Interdisciplinary Center for Life Sciences, South-Westphalia University of Applied Sciences, Frauenstuhlweg 31, 58644 Iserlohn, Germany.
CLAAS Selbstfahrende Erntemaschinen, Muehlenwinkel 1, 33428 Harsewinkel, Germany.
Biosensors (Basel). 2021 Feb 27;11(3):64. doi: 10.3390/bios11030064.
For many years, successful noninvasive blood glucose monitoring assays have been announced, among which near-infrared (NIR) spectroscopy of skin is a promising analytical method. Owing to the tiny absorption bands of the glucose buried among a dominating variable spectral background, multivariate calibration is required to achieve applicability for blood glucose self-monitoring. The most useful spectral range with important analyte fingerprint signatures is the NIR spectral interval containing combination and overtone vibration band regions. A strategy called science-based calibration (SBC) has been developed that relies on a priori information of the glucose signal ("response spectrum") and the spectral noise, i.e., estimates of the variance of a sample population with negligible glucose dynamics. For the SBC method using transcutaneous reflection skin spectra, the response spectrum requires scaling due to the wavelength-dependent photon penetration depth, as obtained by Monte Carlo simulations of photon migration based on estimates of optical tissue constants. Results for tissue glucose concentrations are presented using lip NIR-spectra of a type-1 diabetic subject recorded under modified oral glucose tolerance test (OGTT) conditions. The results from the SBC method are extremely promising, as statistical calibrations show limitations under the conditions of ill-posed equation systems as experienced for tissue measurements. The temporal profile differences between the glucose concentration in blood and skin tissue were discussed in detail but needed to be further evaluated.
多年来,已经宣布了许多成功的非侵入式血糖监测检测方法,其中近红外(NIR)皮肤光谱是一种很有前途的分析方法。由于葡萄糖的微小吸收带埋藏在主导的可变光谱背景中,因此需要进行多元校准才能实现用于血糖自我监测的适用性。最有用的光谱范围具有重要的分析物指纹特征,是包含组合和泛频振动带区域的近红外光谱间隔。已经开发了一种称为基于科学的校准(SBC)的策略,该策略依赖于葡萄糖信号的先验信息(“响应光谱”)和光谱噪声,即对具有可忽略的葡萄糖动力学的样本群体的方差的估计。对于使用经皮反射皮肤光谱的 SBC 方法,由于基于光组织常数估计的光子迁移的蒙特卡罗模拟,响应光谱需要缩放,因为这与波长相关的光子穿透深度有关。使用在改良口服葡萄糖耐量测试(OGTT)条件下记录的 1 型糖尿病患者的嘴唇 NIR 光谱,给出了组织葡萄糖浓度的结果。SBC 方法的结果非常有希望,因为统计校准在经历组织测量的不适定方程组条件下显示出局限性。详细讨论了血液和皮肤组织中葡萄糖浓度之间的时间分布差异,但需要进一步评估。