School of Computer Science, University of Birmingham, Birmingham, UK.
J Biophotonics. 2019 Oct;12(10):e201900064. doi: 10.1002/jbio.201900064. Epub 2019 Jun 23.
Functional Near-Infrared Spectroscopy (fNIRS) aims to recover changes in tissue optical parameters relating to tissue hemodynamics, to infer functional information in biological tissue. A widely-used application of fNIRS relies on continuous wave (CW) methodology that utilizes multiple distance measurements on human head for study of brain health. The typical method used is spatially resolved spectroscopy (SRS), which is shown to recover tissue oxygenation index (TOI) based on gradient of light intensity measured between two detectors. However, this methodology does not account for tissue scattering which is often assumed. A new parameter recovery algorithm is developed, which directly recovers both the scattering parameter and scaled chromophore concentrations and hence TOI from the measured gradient of light-attenuation at multiple wavelengths. It is shown through simulations that in comparison to conventional SRS which estimates cerebral TOI values with an error of ±12.3%, the proposed method provides more accurate estimate of TOI exhibiting an error of ±5.7% without any prior assumptions of tissue scatter, and can be easily implemented within CW fNIRS systems. Using an arm-cuff experiment, the obtained TOI using the proposed method is shown to provide a higher and more realistic value as compared to utilizing any prior assumptions of tissue scatter.
功能近红外光谱（fNIRS）旨在恢复与组织血液动力学相关的组织光学参数变化，以推断生物组织中的功能信息。fNIRS 的一种广泛应用依赖于连续波（CW）方法，该方法利用人类头部的多个距离测量来研究大脑健康。常用的方法是空间分辨光谱（SRS），它基于在两个探测器之间测量的光强梯度来恢复组织氧合指数（TOI）。然而，这种方法没有考虑到通常假设的组织散射。开发了一种新的参数恢复算法，该算法可以直接从多个波长的光衰减梯度测量值中恢复散射参数和缩放的色团浓度，从而恢复 TOI。通过模拟表明，与传统的 SRS 相比，后者估计大脑 TOI 值的误差为±12.3%，该方法提供了更准确的 TOI 估计值，误差为±5.7%，而无需对组织散射进行任何先验假设，并且可以在 CW fNIRS 系统中轻松实现。通过手臂袖带实验，与使用任何组织散射的先验假设相比，所提出的方法获得的 TOI 提供了更高和更现实的值。
