Quantitative Diffuse Correlation Spectroscopy for Assessing Human Brain Function

用于评估人脑功能的定量漫相关光谱

• 批准号: 10265818
• 负责人: Ulas Sunar
• 金额: $ 33.54万
• 依托单位: WRIGHT STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-05 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10265818
• 关键词: Acute Brain Injuries; Address; Adult; Beds; Biological Markers; Blood flow; Brain; Brain Injuries; Brain region; Caring; Cerebrovascular Circulation; Cerebrum; Child; Clinic; Clinical; Custom; Dependence; Diffuse; Diffusion; Evaluation; FDA approved; Fourier Transform; Frequencies; Goals; Gold; Head; Hemorrhage; Human; Intervention; Ischemia; Lasers; Lead; Length; Measurement; Measures; Methods; Modeling; Monitor; Monte Carlo Method; Near-Infrared Spectroscopy; Noise; Optics; Outcome; Oxygen; Patients; Penetration; Performance; Photons; Physiologic pulse; Population; Premature Infant; Prognosis; Protocols documentation; Scalp structure; Secondary to; Signal Transduction; Skin; Source; Spectrum Analysis; Survivors; System; TBI Patients; Techniques; Technology; Testing; Time; Tissues; Translating; Traumatic Brain Injury; Width; base; brain tissue; clinical translation; clinically relevant; cost; cranium; data acquisition; deep learning; detector; digital; experimental study; heterodyning; imaging biomarker; imaging system; improved; innovation; instrument; instrumentation; neonate; neuroimaging; new technology; novel; novel strategies; optical imaging; phantom model; photon-counting detector; programs; prototype; response; simulation; time use; tool

PROJECT SUMMARY/ABSTRACT Acute brain injuries can lead to secondary brain damage that worsens the outcome. Reduced cerebral blood flow can induce ischemia, while excess blood flow can cause hemorrhage. Thus, there is a need for noninvasive, bedside, continuous cerebral blood flow monitoring approaches at neurointensive care units (NICUs). Existing technologies for continuous monitoring of cerebral blood flow have critical limitations. Functional near-infrared spectroscopy has been employed for this clinical need, but it suffers from being not quantitative and prone to errors due to signals from superficial scalp tissue. Moreover, it measures only limited information content of oxygen saturation. Additional blood flow contrast can provide a useful biomarker. Diffuse correlation spectroscopy (DCS) technique is an emerging diffuse optical technique for bedside monitoring of blood flow in humans. Currently, DCS operates in continuous-wave (CW) mode, which has limitations such as superficial signal sensitivity and inaccurate quantification of blood flow due to dependency to priori information of optical parameters. More recent time domain (TD) approach has low signal-to-noise ratio, costly, highly limited for clinical translation. The goal is to address these limitations by proposing a novel technology and method that can quantify both absolute static and dynamic parameters concurrently in a single instrument with fast data acquisition, thus, it is highly suitable for fast functional neuroimaging. It can also separate superficial and brain signals by discriminating early and late photons via time-gating. Additionally, longer wavelength at the infrared allows for enhanced depth penetration. It can quantify blood flow and optical parameters in near- real-time using deep learning, which is highly suitable for NICU settings. The proposed system and method will completely replace the current state-of-the-art (CW-DCS) and is superior TD approach, because it can provide higher signal-to-noise ratio (SNR) in the brain, its simplicity and significantly lower cost in instrumentation, which will lead to fast clinical translation. To achieve our goal, we will construct and optimize the instrument prototype, characterize the signal, and then we will test the system on phantom models and custom-developed analytical and Monte Carlo and deep learning models and determine the quantification accuracy with respect to static and dynamic parameters (Aim-1). We will optimize the system with respect to pulse-width, SNR for improved quantification accuracy of static and dynamic parameters (Aim-2). Then, we will test the system in healthy subjects and traumatic brain injury patients (Aim-3). This innovative DCS system and method will result in quantitative blood flow parameter with enhanced brain sensitivity and will eliminate the roadblocks in both CW and TD approaches, thereby will pave the way for fast clinical translation at NICU settings and for general neuroimaging applications.

项目摘要/摘要 急性脑损伤会导致次要脑损伤，从而恶化结果。脑血减少 流量会诱发缺血，而多余的血流会导致出血。因此，需要 神经性护理单元的无创，床边，连续的脑血流监测方法 （NICUS）。连续监测脑血流的现有技术具有关键的局限性。 已针对这种临床需求采用了功能性的近红外光谱法，但它没有遭受 由于表面头皮组织的信号，定量和容易出现错误。而且，它仅测量有限 氧饱和的信息含量。额外的血流对比可以提供有用的生物标志物。扩散 相关光谱（DCS）技术是一种新兴的弥漫性光学技术，用于床边监测 人类的血流。目前，DCS以连续波（CW）模式运行，该模式具有限制 浅表信号灵敏度和由于对先验信息的依赖而对血流的定量不准确 光学参数。最近的时域（TD）方法的信噪比较低，昂贵，高度高 有限的临床翻译。目的是通过提出一种新技术和 可以在单个仪器中同时量化绝对静态和动态参数的方法 因此，快速数据采集非常适合快速功能性神经影像学。它也可以分开浅表 和大脑信号通过时间门控通过早期和晚期光子进行区分。此外，在较长的波长处 红外线允许增强深度穿透。它可以量化接近 - 的血流和光学参数 实时使用深度学习，非常适合NICU设置。提出的系统和方法将 完全替换当前的最新（CW-DC），并且是出色的TD方法，因为它可以提供 大脑中较高的信噪比（SNR），其简单性和仪器成本明显降低， 这将导致快速的临床翻译。为了实现我们的目标，我们将构建和优化工具 原型，表征信号，然后我们将在幻影模型上测试系统和自定义开发 分析和蒙特卡洛以及深度学习模型，并确定尊重的量化精度 静态和动态参数（AIM-1）。我们将针对脉搏宽度优化系统，SNR 提高静态和动态参数的定量精度（AIM-2）。然后，我们将测试系统 健康受试者和脑外伤患者（AIM-3）。这种创新的DCS系统和方法将 导致定量血流参数具有增强的大脑灵敏度，并将消除障碍 CW和TD方法都将为NICU设置和为快速临床翻译铺平道路 一般神经影像应用。