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(申请人提供)：在阿肯色州医科大学，我们安装了世界上第一个专门为胎儿和新生儿评估而设计和改进的脑磁图(MEG)系统。这个名为SARA(Squid阵列生殖评估)的非侵入性系统由151个主要的超导传感器组成，这些传感器探测人体的生物磁场。自安装SARA以来，朝着为发育中的胎儿开发临床神经学评估工具的最终目标取得了重大进展。自上一个资金周期以来，我们已经证明，在足够的信噪比下，可以从生物磁记录中提取胎儿自发脑信号。此外，我们还展示了它在追踪生长受限胎儿的神经活动方面的适用性。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，以处理在长持续时间数据集中遇到的自发胎儿脑磁图数据的非平稳方面。非平稳性主要由母体运动和胎儿运动引起。基于空间滤波的波束形成器方法在上一个供资周期中进行了测试和实施，在相对稳定的短片段中产生了良好的效果。波束形成器方法需要精确的头部模型，在非平稳段中的性能不是最优的。为了推动这一技术的发展，我们提出了两种新的方法，它们不依赖于可靠的头部模型，并且可以处理长持续时间数据集的非平稳性问题。我们还想开发临床相关的指标。 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危亚群，如慢性和妊娠高血压母亲。将这一群体纳入我们的研究可能会进一步强调自发的胎儿脑磁图记录的潜在临床价值，特别是在怀孕34周之前，当分娩决定需要根据早产的长期影响进行优化时。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自发的胎儿脑磁图活动的检测。-将胎儿脑磁图与其他干扰源分离。目的：建立临床相关的自发性胎儿脑磁图定量指标，可跨胎龄监测胎儿神经发育。(A)检测在胎儿脑磁图中观察到的明显的不连续脑模式。(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)胎儿脑磁图与胎儿状态的相关性--安静而活跃的睡眠；安静而活跃的清醒。目的：评价低风险妊娠胎儿自发脑活动信号中不连续百分率、猝发持续时间和猝发间期等成熟指标的个体发生，并与慢性和妊娠高血压综合征高危妊娠进行比较。

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