Connectivity Measures of Uterine Activity using Magnetomyography.

Area of Science:

• Biophysics
• Computational Neuroscience
• Medical Imaging

Background:

• Uterine activity monitoring is crucial for assessing labor progression.
• Magnetomyography (MMG) offers a noninvasive method to record uterine magnetic fields.
• Understanding uterine network dynamics can improve labor management.

Purpose of the Study:

• To investigate uterine activity interactions using graph-theoretical network analysis.
• To evaluate the evolution of uterine connectivity and centrality metrics over gestational age.
• To validate network analysis methods using simulated and real MMG data.

Main Methods:

• Applied graph analysis to multi-channel SQUID-based MMG data.
• Utilized binary graphs with thresholds (10-35%) to assess network topography.
• Analyzed simulated MMG data from a multiscale uterus model.
• Examined real MMG recordings from subjects at various gestational ages.

Main Results:

• Simulated uterine burst activity showed higher network metrics, indicating signal propagation.
• Local efficiency consistently exceeded global efficiency across thresholds.
• Real MMG data revealed increased global/local efficiency and clustering coefficient approaching labor.
• Betweenness centrality decreased as the patient neared active labor.

Conclusions:

• Graph-theoretical network analysis effectively characterizes uterine activity dynamics.
• Network metrics evolve predictably with approaching labor, reflecting physiological changes.
• This approach provides novel insights into the spatiotemporal organization of uterine contractions.