Development and application of an automated extraction algorithm for fetal magnetocardiography – normal data and arrhythmia detection

Krunoslav Stingl; Henrike Paulsen; Magdalene Weiss; Hubert Preissl; Harald Abele; Rangmar Goelz; Annette Wacker-Gussmann

doi:10.1515/jpm-2013-0031

Article

Development and application of an automated extraction algorithm for fetal magnetocardiography – normal data and arrhythmia detection

Krunoslav Stingl , Henrike Paulsen , Magdalene Weiss , Hubert Preissl , Harald Abele , Rangmar Goelz and Annette Wacker-Gussmann

Published/Copyright: July 4, 2013

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From the journal Journal of Perinatal Medicine Volume 41 Issue 6

Abstract

Introduction: Current standard methods of monitoring fetal heart function are mainly based on echocardiography, which provides indirect information (through mechanical assessment) of the fetal heart rhythm. Fetal magnetocardiography (fMCG) allows a reliable quantification of the temporal structure of fetal heart signals. However, its application in clinical studies is difficult because extracting the fetal heart signal for most current applications requires user intervention. To overcome this limitation, we developed a completely automated extraction algorithm.

Patients and methods: The fMCG recordings were acquired using a 156-channel biomagnetic system. To perform an automated analysis, a combination of orthogonal projection and independent component analysis was used. fMCG recordings from 69 healthy uncomplicated singleton pregnancies with normally developing fetuses were included in the study.

Results: The normal values achieved by the automated algorithm were comparable to previously published data. The majority of the cardiac time intervals were positively correlated with gestational age (GA). The ST segment, T wave and QT interval did not show any correlation.

Conclusions: The automated detection of fetal heart signals was possible beginning at a GA of 19 weeks. This automated analysis of fMCG recordings might be an objective and easily applicable approach for clinicians to analyze fetal heart signals.

Keywords: Cardiac time interval; congenital heart block; fetal magnetocardiography; independent component analysis; orthogonal projection

Corresponding author: Dr. Krunoslav Stingl, fMEG Center, Otfried-Müller-Str. 47, D-72076 Tübingen, Germany, Tel.: +49 70712987658, Fax: +49 7071 294573, E-mail: krunoslav.stingl@med.uni-tuebingen.de

This study was supported by the Deutsche Stiftung für Herzforschung (F02/2011), Friede- Springer HerzStiftung, Habilitandinnenförderung University of Tübingen (TÜFF Application 2156-0-0), Deutsche Forschungsgemeinschaft (BI 195-50), and the Landesstiftung Baden-Württemberg.

References

[1] Chen M, Wakai RT, Van Veen B. Eigenvector based spatial filtering of fetal biomagnetic signals. J Perinat Med. 2001;29:486–96.10.1515/JPM.2001.068Search in Google Scholar PubMed

[2] Comani S, Liberati M, Mantini D, Gabriele E, Brisinda D, Di Luzio S, et al. Characterization of fetal arrhythmias by means of fetal magnetocardiography in three cases of difficult ultrasonographic imaging. Pacing Clin Electrophysiol. 2004;27:1647–55.10.1111/j.1540-8159.2004.00699.xSearch in Google Scholar PubMed

[3] Comani S, Liberati M, Mantini D, Merlino B, Alleva G, Gabriele E, et al. Beat-to-beat estimate of fetal cardiac time intervals using magnetocardiography: longitudinal charts of normality ranges and individual trends. Acta Obstet Gynecol Scand. 2005;84:1175–80.10.1111/j.0001-6349.2005.00855.xSearch in Google Scholar PubMed

[4] Comani S, Mantini D, Alleva G, Di Luzio S, Romani GL. Fetal magnetocardiographic mapping using independent component analysis. Physiol Meas. 2004;25:1459–72.10.1088/0967-3334/25/6/011Search in Google Scholar PubMed

[5] Comani S, Van Leeuwen P, Lange S, Geue D, Gronemeyer D. Influence of gestational age on the effectiveness of spatial and temporal methods for the reconstruction of the fetal magnetocardiogram. Biomed Tech. 2009;54:29–37.10.1515/BMT.2009.005Search in Google Scholar PubMed

[6] Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004;134:9–21.10.1016/j.jneumeth.2003.10.009Search in Google Scholar PubMed

[7] Frank B, Pompe B, Schneider U, Hoyer D. Permutation entropy improves fetal behavioural state classification based on heart rate analysis from biomagnetic recordings in near term fetuses. Med Biol Eng Comput. 2006;44:179–87.10.1007/s11517-005-0015-zSearch in Google Scholar PubMed

[8] Govindan RB, Vairavan S, Ulusar UD, Wilson JD, McKelvey SS, Preissl H, et al. A novel approach to track fetal movement using multi-sensor magnetocardiographic recordings. Ann Biomed Eng. 2011;39:964–72.10.1007/s10439-010-0231-zSearch in Google Scholar PubMed PubMed Central

[9] Jung TP, Makeig S, McKeown MJ, Bell AJ, Lee TW, Sejnowski TJ. Imaging brain dynamics using independent component analysis. Proc IEEE. 2001;89:1107–22.10.1109/5.939827Search in Google Scholar PubMed PubMed Central

[10] Kiefer-Schmidt I, Lim M, Wacker-Gussmann A, Ortiz E, Abele H, Kagan KO, et al. Fetal magnetocardiography (fMCG): moving forward in the establishment of clinical reference data by advanced biomagnetic instrumentation and analysis. J Perinat Med. 2012;40:277–86.10.1515/jpm.2011.139Search in Google Scholar PubMed

[11] Lowery CL, Campbell JQ, Wilson JD, Murphy P, Preissl H, Malak SF, et al. Noninvasive antepartum recording of fetal S-T segment with a newly developed 151-channel magnetic sensor system. Am J Obstet Gynecol. 2003;188:1491–6; discussion 6–7.10.1067/mob.2003.367Search in Google Scholar PubMed

[12] Makeig S, Bell AJ, Jung TP, Sejnowski TJ. Independent component analysis of electroencephalographic data. Adv Neural Inf Process Sys. 1996;8:145–51.Search in Google Scholar

[13] McCubbin J, Robinson SE, Cropp R, Moiseev A, Vrba J, Murphy P, et al. Optimal reduction of MCG in fetal MEG recordings. IEEE Trans Biomed Eng. 2006;53:1720–4.10.1109/TBME.2006.876619Search in Google Scholar PubMed

[14] Schneider U, Haueisen J, Loeff M, Bondarenko N, Schleussner E. Prenatal diagnosis of a long QT syndrome by fetal magnetocardiography in an unshielded bedside environment. Prenat Diagn. 2005;25:704–8.10.1002/pd.1205Search in Google Scholar PubMed

[15] Sreeram N, Brockmeier K. Fetal magnetocardiography: the clinician’s viewpoint. Neurol Clin Neurophysiol. 2004; 64.Search in Google Scholar

[16] Stinstra J, Golbach E, van Leeuwen P, Lange S, Menendez T, Moshage W, et al. Multicentre study of fetal cardiac time intervals using magnetocardiography. Br J Obstet Gynaecol. 2002;109:1235–43.10.1046/j.1471-0528.2002.01057.xSearch in Google Scholar PubMed

[17] Stinstra JG, Peters MJ. The influence of fetoabdominal tissues on fetal ECGs and MCGs. Arch Physiol Biochem. 2002;110: 165–76.10.1076/apab.110.3.165.8293Search in Google Scholar PubMed

[18] Strasburger JF, Cheulkar B, Wakai RT. Magnetocardiography for fetal arrhythmias. Heart Rhythm. 2008;5:1073–6.10.1016/j.hrthm.2008.02.035Search in Google Scholar PubMed PubMed Central

[19] Strasburger JF, Wakai RT. Fetal cardiac arrhythmia detection and in utero therapy. Nature reviews Cardiology. 2010;7: 277–90.10.1038/nrcardio.2010.32Search in Google Scholar PubMed PubMed Central

[20] Taylor MJ, Smith MJ, Thomas M, Green AR, Cheng F, Oseku-Afful S, et al. Non-invasive fetal electrocardiography in singleton and multiple pregnancies. Br J Obstet Gynaecol. 2003;110:668–78.10.1046/j.1471-0528.2003.02005.xSearch in Google Scholar

[21] Ulusar UD, Govindan RB, Wilson JD, Lowery CL, Preissl H, Eswaran H. Adaptive rule based fetal QRS complex detection using Hilbert transform. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:4666–9.10.1109/IEMBS.2009.5334180Search in Google Scholar PubMed PubMed Central

[22] Van Leeuwen P, Lange S, Klein A, Geue D, Gronemeyer DH. Dependency of magnetocardiographically determined fetal cardiac time intervals on gestational age, gender and postnatal biometrics in healthy pregnancies. BMC Preg Childbirth. 2004;4:6.10.1186/1471-2393-4-6Search in Google Scholar PubMed PubMed Central

[23] Vrba J, Robinson SE, McCubbin J, Murphy P, Eswaran H, Wilson JD, et al. Human fetal brain imaging by magnetoencephalography: verification of fetal brain signals by comparison with fetal brain models. NeuroImage. 2004;21:1009–20.10.1016/j.neuroimage.2003.10.022Search in Google Scholar PubMed

[24] Waldert S, Bensch M, Bogdan M, Rosenstiel W, Scholkopf B, Lowery CL, et al. Real-time fetal heart monitoring in biomagnetic measurements using adaptive real-time ICA. IEEE Trans Biomed Eng. 2007;54:1867–74.10.1109/TBME.2007.895749Search in Google Scholar PubMed

[25] Wilson JD, Govindan RB, Hatton JO, Lowery CL, Preissl H. Integrated approach for fetal QRS detection. IEEE Trans Biomed Eng. 2008;55:2190–7.10.1109/TBME.2008.923916Search in Google Scholar PubMed PubMed Central

The authors stated that there are no conflicts of interest regarding the publication of this article.

Received: 2013-2-6

Accepted: 2013-5-27

Published Online: 2013-07-04

Published in Print: 2013-11-01

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Articles in the same Issue

https://doi.org/10.1515/jpm-2013-0031

Keywords for this article

Cardiac time interval; congenital heart block; fetal magnetocardiography; independent component analysis; orthogonal projection