At University of Arkansas for Medical Sciences we have installed the world's first magnetoencephalography (MEG) system specifically designed and modified for fetal and newborn assessment. The non-invasive system called SARA (Squid Array for Reproductive Assessment) consists of 151 primary superconducting sensors which detect biomagnetic fields from the body. Since the installation of SARA, significant progress has been made towards the ultimate goal of developing a clinical neurological assessment tool for the developing fetus. Our first goal was to perform evoked response measurements and develop processing algorithms to extract the response to external stimulus i.e. auditory and visual. After going through various iterations of processing algorithms, interference elimination by orthogonal projection was found to be robust and relatively easy to automate. This procedure has been successfully tested in a large number of fetal recordings and appears to be adequate to extract evoked responses to stimuli when detectable. However, the extraction and analysis of spontaneous brain activity has been more challenging since there is no stimulus locked response. The current method for evaluating and identifying fetal spontaneous MEG is based on visual examination of time traces for characteristic morphology based on neonatal EEC. Although we have shown the feasibility of recording spontaneous activity, we need to improve the detection of the fetal spontaneous brain patterns. This proposal has two specific aims, one is to improve fetal spontaneous MEG signal extraction by using advance spatial filter processing methods and the other is to apply this technology to assess the spontaneous brain activity in a specific group of fetuses who are at risk for developing neurological problems. We particularly want to investigate intrauterine growth restricted (IUGR) fetuses since their compromised intrauterine environment affects potential growth and brain development. The spontaneous brain activity characteristics of IUGR fetuses will be compared to the fetus with normal growth. The overall aims are listed below: 1. Enhance the detection of spontaneous fetal magnetoencephalographic signals using advanced signal processing methods. 2. Assess fetal spontaneous brain activity signals in intrauterine growth restricted fetuses since they are at potential risk for adverse neurodevelopmental outcomes. Relevance: Evaluation of fetal cerebral functions presents a very precious goal since we currently lack the means to directly monitor such functions.
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