Scattering-independent glucose absorption measurement using a spectrally resolved reflectance setup with specialized variable source-detector separations

: We report a novel approach for the accurate measurement of glucose absorption in turbid media using a spectrally resolved reflectance setup. Our proposed reflectance setup with specialized variable source-detector separations enables scattering-independent absorption measurement, which is critical to in vivo long-term glucose concentration monitoring. Starting from the first-order approximation of the radiative transfer equation (RTE), we developed a scattering-independent glucose absorption measurement method and then evaluated this approach by Monte Carlo simulations as well as tissue-mimicking phantom studies in which glucose concentration was accurately measured. Our study demonstrates the potential of our proposed scattering-independent absorption measurement technique as an effective tool to quantify glucose levels in turbid media, which is an important step towards future in vivo long-term glucose concentration monitoring in human subjects.


Introduction
Near-infrared spectroscopy (NIRS) techniques have been explored extensively for biomedical applications in the past decade [1]. Particularly, NIRS has been considered as one of the most promising techniques for in vivo glucose monitoring as it can potentially provide simple, economical, non-invasive, and convenient real-time measurement on human subjects [2][3][4]. Truly non-invasive continuous glucose monitoring techniques would allow millions of diabetes patients to check their metabolic control at their best conveniences [5].
NIRS based glucose monitoring methods can be divided into two categories. The first category of NIRS methods applies the glucose scattering property to predict glucose concentrations. Bruulsema et al found that there was a strong correlation between blood glucose concentrations in diabetics and noninvasively measured tissue scattering coefficients [6]. Heinemann et al further demonstrated that an increase of glucose concentration leads to a decrease of scattering coefficient of turbid suspension in both phantom studies and Type I diabetic patients [7]. Later the same group used a portable NIRS system to monitor glucose levels by incorporating the glucose scattering information during an oral glucose tolerance test [2]. However, they found that it was challenging to achieve clinically acceptable accuracy for in vivo glucose measurement based on glucose scattering information. This is likely because: (1) glucose-induced scattering change is too small to be detected accurately [7]; and (2) body temperature perturbation may induce significant changes in tissue scattering [6] that could reduce accuracy in glucose scattering quantification.
The second category of NIRS methods uses the Beer's law to estimate glucose concentrations by quantifying glucose absorption. The great potential of absorption-based approach for glucose monitoring is evidenced by the fact that there were over hundreds of relevant papers published over the past few years [8][9][10]. The key for absorption based NIRS approach for glucose quantification is to extract glucose absorption features from measured tissue spectral data. Tissue absorption in the NIR window is mainly contributed by water, fat, hemoglobin et al [11,12] in addition to glucose. Several analyzing methods [10] including principal component regression (PCR), partial least squares regression (PLSR), net analyte signal (NAS) have been explored extensively for extraction of meaningful glucose absorption features. It has been found that the most useful absorption peaks for glucose centration measurement are located at 960 nm, 1150 nm, 1400 nm, and 1600 nm [12]. It is worth mentioning that body temperature change may affect tissue absorption as well [13,14], however, this effect can be easily excluded by using special data processing techniques [10,14]. Basically, body temperature was treated as a component similar to the other absorbers in the spectral data processing [15,16]. Tissue background scattering is another major factor that could alter the glucose absorption features extraction [17,18]. Many analyzing techniques have been developed to reduce scattering effect and some of them achieved decent results as long as sufficient training data was used [19][20][21][22], while most of these techniques failed when they were used for in vivo long-term glucose monitoring [23,24]. This is likely because tissue scattering is sensitive to body temperature and motion artifact et al [25]. In order to adapt absorption based NIRS techniques to accurately monitor glucose levels in human subjects in vivo, it is vital to minimize tissue background scattering effect.
To minimize the scattering effect on tissue absorption measurement, many other groups have developed different isobaric-points based approaches to perform scattering-independent optical measurements. Kumar et al reported two opposite sensitivities of NIR reflectance to the reduced scattering coefficient and demonstrated that the sensitivity of the reflectance to the variations of the reduced scattering coefficient can be minimized for some source and detector separations [26]. Mourant et al found that for appropriate separations between source and detector fibers, the optical path length of the collected photons does not depend on scattering parameters for a range of biological tissue relevant optical properties [27]. Liu et al conducted a unified analysis on these findings to provide some theoretical support and meaningful guidelines for the use of isobaric-points based approaches [28]. Kanick et al later developed an empirical model to describe this phenomenon and utilized their model to explore the path length isobaric-points in both ultraviolet/visible and near-infrared regions [29]. Mehrabi et al have adapted this isobaric-points based approach in an oximeter design to reduce the influence of unconscious movement [30]. Duadi et al [31] has taken an angularisobaric-points based approach to perform scattering insensitive reflectance measurements on cylindrical tissues like fingertip or earlobe with a goal of quantifying tissue blood content. Their angular-based source-detector design will potentially improve the accuracy of vascular endpoints quantification using a pulse oximeter [32].
In our study, we further developed the isobaric-points based approach by providing a strong theoretical support and demonstrating its use for glucose concentration monitoring. Starting from the first-order approximation of the radiative transfer equation (RTE) [33], we developed a novel equation to describe the relationship between the scattering independent source-detector separations and the tissue background optical properties. We then further evaluated our approach by using Monte Carlo simulations [34] as well as tissue mimicking phantom studies. By using a set of specialized source-detector separations, our method is only sensitive to glucose absorption changes but insensitive to medium background optical properties. To demonstrate the proof-of-concept, we reported a reflectance setup with specialized variable source-detector separations to enable accurate glucose absorption measurement from a turbid medium. Our optical reflectance setup was tested by tissuemimicking phantom studies from which scattering-independent glucose absorptions were accurately extracted. The foundation of our technique is that diffuse reflectance intensities are insensitive to medium background optical properties but sensitive to the absorption perturbations at certain special source-detector distances for a given turbid medium [27]. Our study demonstrates the great potential of our technique for scattering-independent glucose absorption measurement in turbid media, which is an important step towards future long-term in vivo glucose concentration monitoring in human subjects. It should be noted that the isobaric-points based techniques would generally be applicable to the characterization of other tissue components [35] in addition to glucose, other fields including milk purity characterization, juice purity characterization, and so on, as long as the specialized sourcedetector separations for a given turbid medium were found.

Scattering-variation-insensitive source-detector separations (SVI-SDS)
The first-order approximation of steady-state diffuse light flux density ( ) ϕ ρ in an infinite media is: where ρ is source-detector separation (SDS); eff μ is the effective attenuation coefficient, At SVI-SDS, scattering and absorption variation induced diffuse light energy flux density change ( ) ϕ ρ Δ is: umber of ption and s used to (11) g, d,C i is the be easily bsorption   Fig. 5(C) w ance. Figure 5   We plan to develop a fiber-probe based setup for actual optical measurement in future. A sourcedetector separation at millimeter scale will be practical for a fiber-probe fabrication. The fiber-probe based approach will help avoid specular refection by contacting probe on skin surface during an actual measurement. A SVI-SDS that close to 1-3 mm would yield a sensing depth of over 500 µm, which is sufficient enough for measuring vascular network on skin given that vessels are within and under dermis layer, which is about 150 µm deep from tissue surface [40].

Discussio
In the current proof-of-concept study, we used a glucose concentration range that is much higher than that in human body. To move our technique forward towards human subject glucose quantification, an instrument with higher sensitivity is necessary. Also, more work needs to be done to improve the sensitivity of the SVI-SDS based technique, which can be achieved by increasing the number of most meaningful wavelengths or SVI-SDS. However, there will be a possibility that certain substance other than glucose might show absorption lines in similar wavelength region, thus careful selection of wavelengths is critical for achieving a clinical acceptable specificity. In one word, there will be always a trade-off between the sensitivity and specificity when picking the wavelengths for data processing. To show glucose relevant SVI-SDS for a wide range of wavelengths in the NIR band, more than 9 wavelengths from 1000 nm to 1400 nm were investigated for glucose concentration quantification. Our former study found that the most useful absorption peaks for glucose centration measurement are located at 960 nm, 1150 nm, 1400 nm, and 1600 nm [12]. By using these wavelengths might help improve the specificity for glucose quantification with a reasonable sensitivity. It should be noted that the use of multiple SVI-SDS would potentially increase the complexity of an actual optical system design. We intend to reduce the SVI-SDS number without sacrificing prediction accuracy and specificity. Our preliminary test showed that it is feasible to reduce the SVS-SDS number as long as the most meaningful wavelengths were picked. SVI-SDS can be easily estimated either through MC simulations or tissuemimicking phantom studies for a given subject as long as its baseline optical properties (assuming it contains minimal glucose content) are given. However, it will not be practical to use MC simulations or phantom studies to find precise SVI-SDS for a particular human subject. To address this challenging, we are currently collecting optical data from volunteers to build a big human skin spectral database from which we intend to find the correlation between SVI-SDS values and human skin optical properties. We expect that the big database will enable us to look for SVI-SDS with a reasonable accuracy for a subject that has a set of skin tissue optical properties that fall within the database.
It has been noticed that it is challenging to adapt the glucose prediction model built from one subject to other different subjects using existing NIRS techniques. This is likely because different subjects might have significantly different background tissue optical properties, while the background tissue scattering properties have a strong effect on the performance of a glucose concentration prediction model. It is also not feasible to use existing NIRS techniques to perform long-term in vivo glucose monitoring since human skin tissue optical properties are sensitive to body temperature change. Our technique might be able to address these problems as the measured diffuse reflectance at SVI-SDS is insensitive to tissue background optical properties. Even if there are considerable differences of tissue background optical properties among different subjects or different time points for the same subject, a simple linear calibration can be easily utilized to reduce any offset of glucose concentrations as illustrated in Fig. 4. Because of the above reasons, our technique will have great potential for in vivo long-term glucose concentration measurement on human subjects.
To move our technique forwards towards clinical applications, we will continue to develop our technique for in vivo studies. Specifically, we are interested in performing long-term diffuse reflectance measurements at different skin locations on volunteers to understand the key factors that might affect the performance of our method. Ultimately, we will optimize the SVI-SDS number, wavelengths, prediction model etc. with a goal of pushing our technique for human subject applications.

Conclusion
Our study demonstrates that our proposed SVI-SDS based technique is an effective approach for scattering-independent glucose absorption measurement, which is critical to in vivo longterm glucose concentration monitoring. Our scattering-independent glucose absorption quantification method provides new opportunities to improve the accuracy of in vivo glucose concentration measurement with an ultimate goal of providing clinical acceptable noninvasive NIR optical instrumentations for diabetes patients.