Department of Metrology and Optoelectronics, Faculty of Electronics, Telecommunications, and Informatics, Gdańsk University of Technology, G. Narutowicza 11/12, 80-233, Gdańsk, Poland.
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Biosens Bioelectron. 2021 May 15;180:113115. doi: 10.1016/j.bios.2021.113115. Epub 2021 Feb 26.
Non-invasive measurement methods offer great benefits in the field of medical diagnostics with molecular-specific techniques such as Raman spectroscopy which is increasingly being used for quantitative measurements of tissue biochemistry in vivo. However, some important challenges still remain for label-free optical spectroscopy to be incorporated into the clinical laboratory for routine testing. In particular, non-analyte-specific variations in tissue properties introduce significant variability of the spectra, thereby preventing reliable calibration. For measurements of blood analytes such as glucose, we propose to decrease the interference from individual tissue characteristics by exploiting the known dynamics of the blood-tissue matrix. We reason that by leveraging the natural blood pulse rhythm, the signals from the blood analytes can be enhanced while those from the static components can be effectively suppressed. Here, time-resolved measurements with subsequent pulse frequency estimation and phase-sensitive detection are proposed to recover the Raman spectra correlated with the dynamic changes at blood-pulse frequency. Pilot in vivo study results are presented to establish the benefits as well as outline the challenges of the proposed method in terms of instrumentation and signal processing.
非侵入式测量方法在医学诊断领域具有重要的应用价值，其中分子特异性技术如拉曼光谱学的应用越来越广泛，可用于对组织生物化学进行体内的定量测量。然而，对于无标记的光学光谱学技术而言，要将其纳入临床实验室进行常规检测，仍然存在一些重要的挑战。特别是，组织性质中的非分析物特异性变化会导致光谱的显著变化，从而阻止了可靠的校准。对于血液分析物（如葡萄糖）的测量，我们建议通过利用血液-组织基质的已知动力学，来减少个体组织特征的干扰。我们认为，通过利用自然的血液脉搏节律，可以增强来自血液分析物的信号，同时有效地抑制来自静态成分的信号。在此，我们提出了时间分辨测量方法，并随后进行了脉冲频率估计和相敏检测，以恢复与血液脉搏频率的动态变化相关的拉曼光谱。提出了初步的体内研究结果，以确立该方法在仪器和信号处理方面的优势，以及概述该方法所面临的挑战。
