WO2011068998A2

WO2011068998A2 - Systems and methods for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths

Info

Publication number: WO2011068998A2
Application number: PCT/US2010/058771
Authority: WO
Inventors: Nirmala Ramanujam; Janelle E. Phelps
Original assignee: Duke University
Priority date: 2009-12-02
Filing date: 2010-12-02
Publication date: 2011-06-09
Also published as: WO2011068998A3

Abstract

Systems and methods for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths are provided. In one embodiment, the method includes emitting light onto a tissue mass, measuring diffuse reflectance from the tissue mass, and calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured diffuse reflectance. The method also includes determining a hemoglobin concentration associated with the tissue mass by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths.

Description

DESCRIPTION

SYSTEMS AND METHODS FOR DETERMINING HEMOGLOBIN CONCENTRATION UTILIZING DIFFUSE REFLECTANCE AT ISOSBESTIC

WAVELENGTHS

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application Serial No. 61/266,119, filed December 2, 2009; the disclosure of each of which is incorporated herein by reference in its entirety.

TECHNICAL FIELD

The subject matter disclosed herein relates to optical spectroscopy and tissue physiology. More particularly, the subject matter disclosed herein relates to systems and methods for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths.

BACKGROUND

Hemoglobin (Hb) concentration is a metric used for many applications in the medical field, including anemia diagnosis and transfusion guidance. The current strategy for determining hemoglobin concentration is an invasive procedure where blood is drawn from an artery and sent to a laboratory for further analysis, such as arterial blood gas (ABG) measurements or optical methods of measurement. Notably, the current strategy can be invasive, time-consuming, subject to operator error, and/or carry the risk of infection for a tested patient. For example, although capable of measuring hemoglobin concentration with a high degree of accuracy, present optical methods generally require a sophisticated computational technique such as diffusion approximation or Monte Carlo modeling to extract hemoglobin concentration from the measured spectra. Moreover, present optical methods employing computational techniques typically require robust computer systems, thereby rendering the hemoglobin concentration measurement systems impracticable for applications requiring portability/mobility or immediate results. For example, a portable device capable of determining hemoglobin concentration would have wide applicability in various areas where rapid hemoglobin measurements are required, such as in the emergency or operating room, in the back of an ambulance, in the battlefield, and in other resource-limited settings.

Thus, there remains a need for an improved system and method for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths in biological tissue.

SUMMARY

The subject matter described herein includes systems and methods for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths. In one embodiment, the method includes emitting light onto a tissue mass, measuring diffuse reflectance from the tissue mass, and calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured diffuse reflectance. The method also includes determining a hemoglobin concentration associated with the tissue mass by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths.

In another embodiment, the system comprises a light source for emitting light onto a tissue mass and a measurement device for measuring diffuse reflectance from the tissue mass. The system further includes a processing unit for calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured reflectance, and determining a hemoglobin concentration associated with the tissue mass by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths.

The subject matter described herein for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths may be implemented in hardware, software, firmware, or any combination thereof. As such, the terms "function" or "module" as used herein refer to hardware, which may also include software and/or firmware components, for implementing the feature being described. In one exemplary implementation, the subject matter described herein may be implemented using a computer readable medium having stored thereon computer executable instructions that when executed by the processor of a computer control the computer to perform steps. Exemplary computer readable media suitable for implementing the subject matter described herein include non- transitory computer-readable media, such as disk memory devices, chip memory devices, programmable logic devices, and application specific integrated circuits. In addition, a computer readable medium that implements the subject matter described herein may be located on a single device or computing platform or may be distributed across multiple devices or computing platforms.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the subject matter described herein will now be explained with reference to the accompanying drawings, wherein like reference numerals represent like parts, of which:

Figure 1 is a block diagram of a system for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths according to an embodiment of the subject matter described herein;

Figure 2 is a flow chart of an exemplary process to generate an analytical expression for determining hemoglobin concentration according to an embodiment of the subject matter described herein.

Figure 3 is a flow chart of an exemplary process for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths according to an embodiment of the subject matter described herein.

DETAILED DESCRIPTION

The subject matter described herein includes systems and methods for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths. According to one embodiment, the present subject matter includes a noninvasive device that is configured to measure hemoglobin concentration in near real-time due to utilizing calculated ratios of diffuse reflectance intensities. Hemoglobin concentration (Hb) levels typically range from 12-16 grams of hemoglobin per deciliter of blood (g/dL). Blood transfusions are indicated when Hb levels reach between 6-10 g/dl and are also dependent upon signs of organ ischemia, the patient's intravascular volume status, and the presence of other patient risk factors. Thus, providing an immediate measurement of hemoglobin concentration in the manner performed by the present subject matter can be invaluable.

One embodiment of the present subject matter involves the monitoring Hb concentration in surgical patients using a fiber probe-based diffuse reflectance spectroscopy system. Diffuse reflectance spectra reflect tissue absorption and scattering. The primary absorbers in soft tissues are oxygenated and deoxygenated Hb (oxy- and deoxy-Hb, respectively). Further, diffuse reflectance spectroscopy measures a mixture of venous and arterial components and does not require pulsatile blood flow.

. In one embodiment, an optical spectrometer system may be used to obtain optical measurements and process diffuse reflectance measurement data in order to yield hemoglobin concentrations. Figure 1 depicts an exemplary optical spectrometer system 100 that includes a fiber optic probe 102. In an alternate embodiment, relay optics may be used instead of a fiber optic probe to emit (i.e., deliver) light on a tissue mass 114. Spectrometer system 100 may also include a light source 104, a monochromator 106 (e.g., a scanning double-excitation monochromator), an emission monochromator 108, a charged-couple device (CCD) unit 110, and a processing unit 112 (e.g., a processor within a personal computer). In one embodiment, the light source may include a xenon arc lamp or a light emitting diode (LED) light source. Also, monochromator 106 may comprise a double-grating excitation monochromator. In an alternate embodiment, a filter wheel may be utilized in system 100 instead of monochromator 106. Similarly, an extended red photomultiplier tube (PMT), a photodiode, or a single channel detector may be used in lieu of CCD unit 110 in system 100.

In one embodiment, fiber optic probe 102 may be used for obtaining in vivo measurements of blood parameters. For example, fiber optic probe 102 may be used to quantitatively determine the concentration of "total hemoglobin" (e.g., the total hemoglobin content in a tissue mass), blood loss, dilutional effects from fluid intake, porphyrin levels, cellular metabolism, and the hemoglobin saturation of a tissue mass in vivo. Notably, fiber optic probe 102 may be configured to measure the concentration of a hemoglobin analyte by being placed in an oral mucosa, under the tongue, or taped to any exposed surfaces (such as an arm), thereby providing real-time measurements of the analyte of interest. Applications of this technology include, but are not limited to, a quick non-invasive screening test for hemoglobin concentration, quantifying tissue blood loss in vivo, quantifying dilutional effects of fluids in the tissue, and quantifying tissue oxygenation in vivo. One other advantage of the present subject matter includes eliminating the need for all handling and disposal of blood and sharp medical equipment (e.g., syringes).

In one embodiment, fiber optic probe 102 comprises a flexible steel sheathed tubing that contains a plurality of optical fibers (i.e., illumination and collection fibers). Fiber optic probe 102 may further include a rigid probe tip on one end that may include a plurality of fibers arranged in any number of different illumination-collection configurations. For example, the fiber optic probe may comprise a plurality of illumination fibers centrally grouped to form an illumination core. In one embodiment, fiber optic probe 102 may include a single collection ring comprising 18 collection fibers that may be interfaced with tissue mass 114 positioned around a 19-fiber illumination core. In an alternate embodiment, fiber optic probe 102 includes at least one collection fiber and at least one illumination fiber. For example, the illumination core may include any number of fibers to obtain an illumination core diameter that maximizes the coupling efficiency for the light source. In one embodiment, the illumination fibers are used to emit light on the tissue mass to be examined.

In one embodiment, the light may be generated by light source 104 and provided to fiber optic probe 102 via monochromator 106. Specifically, light is emitted into one end of one or more illumination fibers. After the light is emitted by the illumination fibers on tissue mass 114, at least one collection fiber in the fiber optic probe 102 captures the diffuse reflected light which is ultimately provided to monochromator 108. In one embodiment, the present subject matter may collect on a diffuse reflectance spectrum, such as in the ultraviolet and visible (UV-VIS) range. In one embodiment, fiber optic probe 102 is configured to collect wavelength dependent diffuse reflectance spectra measured from 350-800 nm.

In one embodiment, the diffuse reflectance signals from the various collection fibers are spatially separated by CCD unit 110, thereby enabling diffuse reflectance spectra to be measured at different illumination-collection separations simultaneously. In another embodiment, a PMT is configured to measure the diffuse reflectance. Once the diffuse reflectance spectra is measured, the data is provided to processing unit 112, which then calculates a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured diffuse reflectance. In one embodiment, processing unit 112 may be configured to calculate a ratio of diffuse reflectance intensities at two isosbestic wavelengths includes dividing the diffuse reflectance intensity of a first isosbestic wavelength by the diffuse reflectance intensity of a second isosbestic wavelength. For example, a ratio for wavelength ratio pair of 545/390 nm may be calculated by dividing the diffuse reflectance intensity found at 545 nm by the diffuse reflectance intensity found at 390 nm. Processing unit 112 may be configured to calculate a calculate a ratio of diffuse reflectance intensities at any two wavelengths, but is typically adapted to perform a calculation using a isosbestic wavelength ratio pair that has been determined to be highly correlated to hemoglobin concentration levels.

In one embodiment, processing unit 112 is further configured to determine a hemoglobin concentration associated with tissue mass 114 by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths (e.g., there are other predefined analytical expressions that are respectively associated to other isosbestic wavelength pairs). The predefined analytical expression may be a linear equation that defines or indicates the relationship between the calculated ratio and hemoglobin concentration. The linear equation may be in the form of y=mx+b that has been derived using linear regression analysis of hemoglobin concentration data and measured intensity ratios (as described below), where y=hemoglobin concentration, x=calculated ratio, m=a slope derived from the linear regression analysis, and b=an intercept derived from the linear regression analysis. Notably, by using a ratio of measured diffuse reflectance intensities associated with a wavelength ratio pair as a variable in a predefined linear equation, the present subject matter is able to determine a hemoglobin concentration much faster than a system that relies on a Monte Carlo algorithm to process diffuse reflectance data.

Before the present subject matter is able to utilize the predefined analytical expression to determine a hemoglobin concentration in real-time, the analytical expression needs to be derived, such as through linear regression or some other mathematical technique.

In one embodiment, the present subject matter determines a total Hb concentration estimation, independent of Hb saturation and scattering, using a simple isosbestic ratiometric analysis of diffuse reflectance intensities developed using Monte Carlo simulations. Analytical expressions may be derived through the use of tissue-mimicking phantoms and in vivo human tissue data. Diffuse reflectance spectra may be generated using a forward Monte Carlo model, then equations of linear regression between Hb concentration and the ratios may be established from the simulations and applied to phantom data. A single reference phantom may be used to calibrate a Monte Carlo-generated reflectance to the same scale as the experimentally-measured data. In one embodiment, the simulation equations are specific to the probe and instrument used experimentally.

In one embodiment, simulations may be conducted for five scattering levels for each of ten absorption levels (Hb concentrations). There may be 28 total ratios tested for isosbestic points between 350-600 nm. Using this data, a simple analytical equation can ultimately be developed to predict Hb concentration. Twenty-five of the 28 ratios had average percent errors within 20% for the simulations when the ratios were averaged over all five scattering levels, four of which were below 5%, nine of which were between 5-10%, and seven of which were between 10-15%. Linear regression equations from the simulations may then then applied to three sets of experimental phantom data. In one instance, of the 25 best ratios from simulations, 12 ratios yielded average percent error within a 20% threshold in extracting Hb concentration from phantoms (Phantom Set 1 ) with constant Hb concentration and scattering, but variable Hb saturation. Seven of these ratios had errors below 5%, two had errors between 5-10%, and three had errors between 15-20%. From these 12 ratios, there were a total of six ratios (545/390, 452/390, 570/390, 529/390, 584/390, and 500/390) which could extract Hb concentration from two sets of phantoms (Phantom Sets 2 and 3) with variable Hb concentration and scattering with errors below a 20% threshold. For 452/390 nm, the average percent error was below 15% for both phantom sets. For Phantom Set 2, the average percent error was below 10% for 452/390 nm, between 10-15% for 529/390 and 500/390 nm, and between 15-20% for 545/390, 570/390, and 584/390 nm. For Phantom Set 3, the average percent error was between 10-15% for 545/390, 452/390, 570/390, and 584/390 nm and between 15-20% for 529/390 and 500/390 nm.

In one embodiment, in order to assess the instrument-independence of the ratiometric method, the six best ratios may be tested for two sets of phantoms with variable scattering and Hb concentration measured with a CCD, PMT, or other measurement device. Three of these ratios - 545/390, 452/390, and 529/390 nm - had similarly low errors within 20%, indicating this method can be considered independent of the instrument and probe used. In one instance, data from human tissue measurements measured with both instruments was used to test the correlations with Hb concentration extracted with either the ratiometric method or a more complex inverse Monte Carlo model. Both the inverse Monte Carlo model and ratiometric method extracted a wide range of Hb concentration with Pearson linear correlation coefficients of 0.75, 0.76, and 0.88 for the three best ratios, 545/390, 452/390, and 529/390 nm, respectively

Figure 2 is a flow diagram illustrating the steps of an exemplary process to generate an analytical expression that is used to determine hemoglobin concentration according to an embodiment of the subject matter described herein. Referring to Figure 2, in block 202, diffuse reflectance intensities at isosbestic wavelengths from a specimen or sample with a known hemoglobin concentration is determined. In one embodiment, a plurality of scattering phantom samples is used. Notably, each phantom sample includes a known hemoglobin concentration. In one embodiment, the phantom samples may also include varying known scattering and hemoglobin saturation values as well. For example, the phantoms may be specifically designed to have particular hemoglobin concentrations, as determined from the relative amounts of hemoglobin, scatterer, and solvent (water or PBS) that comprise a given phantom. In another embodiment, instead of phantoms, the known hemoglobin concentration of a typical tissue sample may be used since an ABG analyzer can measure the hemoglobin concentration directly from the tissue sample. In another embodiment, the hemoglobin concentration can be specified by a Monte Carlo model.

In one embodiment, light is emitted on a phantom sample or tissue sample using a fiber optic probe. As diffuse reflectance is collected from tissue sample, the measurement device (e.g., CCD or PMT) determines the diffuse reflectance intensities at isosbestic wavelengths. In one embodiment, the intensities of 8 isosbestic wavelengths may be taken. In an alternate embodiment, simulated samples with known hemoglobin concentration, scattering, and hemoglobin saturation levels are generated and used instead of phantom samples. The diffuse reflectance data of the simulated samples are then generated using a Monte Carlo algorithm. In one embodiment, the diffuse reflectance data of the simulated samples is calibrated by a correction factor in order to place it on the same scale as experimental data (i.e., the measured reflectance from a tissue mass).

In block 204, the diffuse reflectance intensity ratios of the isosbestic wavelength ratio pairs are calculated. For example, the intensity ratio of a wavelength ratio pair 529/500 nm may be calculated by dividing the diffuse reflectance intensity at the 529 nm wavelength by the diffuse reflectance intensity at the 500 nm wavelength. Notably, an intensity ratio is calculated for each predefined wavelength ratio pair.

In block 206, a database associated with each isosbestic wavelength ratio pair (i.e., two isosbestic wavelengths) is populated with the known hemoglobin concentration and the corresponding calculated intensity ratio. Notably, each wavelength ratio pair is associated with its own database that contains hemoglobin concentration data and corresponding diffuse reflectance intensity ratio data. For example, there is a unique database associated with the 529/500 nm wavelength ratio pair and a second unique database (that is separate from the first unique database) associated with the 529/390 nm wavelength ratio pair.

In block 208, the process outlined by blocks 204-208 is repeated with another known hemoglobin concentration value. Notably, by repeating blocks 204-208, each database associated with a particular wavelength ratio pair is provisioned with another set of hemoglobin concentration and intensity ratio data (that is collected at the respective isosbestic wavelengths). In one embodiment, the iterative process of selecting different hemoglobin concentration values may include the use of phantom samples that are characterized by a particular scattering level and/or hemoglobin saturation level so that the hemoglobin concentrations may exhibit some variance. Once one desired known hemoglobin concentration has been tested, a phantom specimen(s) with a new scattering level and hemoglobin saturation level may be used so that the database has variable hemoglobin concentrations for different levels of scattering and hemoglobin saturation. Thus, the end result of this process may include a database containing a plurality of hemoglobin concentrations for different scattering and hemoglobin saturation values which are associated with corresponding diffuse reflectance intensity ratios.

In block 210, an analytical expression associated with each wavelength ratio pair is generated. In one embodiment, for each database associated with a wavelength ratio pair, linear regression analysis (or some other mathematical model) is performed on the data contained within the database in order to derive or calculate an analytical expression. For example, once a database is provisioned with a designated number of sets of hemoglobin concentration and intensity ratio data, processing unit 112 may perform linear regression analysis on the data (i.e., calculated intensity ratios and known hemoglobin concentration values) in the database to determine an analytical expression. The analytical expression may be a linear equation (e.g., [Hb]=m*ratio+b) with constant slope (m) and intercept (b) values unique to the associated wavelength ratio pair (where [Hb] is hemoglobin concentration and "ratio" is the calculated intensity ratios). Notably, the analytical expression defines or indicates the relationship between a given intensity ratio and hemoglobin concentration. In one embodiment, the closer (more accurate) the linear equation mathematically represents the relationship between the intensity ratios and hemoglobin concentrations that were used to derive the formula, the higher the correlation factor (r) that is assigned to the associated isosbestic wavelength ratio pair. Diffuse reflectance ratios are expected to correlate well with Hb, because absorption of Hb is a primary source of contrast in the spectra. Isosbestic ratios are taken where the oxy-Hb and deoxy-Hb molar extinction coefficients are equal, and so they would not be expected to correlate with the partial pressure of oxygen in the arterial plasma (PaO₂).

Correlations of a wavelength ratio pair may be derived in several ways. In one embodiment, ratios of all numerator-denominator pairs from 350-600 nm are tested as simple correlates to Hb concentration. Correlations may be tested in Matlab using Pearson's linear correlation coefficients, under the assumption that the data is normally distributed. The spectra may be interpolated to a 1 nm increment using a cubic spline interpolation prior to calculating the ratios, to increase the number of wavelength combinations. Ratios are obtained from raw reflectance spectra.

In one embodiment, correlations between all reflectance ratio pairs between 350-600 nm and ABG Hb values are tested. Over the wavelength range of 350-600 nm, there are eight isosbestic points for oxy- and deoxy- Hb: 390, 422, 452, 500, 529, 545, 570, and 584 nm. In one instance, the suitable correlations of optical ratios to ABG Hb (r>±0.65) exist where the numerator is between 524-537 nm and the denominator between 482-507 nm. For numerators of 474-475 nm and denominators of 466-467 nm, the correlations were equally good (r>±0.65). The reverse case where the numerator was 466-467 nm and the denominator was 474-475 nm also had r>+0.65. The best correlation was at 532/499 nm, which correlated to ABG Hb with r=-0.67. The ratio of 532/499 nm is close to the isosbestic ratio of 529/500 nm, which had r=-0.66. Because the correlation coefficients were so similar for both these ratios, the ratio 529/500 nm was retained. In another embodiment, simulations of 50 tissue models, with five scattering levels for each of ten absorption levels were conducted. Upon determining the best ratios, tissue-mimicking phantoms were used for testing the linear regression equations developed from the simulations. Because the testing was conducted using the linear regression equations derived directly from the simulations, training on tissue phantoms was not required. The three sets of phantoms were designed to test the independence of the ratiometric method to Hb saturation (Set 1 ) and scattering (Sets 2-3). Phantom Set 1 contained 51 phantoms with variable Hb saturation and constant Hb concentration and scattering. Phantom Set 2 had four Hb levels for two initial scattering levels which decreased slightly due to addition of Hb. Phantom Set 3 consisted of 13 Hb levels for a single initial scattering level which decreased to a greater extent due to addition of Hb. A subset of ratios was tested for Phantom Sets 2 and 3, based upon the best ratio(s) from Phantom Set 1. A new set of ratios was then selected and tested on Phantom Sets 2 and 3 measured with a different instrument, to establish that this method was independent of instrument response.

In another embodiment, forward Monte Carlo simulations were conducted to determine the isosbestic ratios of oxy-Hb and deoxy-Hb that could predict Hb concentration. For example, there are eight isosbestic points for oxy-Hb and deoxy-Hb over the 350-600 nm wavelength range: 390, 422, 452, 500, 529, 545, 570, and 584 nm. Combinations of ten absorption and five scattering levels were used to generate optical property inputs to the 400 simulated tissue models (10 Hb levels, 5 scattering levels, 8 wavelengths). The absorption levels (Table 1 ) corresponded to total Hb concentrations of 5-50 μΜ with different fractions of oxy-HB and deoxy-Hb (thus different Hb saturations). The absorption coefficient (p_a) at each isosbestic wavelength was determined using the molar extinction coefficients for each hemoglobin species. Table 1. Total Hb concentration and Hb saturation used in the simulations

[Total Hb] (μΜ) Hb saturation (%)

5 50

10 100

15 66.7

20 25

25 80

30 50

35 85.7

40 62.5

45 77.8

50 100

Furthermore, five different scattering levels, S1-S5 (Table 2), were combined with each of the absorption levels. The reduced scattering coefficient (μ₃') at each of the eight isosbestic wavelengths was calculated using software algorithms. For a given wavelength pair, the ratio of scattering was independent of the scattering level.

Table 2. μ,' for each of the five scattering levels as a function of isosbestic wavelength

Wavelength

S1 (cm^'1) S2 (cm^'1) S3 (cm ¹) S4 (cm^'1) S5 (cm ¹)

(nm)

390 10.0 15.0 20.1 25.0 30.0

422 9.4 14.1 18.8 23.4 28.1

452 9.0 13.5 18.0 22.5 27.0

500 8.4 12.5 16.7 20.9 25.0

529 8.1 12.1 16.1 20.1 24.2

545 8.0 12.0 16.0 20.0 24.0

570 7.9 11.8 15.8 19.6 23.6

584 7.7 11.5 15.4 19.2 23.0 In one embodiment, the simulations were scaled for the exact probe geometry used in the experimental measurements on which the ratios were tested. For example, the probe geometry may include of a central illumination core of 18 illumination fibers surrounded by 19 collection fibers in a concentric arrangement, with each individual fiber being 200 pm in diameter with numerical aperture (NA) of 0.22. The approximate spatial resolution of this probe is 1 mm, as determined by the full-width at half maximum of the collected fraction versus source detector separation distance. The collected fraction was determined from convolution over the illumination and collection fibers. The average 90% sensing depth over 350- 600 nm is approximately 2.2 ± 0.7 mm. For all tissue models, the anisotropy factor, g, was 0.8, and the refractive indices for the fibers and tissue were at 1.45 and 1.37, respectively. From the forward Monte Carlo model, the diffuse reflectance was determined using a lookup table method described previously. In one embodiment, reflectance ratios may be calculated from the modeled diffuse reflectance at each isosbestic point.

In one embodiment, the simulations were used to determine which ratios best correlated to Hb concentration. Reflectance ratios at isosbestic wavelengths were only computed when the numerator wavelength was higher than the denominator wavelength yielding a total of 28 possible ratio combinations. The criterion for the simulation data was to minimize the goodness of fit, or the average percent error, %error, defined in Equation 1 , where n is the number of Hb levels, Hb is the concentration of Hb, and fit is the linear regression equation for Hb versus ratio: fit -Hb

Hb

%e/vw = 100- (1)

The errors were determined after the ratios were averaged over all scattering levels, and the best ratios were defined as having %error < 20%.

As indicated above, the efficacy of isosbestic ratiometric correlations to Hb concentration may evaluated by testing tissue-mimicking phantoms (e.g., 3 independent sets). The linear regression equations for the best ratios from the simulations were applied to the phantom data. In order to correct for the instrument dependence, the simulated reflectance was first calibrated by a correction factor determined using a single phantom measurement to put the Monte Carlo data and the experimental data on the same scale. Briefly, the calibration phantom was selected from a set of master phantoms that has previously been found to most accurately estimate μ₃ and μ₅' over a large range of target phantom optical properties. The calibration phantoms used for either instrument here had approximate absorption coefficient, μ₃=2.2 cm^"1 and reduced scattering coefficient, μ₅'=24.8 cm^"1, averaged over 350-600 nm. The calibration phantom can be measured prior to taking the laboratory or clinical measurements, and so the time taken to measure it is not relevant to the time it would take to estimate Hb concentration using this ratiometric method. All diffuse reflectance data from the phantoms were divided by the spectrum of a reflectance standard measured on the same day prior to taking the ratios, so that the ratios were calculated from the true diffuse reflectance spectrum of the interrogated medium independent of lamp and/or detector response. For the phantom measurements, the percent error was calculated from Equation 1 , where the fit refers to the extracted Hb concentration using the linear regression equation derived from calibrated simulation data.

After the analytical expression is derived for one or more wavelength ratio pairs, the present subject matter may be utilized in a practical setting (e.g., in surgery) in order to determine hemoglobin concentration in a tissue mass. In one embodiment, a number of analytical expressions are derived for a plurality of isosbestic wavelength ratio pairs, but only testing on one wavelength ratio pair is needed to measure hemoglobin concentration. Typically, a wavelength ratio pair associated with a high correlation factor is used for the benefit of greater predictive accuracy.

Figure 3 is a flow diagram illustrating the steps of an exemplary method 300 for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths according to an embodiment of the subject matter described herein. Referring to Figure 3, in block 302, a light source is emitted onto a tissue mass. In one embodiment, fiber optic probe 102 configured with at least one illumination fiber may be used to emit light on tissue mass 114. The tissue mass may either be ex vivo (e.g., a lab specimen) or in vivo (e.g., sublingual lining). In one embodiment, the tissue surface chosen for placement of the probe was the floor of the mouth, a highly vascular and perfused mucosal surface that can be directly accessed by the fiber optic probe.

In block 304, the diffuse reflectance from the tissue mass is measured, in one embodiment, one or more collection fibers of fiber optic probe 102 are used to collect the diffuse reflectance emitted from the tissue mass. The wavelength intensities of collected diffuse reflectance are then measured by a measurement device, such as the CCD 112 or a PMT. In one embodiment, the diffuse reflectance across the spectra of 350 nm to 800 nm is measured. In an alternate embodiment, only isosbestic wavelength intensities are measured instead of wavelength intensities within the 350-800 nm spectra. In yet another embodiment, the diffuse reflectance across the spectra of 350 nm to 600 nm is measured. In one embodiment, the bandwidth for the diffuse reflectance signal that is measured which may be as high as 25 nm for each wavelength.

In block 306, an intensity ratio using the measured reflectance at two isosbestic wavelengths (i.e., a wavelength ratio pair) is determined. In one embodiment, a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured diffuse reflectance is calculated. The isosbestic wavelength ratio pair may include any two isosbestic wavelengths. In one embodiment, the isosbestic wavelength ratio pair is a wavelength ratio pair that has been determined to be highly correlated to hemoglobin concentration. In one embodiment, processing unit 112 calculates the ratio of diffuse reflectance intensities by dividing the diffuse reflectance intensity of a first isosbestic wavelength (e.g., 545 nm) by the diffuse reflectance intensity of a second isosbestic wavelength (e.g., 390 nm).

In block 308, a hemoglobin concentration is determined by applying the calculated ratio to a predefined analytical expression. In one embodiment, an associated predefined linear equation (e.g., the analytical equation determined in method 200) with a known slope value and intercept value is used by processing unit 112 to determine the hemoglobin concentration of the tissue mass. For example, the calculated intensity ratio may be applied to the linear equation, y=mx+b (where y=hemoglobin concentration, x=calculated intensity ratio, m=slope value, and b=intercept value) in order to determine a hemoglobin concentration. Notably, this processing is conducted with greater efficiency as opposed to determining the hemoglobin concentration using a Monte Carlo algorithm. As indicated above, using a Monte Carlo algorithm takes a significant amount of time and processing resources that is not conducive for portable applications. It will be understood that various details of the presently disclosed subject matter may be changed without departing from the scope of the presently disclosed subject matter. Furthermore, the foregoing description is for the purpose of illustration only, and not for the purpose of limitation.

Claims

CLAIMS What is claimed is:

1. A system for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths, the system comprising:

a light source for emitting light onto a tissue mass; a measurement device for measuring diffuse reflectance from the tissue mass; and

a processing unit for calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured reflectance, and determining a hemoglobin concentration associated with the tissue mass by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths.

2. The system of claim 1 wherein the light source is at least one of an LED light source and xenon arc lamp and delivered by at least one of relay optics or a fiber optic probe equipped with illumination fibers.

3. The system of claim 1 wherein the diffuse reflectance is wavelength dependent diffuse reflectance.

4. The system of claim 1 wherein the measurement device includes at least one of a photomultiplier tube (PMT), a charged coupled device (CCD) unit, or a photodiode.

5. The system of claim 1 wherein the predefined analytical expression is a linear equation that indicates a relationship between the calculated ratio and the hemoglobin concentration.

6. The system of claim 1 wherein the tissue mass includes either an in vivo tissue mass or an ex vivo tissue mass.

7. The system of claim 1 wherein the two isosbestic wavelengths are 529 nm and 500 nm, 545 nm and 390 nm, 452 nm and 390 nm, 529 nm and 390 nm, 570 nm and 390 nm, 584 nm and 390 nm, or 500 nm and 390.

8. The system of claim 1 wherein the two isosbestic wavelengths are independent of scattering.

The system of claim 3 wherein the wavelength dependent diffuse reflectance is measured across a spectrum ranging from 360 nm to 800 nm.

The system of claim 1 wherein the measurement device is further configured to measure the diffuse reflectance of the tissue mass as an image.

The system of claim 1 wherein the predefined analytical expression is generated by determining diffuse reflectance intensities from a plurality of phantom scattering samples with known hemoglobin concentrations at the two isosbestic wavelengths, calculating a diffuse reflectance intensity ratio associated with the two isosbestic wavelengths for each of the phantom scattering samples, populating a database associated with the two isosbestic wavelengths with the known hemoglobin concentrations and corresponding calculated diffuse reflectance intensity ratios, and performing regression analysis using the hemoglobin concentrations and calculated intensity ratios in the database to generate the predefined analytical expression.

The system of claim 1 wherein the predefined analytical expression is generated by determining diffuse reflectance intensities from a simulation of a scattering medium with known hemoglobin concentrations at the two isosbestic wavelengths using a Monte Carlo algorithm wherein the diffuse reflectance intensities from the simulation are calibrated by a correction factor, calculating a diffuse reflectance intensity ratio associated with the two isosbestic wavelengths for each of the simulations, populating a database associated with the two isosbestic wavelengths with the known hemoglobin concentrations and corresponding calculated diffuse reflectance intensity ratios, and performing regression analysis using the hemoglobin concentrations and calculated intensity ratios in the database to generate the predefined analytical expression.

The system of claim 1 wherein the processing unit calculates the ratio of diffuse reflectance intensities by dividing the diffuse reflectance intensity of a first isosbestic wavelength by the diffuse reflectance intensity of a second isosbestic wavelength.

14. A method for determining hemoglobin concentration utilizing diffuse reflectance at isosbestic wavelengths, the method comprising:

emitting light onto a tissue mass;

measuring diffuse reflectance from the tissue mass; calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured diffuse reflectance; and determining a hemoglobin concentration associated with the tissue mass by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths.

15. The method of claim 14 wherein the diffuse reflectance is wavelength dependent diffuse reflectance.

16. The method of claim 14 wherein the predefined analytical expression is a linear equation that indicates the relationship between the calculated ratio and the hemoglobin concentration.

The method of claim 14 wherein the tissue mass includes either an in vivo tissue mass or an ex vivo tissue mass.

The method of claim 14 wherein the two isosbestic wavelengths wherein the two isosbestic wavelengths are 529 nm and 500 nm, 545 nm and 390 nm, 452 nm and 390 nm, 529 nm and 390 nm, 570 nm and 390 nm, 584 nm and 390 nm, or 500 nm and 390.

19. The method of claim 14 wherein the two isosbestic wavelengths are independent of scattering.

20. The method of claim 15 wherein the wavelength dependent diffuse reflectance is measured across a spectrum ranging from 360 nm to 800 nm.

21. The method of claim 14 wherein measuring the diffuse reflectance includes measuring the diffuse reflectance from the tissue mass as an image.

22. The method of claim 14 wherein the predefined analytical expression is generated by determining diffuse reflectance intensities from a plurality of phantom scattering samples with known hemoglobin concentrations at the two isosbestic wavelengths, calculating a diffuse reflectance intensity ratio associated with the two isosbestic wavelengths for each of the scattering phantom samples, populating a database associated with the two isosbestic wavelengths with the known hemoglobin concentrations and corresponding calculated diffuse reflectance intensity ratios, and performing regression analysis using the hemoglobin concentrations and calculated intensity ratios in the database to generate the predefined analytical expression.

The method of claim 14 wherein the predefined analytical expression is generated by determining diffuse reflectance intensities from a simulation of a scattering medium with known hemoglobin concentrations at the two isosbestic wavelengths using a Monte Carlo algorithm wherein the diffuse reflectance intensities from the simulation are calibrated by a correction factor, calculating a diffuse reflectance intensity ratio associated with the two isosbestic wavelengths for each of the simulations, populating a database associated with the two isosbestic wavelengths with the known hemoglobin concentrations and corresponding calculated diffuse reflectance intensity ratios, and performing regression analysis using the hemoglobin concentrations and calculated intensity ratios in the database to generate the predefined analytical expression.

The method of claim 14 wherein calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths includes dividing the diffuse reflectance intensity of a first isosbestic wavelength by the diffuse reflectance intensity of a second isosbestic wavelength.

A computer readable medium having stored thereon computer executable instructions that when executed by a processor of a computer control the computer to perform steps comprising:

emitting light onto a tissue mass;

measuring diffuse reflectance from the tissue mass;

calculating a ratio of diffuse reflectance intensities at two isosbestic wavelengths using the measured diffuse reflectance; and determining a hemoglobin concentration associated with the tissue mass by applying the calculated ratio to a predefined analytical expression associated with the two isosbestic wavelengths.