Surgery – Diagnostic testing – Measuring or detecting nonradioactive constituent of body...
Reexamination Certificate
2000-01-21
2003-07-01
Shaver, Kevin (Department: 3736)
Surgery
Diagnostic testing
Measuring or detecting nonradioactive constituent of body...
C600S306000, C600S473000
Reexamination Certificate
active
06587702
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Technical Field
This invention relates to the classification of individuals by features related to tissue properties. More particularly, the invention relates to methods of characterizing the tissue by features related to the absorbance spectrum of fat in adipose tissue, based on near-IR spectral measurements.
2. Discussion of the Prior Art
Near-infrared (NIR) tissue spectroscopy is a promising noninvasive technology that bases measurements on the irradiation of a tissue site with NIR energy in the 700-2500 nm wavelength range. The energy is focused onto an area of the skin and propagates according to the scattering and absorbance properties of the skin tissue. Thus, energy that is reflected by the skin or that is transmitted through the skin and is detected provides information about the tissue volume encountered. Specifically, the attenuation of the light energy at each wavelength is a function of the structural properties and chemical composition of the tissue. Tissue layers, each containing a unique heterogeneous particulate distribution, affect light absorbance through scattering. Chemical components such as water, protein, fat and blood analytes absorb light proportionally to their molar concentration through unique absorbance profiles or signatures. The measurement of tissue properties, characteristics or composition is based on the technique of detecting the magnitude of light attenuation resulting from its respective scattering and/or absorbance properties.
Blood Analyte Prediction
While noninvasive prediction of blood analytes, such as blood glucose concentration, has been pursued through NIR spectroscopy, the reported success and product viability has been limited by the lack of a system for compensating for variations between individuals that produce dramatic changes in the optical properties of the tissue sample. For example, see O. Khalil
Spectroscopic and clinical aspects of non
-
invasive glucose measurements,
Clin Chem; vol. 45: pp. 165-77 (1999); or J. Roe, B. Smoller,
Bloodless Glucose Measurements,
Critical Reviews in Therapeutic Drug Carrier Systems, vol. 15, no. 3, pp. 199-241, (1998). These variations are related to structural differences in the irradiated tissue sample between individuals and include, for example, the thickness of the dermis, distribution and density of skin collagen and percent body fat. While the absorbance features caused by structural variation are repeatable by subject, over a population of subjects they produce confounding nonlinear spectral variation. See C. Tan, B. Statham, R. Marks and P. Payne.
Skin thickness measurement by pulsed ultrasound: its reproducibility, validation and variability,
British Journal of Dermatology, vol. 106, pp. 657-667, (1982). Also see S. Shuster, M. Black, E. McVitie,
The influence of age and sex on skin thickness, skin collagen and density
British Journal of Dermatology, vol. 93, (1975). See also J. Durnin, M. Rahaman,
The assessment of the amount of fat in the human body from measurements of skin fold thickness,
British Journal of Nutrition, vol. 21, (1967).
Additionally, variations in the subject's physiological state affect the optical properties of tissue layers and compartments over a relatively short period of time. Such variations, for example, may be related to hydration levels, changes in the volume fraction of blood in the tissue, hormonal stimulation, temperature fluctuations and blood hemoglobin levels.
While these structural and state variations are the largest sources of variation in the measured near-infrared absorbance spectra, they are not indicative of blood analyte concentrations. Instead they cause significant nonlinear spectral variation that limits the noninvasive measurement of blood analytes through optically based methods. For example, several reported methods of noninvasive glucose measurement develop calibration models that are specific to an individual over a short period of time. See, K. Hazen,
Glucose determination in biological matrices using near
-
infrared spectroscopy,
Doctoral Dissertation, University of Iowa, (August 1995). Also see M. Robinson, R. Eaton, D. Haaland, G. Koepp, E. Thomas, B. Stallard and P. Robinson,
Noninvasive glucose monitoring in diabetic patients: a preliminary evaluation,
Clin. Chem, vol. 38/9, pp. 1618-1622, (1992). Also see S. Malin, T. Ruchti, T. Blank, S. Thennadil and S. Monfre,
Noninvasive prediction of glucose by near
-
infrared diffuse reflectance spectroscopy,
Clin. Chem, vol. 45:9, pp.1651-1658, (1999).
A related application, S. Malin, T. Ruchti,
An Intelligent System For Noninvasive Blood Analyte Prediction,
U.S. patent application Ser. No 09/359,191; filed Jul. 22, 1999, disclosed an apparatus and procedure for substantially reducing this problem, by classifying subjects according to spectral features that are related to the tissue characteristics prior to blood analyte prediction. The extracted features are representative of the actual tissue volume irradiated. The groups or classes are defined on the basis of tissue similarity such that the spectral variation within a class is small compared to the variation between classes. These internally consistent classes are more suitable for multivariate analysis of blood analytes since the largest source of spectral interference is substantially reduced. In this manner, by grouping individuals according to the similarity of spectral characteristics that represents the tissue state and structure, the confounding nonlinear variation described above is reduced and prediction of blood analytes is made more accurate.
The general method of classification relies on the determination of spectral features most indicative of the sampled tissue volume. The magnitude of such features represents an underlying variable, such as the thickness of tissue or level of hydration.
The absorbance of light by adipose tissue in the sub-dermis, consisting primarily of cells rich in triglycerides, a class of fatty substance, is among the most significant source of spectral variation in noninvasive near-infrared measurements. While adipose tissue profoundly influences the overall measurement, the volume fraction of fluid rich in blood analytes is relatively small compared to that present in other layers of the skin.
The dermis, for example, is richly supplied with a vascular network. At the interface between the dermis and subcutaneous fat is the deep vascular plexus, a collection of vessels that runs parallel to the skin surface. From the deep vascular plexus, blood vessels rise toward the skin surface to another dense parallel collection of vessels called the superficial vascular plexus, located 0.3 mm to 0.6 mm from the skin surface.
Consequently, the capillary beds of the dermis are targeted for irradiation and measurement of blood analytes, since they have a high volume fraction of analytes, such as glucose, that vary in accordance with actual blood concentration, compared to other layers of the skin. On the other hand, the absorbance of light by the constituents of adipose tissue contributes only confounding effects to the measurement of the targeted analyte, yet it represents, second only to the absorbance of water, the largest source of spectral variation. For example,
FIG. 1
shows a near-infrared absorbance spectrum measured on a human subject with large absorbance bands
101
,
102
,
103
, marked by arrows, due to fat stored in adipose tissue. The relative absorbance due to the presence of a typical blood analyte in the sampled tissue volume, such as glucose, is approximately three orders of magnitude smaller than the designated fat absorbance bands.
Thus, the absorbance of light by adipose tissue creates two major obstacles to accurate blood analyte determination. First, the total absorbance related to adipose tissue is a large interference and is not indicative of blood analyte concentrations. Compounding this interference is the fact that the varied attenuation of light by adipose tissue is difficult to model due to the complex nature of the di
Acosta George M.
Hazen Kevin H.
Makarewicz Marcy R.
Ruchti Timothy L.
Glenn Michael A.
Instrumentation Metrics, Inc
Kremer Matthew
Peil Christopher
Shaver Kevin
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