Dense Array Image compatible EEG for enhanced neonatal care

新生儿脑病是一种中枢神经系统疾病，常伴有癫痫发作。 癫痫发作是癫痫、缺氧、异常分娩、睡眠的独特临床表现之一。 剥夺和压力。磁共振成像(MRI)在诊断和鉴别诊断中起着至关重要的作用。 对新生儿癫痫的认识。然而，新生儿MRI评估在评估整个 新生儿的神经状态，尤其是在皮质功能方面。在这种情况下，连续 视频EEG可以是有用的，因为它提供了关于频率、同步 大脑皮层活动的分布等特点。脑电也是一种关键的检测手段。 从儿童早期就了解发育障碍。最先进的脑电或密集阵列脑电 (HD-EEG-或更多通道)使EEG作为神经成像工具的潜力得以实现 通过对正常和病理脑活动的来源定位和网络动力学。然而，无论是 传统的EEG或HD-EEG都不兼容成像(MRI或CT)；因此，EEG电极通常 在任何成像检查之前删除，由于额外的延迟而对患者管理产生负面影响 以及额外的费用。 该R01项目的目标是演示开发与成像兼容的 HD-EEG网络用于无伪影图像质量的跨模式新生儿神经监测。建议数 新生儿HD-EEG网络或“NeoNet”将利用创新3D打印方面的专业知识进行设计 马萨诸塞州总医院A.A.马蒂诺斯中心的技术和薄膜沉积。严谨 比吸收沉积速率和温度的安全评估将使用有限的 用解剖准确的男性和女性2周大的新生儿进行有限元模拟 全身模型，将向公众发布。模拟将通过实际温度进行验证 使用穿戴NeoNet的新生儿模体测量诱导射频加热，并与 单独使用幻影的黄金标准，以及使用传统铜缆构建的与MR兼容的商用网络 电线技术。类似地，磁共振成像数据质量将与幻影单独黄金标准的数据进行比较， 并与商用HD-EEG的数据进行对比。还将评估CT数据的完整性。 建议的NeoNet将实现廉价、非侵入性的HD-EEG，并克服目前的跨模式安全 和伪影问题，到目前为止严重限制了同步HD-EEG/MRI的有效性，允许 研究人员和临床医生将受益于MRI的高空间分辨率和高时间分辨率 HD-EEG。此外，该技术将重量轻，体积小，利用先进的 制造技术。新的NeoNet将允许研究健康新生儿的脑功能 自然环境，以及对不同新生儿神经病理的了解，如癫痫。

Neonatal encephalopathies are central nervous system disorders that are often accompanied by seizures. Seizures are one of the distinctive clinical manifestations of epilepsy, hypoxia, abnormal delivery, sleep deprivation and stress. Magnetic Resonance Imaging (MRI) plays a crucial role in the diagnosis and understanding of neonatal seizures. However, neonatal MRI evaluation is incomplete in assessing the entire neonate’s neurologic status, especially in regards to cortical functioning. In such circumstances, continuous video EEG can be useful as it provides important information about changes in frequency, synchrony, distribution and other characteristics of cerebral cortical activity. EEG is also a key modality in the understanding of developmental disabilities from early childhood. State-of-the-art EEG or dense array EEG (HD-EEG – 64 or more channels) has enabled the realization of EEG’s potential as a neuroimaging tool through source localization of normal and pathological brain activity and network dynamics. However, neither conventional EEG nor HD-EEG are imaging (MRI or CT) compatible; hence, EEG electrodes are typically removed prior to any imaging study, with negative impacts on patient management because of extra delays and additional costs. The goal of this R01 project is to demonstrate the feasibility and safety of developing an imaging-compatible HD-EEG net for cross-modal neonatal neural monitoring with artifact-free image quality. The proposed neonatal HD-EEG net or “NeoNet” will be designed by leveraging expertise in innovative 3D printing technology and thin film deposition at the A. A. Martinos Center, Massachusetts General Hospital. Rigorous safety assessment of specific absorption deposition rate and temperature will be performed using Finite Elements Method (FEM) simulations employing anatomically accurate male and female 2-week-old neonatal whole body models, which will be released to the public. Simulations will be validated by actual temperature measurements of induced RF heating using neonate phantoms wearing the NeoNet and compared against the gold standard of the phantom alone and against a commercial MR-compatible net built with traditional copper wire technology. Similarly, MRI data quality will be compared to data from the phantom-alone gold standard, and against data from the commercial HD-EEG. CT data integrity will also be evaluated. The proposed NeoNet will enable inexpensive, noninvasive HD-EEG and overcome current cross-modal safety and artifact issues that have so far severely limited the effectiveness of simultaneous HD-EEG/MRI allowing researchers and clinicians to benefit from the high spatial resolution of MRI and the high temporal resolution of HD-EEG. Furthermore, the technology will be light weight and small in size, taking advantage of advanced manufacturing technologies. The novel NeoNet will allow the study of brain function in healthy neonates in natural settings, as well as the understanding of different neonatal neural pathologies, such as epilepsy.