and G. Saade. Predicting term and preterm delivery with transabdominal uterine electromyography. Obstet. Gynecol. 101(6):1254–1260, 2003.Marque, C., J. M. Duchene, S. Leclercq, G. S. Panczer, and J. Chaumont. Uterine EHG processing for obstetrical monitoring. IEEE Trans. Biomed. Eng. 33(12):1182–1187, 1986.Marque, C. K., J. Terrien, S. Rihana, and G. Germain. Preterm labour detection by use of a biophysical marker: the uterine electrical activity. BMC. Pregnancy Childbirth. 7(Suppl1):S5, 2007.Maul, H., W. L. Maner, G. Olson, G. R. Saade, and R. E. Garfield. Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. J. Matern. Fetal Neonatal Med. 15(5):297–301, 2004.Miles, A. M., M. Monga, and K. S. Richeson. Correlation of external and internal monitoring of uterine activity in a cohort of term patients. Am. J. Perinatol. 18(3):137–140, 2001.Prats-Boluda, G., J. Garcia-Casado, J. L. Martinez-de-Juan, and Y. Ye-Lin. Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Med. Eng. Phys. 33(4):446–455, 2010.Prats-Boluda, G., Y. Ye-Lin, E. Garcia-Breijo, J. Ibañez, and J. Garcia-Casado. Active flexible concentric ring electrode for non-invasive surface bioelectrical recordings. Meas. Sci. Technol. 23(12):1–10, 2012.Rabotti, C., M. Mischi, S. G. Oei, and J. W. Bergmans. Noninvasive estimation of the electrohysterographic action-potential conduction velocity. IEEE Trans. Biomed. Eng. 57(9):2178–2187, 2010.Rabotti, C., S. G. Oei, H. J. van ‘t, and M. Mischi. Electrohysterographic propagation velocity for preterm delivery prediction. Am. J. Obstet. Gynecol. 205(6):e9–e10, 2011.Rooijakkers, M. J., S. Song, C. Rabotti, S. G. Oei, J. W. Bergmans, E. Cantatore, and M. Mischi. Influence of electrode placement on signal quality for ambulatory pregnancy monitoring. Comput. Math. Methods Med. 2014(1):960980, 2014.Schlembach, D., W. L. Maner, R. E. Garfield, and H. Maul. Monitoring the progress of pregnancy and labor using electromyography. Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl1):S33–S39, 2009.Sikora, J., A. Matonia, R. Czabanski, K. Horoba, J. Jezewski, and T. Kupka. Recognition of premature threatening labour symptoms from bioelectrical uterine activity signals. Arch. Perinatal Med. 17(2):97–103, 2011.Terrien, J., C. Marque, and B. Karlsson. Spectral characterization of human EHG frequency components based on the extraction and reconstruction of the ridges in the scalogram, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 2007, pp. 1872–1875.Terrien, J., C. Marque, T. Steingrimsdottir, and B. Karlsson. Evaluation of adaptive filtering methods on a 16 electrode electrohysterogram recorded externally in labor, 11th Mediterranean Conference on Medical and Biomedical Engineering and Computing, 2007, Vol. 16, pp. 135–138.U.S. Preventive Services Task Force. Guide to clinical preventive services: an assessment of the effectiveness of 169 interventions. Baltimore: Willams & Wilkins, 1989

Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment

[EN] As one of the main aims of obstetrics is to be able to detect imminent delivery in patients with threatened preterm labor, the techniques currently used in clinical practice have serious limitations in this respect. The electrohysterogram (EHG) has now emerged as an alternative technique, providing relevant information about labor onset when recorded in controlled checkups without administration of tocolytic drugs. The studies published to date mainly focus on EHG-burst analysis and, to a lesser extent, on whole EHG window analysis. The study described here assessed the ability of EHG signals to discriminate imminent labor (The ability of EHG recordings to predict imminent labor (<7days) was analyzed in preterm threatened patients undergoing tocolytic therapies by means of EHG-burst and whole EHG window analysis. The non-linear features were found to have better performance than the temporal and spectral parameters in separating women who delivered in less than 7days from those who did not.Mas-Cabo, J.; Prats-Boluda, G.; Perales Marín, AJ.; Garcia-Casado, J.; Alberola Rubio, J.; Ye Lin, Y. (2019). Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment. Medical & Biological Engineering & Computing. 57:401-411. https://doi.org/10.1007/s11517-018-1888-yS40141157Aboy M, Cuesta-Frau D, Austin D, Micó-Tormos P (2007) Characterization of sample entropy in the context of biomedical signal analysis. Conf Proc IEEE Eng Med Biol Soc:5942–5945. https://doi.org/10.1109/IEMBS.2007.4353701Aboy M, Hornero R, Abásolo D, Álvarez D (2006) Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis. IEEE Trans Biomed Eng 53:2282–2288. https://doi.org/10.1109/TBME.2006.883696Chkeir A, Fleury MJ, Karlsson B, Hassan M, Marque C (2013) Patterns of electrical activity synchronization in the pregnant rat uterus. Biomed 3:140–144. https://doi.org/10.1016/j.biomed.2013.04.007Crandon AJ (1979) Maternal anxiety and neonatal wellbeing. J Psychosom Res 23:113–115. https://doi.org/10.1016/0022-3999(79)90015-1Devedeux D, Marque C, Mansour S, Germain G, Duchêne J (1993) Uterine electromyography: a critical review. Am J Obstet Gynecol 169:1636–1653. https://doi.org/10.1016/0002-9378(93)90456-SFele-Žorž G, Kavšek G, Novak-Antolič Ž, Jager F (2008) A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Med Biol Eng Comput 46:911–922. https://doi.org/10.1007/s11517-008-0350-yFergus P, Cheung P, Hussain A, al-Jumeily D, Dobbins C, Iram S (2013) Prediction of preterm deliveries from EHG signals using machine learning. PLoS One 8:e77154. https://doi.org/10.1371/journal.pone.0077154Garfield RE, Maner WL (2006) Biophysical methods of prediction and prevention of preterm labor: uterine electromyography and cervical light-induced fluorescence—new obstetrical diagnostic techniques. In: Preterm Birth pp 131–144Garfield RE, Maner WL (2007) Physiology and electrical activity of uterine contractions. Semin Cell Dev Biol 18:289–295. https://doi.org/10.1016/j.semcdb.2007.05.004Garfield RE, Maner WL, MacKay LB et al (2005) Comparing uterine electromyography activity of antepartum patients versus term labor patients. Am J Obstet Gynecol 193:23–29. https://doi.org/10.1016/j.ajog.2005.01.050Goldenberg RL, Culhane JF, Iams JD, Romero R (2008) Epidemiology and causes of preterm birth. Lancet 371:75–84. https://doi.org/10.1016/S0140-6736(08)60074-4American College of Obstetricians and Gynecologists and Committee on Practice Bulletins— Obstetrics (2012) Practice bulletin no. 127. Obstet Gynecol 119(6):1308–1317.Hadar E, Biron-Shental T, Gavish O, Raban O, Yogev Y (2015) A comparison between electrical uterine monitor, tocodynamometer and intra uterine pressure catheter for uterine activity in labor. J Matern Neonatal Med 28:1367–1374. https://doi.org/10.3109/14767058.2014.954539Hans P, Dewandre P, Brichant JF, Bonhomme V (2005) Comparative effects of ketamine on Bispectral Index and spectral entropy of the electroencephalogram under sevoflurane anaesthesia. Br J Anaesth 94:336–340. https://doi.org/10.1093/bja/aei047Hassan M, Terrien J, Marque C, Karlsson B (2011) Comparison between approximate entropy, correntropy and time reversibility: application to uterine electromyogram signals. Med Eng Phys 33:980–986. https://doi.org/10.1016/j.medengphy.2011.03.010Hassan M, Terrien J, Muszynski C et al (2013) Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans Biomed Eng 60:1160–1166. https://doi.org/10.1109/TBME.2012.2229279Horoba K, Jezewski J, Matonia A, Wrobel J, Czabanski R, Jezewski M (2016) Early predicting a risk of preterm labour by analysis of antepartum electrohysterograhic signals. Biocybern Biomed Eng 36:574–583. https://doi.org/10.1016/j.bbe.2016.06.004Lawn JE, Wilczynska-Ketende K, Cousens SN (2006) Estimating the causes of 4 million neonatal deaths in the year 2000. Int J Epidemiol 35:706–718. https://doi.org/10.1093/ije/dyl043Lemancewicz A, Borowska M, Kuć P, Jasińska E, Laudański P, Laudański T, Oczeretko E (2016) Early diagnosis of threatened premature labor by electrohysterographic recordings—the use of digital signal processing. Biocybern Biomed Eng 36:302–307. https://doi.org/10.1016/j.bbe.2015.11.005M L WLM, LR C (2012) Noninvasive uterine electromyography for prediction of preterm delivery. Am J Obstet Gynecol 204:1–20. https://doi.org/10.1016/j.ajog.2010.09.024.NoninvasiveManer WL, Garfield RE (2007) Identification of human term and preterm labor using artificial neural networks on uterine electromyography data. Ann Biomed Eng 35:465–473. https://doi.org/10.1007/s10439-006-9248-8Maner WL, Garfield RE, Maul H, Olson G, Saade G (2003) Predicting term and preterm delivery with transabdominal uterine electromyography. Obstet Gynecol 101:1254–1260. https://doi.org/10.1016/S0029-7844(03)00341-7Marque C, Gondry J (1999) Use of the electrohysterogram signal for characterization of contractions during pregnancy. 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BJOG 112:10–15. https://doi.org/10.1111/j.1471-0528.2005.00577.xRabotti C, Sammali F, Kuijsters N, et al (2015) Analysis of uterine activity in nonpregnant women by electrohysterography: a feasibility study. In: Proc Annu Int Conf IEEE Eng Med Biol Soc EMBS pp 5916–5919Schlembach D, Maner WL, Garfield RE, Maul H (2009) Monitoring the progress of pregnancy and labor using electromyography. Eur J Obstet Gynecol Reprod Biol 144:2–8. https://doi.org/10.1016/j.ejogrb.2009.02.016Sikora J, Matonia A, Czabański R et al (2011) Recognition of premature threatening labour symptoms from bioelectrical uterine activity signals. Arch Perinat Med 17:97–103Vinken MPGC, Rabotti C, Mischi M, van Laar JOEH, Oei SG (2010) Nifedipine-induced changes in the electrohysterogram of preterm contractions: feasibility in clinical practice. Obstet Gynecol Int 2010:325635. https://doi.org/10.1155/2010/325635Vrhovec J, Lebar AM (2012) An uterine electromyographic activity as a measure of labor progression. 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Placental site does not change background uterine electromyographic activity in the middle trimester of pregnancy

OBJECTIVE: This study was performed in order to assess the potential influence of placental implantation site on transabdominal electromyographic (EMG) assessment of the uterine electrical activity in the middle trimester of pregnancy. - - - - - STUDY DESIGN: In this prospective study 251 unselected, nulliparous asymptomatic women with a singleton pregnancy underwent transabdominal uterine EMG. Uterine electrical activity was recorded using bipolar electrodes placed on the abdominal surface for 20min. Regarding the placental implantation site and presence of action potentials (AP) pregnant women were divided into two groups: the anterior placenta group (APG) and the posterior placenta group (PPG). Outcome measures were differences in the median frequency (MF) and median amplitude (MA) of AP between the two groups. - - - - - RESULTS: Action potentials were detected in 56 women: 33/56 in the APG versus 23/56 in the PPG. The parameters analyzed (MF, p=0.527, Fisher's exact test, and MA, p=0.255, Fisher's exact test) did not produce any statistical significant differences between the two groups. - - - - - CONCLUSION: Background uterine EMG activity measured from the abdominal surface in the middle trimester of pregnancy does not depend on the placental implantation site

Time-frequency distributions applied to uterine EMG. Characterization and assessment

International audienc

La reallocation dans les représentations temps/fréquence : Application à l'EMG uterin

La réallocation de l'énergie d'une représentation temps/fréquence est un post-traitement permettant de réaffecter à leur véritable position des énergies dispersées dans le plan temps/fréquence. Nous nous proposons d'évaluer les performances de cette technique appliquée au spectrogramme dans le cas de signaux présentant une modulation de leur fréquence principale. Les résultats obtenus dans le cas de signaux artificiels sont très prometteurs. Appliquée à des électromyogrammes utérins réels, la réallocation présente l'inconvénient de créer des discontinuités dans le suivi de la fréquence modulée

Reassigned time/Frequency representations for estimation methods

International audienc