Detection of Aqueous Glucose Based on a Cavity ... - ACS Publications

May 2, 2012 - Human Capital Management Group, Research and Development Planning .... transducer, which converts the information into electrical signal...
2 downloads 0 Views 2MB Size
Download PDF
Article pubs.acs.org/ac

Detection of Aqueous Glucose Based on a Cavity Size- and OpticalWavelength-Independent Continuous-Wave Photoacoustic Technique S. Camou,*,† T. Haga,‡ T. Tajima,§ and E. Tamechika† †

Microsystem Integration Laboratories, Microsensor Research Group, NTT Corp., Atsugi, Japan Human Capital Management Group, Research and Development Planning Department, NTT Corp., Tokyo, Japan § Intellectual Property Center, Patent and Trademark Group, NTT Corp., Tokyo, Japan ‡

S Supporting Information *

ABSTRACT: Toward the achievement of noninvasive and continuous monitoring of blood glucose level, we developed a new measurement method based on the continuous-wave photoacoustic (CW-PA) technique and performed the first validation in vitro with calibrated aqueous glucose solutions. The PA technique has been studied in the past but exclusively based on the pulse setup since the CW one exhibits dependence on the cavity dimensions, which is not compatible with the final application requirements. This paper describes a new strategy relying on the monitoring of the resonant-frequency relative shift induced by the change of glucose concentrations rather than amplitude signal levels at a fixed frequency. From in vitro results, we demonstrate a stable and reproducible response to glucose at various cavity dimensions and optical wavelengths, with a slope of 0.19 ±0.01%/g/dL. From theoretical considerations, this method is consistent with a relative acoustic velocity measurement, which also explains the aforementioned stability. The proposed method then resolves most of the issues usually associated with the CW-PA technique and makes it a potential alternative for the noninvasive and continuous monitoring of glycemia levels. However, experimental determination of sensor responses to albumin and temperature as two potential interferents shows similar levels, which points to the selectivity to glucose as a major issue we should deal with in future development. control.6,7 So-called “minimally invasive” sensing systems have been developed. Though the sensing element must still make direct contact with body fluids, the possibility of continuously monitoring the blood glucose level over a certain period of time has been a major breakthrough.8−12 Noninvasive sensing is also an important feature for increasing compliance and making the technology available to patients themselves without supervision. A noninvasive and continuous blood sugar sensor has then been viewed as the ideal solution and pursued for years by the scientific community. Several techniques that potentially fulfill the requirements for a noninvasive and continuous blood sugar sensor have been investigated, and several review papers have provided exhaustive overviews of the latest developments and appropriate references to original papers.13−17 Among the various approaches, near-infrared spectroscopy (NIR) with chemometrics has received certainly the most interest over the last few decades18−23 despite intrinsic limitations due to the scattering property of tissues and the low relative optical absorption coefficient of glucose compared to water.24 In contrast, photoacoustic (PA) spectroscopy utilizes a similar optical excitation sequence but exhibits two interesting

D

iabetes mellitus, often referred to as diabetes, is a group of common metabolic disorders that result in loose control of the blood glucose level and thereby hyperglycemia (raised blood sugar levels).1,2 To decrease the diabetes impact on the patient’s health,34 regular monitoring of blood glucose levels, followed by the appropriate action when necessary, is then of major importance. Monitoring systems based on fingerprick invasive blood collection dedicated to intermittent selftesting have been developed and are already commercially available.5 Mostly based on amperometric or colometric detection, they offer good accuracy, portability, and fast response time at a reasonable cost. The first release of these self-testing sensors was welcome as a huge step forward toward improved quality of care for type 1 diabetes on a case-by-case basis. Nevertheless, the technique has shown strong limitations with several years of daily usage. The analysis method relies on fingertip-prick blood samples and is therefore invasive (discomfort, potential infection) and discontinuous. The intermittent testing can therefore miss episodes of hyper- and hypoglycemia and mislead patients about the appropriate insulin quantity required. Underestimating the insulin quantity enables hyperglycemia to endure while overestimating it can also result in hypoglycemia with devastating outcomes. In this regard, continuous glucose monitoring remains an essential feature that enables accurate adjustment of insulin intake through continuous blood glucose measurements as a feedback © 2012 American Chemical Society

Received: December 22, 2011 Accepted: May 2, 2012 Published: May 2, 2012 4718

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724

Analytical Chemistry

Article

approach then solves most of the issues usually associated with CW-PA methodology. However, a few issues, also detailed in this manuscript, have to be resolved before this technique can be used for real patients.

advantages: insensitivity to the scattering property of tissue and high sensitivity.25 The PA technique couples optics and acoustics within the same concept and can be briefly described as follows. First, a modulated light beam illuminates the media (part of the body containing blood vessels) where optical absorption occurs (Figure S-1 in the Supporting Information). As a result, assuming that most of the absorbed energy is converted into heat, cyclic thermal expansion generates pressure waves within the media which propagate until the transducer, which converts the information into electrical signal. This electrical signal is then processed in order to selectively extract the parameters under investigation. When applying this method to glycemia sensing, all the successive steps of PA spectroscopy (optical absorption, acoustic wave generation, and propagation) depend on the blood glucose levels among other parameters and therefore make this approach a powerful tool. Two optical modulation patterns have been used to perform PA spectroscopy: pulse (low duty cycle, frequency up to 100 Hz) and square-wave (duty cycle of 50%, frequency up to 1 GHz), also referred to as pulse (operation in the time domain with time gating to suppress noise contribution) and continuous-wave (CW) (operation in the frequency domain (lock-in detection) with filters to suppress noise contribution) setups. Extensive comparisons between the two methodologies have been described previously,26,27 from the basic concept to a practical overview of the latest achievements based on either pulse or CW excitation sequence. As a brief summary, both techniques can potentially provide high sensitivity, but three issues remain of particular importance in order to choose the most appropriate excitation sequence: (1) the dominant origin of the noise and the efficiency of its suppression method, where pulse with time gating may be more suitable when dealing with systematic noise, while CW and frequency filters may provide better suppression efficiency with random noise; (2) the dependence on acoustic boundary conditions, which is only an issue with the CW technique where the acoustic propagation distance is usually much longer than the sample size; and (3) the thermal diffusion effect, which may not be negligible in the case of CW. When dealing with an in vivo environment, where the sample size and properties are difficult to control and stabilize along time, the source of noise may more likely be assimilated as random, which points to CW as the preferable excitation sequence. However, only the pulse methodology has been cited in the literature dedicated to noninvasive glucose monitoring.28−30 Despite CW-PA exhibiting also other advantages in terms of potential ease of miniaturization down to a portable size and low cost, it was disregarded at a very early stage due to its dependence on cavity dimensions, which are parameters impossible to control precisely when it comes to dealing with a real patient. In the present study, we developed a new method called frequency-shift (FS) for the noninvasive and continuous blood glucose sensing based on the CW-PA technique and demonstrated promising in vitro results with aqueous glucose solutions. This method, which actually measures the acoustic properties of the propagation medium, is then independent of the boundary conditions such as the cavity shape and length. Measurements at various cavity dimensions and optical wavelengths showed a stable and reproducible response, thus validating the approach. Furthermore, long-term CW-PA generation in static sample solution also demonstrated that the long-term thermal drift could be neglected. The proposed

■

MATERIALS AND METHODS Experimental Setup. Figure 1 (top) shows a schematic view of the experimental setup used to perform PA-based

Figure 1. Experimental setup with a cylindrical in shape detection cell whose length can be varied continuously (top) and a schematic view of the glucose concentration change effect on the amplitude/phase photoacoustic signal: the amplitude undergoes a resonance frequency shift (horizontal shift) combined with an amplitude variation, also referred to as a vertical shift; the phase only exhibits one resonance frequency shift (bottom).

measurements of aqueous glucose solutions. The function generator (FG) (FG120, Yokogawa, Japan) creates a square wave voltage signal (duty cycle, 50%) that triggers the lock-in amplifier (SR844RF, Stanford Research System) and drives the distributed feedback laser diode (DFB-LD), (1382 and 1610 nm ±1 nm wavelengths, 5 mW average output power, NTT Electronics, Japan) through the LD driver as well. The optical signal modulated in intensity is then sent to the measurement cell through a single-mode optical fiber. The acoustic pressure sensed by the transducer (Acoustic Emission R-CAST M-204A, Fujicera, Japan) is first preamplified (Pre-Amp Unit A1002, Fujicera, Japan) before it is fed into the lock-in amplifier. A computer pilots all the different elements via a LabVIEW interface (LabVIEW 8, National Instruments). This experimental system enables amplitude and phase measurements at any frequency within the frequency generator’s capabilities. However, the frequency range is limited to the 300−600 kHz domain due to the transducer’s narrow bandwidth. The two optical wavelengths were selected due to the identical absorbance of water (0.31 for both 1382 and 1610 nm), while the absorptivity per gram per deciliter of glucose in aqueous solution strongly differs with coefficients of −0.0023 at 1382 nm and 0.0011 at 1610 nm (spectroscopic data obtained with a 1-mm-long light-path measurement cell). Furthermore, despite the lower absorptivity level than those at wavelengths in the range of 2120 nm,23 the ratio defined as the absorptivity of glucose/absorbance of water gives comparable results for both 1610 (0.35%/g/dL) and 2120 nm (0.43%/g/dL), the latter being the maximum value in the NIR range. 4719

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724

Analytical Chemistry

Article

Detection Cell. For the in vitro measurements, we designed a custom-made measurement cell, sometimes also referred to as the PA cell (Figure S-2 in the Supporting Information). The cell is made of brass, which provides a sufficient acoustic impedance mismatch with water so that acoustic energy remains confined within the inner volume of the cell. The inner volume exhibits a 10 mm in diameter cylindrical shape, whose length can be adjusted freely from a few millimeters to several centimeters, leading to an inner volume varying from 0.3 to 1.5 mL. The optical fiber and transducer face each other and are aligned along the symmetry axis of the cell, which is an unusual configuration when dealing with the CW technique. Trace gas detection is often associated with very low optical absorption coefficients so that the excitation light beam can travel through the entire cell without significant losses. The optical fiber and transducer are then usually set perpendicular to each other so that the light beam cannot directly strike the transducer’s sensitive surface. However, because of the high absorption coefficient of water in the NIR range, most of the optical energy is absorbed within the first few millimeters of propagation through water, thus preventing any direct illumination of the transducer. With a cavity length shorter than 2 mm, despite strong attenuation provided by the water medium, the remaining optical energy strikes the piezoelectric transducers, which drastically impacts the sensor response. This direct coupling between the light source and acoustic sensing device yields a strong increase of the amplitude response in the 350−450 kHz frequency range, which probably corresponds to the resonance domain of the piezoelectric ceramic (Figure S-3 in the Supporting Information). These artifacts are easily identifiable, and increasing the sample thickness above 3 mm can prevent them. Glucose/Albumin Solution Preparation. Glucose and albumin solutions were prepared at known concentrations by dissolving dried pure glucose (D-(+)-glucose, G5767, SigmaAldrich Japan, Tokyo, Japan) or albumin (Bovine Serum Albumin, A7888, Sigma-Aldrich Japan, Tokyo, Japan) in deionized water. The glucose compound exhibits high solubility in water, which allows easy preparation of sample solution at concentrations ranging from a few milligrams per deciliter to several ten grams per deciliter. However, the solubility of albumin in water is lower, and albumin has the tendency to aggregate within the aqueous matrix, which limits the concentration levels of albumin aqueous solution to a few grams per deciliter. Frequency Shift Method. This method relies on the measurement of the resonant peak frequency shift induced by the change of sample solution concentration. The use of the CW excitation sequence creates standing acoustic waves within the propagation medium (liquid medium) due to physical boundaries at the liquid/brass interface. As a result, at certain frequencies defined by the boundary geometries and propagation medium properties, resonance occurs, which increases the signal amplitude considerably. As the boundary geometries or the propagation medium properties change, the frequencies that satisfy the conditions for resonance are shifted. However, when working with fixed cavity dimensions, this shift enables one to monitor specifically the propagation medium’s properties changes due to the change of diluted compound concentration. The FS technique then takes advantage of this phenomenon and provides a detection scheme independent of the local environment’s dimensions and shape.

Figure 1 (bottom) shows a schematic view of the resonancepeak shift induced by a change of diluted compound concentration. From the amplitude signal, the Gaussian-like response is shifted along the x-axis (frequency shift), but the signal also undergoes a vertical shift (amplitude variations). This shift along the y-axis is coming from the change of the energy transfer efficiency through the photothermal effect, which involves several parameters, such as optical absorption, specific heat at constant pressure, acoustic velocity, and thermal expansion. Indeed, these four parameters depend on the solution composition so that glucose concentration variation concomitantly affects the energy transfer, i.e., the amplitude signal level. Comparatively, the phase signal exhibits only a shift along the x-axis, and its local linear behavior around the resonance peak frequency makes the fitting process faster, easier, and more accurate. We can then describe the FS measurement methodology as follows. At a known glucose concentration, we first identify one resonant peak from the amplitude signal and adjust the phase signal to set a 0-phase at the resonant frequency f 0w. Then, after changing the sample solution to another glucose concentration, we adjust the frequency of the FG to f 0g to return to the 0phase signal in the closest proximity of f 0w. The final result is then computed as the relative frequency shift, i.e., the quantity ( f 0g − f 0w)/f 0w. Theoretically, only two points are sufficient for estimating the linear phase. However, with the noise contribution, several data are captured around the 0-phase point of the previous measurement. Linear regression over the set of data, here equivalent to averaging over the experimental points, then enables one to find the 0-phase point with good reliability. Increasing the number of measurements can therefore improve the measurement accuracy, but the sensor response time will simultaneously increase so that a compromise taking into account the two characteristics may be considered with respect to the objectives.

■

RESULTS AND DISCUSSION Detection Cell Frequency Response. The ability to excite standing waves within the detection cell was first investigated with pure water solution over a wide range of frequencies and cavity lengths. The experimental procedure can be described as follows. After the measurement cell length is fixed, the frequency is swept over the full range. Then, the cell length is incremented, and a frequency sweep over the full range is performed again. The same procedure is then repeated several times in order to scan the desired range of cavity length. Figure 2 shows the amplitude response signal over the 4−10.25 mm cavity length and 300−500 kHz frequency range. First, measurements show consistency with smooth variation between consecutive series. Second, the amplitude response looks like the superposition of several modes that exist only within a very limited range of frequency/cavity length, without any obvious or easily identifiable patterns. Furthermore, the PA signal in Figure 2 exhibits consistent levels along the full range of measurements due to cavity lengths longer than 4 mm, which prevent direct coupling between the light source and the piezoelectric sensor. In the particular case of a cylindrical resonant cavity, an analytical model describing the acoustic modes has been derived.31 From theoretical consideration, the following equation describes the acoustic frequencies of resonant acoustic modes in a cylindrical cavity (this equation is purely acoustic 4720

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724

Analytical Chemistry

Article

Figure 2. Three-dimensional view of the amplitude signal versus the cavity length and excitation frequency.

without any consideration of the way acoustic waves are generated within the cavity): f j = fmnq =

ωmnq 2π

=

vac ⎛ αmn ⎞2 ⎛ q ⎞2 ⎜ ⎟ + ⎜ ⎟ ⎝L⎠ 2 ⎝ R ⎠

(1)

where j = (mnq), and m, n, and q are the azimuthal, radial, and longitudinal mode numbers, respectively, vac is the acoustic velocity, R and L are the inner radius and length of the cylinder, respectively, and αmn the (n + 1)th root of the following equation: d ⎛⎜ παmn ⎞⎟ =0 J dr m ⎝ Rr ⎠ r = R

with Jm as the mth order Bessel function. The final resonant spectrum, as shown in Figure 2, results then from the superposition and combination of three different components: the longitudinal [the ones obtained with the onedimension cavity (Figures S-4−S-7 in the Supporting Information)], the radial mode, and the azimuthal mode. However, eq 1 states all the theoretical modes that satisfy the basic requirements in terms of symmetry and boundary conditions and does not include the excitation efficiency that may depend on the mode. As a result, all the modes from eq 1 do not appear in the amplitude spectrum shown in Figure 2. Nevertheless, the FS method requires at least one resonant peak so that these results satisfy our basic requirement: whatever the cavity length is, several modes are available and can be used to perform FS-based measurements. Measurement of Glucose Solutions. Glucose solution measurements were then performed according to the sequence described earlier. With pure water, once the cavity length had been fixed arbitrarily, we first searched for a resonant peak by spanning the frequency range within 300−500 kHz. Then, after sweeping the frequency locally around the resonance (typically in the ±a few kilohertz range around the resonant frequency), we switched the sample solution to 5 g/dL aqueous glucose solution, keeping the cavity length constant. After manually scanning the frequency in the vicinity of the previous one in order to find the modulation frequency that provides a 0-phase reference, we performed another sweep locally. The same sequence was repeated at 10 and 15 g/dL glucose concentrations at 1382 and 1610 nm. Figure 3 shows amplitude and phase signals obtained at all the concentration levels, for both optical wavelengths. As expected, the aforementioned frequency shift then appears clearly in both the amplitude and phase signals.

Figure 3. Amplitude (lines) and phase (dots) signal of FS response from 1382 (top) and 1610 (bottom) nm optical wavelength excitation and four aqueous glucose concentrations ranging from 0 to 15 g/dL.

However, the linear behavior of the phase signal makes the extraction of this shift easy, fast, and accurate, while the Gaussian-like response of the amplitude may require more data points and a more complex approach, which would also increase the response time. It is worth noting that the amplitude signal varies depending on the glucose concentration and the optical wavelength used for the excitation, but the tendency is not trivial. Nevertheless, without the frequency shift induced by the sample solution change of composition taken into account, amplitude-based measurements performed at a fixed frequency are strongly biased due to the Gaussian-shape response of the amplitude signal. Thus, prior to any amplitude-based measurement, the FS should be measured and corrected as a basic procedure. Sensor Response. Measurements of glucose aqueous solution at various glucose concentrations, cavity lengths, and optical wavelengths were then performed leading to the results shown in Figure 4. Despite using different acoustic modes with different characteristics (given by the number (mnq) in eq 1) and resonant frequencies, the glucose dependence of the FS remains unchanged with a slope of about 0.19 ± 0.01%/g/dL. In order to explain this result, eq 1 should be rewritten to v f j = fmnq = ac λmnq (2) with vac as the acoustic velocity in the propagation medium and λmnq as a term including all the cavity geometrical features and 4721

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724

Analytical Chemistry

Article

requires calibration measurement from a standard sample solution. Selectivity. One major issue remains from the fact that the FS method is equivalent to an acoustic velocity measurement. Acoustic velocity depends on glucose concentration according to a value that is a physical parameter and therefore impossible to improve. Furthermore, this is a scalar parameter that depends not only on the glucose concentration but also on various others parameters like other diluted compounds and temperature. From the scalar value change, it is impossible to state whether this is coming from a glucose concentration change, a temperature change, or any other parameter variation or even from a combination of several ones. Especially noteworthy is that the aforementioned experiments were performed with the detection cell immersed in a large volume of water in order to prevent fast temperature variation. However, we could measure temperature drift throughout the day with a temperature difference of about 1−2 °C. As a potential interfering parameter, we then investigated the influence of temperature as well as of albumin, one of the most abundant human blood plasma compounds. Measurements of albumin aqueous solutions are quite similar to that of glucose. However, measurements of temperature dependence are more complex because we do not have access to the temperature of the sample liquid inside the cell. With a drifting temperature, there are also possible inhomogeneities, the sample liquid being separated from the tank water by the detection cell, with some thermal inertia. We then replaced the large slow-temperature-drift water tank with a thermoregulated tank whose temperature can be controlled with a ±0.05 °C accuracy. The FS sensitivity to glucose, albumin, and temperature finally exhibits very similar levels with coefficients of 0.19%/g/ dL, 0.15%/g/dL, and 0.16%/°C (Figure S-8 in the Supporting Information), respectively (Table S-1 in the Supporting Information). Sensitivity. The dependence of FS on cofounding parameters such as albumin concentration and temperature leads to non-negligible potential bias in measurements of glucose, the only parameter of interest here. For example, a 1 °C temperature drift will yield a 0.84 g/dL bias in the glucose measurement. To further demonstrate this property, we evaluated the sensor response to glucose one more time but in the aforementioned temperature-controlled bath system. Figure 5 compares two sets of data in the low range of glucose concentration. The overall tendency remains consistent with previous results, with the 0.195%/g/dL linear response. However, the control of temperature drastically decreased the discrepancies with all the data points lying in close proximity to the ideal linear fit. From these results, we evaluated the LOD to be about 75 mg/dL despite few data points. This level is compatible with the physiological range of blood glucose levels, despite all the experiments performed with pure aqueous glucose solutions and well controlled conditions, and comparable to other PA-based LOD reported in the literature.30,34 Further investigations are necessary to precisely address the FS detection limit, but high-sensitivity measurements in the low milligram per deciliter range seem reachable by carefully addressing the temperature stability. Sample Solution Heating by CW-PA. The CW technique requires a 50% duty cycle that yields long-time exposure of sample solution compared to the pulse setup. Despite the low power of the light source, the sample solution undergoes

Figure 4. Normalized FS versus aqueous glucose concentration at several cavity lengths, modulation frequencies, and optical wavelengths. The inset corresponds to the results at high concentration levels shown in Figure 3.

proportional to a distance. The term λmnq, which has the dimension of length, can then be considered as the acoustic wavelength of the mode considered. However, when sweeping the frequencies centered around the reference value with fixed cavity dimensions, the same acoustic mode is considered, providing a constant term λmnq. As a consequence, the relative variation of the resonant frequency is coming only and exclusively from the propagation medium change of properties or, more precisely, its acoustic velocity variation. From eq 2, we then have Δfmnq fmnq

=

Δvac vac

(3)

This approach, including eqs 2 and 3, is also extendable to any arbitrary cavity geometry, despite the fact that no analytical equation may be available to describe the term λmnq. The glucose dependence of the FS can then be compared to the acoustic velocity dependence to glucose from the literature. Depending on the method and accuracy, the reported values vary greatly between 0.15,32 0.20,33 and 0.28%/g/dL25 but are consistent with the experimental determination of FS response reported in this manuscript. By monitoring the acoustic velocity changes, i.e., one specific characteristic of the propagation medium, the FS method then provides a powerful tool that can be applied as long as resonant peaks appear in the frequency spectrum and whatever the initial conditions are. The proposed approach solves most of the problems usually associated with the CW-PA setup. Furthermore, FS measurements from phase signal also provide two valuable features: insensitivity to amplitude variation that can occur from instruments’ instabilities (light source) and control of the frequency with excellent accuracy, especially when using a frequency generator. The frequency generator delivers frequencies of a few hundred kilohertz with an accuracy better than one millihertz, which is standard for this kind of equipment. However, those performance levels are equivalent to a theoretical detection limit (LOD) at the microgram per deciliter glucose concentration level, far below the practical expected LOD subject to other limiting factors such as noise. The proposed FS provides information about the change of concentration relative to a reference point and therefore 4722

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724

Analytical Chemistry

Article

the glucose concentration increases from 0 to 5 g/dL, followed by a smooth decrease at higher concentration levels. The faster decrease of the amplitude signal levels with 1382 nm is consistent with the fact that this signal change is proportional to several parameters, including the optical absorption coefficient, which is lower in the case of 1382 nm. Similar to NIR absorptiometry methods, this optical absorptivity dependence is a key feature toward the selective determination of glucose since it depends on the compound and the optical wavelength used for the excitation. As a consequence, we are now dedicating special efforts to developing an accurate and compound-selective measurement method based on the CWPA amplitude signal.

■

CONCLUSIONS A novel method for noninvasively measuring the glucose concentration from aqueous solution has been developed based on the continuous-wave photoacoustic technique. Instead of using the amplitude signal, the frequency shift of the resonant peak induced by the change of glucose concentration is monitored through the phase signal for a fast and accurate methodology. A linear response to glucose over a concentration range of up to 15 g/dL has been demonstrated. This method, equivalent to acoustic velocity-based measurements of a propagating medium, then provides a stable response whatever the resonant mode, the cavity dimensions, and the optical wavelength. The proposed frequency-shift approach then resolves most of the issues usually associated with the CW excitation technique and makes it a promising alternative as a noninvasive blood glucose sensor. However, a major remaining issue is the selectivity of the measurement method. Further characterization of the method for temperature and the albumin compound revealed similar sensitivity to the three parameters, making this concept potentially biased by temperature or albumin concentration variation during glucose monitoring. Further studies will then focus on using the amplitude information as well in order to improve the selectivity to the glucose compound.

Figure 5. Normalized FS versus aqueous glucose concentration at low concentration levels for two experimental setups with (circles) and without (dots) the temperature control system (accuracy ±0.05 °C).

thermal expansion-relaxation cycles repeatedly so that heating of the sample solution has been identified as a potential bias, especially when using static measurements (no flow). To experimentally assess this issue, we took advantage of the temperature dependence of FS and then performed a long-term exposure measurement (almost 24 h) with pure water and no flow. Despite oscillations of the amplitude and phase signals consistent with temperature variation of the water bath along time, we could not measure any long-term drift of the response, which should indicate a gradual and constant increase of the sample temperature from the photothermal effect, notwithstanding the 24 h time scale. We can then neglect this phenomenon and assume no heating of the sample solution from the CW-PA technique. Future Development. Regarding the final application, the proposed FS protocol should then be considered as one potential technique toward the development of a noninvasive blood glucose sensor. However, the lack of selectivity remains an important issue that we need to deal with in the future since only the glycemia level is of interest. To overcome this problem, two approaches are possible. The first method consists of limiting the measurement time to the period during which the body temperature and albumin concentration can be assumed to be constant. This may represent a strong limitation, requiring regular calibration to compensate for any drift of potential biasing parameters along time. However, it is believed that this sensor may enable one to get continuous monitoring of blood glucose levels between two consecutive and proximate measurements based on the finger-prick standard protocol. The second strategy consists of coupling the FS protocol with another sensor or sensing method to provide simultaneous measurements of potential bias, such as temperature and albumin concentration. This second approach is actually favored due to its potential high impact as a noninvasive blood glucose sensor. As shown in Figure 3, the amplitude signal also contains information about the sample composition, with variation of the amplitude peak maxima as the glucose concentration changes. With a negative absorptivity coefficient to glucose at 1382 nm, the amplitude maxima of the resonant peak constantly decrease as the glucose concentration increases but in an obviously nonlinear relationship. Furthermore, the experimental results with the LD operating at 1610 nm reveal a different trend, with a first increase of the signal amplitude as

■

ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail:[email protected]. Notes

The authors declare no competing financial interest.

■

REFERENCES

(1) Wild, S.; Roglic, G.; Green, A.; Sicree, R.; King, H. Diabetes Care 2004, 27 (5).1047−1052 (2) World Health Organization. August 2011, available at http:// www.who.int/mediacentre/facsheets/fs312/en/. (3) Roglic, G.; Unwin, N.; Bennett, P. H.; Mathers, C.; Tuomilehto, J.; Nag, S.; Connolly, V.; King, H. Diabetes Care 2005, 28 (9).2130− 2135 (4) World Health Organization. International Diabetes Federation, 2004, available at http://www.who.int/diabetes/publications/ diabetes_booklet/en/index.html. (5) Rubin, A. L. Diabetes for Dummies, 3rd ed.; Wiley Publishing, Inc.: Hoboken, NJ, 2008. 4723

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724

Analytical Chemistry

Article

(6) Chee, F.; Fernando, T.; van Heerden, P. V. IEEE Trans. Inf. Technol. Biomed. 2003, 7 (1), 43−53. (7) Wang, J. Talanta 2008, 75 (Issue 3), 636−641. (8) Chuang, H.; Taylor, E.; Davison, W. Diabetes Technol. Ther. 2004, 6 (1), 21−30. (9) Erdman, C. P.; Goldman, S. M.; Lynn, P. J.; Ward, M. C. J. Med. Devices 2008, 2 (2), 027518. (10) Ginsberg, B. H. Clin. Chem. 1992, 38 (9), 1596−1600. (11) Kost, J.; Mitragotri, S.; Gabbay, R. A.; Pishko, M.; Langer, R. Nat. Med. 2000, 6 (3), 347−350. (12) Ma, K.; Yuen, J. M.; Shah, N. C.; Walsh, J. T., Jr.; Glucksberg, M. R.; Van Duyne, R. P. Anal. Chem. 2011, 83, 9146−9152. (13) Tura, A.; Maran, A.; Pacini, G. Diabetes Res. Clin. Pract. 2007, 77, 16−40. (14) Pickup, J. C.; Hussain, F.; Evans, N. D.; Sachedina, N. Biosens. Bioelectron. 2005, 20, 1897−1902. (15) Heinemann, L.; Schmelzeisen-Redeker, G. Diabetologia 1998, 41, 848−854. (16) Khalil, O. S. Diabetes Technol. Ther. 2004, 6 (5), 660−697. (17) Chee, F. Fernando, T.. Closed-Loop Control of Blood Glucose; Lecture Notes in Control and Information Sciences, No. 368; Springer: Berlin, Heidelberg, Germany, 2007. (18) Chung, H.; Arnold, M. A.; Rhiel, M.; Murhammer, D. W. Appl. Spectrosc. 1996, 50 (2), 270−276. (19) Spanner, G.; Nieβner, R. Fresenius J. Anal Chem. 1996, 354, 306−310. (20) Heise, H. M.; Marbach, R.; Koschinsky, T.; Gries, F. A. Appl. Spectrosc. 1994, 48 (1), 85−95. (21) Hall, J. W.; Pollard, A. Clin. Chem. 1992, 38 (9), 1623−1631. (22) Ward, K. J.; Haaland, D. M.; Robinson, M. R.; Eaton, R. P. Appl. Spectrosc. 1992, 46 (6), 959−965. (23) Haaland, D. M.; Robinson, M. R.; Koepp, G. W.; Thomas, E. V.; Eaton, R. P. Appl. Spectrosc. 1992, 46 (10), 1575−1578. (24) Yoon G., Amerov A. K., Jeon K. J., Kim J. B., Kim Y. J. In Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1998; Vol. 20 (4), pp 1897−1899. (25) Zhao, Z. Pulsed Photoacoustic Techniques and Glucose Determination in Human Blood and Tissue; Oulu University Press: Oulu, Finland, 2002. (26) Tam, A. C. Rev. Mod. Phys. 1986, 58 (2), 381−434. (27) Atalar, A. Appl. Opt. 1980, 19 (18), 3204−3210. (28) Weiss, R.; Yegorchikov, Y.; Shusterman, A.; Raz, I. Diabetes Technol. Ther. 2007, 9 (1), 68−74. (29) MacKenzie, H. A.; Ashton, H. S.; Shen, Y. C.; Lindberg, J.; Rae, P.; Quan, K. M.; Spiers, S. Biomed. Opt. Spectrosc. Diagn./Ther. Laser App. 1998, 22, 156−159. (30) MacKenzie, H. A.; Ashton, H. S.; Spiers, S.; Shen, Y.; Freeborn, S. S.; Hannigan, J.; Lindberg, J.; Rae, P. Clin. Chem. 1999, 45 (9), 1587−1595. (31) Hao, L.-Y.; Ren, Z.; Shi, Q.; Wu, J.-L.; Zheng, Y.; Zheng, J.-J.; Zhu, Q.-S. Rev. Sci. Instrum. 2002, 73 (2), 404−410. (32) Shen, Y.; Spiers, S.; MacKenzie, H. A. Anal. Sci. 2001, 17 (Special Issue), 221−222. (33) Zips, A.; Faust, U. Appl. Environ. Microbiol. 1989, 55 (7), 1801− 1807. (34) Kottmann, J.; Rey, J. M.; Sigrist, M. W. Rev. Sci. Instrum. 2011, 82, 084903.

4724

dx.doi.org/10.1021/ac203331w | Anal. Chem. 2012, 84, 4718−4724