At University of Arkansas for Medical Sciences (UAMS) we have installed the world's first non-invasive biomagnetic sensing system that was specifically modified and designed to study various aspects of maternal-fetal health. This system can record the magnetic field corresponding to the electrical activity of uterine contraction and provide requisite spatial-temporal information. Our preliminary studies show that by recording uterine magnetomyographic (MMG) signals we can localize the area of activation over the uterus during a contraction. This allows us to explore the origin and propagation of uterine contraction despite the shifting of the pacemaker site from one contraction to another. We can localize the pacemaker by mapping the magnetic field distribution and quantify the spread by obtaining the percent of sensors active during each contraction with sensors spread over the entire maternal abdomen. To take advantage of the spatial-temporal resolution obtained by this instrument, we need to further enhance computational and analysis tools to develop it as a clinical device to predict the onset of labor both in the case of term and preterm patients. In this proposal our goal is to develop techniques to improve extraction, recognition and validation process of uterine magnetomyographic activity. By accomplishing this goal we can work towards achieving a comprehensive instrumentation and protocol that would aid in prediction of onset of labor. This ability would be of great clinical benefit for the management of the term patient and especially for the management of patients at high risk for premature delivery. We would like to advance the present state of development by first improving data collection and reliability of signal extraction. Then we want to develop techniques for verifying consistency of the signal so that data interpretation can proceed. The overall goals of the project include: (1) EXTRACTION and DETECTION: Improve methods for extraction and development of efficient separation algorithms for the spatial-temporal uterine MMG signals. (2) QUANTIFICATION: We propose to quantify the spatial and temporal parameters that could be would aid in prediction of the onset of labor. (3) CHARECTERIZATION: As a further step we plan to characterize the regions of activation, propagation velocity and direction, and the spread of activity as a function of distance.(4) MODELING: Develop a simple bidomain model and explore its relationship to MMG recordings. Relevance: An objective technique to predict the onset of labor in term and preterm patients would be of great clinical benefit to aid in management of pregnancies. Information gained can result in methods focusing on specific applications to prevent or control preterm labor thereby reducing the incidence of preterm birth. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB007264-01A2
Application #
7389099
Study Section
Special Emphasis Panel (ZRG1-SBIB-U (92))
Program Officer
Peng, Grace
Project Start
2007-09-01
Project End
2010-06-30
Budget Start
2007-09-01
Budget End
2008-06-30
Support Year
1
Fiscal Year
2007
Total Cost
$296,246
Indirect Cost
Name
University of Arkansas for Medical Sciences
Department
Obstetrics & Gynecology
Type
Schools of Medicine
DUNS #
122452563
City
Little Rock
State
AR
Country
United States
Zip Code
72205
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Govindan, Rathinaswamy B; Siegel, Eric; Mckelvey, Samantha et al. (2015) Tracking the changes in synchrony of the electrophysiological activity as the uterus approaches labor using magnetomyographic technique. Reprod Sci 22:595-601
Furdea, Adrian; Preissl, Hubert; Lowery, Curtis L et al. (2011) Conduction velocity of the uterine contraction in serial magnetomyogram (MMG) data: event based simulation and validation. Conf Proc IEEE Eng Med Biol Soc 2011:6025-8
Govindan, Rathinaswamy B; Vairavan, Srinivasan; Furdea, Adrian et al. (2010) Decrement of uterine myometrial burst duration as a correlate to active labor: a Hilbert phase approach. Conf Proc IEEE Eng Med Biol Soc 2010:4618-21
Govindan, Rathinaswamy B; Vairavan, Srinivasan; Haddad, Naim et al. (2009) Localizing the neonatal and fetal spontaneous brain activity by Hilbert phase analysis. Conf Proc IEEE Eng Med Biol Soc 2009:6616-9
Eswaran, Hari; Govindan, Rathinaswamy B; Furdea, Adrian et al. (2009) Extraction, quantification and characterization of uterine magnetomyographic activity--a proof of concept case study. Eur J Obstet Gynecol Reprod Biol 144 Suppl 1:S96-100
Furdea, A; Eswaran, H; Wilson, J D et al. (2009) Magnetomyographic recording and identification of uterine contractions using Hilbert-wavelet transforms. Physiol Meas 30:1051-60