TRD2: Interferometric Near Infrared Spectroscopy (iNIRS)

项目总结-技术研究和开发项目#2 漫反射光谱学(DOS)领域长期以来一直被认为是无创的、深层组织监测的希望所在 使用良性的近红外光。然而，临床DOS器械受到了有限的量化的挑战 血红蛋白氧合测量的准确性、缺乏深度特异性和固有的模糊性。这些 现有技术只是部分地、不充分地解决了挑战。我们加州大学的团队 戴维斯最近发明了干涉漫反射光谱学(IDOS)，它克服了其中的许多缺点 关键的路障。在这项技术研究中，我们将推进和推广两项相辅相成的iDOS技术： 1)干涉漫反射波谱(IDWS)使用低成本的互补金属氧化物- 半导体(CMOS)传感器创造了一种新的近红外光学设备，可以测量深度 血流(BF)指标连续、无创。利用干涉测量的光学“技巧”， IDWS将每个cmos像素转换为对相干光波动敏感的探测器，该探测器编码 深厚的高炉动力。由于cmos摄像头像素便宜且数量众多，iDWS改进了 并降低了光学高炉测量的成本。在这里，我们将开发和验证 变革性的多次曝光iDWS方法，可实现脑和其他深层组织的测量 在拥有大规模生产的2D百万像素传感器的成年人身上。而干涉测量方法是 已建立的多重曝光方法是新的和高影响的，使进一步的两个顺序- 与iDWS相比，性价比大幅提升。这些进展将使访问变得民主化 到大脑BF(CBF)，导致1)更好的脑机接口2)CBF的护理点评估， 3)可穿戴式脑血流监测仪，类似于血压和心率监测仪。 2)干涉近红外光谱(INIRS)通过以下方式增强了iDOS的定量能力 激光调谐。关键的是，iNIRS以几十皮秒的分辨率测量光的飞行时间(TOF)， 使得能够直接量化光学属性。此外，通过测量相干光波动， INIRS将血流指数量化，并具有额外的深度动力学解析能力(例如，头皮-头骨-头皮-头骨-头皮-头盖骨-头皮-头骨-头皮-头盖骨-头皮-头皮-头盖骨-头皮-头皮-头骨- 大脑)。在这一方案中，除了使用iNIR作为常规连续波的定量补充外， 方法，我们将进一步提高iNIRS的飞行时间分辨率一个数量级，而 实现光谱(多波长)能力。我们还将提供亚漫反射检测 零光源-收集器分离的光，实现了iNIR和光纤介观的集成 方法如iFLIM(TRD1)和光学相干层析成像(OCT)。 选择协作和服务项目来代表从显微手术到非侵入性的各种环境 监测，以及从临床神经监测到外科技能评估到人群筛查的应用。 这些多样化的合作将有助于评估和展示iDOS方法的独特能力。

PROJECT SUMMARY – Technology Research and Development Project #2 The field of diffuse optical spectroscopy (DOS) has long held the promise of non-invasive, deep tissue monitoring with benign, near-infrared light. Yet clinical DOS instrumentation has been challenged by limited quantitative accuracy, lack of depth specificity, and the inherent ambiguity of hemoglobin oxygenation measures. These challenges have been only partially, and inadequately, addressed by existing technologies. Our team at UC Davis recently invented interferometric diffuse optical spectroscopy (iDOS), which overcomes many of these critical roadblocks. In this TRD, we will advance and disseminate two complementary iDOS technologies: 1) Interferometric Diffusing Wave Spectroscopy (iDWS) uses low-cost complementary metal–oxide– semiconductor (CMOS) sensors to create a new class of near-infrared optical devices that measure deep blood flow (BF) index continuously and non-invasively. Employing the optical “trick” of interferometry, iDWS transforms each CMOS pixel into a sensitive detector for coherent light fluctuations that encode deep BF dynamics. Since CMOS camera pixels are cheap and numerous, iDWS improves the performance and reduces the cost of optical BF measurements. Here, we will develop and validate a transformative, multi-exposure iDWS approach, to enable brain and other deep tissue measurements in adult humans with mass-produced, 2D megapixel sensors. While the interferometric approach is established, the multi-exposure approach is new and high impact, enabling a further two order-of- magnitude improvement in performance-to-cost over iDWS. These advances will democratize access to cerebral BF (CBF), leading to 1) better brain-computer interfaces 2) point-of-care assessments of CBF, and 3) wearable CBF monitors, analogous to blood pressure and heart rate monitors. 2) Interferometric Near-Infrared Spectroscopy (iNIRS) enhances quantitative capabilities of iDOS through laser tuning. Critically, iNIRS measures the time-of-flight (TOF) of light with tens of picosecond resolution, enabling direct quantification of optical properties. Additionally, by measuring coherent light fluctuations, iNIRS quantifies blood flow index, with the additional ability to resolve dynamics in depth (e.g. scalp-skull- brain). In this proposal, besides using iNIRS as a quantitative adjunct to conventional continuous wave methods, we will further improve the TOF resolution of iNIRS by an order of magnitude, while achieving spectroscopic (multi-wavelength) capabilities. We will also provide detection of sub-diffuse light at null source-collector separation, enabling integration of iNIRS and fiber-based mesoscopic approaches such as iFLIM (TRD 1) and Optical Coherence Tomography (OCT). Collaborative and service projects are selected to represent settings ranging from microsurgery to non-invasive monitoring, and applications from clinical neuro-monitoring to surgical skill assessment to population screening. These diverse collaborations will help to evaluate and demonstrate the unique capabilities of the iDOS approach.