Development of Analysis Tools to Enhance Fetal Neurological Assessment

开发分析工具以增强胎儿神经学评估

• 批准号: 8545845
• 负责人: Hari Eswaran
• 金额: $ 24.51万
• 依托单位: UNIV OF ARKANSAS FOR MED SCIS
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-06 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8545845
• 关键词: Abdomen; Arkansas; Auditory; Biological; Brain; Cerebrum; Chronic; Clinical; Data; Data Set; Detection; Development; Environment; Evaluation; Fetal Development; Fetal Heart; Fetal Movement; Fetus; Funding; Gestational Age; Goals; Growth; Head; Hypertension; Investigation; Knowledge; Lead; Location; Long-Term Effects; Magnetism; Magnetoencephalography; Maternal Physiology; Measurement; Medical; Modeling; Monitor; Mothers; Movement; Neurologic; Newborn Infant; Noise; Patients; Pattern; Performance; Pregnancy; Premature Birth; Records; Research Personnel; Risk; Science; Signal Transduction; Sleep; Smooth Muscle; Source; Squid; Subgroup; System; Techniques; Technology; Testing; Universities; Visual; acronyms; awake; base; clinically relevant; design; experience; fetal; gastrointestinal; high risk; improved; indexing; member; multidisciplinary; myometrium; non-invasive system; novel strategies; pregnant; public health relevance; reproductive; response; sensor; success; superconducting quantum interference device; tool

DESCRIPTION (provided by applicant): 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. Since the last funding cycle we have shown that the fetal spontaneous brain signals can be extracted from biomagnetic recordings with sufficient signal to noise ratio. Further we have shown its applicability in tracking the neurological activity of growth restricted fetuses. The success of these studies was largely dependent on the development of appropriate analysis tools. Based on our experience we believe the analysis strategy needs to be improved to deal with non-stationarity aspects of the spontaneous fetal MEG data that were encountered in long duration data sets. The non-stationarity was mainly caused by maternal and fetal movement. The spatial filter based beamformer approach was tested and implemented in the previous funding cycle and produced good results in short segments that are relatively stationary. The beamformer approach requires an accurate head model and its performance in the non-stationary segments was suboptimal. In order to advance this technology, we propose two novel approaches that are not dependent on a reliable head model and can deal with non-stationarity issues in long duration data sets. We also want to develop clinically relevant indices that can track the fetal neurological maturation. Further we plan to extend our studies to the other high-risk subgroups such as chronic and pregnancy-induced hypertensive mothers. The inclusion of this group in our studies could further emphasize the potential clinical value of spontaneous fetal MEG brain recordings, especially prior to 34 weeks of gestation, when the decision to deliver needs to be optimized based on the long-term effects of premature delivery. The specific aims of the project are: Aim 1: Develop analysis tools for improved detection of spontaneous fetal MEG activity in recordings with large non-stationarities. - Separating fetal MEG from other interfering sources. Aim2: Develop clinically relevant quantification indices for spontaneous fetal MEG that can be applied across the gestational age to monitor the neurological development of the fetus. (a) Detect the distinct discontinuous brain patterns observed in fetal MEG. (2) Calculate burst duration (BD) and interburst interval (IBI) observed in the detected discontinuous brain patterns. (3) Correlate fetal MEG with fetal states - quiet and active sleep; quiet and active awake. Aim 3: Assess the ontogeny of the maturation indices such as percent discontinuity, burst duration and interburst interval in fetal spontaneous brain activit signals of low-risk pregnancies and compare it to pregnancies classified as high-risk due to maternal hypertension both chronic and pregnancy-induced.

描述（由申请人提供）：在阿肯色州大学医学院，我们安装了世界上第一个专门为胎儿和新生儿评估设计和修改的脑磁图（MEG）系统。这个名为SARA（Squid Array for Reproductive Assessment）的非侵入性系统由151个主要的超导传感器组成，这些传感器可以检测来自身体的生物磁场。自SARA安装以来，在为发育中的胎儿开发临床神经评估工具的最终目标方面取得了重大进展。自上一个资助周期以来，我们已经表明，胎儿自发脑信号可以从生物磁记录中提取，具有足够的信噪比。此外，我们已经证明了其适用于跟踪生长受限胎儿的神经活动。这些研究的成功在很大程度上取决于开发适当的分析工具。根据我们的经验，我们认为分析策略需要改进，以处理在长时间数据集中遇到的自发胎儿MEG数据的非平稳性方面。非平稳性主要是由母胎运动引起的。基于空间滤波器的波束形成器方法在前一个供资周期中进行了测试和实施，并在相对稳定的短段中产生了良好的结果。波束形成器方法需要精确的头部模型，并且其在非平稳段中的性能是次优的。为了推进这项技术，我们提出了两种新的方法，不依赖于一个可靠的头部模型，可以处理非平稳性问题，在长时间的数据集。我们还希望开发临床相关指数 可以追踪胎儿的神经成熟度此外，我们计划将我们的研究扩展到其他高风险亚组，如慢性和妊娠高血压母亲。在我们的研究中纳入这一组可以进一步强调自发性胎儿脑MEG记录的潜在临床价值，特别是在妊娠34周之前，此时需要根据早产的长期影响优化分娩决策。该项目的具体目标是：目标1：开发分析工具，以改进对具有较大非平稳性的记录中的自发胎儿脑磁活动的检测。- 从其他干扰源中分离胎儿脑磁图。目标2：为自发性胎儿MEG开发临床相关的量化指标，可应用于整个胎龄，以监测胎儿的神经发育。(a)检测在胎儿脑磁图中观察到的不同的不连续脑模式。(2)计算在检测到的不连续脑模式中观察到的爆发持续时间（BD）和爆发间隔（IBI）。(3)将胎儿MEG与胎儿状态相关联-安静和活跃的睡眠;安静和活跃的清醒。目标3：评估低风险妊娠的胎儿自发脑活动信号中的成熟指标的个体发育，如百分比不连续性，爆发持续时间和爆发间隔，并将其与因慢性和妊娠诱发的母体高血压而被归类为高风险的妊娠进行比较。

项目成果

Verification of fetal brain responses by coregistration of fetal ultrasound and fetal magnetoencephalography data.

• DOI: 10.1016/j.neuroimage.2009.09.025
• 发表时间: 2010-01-15
• 期刊: NEUROIMAGE
• 影响因子: 5.7
• 作者: Micheli, C.;McCubbin, J.;Murphy, P.;Eswaran, H.;Lowery, C. L.;Ortiz, E.;Preissl, H.
• 通讯作者: Preissl, H.

Coupling Analysis of Fetal and Maternal Heart Rates via Transfer Entropy Using Magnetocardiography.

• DOI: 10.1109/embc.2018.8513053
• 发表时间: 2018-07
• 期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
• 作者: Avci R;Escalona-Vargas D;Siegel ER;Lowery CL;Eswaran H
• 通讯作者: Eswaran H

Selection of Reference Channels Based on Mutual Information for Frequency-Dependent Subtraction Method Applied to Fetal Biomagnetic Signals.

• DOI: 10.1109/tbme.2016.2591443
• 发表时间: 2017-05
• 期刊: IEEE transactions on bio-medical engineering
• 作者: Escalona-Vargas D;Siegel ER;Murphy P;Lowery CL;Eswaran H
• 通讯作者: Eswaran H

Studying the Effect of Maternal Pregestational Diabetes on Fetal Neurodevelopment Using Magnetoencephalography.

• DOI: 10.1177/1550059420909658
• 发表时间: 2020-09
• 期刊: Clinical EEG and neuroscience
• 影响因子: 2
• 作者: Avci R;Whittington JR;Blossom SJ;Escalona-Vargas D;Siegel ER;Preissl HT;Eswaran H
• 通讯作者: Eswaran H

Observations of fetal brain activity via non-invasive magnetoencephalography following administration of magnesium sulfate for neuroprotection in preterm labor.

在早产中使用硫酸镁进行神经保护后，通过无创脑磁图观察胎儿大脑活动。

• DOI: 10.1002/pd.4919
• 发表时间: 2016
• 期刊: Prenatal diagnosis
• 影响因子: 3
• 作者: Escalona-Vargas,DianaI;Thagard,AndrewS;McGrail,Kaitlin;Napolitano,PeterG;Magann,EverettF;Lowery,CurtisL;Eswaran,Hari
• 通讯作者: Eswaran,Hari