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光程长度选择性干涉式扩散相关光谱学

Pathlength-selective, interferometric diffuse correlation spectroscopy.

作者信息

Robinson Mitchell B, Renna Marco, Otic Nikola, Kierul Olivia S, Muldoon Ailis, Franceschini Maria Angela, Carp Stefan A

机构信息

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Neurophotonics Center, Boston University, Boston, Massachusetts, USA.

出版信息

bioRxiv. 2025 Mar 4:2024.06.21.600096. doi: 10.1101/2024.06.21.600096.

Abstract

Diffuse correlation spectroscopy (DCS) is an optical method that offers non-invasive assessment of blood flow in tissue through the analysis of intensity fluctuations in diffusely backscattered coherent light. The non-invasive nature of DCS has enabled several clinical application areas for deep tissue blood flow measurements, including neuromonitoring, cancer imaging, and exercise physiology. While promising, in measurement configurations targeting deep tissue hemodynamics, standard DCS implementations suffer from insufficient signal-to-noise ratio (SNR), depth sensitivity, and sampling rate, limiting their utility. In this work, we present an enhanced DCS method called pathlength-selective, interferometric DCS (PaLS-iDCS), which uses pathlength-specific coherent gain to improve both the sensitivity to deep tissue hemodynamics and measurement SNR. Through interferometric detection, PaLS-iDCS can provide time-of-flight (ToF) specific blood flow information without the use of expensive time-tagging electronics and low-jitter detectors. The technique is compared to time-domain DCS (TD-DCS), another enhanced DCS method able to resolve photon ToF in tissue, through Monte Carlo simulation, phantom experiments, and human subject measurements. PaLS-iDCS consistently demonstrates improvements in SNR (>2x) for similar measurement conditions (same photon ToF), and the SNR improvements allow for measurements at extended photon ToFs, which have increased sensitivity to deep tissue hemodynamics (~50% increase). Further, like TD-DCS, PaLS-iDCS allows direct estimation of tissue optical properties from the sampled ToF distribution. This method offers a relatively straightforward way to allow DCS systems to make robust measurements of blood flow with greatly enhanced sensitivity to deep tissue hemodynamics without the need for time-resolved detection, enabling further applications of this non-invasive technology.

摘要

扩散相关光谱法(DCS)是一种光学方法,通过分析漫反射相干光的强度波动来对组织中的血流进行非侵入性评估。DCS的非侵入性特性使其在多个临床应用领域可用于深部组织血流测量,包括神经监测、癌症成像和运动生理学。尽管前景广阔,但在针对深部组织血流动力学的测量配置中,标准的DCS实现方式存在信噪比(SNR)不足、深度敏感性和采样率问题,限制了其效用。在这项工作中,我们提出了一种增强的DCS方法,称为路径长度选择性干涉式DCS(PaLS-iDCS),它利用特定路径长度的相干增益来提高对深部组织血流动力学的敏感性和测量SNR。通过干涉检测,PaLS-iDCS无需使用昂贵的时间标记电子设备和低抖动探测器就能提供飞行时间(ToF)特定的血流信息。通过蒙特卡罗模拟、体模实验和人体测量,将该技术与时域DCS(TD-DCS)进行了比较,TD-DCS是另一种能够解析组织中光子ToF的增强型DCS方法。在相似的测量条件下(相同的光子ToF),PaLS-iDCS始终能实现SNR的提升(>2倍),而SNR的提升使得在更长的光子ToF下进行测量成为可能,这对深部组织血流动力学的敏感性有所提高(增加约50%)。此外,与TD-DCS一样,PaLS-iDCS允许从采样的ToF分布直接估计组织光学特性。这种方法提供了一种相对简单的方式,使DCS系统能够以对深部组织血流动力学大大增强的敏感性进行可靠的血流测量,而无需时间分辨检测,从而推动了这种非侵入性技术的进一步应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35d0/11887777/d6ea6f921b76/nihpp-2024.06.21.600096v2-f0001.jpg

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