Surgery – Diagnostic testing – Measuring or detecting nonradioactive constituent of body...
Reexamination Certificate
2001-04-11
2003-06-03
Walberg, Teresa (Department: 3742)
Surgery
Diagnostic testing
Measuring or detecting nonradioactive constituent of body...
C600S310000, C600S322000, C600S326000, C356S039000
Reexamination Certificate
active
06574490
ABSTRACT:
TECHNICAL FIELD
The present invention generally relates to a quantitative spectroscopy system for measuring analyte concentrations or other attributes of tissue utilizing non-invasive techniques in combination with multivariate analysis. More specifically, the present invention relates to a quantitative near-infrared spectroscopy system, incorporating multiple subsystems in combination, providing precision and accuracy to measure analytes such as glucose at clinically relevant levels in human tissue.
BACKGROUND OF THE INVENTION
The non-invasive measurement of substances in the human body by quantitative spectroscopy has been found to be highly desirable, yet very difficult to accomplish. Non-invasive measurements via quantitative spectroscopy are desirable because they are painless, do not require a fluid draw from the body, carry little risk of contamination or infection, do not generate any hazardous waste and have short measurement times. A prime example of a desirable application of such technology is the non-invasive measurement of blood glucose levels in diabetic patients, which would greatly improve diabetes treatment. U.S. Pat. No. 5,379,764 to Barnes et al. discloses the necessity for diabetics to frequently monitor blood glucose levels. The more frequent the blood glucose levels are measured, the less likely the occurrence of large swings in blood glucose levels. These large swings are associated with the very undesirable short-term symptoms and long-term complications of diabetes. Such long-term complications include heart disease, arteriosclerosis, blindness, stroke, hypertension, kidney failure and premature death.
Several systems have been proposed for the non-invasive measurement of blood glucose levels. These systems have included technologies incorporating polarimetry, mid-infrared spectroscopy, Raman spectroscopy, Kromoscopy, fluorescence spectroscopy, nuclear magnetic resonance spectroscopy, radio-frequency spectroscopy, ultrasound, transdermal measurements, photoacoustic spectroscopy and near-infrared spectroscopy. However, despite these efforts, direct and invasive measurements (e.g., blood sampling by a lancet cut into the finger) are still necessary for most, if not all, presently FDA approved and commercially available glucose monitors. Because invasive measurements are painful, inconvenient and costly to the diabetic patient, sufficiently frequent blood glucose measurement, which is necessary to ensure effective diabetes management, is rarely achieved.
Of particular interest to the present invention are prior art systems which incorporate or generally utilize quantitative infrared spectroscopy as a theoretical basis for the analysis. In general, these methods involve probing glucose-containing tissue using infrared radiation in absorption or diffuse reflectance mode. It is known that glucose absorbs at multiple frequencies in both the mid- and near-infrared range. There are, however, other infrared active analytes in the tissue and blood that also absorb at similar frequencies. Due to the overlapping nature of these absorption bands, no single or specific frequency can be used for reliable non-invasive glucose measurement. Analysis of spectral data for glucose measurement thus requires evaluation of many intensities over a wide spectral range to achieve the sensitivity, precision, accuracy, and reliability necessary for quantitative determination.
For example, Robinson et al. in U.S. Pat. No. 4,975,581 disclose a method and apparatus for measuring a characteristic of unknown value in a biological sample using infrared spectroscopy in conjunction with a multivariate model that is empirically derived from a set of spectra of biological samples of known characteristic values. The above-mentioned characteristic is generally the concentration of an analyte, such as glucose, but also may be any chemical or physical property of the sample. The method of Robinson et al. involves a two-step process that includes both calibration and prediction steps.
In the calibration step, the infrared light is coupled to calibration samples of known characteristic values so that there is attenuation of at least several wavelengths of the infrared radiation as a function of the various components and analytes comprising the sample with known characteristic value. The infrared light is coupled to the sample by passing the light through the sample or by reflecting the light off the sample. Absorption of the infrared light by the sample causes intensity variations of the light that are a function of the wavelength of the light. The resulting intensity variations at a minimum of several wavelengths are measured for the set of calibration samples of known characteristic values. Original or transformed intensity variations are then empirically related to the known characteristics of the calibration samples using multivariate algorithms to obtain a multivariate calibration model. The model preferably accounts for subject variability, instrument variability and environment variability.
In the prediction step, the infrared light is coupled to a sample of unknown characteristic value, and a multivariate calibration model is applied to the original or transformed intensity variations of the appropriate wavelengths of light measured from this unknown sample. The result of the prediction step is the estimated value of the characteristic of the unknown sample. The disclosure of Robinson et al. is incorporated herein by reference.
A further method of building a calibration model and using such model for prediction of analytes and/or attributes of tissue is disclosed in commonly assigned U.S. Pat. No. 6,157,041 to Thomas et al., entitled “Method and Apparatus for Tailoring Spectrographic Calibration Models,” the disclosure of which is incorporated herein by reference.
In “Near-Infrared Spectroscopy for Non-invasive Monitoring of Metabolites”,
Clinical Chemistry Lab Med
2000, 38(2): 137-145, 2000, Heise et al. disclose the non-invasive measurement of glucose in the inner lip of a subject utilizing a Fourier transform infrared (FTIR) spectrometer and a diffuse reflectance accessory. The instrument used for this measurement contained a tungsten light source with an output that was collimated and sent into a Bruker IFS-66 FTIR spectrometer. The FTIR spectrometer modulated the light in a manner that created an interferogram and the collimated interferogram was sent to a diffuse reflectance accessory. The diffuse reflectance accessory was a bifurcated, Y-shaped fiber optic probe. The input fibers of the probe radiated the inner lip of a subject or a spectralon reference standard with the interferogram from the FTIR spectrometer. Light diffusely reflected from the inner lip was collected by the output fibers of the diffuse reflectance accessory and focused onto a liquid nitrogen cooled InSb detector. The optical interferograms were converted to an electrical signal by the InSb detector and the electrical signal was digitized by an analog-to-digital converter (ADC). The digitized interferogram was then converted into an NIR spectrum and a collection of these spectra and corresponding blood glucose reference values were correlated using multivariate techniques to produce a calibration for non-invasive glucose measurements. This instrument was able to produce cross-validated, leave-one-out-at-a-time glucose standard error of predictions (SEP) of 36.4 mg/dl. This level of accuracy and precision is not of clinical utility.
In “Near-Infrared Spectrometric Investigation of Pulsatile Blood Flow for Non-Invasive Metabolite Monitoring”, CP430,
Fourier Transform Spectroscopy:
11
th
International Conference, 1998, Heise et al. discuss the non-invasive measurement of glucose in the inner lip of a subject using multivariate analysis of spectra with pulsatile blood flow. Heise et al. assert that by taking the difference between the systolic and diastolic portions of the cardiac cycle, interferences can be removed and glucose predictions are done on the spectra due to the additional blood volume. The optical
Abbink Russell E.
Johnson Robert D.
Maynard John D.
Crompton Seager & Tufte LLC
Fuqua Shawntina
Rio Grande Medical Technologies, Inc.
Walberg Teresa
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