Method for the detection of cellular abnormalities using Fourier transform infrared spectroscopy

• US 6,146,897 A
• Filed: 05/06/1997
• Issued: 11/14/2000
• Est. Priority Date: 11/13/1995
• Status: Expired due to Term

• Current Assignee: Agilent Technologies Australia (M) Pty., Ltd. (Agilent Technologies, Inc.)
• Original Assignee: Bio-Rad Laboratories Incorporated
• Inventors: Rigas, Basil, Cohenford, Menashi A., Bhandare, Prashant S.
• Primary Examiner(s): WALLENHORST, MAUREEN
• Application Number:
  US08/851,776
• Time in Patent Office: 1,288 Days
• Field of Search: 436/63, 436/64, 436/171, 436/172, 600/473, 600/475, 600/476-478, 250/338.1, 250/339.01, 250/339.09, 250/339.12, 250/341.1, 250/341.8, 250/461.2
• US Class Current: 436/63
• CPC Class Codes: G01J 2003/2866 Markers; Calibrating of scan
• CPC Class Codes: G01J 3/28 Investigating the spectrum using colour filters G01J3/51
• CPC Class Codes: G01J 3/453 by correlation of the amplitudes
• CPC Class Codes: G01N 2021/3595 using FTIR
• CPC Class Codes: G01N 21/35 using infrared light G01N21/39 takes precedence

Abstract

This invention teaches a method to identify cellular abnormalities which are associated with disease states. The method utilizes infrared (IR) spectra of cell samples which are dried on an infrared-transparent matrix and scanned at the frequency range from 3000-950 cm^-1. The identification of samples is based on establishing a reference using a representative set of spectra of normal and/or diseased specimens. During the reference assembly process, multivariate techniques such as Principal Component Analysis (PCA) and/or Partial Least Squares (PLS) are used. PCA and PLS reduce the data based on maximum variations between the spectra, and generate clusters in a multidimensional space representing the different populations. The utilization of Mahalinobis distances, or linear regression (e.g., Principle Component Regression on the reduced data from PCA) form the basis for the discrimination. In one embodiment, the invention is a method to distinguish premalignant and malignant stages of cervical cancer from normal cervical cells. This method is simple to use and achieves statistically reliable distinction between the following groups of cervical smears: normal (individuals with no prior history of dysplasia), dysplasia and malignant samples. Further, this invention discloses a method to obtain the IR spectrum of individual cervical cells fixed on an infrared-transparent matrix and to use the spectra of the individual cells in the method described above. In another aspect, the invention is a method for using vibrational spectroscopic imaging to distinguish between normal and diseased cells. In another aspect, the invention is a method to identify women at a high risk for developing cervical dysplasia.

Claims

1. A method for detecting chemical differences between a cell sample and a reference cell sample, utilizing single-cell infrared microspectroscopy, said method comprising:

(a) directing a beam of infrared light through an aperture of approximately single cell size at single cells in a cell sample to produce absorption data for each of said single cells;

(b) comparing said absorption data for each of said single cells with infrared absorption data acquired from individual cells in at least one reference cell sample to provide comparison data for each of said single cells in said cell sample;

(c) generating scores for said absorption data using said comparison data;

(d) creating frequency distribution profiles from said scores; and

(e) detecting said chemical differences using said frequency distribution profiles.

2. A method in accordance with claim 1, wherein said cell sample and said reference cell sample each comprise cells from human tissue.

3. A method in accordance with claim 2, wherein said cell sample and said reference cell sample are from tissues selected from the group consisting of breast, bladder, male reproductive system, female reproductive system, bone, pancreas, brain, skin, digestive tract and lung tissues.

4. A method in accordance with claim 3, wherein said cell sample and said reference cell sample are from tissues selected from the group consisting of breast, male reproductive system and female reproductive system tissues.

5. A method in accordance with claim 1, wherein said cell sample is dried prior to producing said absorption data in step (a).

6. A method in accordance with claim 1, wherein said cell sample is substantially free of non-diagnostic debris.

7. A method according to claim 6, wherein said cell sample and said reference cell sample are cervical cells.

8. A method in accordance with claim 7, wherein infrared absorption data acquired from the cell sample and infrared absorption data acquired from the reference cell sample are compared at one or more frequency ranges selected from the group consisting of 1200 cm^-1 to 1000 cm^-1 and 3000 cm^-1 to 2800 cm^-1.

9. A method according to claim 1, wherein said chemical differences are due to a disease state in said cell sample.

10. A method according to claim 9, wherein said disease state is a member selected from the group consisting of diseases caused by pathological agents and diseases caused by genetic anomalies.

11. A method according to claim 9, wherein said disease state is a member selected from the group consisting of cancer, hypertrophy and dysplasia.

12. A method according to claim 1, wherein said chemical differences arise from the treatment of a disease state.

13. A method according to claim 1, wherein step (c) further comprises;

using multivariate analysis of said comparison data to generate said scores.

14. A method according to claim 1, wherein step (c) further comprises:

using classical spectroscopic analytical methods to generate said scores.

15. A method according to claim 1, wherein said absorption data is a member selected from the group consisting of smoothed, derivatized and smoothed and derivatized absorption data.

16. A method according to claim 1, wherein the absorption data is a member selected from the group consisting of unsmoothed absorption data, underivatized absorption data and unsmoothed and underivatized absorption data.

17. A method for detecting chemical differences between a cell sample and a reference cell sample utilizing single-cell infrared microspectroscopy, said method comprising:

(a) directing a beam of infrared light through an aperture of approximately single cell size at single cells in said cell sample to produce absorption data for each of said single cells;

(b) comparing said absorption data for said single cells with infrared absorption spectra acquired from individual cells in at least one reference cell sample to provide comparison data for said single cells;

(c) generating scores for said absorption data using said comparison data;

(d) establishing a mean of said scores for said single cells;

(e) comparing said mean with a reference distribution curve of scores, to detect said chemical differences in said cell sample.

18. A method in accordance with claim 17, wherein said cell sample and said reference cell sample each comprise cells from human tissue.

19. A method in accordance with claim 18, wherein said cell sample and said reference cell sample are from tissues selected from the group consisting of breast, bladder, male reproductive system, female reproductive system, bone, pancreas, brain, skin, digestive tract and lung tissues.

20. A method according to claim 19, wherein said cell sample and said reference cell sample are cervical cells.

21. A method in accordance with claim 20, wherein infrared absorption data acquired from the cell sample and infrared absorption data acquired from the reference cell sample are compared at one or more frequency ranges selected from the group consisting of 1200 cm^-1 to 1000 cm^-1 and 3000 cm^-1 to 2800 cm^-1.

22. A method in accordance with claim 17, wherein said cell sample is dried prior to producing said absorption data in step (a).

23. A method in accordance with claim 17, wherein said cell sample is substantially free of non-diagnostic debris.

24. A method according to claim 17, wherein said chemical differences are due to a disease state in said cell sample.

25. A method according to claim 24, wherein said disease state is a member selected from the group consisting of diseases caused by pathological agents and diseases caused by genetic anomalies.

26. A method according to claim 24, wherein said disease state is a member selected from the group consisting of cancer, benign hypertrophy and dysplasia.

27. A method according to claim 17, wherein said chemical differences arise from the treatment of a disease state.

28. A method in accordance with claim 17, wherein step (c) further comprises:

using multivariate analysis of said comparison data to generate said scores.

29. A method in accordance with claim 17, wherein step (c) further comprises:

using classical spectroscopic analytical methods to generate said scores.

30. A method according to claim 17, wherein said absorption data is a member selected from the group consisting of smoothed, derivatized and smoothed and derivatized absorption data.

31. A method according to claim 17, wherein the absorption data is a member selected from the group consisting of unsmoothed absorption data, underivatized absorption data and unsmoothed and underivatized absorption data.

32. A method for detecting chemical differences between a cell sample and a reference cell sample utilizing infrared spectroscopic imaging, said method comprising:

(a) directing a beam of infrared light at a cell sample to produce absorption data, substantially simultaneously, for each of a plurality of single cells in said cell sample;

(b) comparing said absorption data for each of said single cells with a reference set of absorption spectra acquired from individual cells in at least one reference cell sample to provide comparison data for each of said single cells in said cell sample;

(c) generating scores for said absorption data using said comparison data;

(d) creating frequency distribution profiles from said scores; and

(e) detecting said chemical differences using said frequency distribution profiles.

33. A method in accordance with claim 32, wherein said cell sample and said reference cell sample are from human tissue.

34. A method in accordance with claim 33, wherein said cell sample and said reference cell sample are from tissues selected from the group consisting of breast, bladder, male reproductive system, female reproductive system, bone, pancreas, brain, skin, digestive tract and lung tissues.

35. A method according to claim 34, wherein said cell sample and said reference cell sample are cervical cells.

36. A method according to claim 33, wherein said chemical differences are due to a disease state in said cell sample.

37. A method according to claim 36, wherein said disease state is a member selected from the group consisting of diseases caused by pathological agents and diseases caused by genetic anomalies.

38. A method according to claim 36, wherein said disease state is a member selected from the group consisting of cancer, benign hypertrophy and dysplasia.

39. A method in accordance with claim 32, wherein said cell sample and said reference cell sample are dried cell samples.

40. A method in accordance with claim 32, wherein said cell sample is substantially free of non-diagnostic debris.