Spectral bio-imaging data for cell classification using internal reference

• US 6,690,817 B1
• Filed: 09/18/1998
• Issued: 02/10/2004
• Est. Priority Date: 08/18/1993
• Status: Expired due to Fees

• Current Assignee: Applied Spectral Imaging Ltd.
• Original Assignee: Applied Spectral Imaging Ltd.
• Inventors: Ben-Yosef, Nissim, Buckwald, Robert A., Cabib, Dario
• Primary Examiner(s): CHANG, JON CARLTON
• Application Number:
  US09/157,138
• Time in Patent Office: 1,971 Days
• Field of Search: 382/133, 382/134, 382/164-165, 382/167, 382/224, 382/225, 702/21, 435/7.23, 435/7.24, 435/7.25, 435/6, 356/346
• US Class Current: 382/134
• CPC Class Codes: G01B 11/0675 using interferometry
• CPC Class Codes: G01J 2003/2866 Markers; Calibrating of scan
• CPC Class Codes: G01J 3/02 Details
• CPC Class Codes: G01J 3/12 Generating the spectrum; Monochromators
• CPC Class Codes: G01J 3/1256 using acousto-optic tunable filter; acousto-optic elements or systems G02F1/11, G02F1/33
• CPC Class Codes: G01J 3/26 using multiple reflection, e.g. Fabry-Perot interferometer, variable interference filters
• CPC Class Codes: G01J 3/2823 Imaging spectrometer
• CPC Class Codes: G01J 3/4406 Fluorescence spectrometry
• CPC Class Codes: G01J 3/453 by correlation of the amplitudes
• CPC Class Codes: G01J 5/10 using electric radiation detectors
• CPC Class Codes: G01N 1/30 Staining; Impregnating ; Fixation; Dehydration; Multistep processes for preparing samples of tissue, cell or nucleic acid material and the like for analysis
• CPC Class Codes: G01N 15/1433 using image recognition
• CPC Class Codes: G01N 2021/6417 Spectrofluorimetric devices
• CPC Class Codes: G01N 21/6428 Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes" in vivo A61B5/00; immunoassay G01N33/53
• CPC Class Codes: G01N 21/6458 Fluorescence microscopy fluorescence microscopes per se G02B21/0076 and G02B21/16
• CPC Class Codes: G01N 33/5005 involving human or animal cells immunoassay G01N33/56966; immunoassays of protozoa G01N33/56905; protozoa in screening assays C12Q1/025
• CPC Class Codes: G01N 33/56966 Animal cells
• CPC Class Codes: G01N 33/582 with fluorescent label
• CPC Class Codes: G06V 10/88 Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters
• CPC Class Codes: G06V 20/69 Microscopic objects, e.g. biological cells or cellular parts

Abstract

A method of spectral-morphometric analysis of biological samples, the biological samples including substantially constant components and suspected variable components, the method is effected by following the steps of (a) using a spectral data collection device for collecting spectral data of picture elements of the biological samples; (b) defining a spectral vector associated with picture elements representing a constant component of at least one of the biological samples; (c) using the spectral vector for defining a correcting function being selected such that when operated on spectral vectors associated with picture elements representing other constant components, spectral vectors of the other constant components are modified to substantially resemble the spectral vector; (d) operating the correcting function on spectral vectors associated with at least the variable components for obtaining corrected spectral vectors thereof; and (e) classifying the corrected spectral vectors into classification groups.

Claims

1. A method of spectral-morphometric analysis of biological samples, the biological samples including substantially constant components and suspected variable components, the method comprising the steps of:

(a) using a spectral data collection device for collecting spectral data of picture elements of the biological samples;

(b) defining a spectral vector associated with picture elements representing a constant component of at least one of the biological samples;

(c) using said spectral vector for defining a correcting function being selected such that when operated on spectral vectors associated with picture elements representing other constant components, spectral vectors of said other constant components are modified to substantially resemble said spectral vector;

(d) operating said correcting function on spectral vectors associated with at least said variable components for obtaining corrected spectral vectors thereof; and

(e) classifying said corrected spectral vectors into classification groups.

2. The method of claim 1, further comprising the step of:

(f) presenting pixels associated with each of said classification groups in a distinctive color.

3. The method of claim 1, wherein the substantially constant components are red blood cells.

4. The method of claim 3, wherein said red blood cells are added to the biological sample.

5. The method of claim 3, wherein said red blood cells are inherent to the biological sample.

6. The method of claim 1, wherein said suspected variable components are tumor cells, tumor tissues or parts thereof.

7. The method of claim 6, wherein said tumor cells are hematopoietic tumor cells.

8. The method of claim 6, wherein the substantially constant components are red blood cells.

9. The method of claim 1, wherein said biological sample is a blood sample of a patient suspected to have or having a hematopoietic tumor.

10. The method of claim 9, wherein said hematopoietic tumor is selected from the group consisting of leukemia and lymphoma.

11. The method of claim 1, wherein said biological sample is of a patient suspected of having or having a disease selected from the group consisting of ALL, CLL, IM, PCL, PLL and Sezary syndrome.

12. The method of claim 1, wherein prior to collecting spectral data of picture elements of the biological samples, the biological sample is stained.

13. The method of claim 12, wherein staining said biological sample is effected via a stain selected from the group consisting of an immunohistochemical stain, a histological stain, a DNA ploidy stain, a nucleic acid sequence specific probe and any combination thereof.

14. The method of claim 13, wherein said histological stain is selected from the group consisting of Hematoxylin-Eosin stain, May Grunwald Giemsa stain, Romanowsky Giemsa stain, Masson'"'"'s trichrome stain and Papanicolaou stain.

15. The method of claim 1, wherein collecting spectral data of picture elements of the biological samples is effected by:

(i) collecting incident light simultaneously from all pixels of said sample using collimating optics;

(ii) passing said incident collimated light through an interferometer system having a number of elements, so that said light is first split into two coherent beams which travel in different directions inside said interferometer and then said two coherent beams recombine to interfere with each other to form an exiting light beam;

(iii) passing said exiting light beam through a focusing optical system which focuses said exiting light beam on a detector having a two-dimensional array of detector elements, so that at each instant each of said detector elements is the image of one and always the same pixel of said sample for the entire duration of the measurement, so that the real image of the sample is stationary on the plane of the detector array and at any time during the measurement the image is still visible and recognizable, and so that each of said detector elements produces a signal which is a particular linear combination of light intensity emitted by said pixel at different wavelengths, wherein said linear combination is- a function of the instantaneous optical path difference;

(iv) scanning one or more of said elements of said interferometer system, so that said optical path difference between said two coherent beams generated by said interferometer system is scanned simultaneously for all said pixels of said sample; and

(v) recording signals of each of said detector elements as function of time using a recording device to form a spectral cube of data.

16. The method of claim 1, wherein said spectral data collection device includes an element selected from the group consisting of a dispersion element, a filter and an interferometer.

17. The method of claim 1, wherein classifying said corrected spectral vectors into classification groups is effected using a classification map algorithm which employs reference spectral vectors for associating picture elements into said classification groups.

18. The method of claim 17, wherein said reference spectral vectors for classification are of a previously prepared reference library.

19. The method of claim 17, wherein at least one of said reference spectral vectors for classification is of picture elements derived from a cell domain selected from the group consisting of nucleolus, inter-chromosomal region, cytoplasm, a first chromatin region of the nucleus, a second chromatin region of the nucleus and background.

20. The method of claim 1, wherein said spectral vector is a normalized spectral vector.

21. The method of claim 1, wherein classifying said corrected spectral vectors into classification groups effected by spectral vector maxima classification.

22. The method of claim 1, wherein said suspected variable components are cells infected by a pathogen.