U.S. patent application number 10/071932 was filed with the patent office on 2002-09-19 for spectroscopic system employing a plurality of data types.
Invention is credited to Costa, Peter J., Flewelling, Ross, Hui, Kwong, Kaufman, Howard, Nordstrom, Robert J..
Application Number | 20020133073 10/071932 |
Document ID | / |
Family ID | 22351348 |
Filed Date | 2002-09-19 |
United States Patent
Application |
20020133073 |
Kind Code |
A1 |
Nordstrom, Robert J. ; et
al. |
September 19, 2002 |
Spectroscopic system employing a plurality of data types
Abstract
A system and method for classifying specimens using a plurality
of spectral data types. Spectra are recorded as amplitudes at a
series of discrete wavelengths. Pluralities of reference spectra
are recorded for specimens having known conditions. A spectrum of a
first type is observed for a test specimen. The specimen is
characterized as to a first known condition. In the event that the
specimen does not exhibit the first known condition, a spectrum of
a second type is observed and analyzed to determine which of a
plurality of conditions is to be ascribed to the test specimen. In
some embodiments, the test specimen can comprise human cervical
tissue, and the known conditions can include normal health,
metaplasia, CIN I and CIN II/III.
Inventors: |
Nordstrom, Robert J.;
(Hanover, MA) ; Costa, Peter J.; (Hudson, MA)
; Hui, Kwong; (Woburn, MA) ; Flewelling, Ross;
(Chelmsford, MA) ; Kaufman, Howard; (Newton,
MA) |
Correspondence
Address: |
TESTA, HURWITZ & THIBEAULT, LLP
HIGH STREET TOWER
125 HIGH STREET
BOSTON
MA
02110
US
|
Family ID: |
22351348 |
Appl. No.: |
10/071932 |
Filed: |
February 8, 2002 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10071932 |
Feb 8, 2002 |
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09738613 |
Dec 15, 2000 |
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6385484 |
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09738613 |
Dec 15, 2000 |
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09470071 |
Dec 22, 1999 |
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60113761 |
Dec 23, 1998 |
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Current U.S.
Class: |
600/426 ;
600/310 |
Current CPC
Class: |
A61B 5/0059 20130101;
A61B 5/0068 20130101 |
Class at
Publication: |
600/426 ;
600/310 |
International
Class: |
A61B 005/00 |
Goverment Interests
[0002] This invention was made with government support under
Contract No. CA 66481 awarded by National Cancer Institute, NIH.
The government may have certain rights in the invention.
Claims
What is claimed is:
1. A method of determining a condition of a test specimen, said
method comprising, identifying a plurality of first test specimens
having a first known condition and observing from each of said
first test specimens a first fluorescence spectrum characteristic
of said first known condition, obtaining an average reflectance
spectrum from said plurality of first test specimens, obtaining a
reflectance spectrum from a second test specimen that is observed
to produce a second fluorescence spectrum that is not
characteristic of said first known condition, obtaining a
reflectance spectrum residual by subtracting said average
reflectance spectrum from said reflectance spectrum obtained from
said second test specimen, and determining said condition of said
second test specimen based at least in part on an amplitude of one
or more features of said reflectance spectrum residual.
2. The method of claim 1, wherein said plurality of first test
specimens comprise a plurality of first tissue specimens and said
second test specimen comprises a second tissue specimen.
3. The method of claim 2, wherein said plurality of first tissue
specimens and said second tissue specimen comprise human cervical
tissue, said first known condition is a known state of health, and
said condition of said second test specimen is a state of health to
be determined.
4. The method of claim 2, wherein said known state of health
comprises one of the conditions of normal squamous tissue,
metaplasia, CIN I, and CIN II/III.
5. The method of claim 1, further comprising, obtaining additional
optical information from said second test specimen, and evaluating
said additional optical information with said fluorescence spectrum
and said reflectance spectrum from said second test specimen to
determine said condition of said second test specimen.
6. The method of claim 5, wherein said additional optical
information comprises video information.
7. The method of claim 5, wherein said additional optical
information comprises an optical image.
8. The method of claim 5, wherein said plurality of first test
specimens comprise a plurality of first tissue specimens and said
second test specimen comprises a second tissue specimen.
9. The method of claim 8, wherein said plurality of first tissue
specimens and said second tissue specimen comprise human cervical
tissue, said first known condition is a known state of health, and
said condition of said second test specimen is a state of health to
be determined.
10. The method of claim 8, wherein said known state of health
comprises one of the conditions of normal squamous tissue,
metaplasia, CIN I, and CIN II/III.
11. A spectroscopic system for determining a condition of a test
specimen, comprising, a data collection module that observes a
first fluorescence spectrum characteristic of a first known
condition from each of a plurality of first test specimens having
said first known condition, that observes a first reflectance
spectrum from each of said plurality of first test specimens, and
that observes a reflectance spectrum from a second test specimen
that is observed to produce a second fluorescence spectrum that is
not characteristic of said first known condition, a computation
module that compute an average reflectance spectrum from said first
reflectance spectrum from each of said plurality of first test
specimens, and that computes a reflectance spectrum residual by
subtracting said average reflectance spectrum from said reflectance
spectrum obtained from said plurality of second test specimens, and
an analysis module that determines a condition of said second test
specimen based at least in part on an amplitude of one or more
features of said reflectance spectrum residual.
12. The system of claim 11, wherein said plurality of first test
specimens comprise a plurality of first tissue specimens and said
second test specimen comprises a second tissue specimen.
13. The system of claim 12, wherein said plurality of first tissue
specimens and said second tissue specimen comprise human cervical
tissue, said first known condition is a known state of health, and
said condition of said second test specimen is a state of health to
be determined.
14. The system of claim 12, wherein said known state of health
comprises one of the conditions of normal squamous tissue,
metaplasia, CIN I, and CIN II/III.
15. The system of claim 11, wherein said data collection module
obtains additional optical information from said second test
specimen, and said analysis module evaluates said additional
optical information with said fluorescence spectrum and said
reflectance spectrum from said second test specimen to determine
said condition of said second test specimen.
16. The system of claim 15, wherein said additional optical
information comprises video information.
17. The system of claim 15, wherein said additional optical
information comprises an optical image.
18. The system of claim 15, wherein said plurality of first test
specimens comprise a plurality of first tissue specimens and said
second test specimen comprises a second tissue specimen.
19. The system of claim 18, wherein said plurality of first tissue
specimens and said second tissue specimen comprise human cervical
tissue, said first known condition is a known state of health, and
said condition of said second test specimen is a state of health to
be determined.
20. The system of claim 18, wherein said known state of health
comprises one of the conditions of normal squamous tissue,
metaplasia, CIN I, and CIN II/III.
21. A method of determining a disease state in a specimen, the
method comprising the steps of: obtaining a reflectance spectrum
from a test specimen having a fluorescence spectrum that is not
characteristic of a healthy tissue; subtracting an average
reflectance spectrum obtained from a plurality of specimens from
said reflectance spectrum to produce a reflectance spectrum
residual, each producing a fluorescence spectrum characteristic of
healthy tissue; and determining disease state in said test specimen
based upon one or more characteristics of said reflectance spectrum
residual.
22. The method of claim 21, wherein said test specimen is selected
from the group consisting of cervical tissue, intestinal tissue,
esophageal tissue, and skin tissue.
23. The method of claim 21, wherein said disease state is selected
from the group consisting of normal squamous tissue, metaplasia,
CIN I, and CIN II/III.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation-in-part of U.S. patent
application Ser. No. 09/470,071, filed Dec. 22, 1999, which claims
priority to and the benefit of U.S. provisional patent application
Serial No. 60/113,761, filed Dec. 23, 1998, and this application is
related to the U.S. patent application entitled, "System for
Normalizing Spectra" and identified by Attorney Docket Number
MDS-020, filed on even date herewith, and to the U.S. patent
application entitled, "Spectral Data Classification Of Samples" and
identified by Attorney Docket Number MDS-021, filed on even date
herewith. All of the above applications are assigned to the common
assignee of this application, and are hereby incorporated by
reference.
FIELD OF THE INVENTION
[0003] This invention relates generally to spectroscopic systems.
More particularly, in one embodiment, the invention relates to a
spectroscopic system for characterizing test specimens using a
plurality of spectral data types.
BACKGROUND OF THE INVENTION
[0004] Spectral analysis of biological specimens has been used for
disease diagnosis. In general, spectra are recorded as values of
amplitude, typically measured as a response to an excitation, as a
function of wavelength (or the inverse of wavelength, namely
frequency). In the field of spectral analysis, different kinds of
information are conveyed by different spectral types. For example,
fluorescence spectra are recorded using a source of excitation
illumination that is absorbed by a specimen and that causes the
specimen to emit a fluorescence spectrum that depends in part on
the transfer of energy within and among atoms and/or molecules in
the specimen. An illumination source for use in observing and
recording fluorescence spectra generally operates at a selected
monochromatic wavelength, or a narrow range of wavelengths.
Different sources of illumination that operate at different
wavelengths can excite different constituents of a specimen. In
addition, different sources of illumination that operate at
different wavelengths can excite the same constituent with
different efficiencies. Thus, a fluorescence spectrum can depend on
both the excitation wavelength that is used to illuminate a
specimen and on the composition of the specimen itself. Other
effects also play a role in determining a fluorescence spectrum,
for example, instrumental effects, effects relating to polarization
of the illumination, or thermal effects.
[0005] Some progress has been made in using various optical
spectral methods for analysis of test specimens, including
biological specimens. However, the wide variety of physical and
chemical influences present in a test specimen that play roles in
determining an observed spectrum make difficult both the choice of
a suitable illumination source, and the interpretation of the
resulting spectrum. This is in part true because there are so many
influences on the kind and amount of information that an optical
spectrum conveys that it is hard to find clear cause and effect
relationships among the multitude of competing influences.
SUMMARY OF THE INVENTION
[0006] The invention provides methods of determining the disease
state of a biological specimen based upon a reflectance spectrum
residual derived by subtracting from a reflectance spectrum
obtained from a test specimen an average reflectance spectrum
obtained from a plurality if healthy specimens. In a preferred
embodiment, members of the plurality of healthy specimens are
determined to be healthy based upon the fluorescence spectra
emitted by those samples. Typically, the specimen to be tested
exhibits a fluorescence spectrum that is not characteristic of
healthy tissue.
[0007] The reflectance spectrum residual provides a criterion for
diagnostic classification of a specimen that is judged to be
indeterminate in classification by its fluorescence spectrum alone.
Accordingly, methods of the invention resolve diagnostic
ambiguities created when a specimen produces a fluorescence
spectrum that is not characteristic of a healthy tissue. Similarly,
methods of the invention are also useful to resolve diagnostic
ambiguities created when the fluorescence spectrum of a test
specimen is not characteristic of any known disease state.
[0008] In one aspect, the invention provides a method of
determining a condition of a test specimen. The method comprises
recording both fluorescence and reflectance spectra from specific
specimen. The method then comprises identifying a plurality of
specimens having a fluorescence spectrum characteristic of a known
condition; obtaining an average reflectance spectrum based upon the
plurality of first test specimens; obtaining a reflectance spectrum
from a test specimen that produces a fluorescence spectrum that is
not characteristic of the known condition; and obtaining a
reflectance spectrum residual by subtracting the average
reflectance spectrum from the reflectance spectrum obtained from
the test specimen. Determination of the condition of the test
specimen is based upon the reflectance spectrum residual. In a
preferred embodiment, the condition of the test specimen is based
upon an amplitude of one or more features of the reflectance
spectrum residual. For purposes of the invention a "condition" is a
state of disease, including a healthy state or simply the
physiological makeup of the specimen and/or the patient from whom
it was obtained.
[0009] In one embodiment, the plurality of specimens producing the
average reflectance spectrum comprises tissue specimens and the
test specimen is a tissue specimen of the same type. In one
embodiment, the tissue specimens are human cervical tissue
specimens, the condition of which is healthy, and the condition of
the test specimen is determined by methods of the invention. In one
embodiment, cervical tissue producing the average reflectance
spectrum are selected from normal squamous tissue, metaplasia, mile
cervical intraepithelial neoplasia (CIN I), and moderate to severe
cervical intraepithelial neoplasia (CIN II/III). In another
embodiment, methods of the invention further comprise obtaining
additional optical information from the test specimen, and
evaluating the additional optical information in comparison to the
fluorescence spectrum and the reflectance spectrum from the test
specimen to determine the condition of the test specimen. In one
embodiment, the additional optical information is video
information. In another embodiment, the additional optical
information is an optical image.
[0010] In one aspect, the invention relates to a spectroscopic
system for determining a condition of a test specimen. The system
comprises a data collection module that collects a fluorescence
spectrum characteristic of a known condition from each of a
plurality of first specimens, observes a reflectance spectrum from
each member of the plurality, and observes a reflectance spectrum
from a test specimen that is observed to produce a second
fluorescence spectrum that is not characteristic of the known
condition. The system further comprises a computation module that
computes an average reflectance spectrum based upon each member of
the plurality of first specimens, and that computes a reflectance
spectrum residual by subtracting the average reflectance spectrum
from the reflectance spectrum obtained from a test specimen, and an
analysis module that determines the condition of the test specimen
based at least in part upon the reflectance spectrum residual.
[0011] The foregoing and other objects, aspects, features, and
advantages of the invention will become more apparent from the
following description and from the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The objects and features of the invention can be better
understood with reference to the drawings described below, and the
claims. The drawings are not necessarily to scale, emphasis instead
generally being placed upon illustrating the principles of the
invention. In the drawings, like numerals are used to indicate like
parts throughout the various views.
[0013] FIG. 1 shows an exemplary spectroscopic system that employs
a plurality of spectral types according to an illustrative
embodiment of the invention;
[0014] FIG. 2 shows an exemplary operational block diagram of the
spectroscopic system of FIG. 1;
[0015] FIG. 3 is a detailed schematic flow diagram showing
exemplary steps of combining a fluorescence spectrum analysis
described more fully in FIG. 6 with a reflectance spectrum analysis
described more fully in FIG. 7 to perform tissue characterization
according to an illustrative embodiment of the invention;
[0016] FIG. 4 is a diagram showing an exemplary fluorescence
spectrum recorded using the spectroscopic system of FIG. 1;
[0017] FIG. 5 is a diagram showing an exemplary reflectance
spectrum recorded using the spectroscopic system of FIG. 1;
[0018] FIG. 6 is a schematic flow diagram depicting an analysis of
a fluorescence spectrum in a system according to an illustrative
embodiment of the invention; and
[0019] FIG. 7 is a schematic flow diagram depicting an analysis of
a reflectance spectrum in a system according to an illustrative
embodiment of the invention.
DETAILED DESCRIPTION
[0020] The invention relates to the use of multiple types of
spectral data for determining the status of a test specimen. In the
present invention, a first spectral observation is used to
distinguish between a first condition and a plurality of other
conditions, and a second observation using information obtained
from a different type of spectral data is used to distinguish among
the plurality of other conditions. The invention will be described
in terms of embodiments that relate to the use of multiple optical
spectra in characterization systems and methods, particularly in
the area of medical diagnostics, and especially as such use relates
to the analysis of spectra obtained from human cervical tissue in
the detection of cervical cancer. However, the invention has
applicability generally in the area of characterization of test
specimens based on analysis of a plurality of optical spectra
types.
[0021] FIG. 1 depicts an exemplary spectroscopic system 100
employing a plurality of spectral data types in methods and systems
according to an illustrative embodiment of the invention. The
spectroscopic system includes a console 102 connected to a probe
104 by a cable 106. The cable 106 carries electrical and optical
signals between the console 102 and the probe 104. The probe 104
accommodates a disposable component 108 which used only once, and
discarded after such use. The console 102 and the probe 104 are
mechanically connected by an articulating arm 110, which can also
support the cable 106. The console 102 contains much of the
hardware and the software of the system, and the probe 104 contains
the necessary hardware for making suitable spectroscopic
observations. The details of the system are further explained in
conjunction with FIG. 2.
[0022] FIG. 2 shows an exemplary operational block diagram 200 of a
spectroscopic system of the type depicted in FIG. 1. According to
an illustrative embodiment, the spectroscopic system of FIGS. 1 and
2 is subtantially the same as single-beam spectrometer devices, but
is adapted to include the features of the invention. The console
102 includes a computer 202 which executes software that controls
the operation of the spectroscopic system 100. The software
includes one or more modules recorded on machine-readable media,
which can be any medium such as magnetic disks, magnetic tape,
CD-ROM, semiconductor memory, or the like. Preferably, the
machine-readable medium is resident within the computer 202. In
alternative embodiments, the machine-readable medium can be
connected to the computer 202 by a communication link. In
alternative embodiments, one can substitute computer insructions in
the form of hardwired logic for software, or one can substitute
firmware (i.e., computer instructions recorded on devices such as
PROMs, EPROMS oe EEPROMs, or the like) for software. The term
machine-readable instructions as used herein is intended to
encompass software, hardwired logic, firmware and the like.
[0023] The computer 202 is a general purpose computer. The computer
202 can be an embedded computer, or a personal computer such as a
laptop or desktop computer, that is capable of running the
software, issuing suitable control commands, and recording
information in real time. The computer 202 has a display 204 for
reporting information to an operator of the spectroscopic system
100, a keyboard 206 for enabling the operator to enter information
and commands, and a printer 208 for providing a print-out, or
permanent record, of measurements made by the spectroscopic system
100 and for printing diagnostic results, for example, for inclusion
in the chart of a patient. As described below in more detail, in an
illustrative embodiment of the invention, some commands entered at
the keyboard, enable a user to select a particular spectrum for
analysis or to reject a spectrum, and to select particular segments
of a spectrum for normalization. Other commands enable a user to
select the wavelength range for each particular segment and to
specify both wavelength contiguous and non-contiguous segments.
[0024] The console 102 also includes an ultraviolet (UV) source 210
such as a nitrogen laser or a frequency-tripled Nd:YAG laser, a
white light source 212 such as one or more Xenon flash lamps, and
control electronics 214 for controlling the light sources both as
to intensity and as to the time of onset of operation and the
duration of operation. One or more power supplies 216 are included
in the console 102, to provide regulated power for the operation of
all of the components. The console 102 also includes at least one
spectrometer and at least one detector (spectrometer and detector
218) suitable for use with each of the light sources. In some
embodiments, a single spectrometer can operate with both the UV
light source and the white light source. In some embodiments, the
same detector can record UV and white light signals, and in some
embodiments different detectors are used for each light source.
[0025] The console 102 also includes coupling optics 220 to couple
the UV illumination from the UV light source 210 to one or more
optical fibers in the cable 106 for transmission to the probe 104,
and for coupling the white light illumination from the white light
source 212 to one or more optical fibers in the cable 106 for
transmission to the probe 104. The console 102 also includes
coupling optics 222 to couple the spectral response of a specimen
to UV illumination from the UV light source 210 observed by the
probe 104 and carried by one or more optical fibers in the cable
106 for transmission to the spectrometer and detector 218, and for
coupling the spectral response of a specimen to the white light
illumination from the white light source 212 observed by the probe
104 and carried by one or more optical fibers in the cable 106 for
transmission to the spectrometer and detector 218. The console 102
includes a footswitch 224 to enable an operator of the
spectroscopic system 100 to signal when it is appropriate to
commence a spectral observation by stepping on the switch. In this
manner, the operator has his or her hands free to perform other
tasks, for example, aligning the probe 104.
[0026] The console 102 includes a calibration port 226 for
calibrating the optical components of the spectrometer system. The
operator places the probe 104 in registry with the calibration port
226 and issues a command that starts the calibration operation. In
the calibration operation, a calibrated light source provides
illumination of known intensity as a function of wavelength as a
calibration signal. The probe 104 detects the calibration signal.
The probe 104 transmits the detected signal through the optical
fiber in the cable 106, through the coupling optics 222 to the
spectrometer and detector 218. A test spectral result is obtained.
A calibration of the spectral system is computed as the ratio of
the amplitude of the known illumination at a particular wavelength
divided by the test spectral result at the same wavelength.
[0027] The probe 104 includes probe optics 230 for illuminating a
specimen to be analyzed with UV and white light from the UV source
210 and the white light source 212, and for collecting the
fluorescent and backscatter (or reflectance) illumination from the
specimen that is being analyzed. The probe includes a scanner
assembly 232 that provides illumination from the UV source 210 in a
raster pattern over a target area of the specimen of cervical
tissue to be analyzed. The probe includes a video camera 234 for
observing and recording visual images of the specimen under
analysis. The probe 104 includes a targeting souce 236, which can
be used to determine where on the surface of the specimen to be
analyzed the probe 104 is pointing. The probe 104 also includes a
white light illuminator 238 to assist the operator in visualizing
the specimen to be analyzed. Once the operator aligns the
spectroscopic system and depresses the footswitch 224, the computer
202 controls the actions of the light sources 210, 212, the
coupling optics 220, the transmission of light signals and
electrical signals through the cable 106, the operation of the
probe optics 230 and the scanner assembly 232, the retreival of
observed spectra via the cable 106, the coupling of the observed
spectra via the coupling optics 222 into the spectrometer and
detector 218, the operation of the spectrometer and detector 218,
and the subsequent signal procesing and analysis of the recorded
spectra.
[0028] FIG. 3 is a detailed schematic flow diagram 300 showing
exemplary steps of combining the fluorescence spectrum analysis
described more fully in FIG. 6 below with the reflectance spectrum
analysis described more fully in FIG. 7 below to perform tissue
characterization according to an illustrative embodiment of the
invention. Step 310 indicates that the results presented in FIG. 6
for analysis of fluorescence spectra from a test specimen of
unknown condition or unknown state of health are available. At step
320, the computer 202 determines whether the test specimen can be
classified as "normal," or "metaplasia," or can not be classified
by fluorescence spectroscopy alone. This process is described in
detail at step 665 of FIG. 6 below. As indicated in step 325, a
decision is taken as to whether the test specimen has a definitive
state of health, for example that the specimen is "normal." If the
test specimen can be classified, for example as normal, the method
ends at step 330.
[0029] In the event that a definitive condition or state of health
cannot be ascribed to a test specimen, the computer 202 further
analyses information available from a reflectance spectrum or from
a plurality of reflectance spectra taken from the test specimen. At
step 335, the computer 202 provides reflectance spectra processed
according to the systems and methods described in connection with
FIG. 7 below.
[0030] If the specimen cannot be classified, a mean normalization
step is performed by computer 202, as indicated at step 340. This
mean normalization step is described in detail at step 755 of FIG.
7 below. The mean normalization is carried out using a plurality of
reflectance spectra taken from specimens that are known to
represent normal squamous tissue. In one embodiment, a single test
specimen is examined at multiple locations, each location measuring
approximately one millimeter in diameter. If one or more locations
of the test specimen provide fluorescence spectra that indicate
that those locations can be classified as representing normal
squamous tissue, using the methods and systems described in FIG. 6
below, the reflectance spectra recorded from those locations are
used to mean normalize the reflectance spectra obtained from
locations that are not capable of being classified as "normal" or
"metaplasia" solely on the basis of fluorescence spectra.
[0031] As indicated in step 350, the computer 202 can carry out an
analysis using a metric as described in detail at FIG. 7, step 760
below, for example using the Mahalanobis distance as a metric in
N-dimensional space. In one embodiment, the test reflectance
spectra are truncated to the wavelength regions 391 nm to 484 nm,
and 532 nm to 625 nm. In one embodiment, the classifications CIN I
and CIN II/II are the classifications that are possible for a test
spectrum that is neither classified as "normal" nor "metaplasia" by
fluorescence spectral analysis. As indicated at step 350, the
computer 202 classifies the test specimen as having a condition or
state of health selected from CIN I and CIN II/II based on the
value of the metric computed by the computer 202, provided that the
value of the metric does not exceed a pre-determined maximum
value.
[0032] At step 360, the computer 202 presents the results of the
classification of the test specimen, as a condition or state of
health corresponding to one of normal, metaplasia, CIN I and CIN
II/III.
[0033] FIG. 4 is a diagram 400 showing an exemplary fluorescence
spectrum recorded using the spectroscopic system of FIG. 1. In FIG.
4, a curve 410 having an amplitude defined in terms of number of
counts, for example a signal strength expressed as numbers of
photons, as indicated along the vertical axis 420. An amplitude is
plotted against a wavelength of light expressed in nm, as indicated
along the horizontal axis 430. Such spectra can be recorded using
the methods and systems described in FIGS. 1-3 with an illumination
source that provides optical excitation comprising a substantially
monochromatic source in the ultraviolet portion of the optical
spectrum. The exemplary fluorescence spectrum depicted in FIG. 4
was recorded from human cervical tissue using ultraviolet
illumination.
[0034] FIG. 5 is a diagram 500 showing an exemplary reflectance
spectrum recorded using the spectroscopic system of FIG. 1. In FIG.
5, a curve 510 having an amplitude defined in terms of number of
counts, for example a signal strength expressed as numbers of
photons, as indicated along the vertical axis 520. An amplitude is
plotted against a wavelength of light expressed in nm, as indicated
along the horizontal axis 530. Such spectra can be recorded using
the methods and systems described in FIGS. 1-3 with an illumination
source that provides optical excitation comprising a broadband
source in the visible portion of the optical spectrum. The
exemplary reflectance spectrum depicted in FIG. 5 was recorded from
human cervical tissue using broadband visible light
illumination.
[0035] FIG. 6 is a schematic flow diagram 600 depicting an analysis
of a fluorescence spectrum in a system according to an illustrative
embodiment of the invention. Fluorescence spectra such as the
exemplary spectrum of FIG. 4 are suitable for the analysis
described hereafter. The spectral analysis involves the measurement
of spectra from a test specimen whose condition is to be
determined, and employs a plurality of reference spectra taken from
one or more specimens having known conditions. Those of ordinary
skill in the spectroscopic arts will understand that the reference
spectra can be obtained before, after, or at the same operation
session as the test spectrum or spectra are obtained. For purposes
of exposition, the treatment of the reference spectra will be
described first. The treatment of a test spectrum will then be
described.
[0036] In the present application, the term "characteristic
N-dimensional value" should be understood to comprehend whichever
of a point, a volume, a surface, a probability distribution or the
like is used in the subsequent analysis. In mathematical terms, the
"characteristic N-dimensional value" can be understood to be an
ordered N-tuple of values, each one of which values can be
expressed in its own dimensional units. It is well known in the
spectroscopic arts is to record one or more reference spectra from
specimens that are known to have specific conditions. For example,
it is known to record reference spectra from specimens having known
states of health or known disease conditions. Reference spectra can
be manipulated using the same pre-processing methods that are
applied to spectra recorded from test specimens, so as to be able
to compare spectra having substantially similar processing
histories.
[0037] The computer 202 can store in a machine-readable memory for
later use the information comprising the various characteristic
N-dimensional values that are computed, as well as the
corresponding known condition. The computer 202 can also similarly
store in a machine-readable memory the various reference
reflectance spectra data that were obtained.
[0038] Turning to the discussion of the recording and analysis of a
test spectrum, as indicated in FIG. 6 at step 610, an operator
collects and records a test fluorescence spectrum or a plurality of
test fluorescence spectra from a test specimen of unknown state of
health or unknown condition.
[0039] Step 615 indicates that the computer 202 can smooth the raw
data. Various mathematical smoothing techniques are known in the
art, such as computing moving averages, or applying filters to
remove noise, for example using well-known convolution methods.
[0040] Step 620 indicates that the computer 202 can subtract a
background reading, for example a reading taken using the systems
and methods of FIGS. 1-3 with a standard specimen, or taken without
a test specimen, from the reading observed from a test specimen or
a reference specimen. In step 625, the computer 202 can average a
plurality of spectral data taken from the same specimen, for
example, the computer 202 can average N repeated spectral
measurements taken from the same location of a single specimen,
where N is an integer greater than 1.
[0041] In step 630, the computer 202 can correct the wavelength
assigned to a particular amplitude of a spectrum, or can correct a
plurality of such wavelengths. The computer 202 can perform such a
correction by using a pre-recorded calibration file recorded from
an optical source having lines at known wavelengths, for example a
spectrum recorded from a lamp having the characteristic emission
lines of mercury, or another well known emission source. The
computer 202 uses the known wavelengths of the characteristic
emission lines to determine a relationship between wavelength and a
data channel number assigned by the computer 202 and an A/D
converter to the characteristic spectra. The computer 202 can
determine a wavelength for each A/D channel and thus knows the
correct wavelength to assign to each amplitude.
[0042] As indicated in step 635, the computer 202 can correct the
spectral data for effects ascribable to open air, such as
absorption due to atmospheric constituents, for example gases such
as water vapor, carbon dioxide, and others that have strong
absorption at characteristic wavelengths.
[0043] Step 640 indicates that the computer 202 can correct for
instrument-induced features by dividing an observed spectrum by an
instrument function. The instrument function is obtained by
dividing a known, accurate spectrum, such as a NIST-traceable
tungsten lamp spectrum, by the observed spectrum recorded for
illumination from such a lamp passing through the instrument of
FIGS. 1 and 2. Dividing a first spectrum by a second spectrum
involves dividing the respective amplitudes of the first spectrum
by the corresponding amplitudes for the second spectrum and
recording the result of each such division in a file as a function
of the respective wavelengths, such as the instrument function.
[0044] Step 645 indicates that the computer 202 can truncate a
spectrum to limit the data saved to a file as amplitudes
corresponding to the reduced set of wavelengths, rather than all
the wavelengths that the spectral instrument of FIGS. 1-2 is
capable of recording. The truncation is performed to avoid saving
data that has no significance, such as data corresponding to
amplitudes having zero intensity for wavelengths beyond some
predetermined value. In some embodiments, the operator can use the
keyboard 206, or another input mechanism, to indicate one or both
wavelength limits of the truncated wavelength range to be
retained.
[0045] As indicated at step 650, the computer 202 can reduce the
number of amplitudes, each amplitude corresponding to a selected
wavelength, that are used to characterize a spectrum. In some
embodiments, the number of amplitudes used to characterize a
spectrum is fifty (50). In principle, as few as three amplitudes at
three wavelengths may be sufficient to characterize a fluorescence
spectrum as representing a test specimen comprising healthy normal
squamous cells as distinguished from other tissue types having
other states of health.
[0046] As indicated at step 655, the computer 202 can normalize the
reduced spectral data using a system and method called
normalization using non-uniform segmentation. Normalization using
non-uniform segment normalization is described in detail in the
co-pending patent application entitled "System for Normalizing
Spectra," which application is commonly assigned to the assignee of
the present application, and which application is incorporated
herein by reference in its entirety.
[0047] In one embodiment, where the metric to be used in
classifying a test specimen is a Mahalanaobis distance, the
computer 202 performs a mathematical procedure intended to
guarantee that a matrix used in further analytical steps is capable
of being inverted. Matrix inversion is a mathematical process well
known in the matrix mathematical arts. In one embodiment, the
matrix that is computed is called a Friedman matrix. The data used
in the calculation of the Friedman matrix is obtained from
reference data recorded and stored in machine-readable format. The
step of computing the appropriate Friedman matrix can be performed
at any time after the reference spectral data is available.
[0048] Computation of the Mahalanobis distance requires the
inversion of a weighting matrix. One approach (i.e., Linear
Discriminant Analysis) utilizes the inverse of the pooled
within-groups covariance while another method (Quadratic
Discriminant Analysis) employs the inverse of each within-group
covariance. When a "large" number of wavelengths are used (e.g.,
for large p), either of the aforementioned matrices can be singular
and hence cannot be inverted. Therefore, an alternate weighting
matrix called the Friedman matrix is used. .gamma.
[0049] The Friedman matrix is the weighted linear combination of a
within-group covariance matrix C.sub.j and the pooled within-group
covariance C that is a function of the Friedman parameters .gamma.
and .lambda.. These parameters are selected from the unit interval
[0,1] It is important to note that the Friedman parameters are not
physical quantities whose values carry classification information.
Rather, they are used to insure that the weighting (Friedman)
matrix is non-singular. Equation 1 details the p-by-p Friedman
matrix, which is denoted by .OMEGA.. 1 j ( , ) = ( 1 - ) [ ( 1 - )
C j + C ] + p t r [ ( 1 - ) C j + C ] I p x p Eqn . 1
[0050] N note that tr(A) is the trace of the matrix A, namely the
sum of the diagonal elements. Also, I.sub.pxp is the p-dimensional
identity matrix. 2 A = [ a 1 , 1 a 1 , 2 a 1 , n a 2 , 1 a 2 , 2 a
2 , n a n , 1 a n , 2 a n , n ] t r ( A ) = k = 1 n a k , k Eqn . 2
I p x p = [ 1 0 0 0 1 0 0 0 1 ] p x p Eqn . 3
[0051] Let s(.LAMBDA..sub.p) be ap-dimensional spectrum. The
Mahalanobis distance d from s(.LAMBDA..sub.p) to the group mean
.mu..sub.j with respect to the associated Friedman matrix
.OMEGA..sub.j(.gamma.,.lambda.) and Friedman parameters .gamma. and
.lambda. is given in equation 4 below.
d(s(.LAMBDA..sub.p),.mu..sub.j)={square root}{square root over
(.vertline.(s(.LAMBDA..sub.9)-.mu..sub.j).multidot..OMEGA..sub.j(.gamma.,-
.lambda.).sup.-1.multidot.(s(.LAMBDA..sub.p)-.mu..sub.j).sup.T.vertline.)}
Eqn. 4
[0052] Where other metrics are used to classify a test spectrum and
a test specimen, the step 670 can be replaced by the appropriate
computation.
[0053] As indicated at step 660, the computer 202 computes a metric
from each test spectrum (or from an average value representing a
plurality of spectra, such as performed at step 625) to each
characteristic N-dimensional value for the reference spectra
recorded. In one embodiment, the metric can be a Mahalanobis
distance, as indicated above. In other embodiments, the metric can
be the square root of the sum of the squares of the differences in
coordinates in the N-dimensional space, or the metric can be the
Bhattacharyya distance.
[0054] At step 665, the computer 202 examines the results obtained
in step 660, and determines a classification for the test specimen,
based on the metrics computed with respect to the test fluorescence
spectrum and a classification rule or relation. In one embodiment,
the classification relation is that the condition of the test
specimen is assigned as the condition corresponding to the
reference spectrum constellation or set having the Mahalanobis
shortest distance, provided that the shortest Mahalanobis distance
is less than a pre-determined minimum distance. In one embodiment,
if no Mahalanobis distance is less than a pre-determined minimum
distance, the test spectrum is discarded as being incapable of
being classified, or indeterminate.
[0055] In one embodiment, the test fluorescence spectrum can be
compared to multiple sets of reference spectra in a single
comparison. In one embodiment, the computations can be repeated for
different sets of reference conditions. For example, a test
fluorescence spectrum from a test specimen can be compared in a
first computation to reference fluorescence spectral data for
normal squamous tissue and CIN II/III tissue, compared in a second
computation to reference fluorescence spectral data for normal
squamous tissue and CIN I tissue, and compared in a third
computation to reference fluorescence spectral data for normal
squamous tissue and metaplasia tissue. If the test fluorescence
spectrum is classified in each of the three comparisons as being
more closely related to the reference spectra for normal squamous
tissue, the test specimen can be classified by the computer 202 as
having normal health, and the classification process is complete.
However, if the test fluorescence spectrum is classified in either
of the comparisons involving CIN I or CIN II/III as being less
closely related to the reference spectra for normal squamous tissue
than one of the other conditions or states of health (namely CIN I,
or CIN II/III), the computer 202 can report that the state of
health of the test specimen is not clearly that of normal squamous
tissue, and that further analysis is in order. In one embodiment,
the further analysis involves the recording and examination of
reflectance spectra.
[0056] FIG. 7 is a schematic flow diagram 700 depicting an analysis
of a reflectance spectrum in a system according to an illustrative
embodiment of the invention. Reflectance spectra such as the
exemplary spectrum of FIG. 5 are suitable for the analysis
described hereafter. The spectral analysis involves the measurement
of spectra from a test specimen whose condition is to be
determined, and employs a plurality of reference spectra taken from
one or more specimens having known conditions. Those of ordinary
skill in the spectroscopic arts will understand that the reference
spectra can be obtained before, after, or at the same operation
session as the test spectrum or spectra are obtained.
[0057] The computer 202 can store in a machine-readable memory for
later use the information comprising the various characteristic
N-dimensional values that are computed, as well as the
corresponding known condition. The computer 202 can also similarly
store in a machine-readable memory the various reference
reflectance spectra data that were obtained.
[0058] Turning to the discussion of the recording an analysis of a
test spectrum, as indicated in FIG. 7 at step 710, an operator
collects and records a test reflectance spectrum or a plurality of
test reflectance spectra from a test specimen of unknown state of
health or unknown condition.
[0059] Step 715 indicates that the computer 202 can smooth the raw
data. Various mathematical smoothing techniques are known in the
art, such as computing moving averages, or applying filters to
remove noise, for example using well-known convolution methods.
[0060] Step 720 indicates that the computer 202 can subtract a
background reading, for example a reading taken using the systems
and methods of FIGS. 1-3 with a standard specimen, or taken without
a test specimen, from the reading observed from a test specimen or
a reference specimen. In step 725, the computer 202 can average a
plurality of spectral data taken from the same specimen, for
example, the computer 202 can average N repeated spectral
measurements taken from the same location of a single specimen,
where N is an integer greater than 1.
[0061] In step 730, the computer 202 can correct the wavelength
assigned to a particular amplitude of a spectrum, or can correct a
plurality of such wavelengths. The computer 202 can perform such a
correction by using a pre-recorded calibration file recorded from
an optical source having lines at known wavelengths, for example a
spectrum recorded from a lamp having the characteristic emission
lines of mercury, or another well known emission source. The
computer 202 uses the known wavelengths of the characteristic
emission lines to determine a relationship between wavelength and a
data channel number assigned by the computer 202 and an AID
converter to the characteristic spectra. The computer 202 can
determine a wavelength for each A/D channel and thus knows the
correct wavelength to assign to each amplitude.
[0062] As indicated in step 735, the computer 202 can correct the
spectral data for effects ascribable to open air, such as
absorption due to atmospheric constituents, for example gases such
as water vapor, carbon dioxide, and others that have strong
absorption at characteristic wavelengths.
[0063] Step 740 indicates that the computer 202 can correct for
instrument-induced features by dividing an observed spectrum by an
instrument function. The instrument function is obtained by
dividing a known, accurate spectrum, such as a NIST-traceable
tungsten lamp spectrum, by the observed spectrum recorded for
illumination from such a lamp passing through the instrument of
FIGS. 1 and 2. Dividing a first spectrum by a second spectrum
involves dividing the respective amplitudes of the first spectrum
by the corresponding amplitudes for the second spectrum and
recording the result of each such division in a file as a function
of the respective wavelengths, such as the instrument function.
[0064] Step 745 indicates that the computer 202 can truncate a
spectrum to limit the data saved to a file as amplitudes
corresponding to the reduced set of wavelengths, rather than all
the wavelengths that the spectral instrument of FIGS. 1-2 is
capable of recording. The truncation is performed to avoid saving
data that has no significance, such as data corresponding to
amplitudes having zero intensity for wavelengths beyond some
predetermined value. In some embodiments, the operator can use the
keyboard 206, or another input mechanism, to indicate one or both
wavelength limits of the truncated wavelength range to be
retained.
[0065] As indicated at step 750, the computer 202 can reduce the
number of amplitudes, each amplitude corresponding to a selected
wavelength, that are used to characterize a spectrum. In some
embodiments, the number of amplitudes used to characterize a
spectrum is fifty (50). In principle, as few as three amplitudes at
three wavelengths may be sufficient to characterize a reflectance
spectrum as representing a test specimen comprising healthy normal
squamous cells as distinguished from other tissue types having
other states of health.
[0066] As indicated at step 755, the computer 202 can normalize the
reduced spectral data using a system and method called mean
normalization. Mean normalization involves determining a mean value
at each wavelength of interest for reference reflectance spectra
and subtracting the mean values so determined at a particular
wavelength of interest from the amplitude of the test spectrum (or
spectra) at the same wavelength.
[0067] In one embodiment, at step 760, where the metric to be used
in classifying a test specimen is a Mahalanaobis distance, the
computer 202 performs a mathematical procedure intended to
guarantee that a matrix used in further analytical steps is capable
of being inverted. Matrix inversion is a mathematical process well
known in the matrix mathematical arts. In one embodiment, the
matrix that is computed is called a Friedman matrix. The data used
in the calculation of the Friedman matrix is obtained from the
stored data recorded in machine-readable format. The step of
computing the appropriate Friedman matrix can be performed at any
time after the reference spectral data is available.
[0068] Computation of the Mahalanobis distance requires the
inversion of a weighting matrix. One approach (i.e., Linear
Discriminant Analysis) utilizes the inverse of the pooled
within-groups covariance while another method (Quadratic
Discriminant Analysis) employs the inverse of each within-group
covariance. When a "large" number of wavelengths are used (e.g.,
for large p), either of the aforementioned matrices can be singular
and hence cannot be inverted. Therefore, an alternate weighting
matrix called the Friedman matrix is used.
[0069] The Friedman matrix is the weighted linear combination of a
within-group covariance matrix C.sub.j and the pooled within-group
covariance C that is a function of the Friedman parameters .gamma.
and .lambda.. These parameters are selected from the unit interval
[0,1]. It is important to note that the Friedman parameters are not
physical quantities whose values carry classification information.
Rather, they are used to insure that the weighting (Friedman)
matrix is non-singular. Equation 5 details the p-by-p Friedman
matrix, which is denoted by .OMEGA.. 3 j ( , ) = ( 1 - ) [ ( 1 - )
C j + C ] + p t r [ ( 1 - ) C j + C ] I p x p Eqn . 5
[0070] N note that tr(A) is the trace of the matrix A, namely the
sum of the diagonal elements. Also, I.sub.pxp is the p-dimensional
identity matrix. 4 A = [ a 1 , 1 a 1 , 2 a 1 , n a 2 , 1 a 2 , 2 a
2 , n a n , 1 a n , 2 a n , n ] t r ( A ) = k = 1 n a k , k Eqn . 6
I p x p = [ 1 0 0 0 1 0 0 0 1 ] p x p Eqn . 7
[0071] Let s(Ap) be ap-dimensional spectrum. The Mahalanobis
distance d from s(.LAMBDA..sub.p) to the group mean .mu..sub.j with
respect to the associated Friedman matrix .OMEGA..sub.j(.gamma.,
.lambda.) and Friedman parameters .gamma. and .lambda. is given in
equation 8 below.
d(s(.LAMBDA..sub.p),.mu..sub.j)={square root}{square root over
(.vertline.(s(.LAMBDA..sub.p)-.mu..sub.j).OMEGA..OMEGA.,(.gamma.,.lambda.-
).sup.-1.multidot.(s(.LAMBDA..sub.p)-.mu..sub.j).sup.T.vertline.)}
Eqn. 8
[0072] Where other metrics are used to classify a test spectrum and
a test specimen, the step 770 can be replaced by the appropriate
computation.
[0073] As indicated at step 760, the computer 202 computes a metric
from each test spectrum (or from an average value representing a
plurality of spectra, such as performed at step 725) to each u
characteristic N-dimensional value for the reference spectra
recorded. In one embodiment, the metric can be a Mahalanobis
distance, as indicated above. In other embodiments, the metric can
be the square root of the sum of the squares of the differences in
coordinates in the N-dimensional space, or the metric can be the
Bhattacharyya distance.
[0074] At step 765, the computer 202 examines the results obtained
in step 760, and determines a classification for the test specimen,
based on the metrics computed with respect to the test reflectance
spectrum and a classification rule or relation. In one embodiment,
the classification relation is that the condition of the test
specimen is assigned as the condition corresponding to the
reference spectrum constellation or set having the Mahalanobis
shortest distance, provided that the shortest Mahalanobis distance
is less than a pre-determined minimum distance. In one embodiment,
if no Mahalanobis distance is less than a predetermined minimum
distance, the test spectrum is discarded as being incapable of
being classified, or indeterminate.
[0075] In one embodiment, the test reflectance spectrum can be
compared to multiple sets of reference spectra in a single
comparison. In one embodiment, the computations can be repeated for
different sets of reference conditions. For example, a test
reflectance spectrum from a test specimen can be compared in a
first computation to reference reflectance spectral data for normal
squamous tissue and CIN II/III tissue, compared in a second
computation to reference reflectance spectral data for normal
squamous tissue and CIN I tissue, and compared in a third
computation to reference reflectance spectral data for normal
squamous tissue and metaplasia tissue. If the test reflectance
spectrum is classified in each of the three comparisons as being
more closely related to the reference spectra for normal squamous
tissue, the test specimen can be classified by the computer 202 as
having normal health, and the classification process is complete.
However, if the test reflectance spectrum is classified in either
of the comparisons involving CIN I or CIN II/III as being less
closely related to the reference spectra for normal squamous tissue
than one of the other conditions or states of health (namely CIN I,
or CIN II/III), the computer 202 can report that the state of
health of the test specimen is not clearly that of normal squamous
tissue, and that further analysis is in order. In one embodiment,
the further analysis involves the recording and examination of
reflectance spectra.
Equivalents
[0076] While the invention has been particularly shown and
described with reference to specific preferred embodiments, it
should be understood by those skilled in the art that various
changes in form and detail may be made therein without departing
from the spirit and scope of the invention as defined by the
appended claims.
* * * * *