Characterizing biological matter in a dynamic condition using near infrared spectroscopy spectrum

• US 5,729,333 A
• Filed: 12/22/1992
• Issued: 03/17/1998
• Est. Priority Date: 09/18/1989
• Status: Expired due to Fees

• Current Assignee: Terumo Cardiovascular Systems Corporation (Terumo Corporation)
• Original Assignee: 3M Company, Board of Regents of The University of Washington (University of Washington)
• Inventors: Carim, Hatim M., Osten, David W., Callis, James B.
• Primary Examiner(s): Hayes, Gail O.
• Assistant Examiner(s): OH, JUNGHOON
• Application Number:
  US07/995,951
• Time in Patent Office: 1,911 Days
• Field of Search: 364/413.08, 364/498, 128/633, 128/664, 356/39-42, 250/338.1, 250/338.5, 250/339-341
• US Class Current: 356/39
• CPC Class Codes: A61B 5/14535 for measuring haematocrit
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14557 specially adapted to extracorporeal circuits
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: G01N 21/359 using near infrared light
• CPC Class Codes: G01N 2201/129 Using chemometrical methods

Abstract

A method is provided for predicting a property of a matter of biological origin, such as biological fluid, containing water, in a dynamic condition where the biological fluid may be approximated to contain two compartments where one compartment has a proportionally larger or smaller amount of water than the other compartment having the property of interest. The method involves establishing a training set in the near-infrared (NIR) region with independent quantification of the property of the fluid using known techniques. The training set is mathematically analyzed according to a correlation developed by regression analysis after employment of a pre-processing technique such as a multiple derivative transformation of spectra or a ratioing of two wavelengths in the spectra. The result is a mathematical transformation equation which quantitatively relates spectral intensities at specific wavelengths to the property of interest. This transformation equation may be applied to unknown samples so as to predict their properties, thereby eliminating need for the reference method except for validation or recalibration. The method provides rapid and accurate prediction of the property of the unknown sample, which may be the property of hematocrit or hemoglobin concentration in whole animal blood. Other analyses of properties in the biological fluid such as oxygen saturation in hemoglobin in whole animal blood may be included in the mathematical analysis to further refine the prediction of the property of interest. Also, a loop from the patient is disclosed for the purpose of monitoring the property of interest nearly simultaneously with changes in that property of interest.

Claims

1. A method for analyzing a property of biological matter having a water content in a dynamic condition, the biological matter approximated to comprise a first compartment related to the property to be analyzed and a second compartment having a proportionally larger or smaller amount of water than the first compartment, the method comprising:

(a) observing multiple samples of biological matter in a dynamic condition;

(b) irradiating with near infrared light said multiple samples of the biological matter;

(c) detecting the near infrared absorption spectrum of each of said multiple samples as spectral data consisting of absorbance intensities;

(d) applying a ratio pre-processing technique to the spectral data of absorbance intensities of the spectrum of each of said multiple samples to identify a multiplicity of ratio wavelength pairs;

(e) independently quantifying the property to be analyzed for each of said multiple samples;

(f) establishing a training set from said near infrared absorption spectra of step (d) of said multiple samples using the multiplicity of ratio wavelength pairs; and

(g) statistically identifying the nature of a best two compartment mathematical correlation between the property to be analyzed in the first compartment and the water content in the biological matter (1) by correlating values obtained during step (e) with values obtained during step (f) and (2) by selecting a ratio wavelength pair of absorbance intensities in which one wavelength is a strong near infrared wavelength absorbance peak of the water content and in which the second wavelength of the ratio wavelength pair is another near infrared wavelength absorbance measuring point having absorbances in the first compartment which minimize variability in the property to be analyzed.

2. The method according to claim 1, further comprising the steps of:

(h) observing an unknown sample of the biological matter in a dynamic condition;

(i) irradiating said unknown sample with near infrared light;

(j) detecting near infrared spectrum of said unknown sample as spectral data consisting of absorbance intensities;

(k) applying said ratio pre-processing technique using the ratio wavelength pair selected in step (g) to the spectral data of absorbance intensities of said spectrum of said unknown sample; and

(l) predicting the property to be analyzed in said unknown sample by utilizing said best two compartment mathematical correlation obtained in said statistically identifying step (g).

3. A method according to claim 2, wherein the biological matter is whole blood and the property of the first compartment to be analyzed is hematocrit.

4. A method according to claim 2, wherein the biological matter is whole blood and the property of the first compartment to be analyzed is the hemoglobin concentration in the whole blood.

5. A method according to claim 2, wherein said detecting step (c) and said detecting step (j) use spectral analysis instrumentation which records said absorbance spectra of said multiple samples and said unknown sample in the dynamic condition of the biological matter flowing through the spectral analysis instrumentation.

6. A method according to claim 5, wherein detecting step (c) and said detecting step (j) use transmittance detection components in said spectral analysis instrumentation.

7. A method according to claim 5, wherein detecting step (c) and said detecting step (j) use reflectance detection components in said spectral analysis instrumentation.

8. A method according to claim 2, wherein said multiple samples are of at least one known organism of a given biological species;

and wherein said unknown sample is of the same biological species as said multiple samples.

9. A method according to claim 1, wherein said statistically identifying step (g) uses linear regression analysis.

10. A method according to claim 1, wherein said statistically identifying step (g) uses multiple linear regression analysis.

11. A method according to claim 1, wherein said statistically identifying step (g) uses stepwise regression analysis.

12. A method according to claim 1, wherein said statistically identifying step (g) uses partial least squares regression analysis.

13. A method according to claim 1, wherein said mathematical correlation in said statistically identifying step (g) comprises a linear function related to a near infrared absorbance peak of water in the absorbance spectra of said multiple samples subjected to said pre-processing technique.

14. A method according to claim 13, wherein the biological matter is whole blood and said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers.

15. A method according to claim 13, wherein the biological matter is whole blood, said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers, and said another near infrared wavelength absorbance measuring point is the isosbestic point of oxyhemoglobin and deoxyhemoglobin.

16. A method according to claim 2, wherein said mathematical correlation in said statistically identifying step (g) comprises a linear function related to a near infrared absorbance peak of water in the absorbance spectra of said multiple samples subjected to said pre-processing technique.

17. A method according to claim 16, wherein the biological matter is whole blood and said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers.

18. A method according to claim 16, wherein the biological matter is whole blood, said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers, and said another near infrared wavelength absorbance measuring point is the isosbestic point of oxyhemoglobin and deoxyhemoglobin.

19. A method according to claim 18, wherein the property to be analyzed is hematocrit and said mathematical correlation solves the equation:

space="preserve" listing-type="equation">Y=b+m*(Absorbance at Isosbestic Point/Absorbance at said Absorbance Peak of Water)

where Y is the value of hematocrit, b ranges from about -70 to about -128, and m ranges from about 78 to about 126.

20. A method according to claim 18, wherein the property to be analyzed is hemoglobin concentration and said mathematical correlation solves the equation:

space="preserve" listing-type="equation">Y=b+m*(Absorbance at Isosbestic Point/Absorbance at said Absorbance Peak of Water)

where Y is the hemoglobin concentration, b ranges from about -23 to about -45, and m ranges from about 26 to about 44.

21. A method according to claim 1, wherein the biological matter is whole blood and the property of the first compartment to be analyzed is hematocrit.

22. A method according to claim 1, wherein the biological matter is whole blood and the property of the first compartment to be analyzed is the hemoglobin concentration in the whole blood.

23. A method according to claim 1, wherein said mathematical correlation statistically identified in step (g) indicates a complementary relationship between the property to be analyzed and the water content.

24. A method according to claim 1, further comprising the steps of:

(1) observing additional samples of biological matter in a dynamic condition;

(2) independently quantifying the property to be analyzed for each of said additional samples;

(3) performing steps (b), (c), and (d) with respect to said additional samples;

(4) predicting the property to be analyzed in said additional samples by utilizing said mathematical correlation obtained in said statistically identifying step (g); and

(5) validating said mathematical correlation by comparing the property predicted in step (4) to the property independently quantified in step (2).

25. A method according to claim 24, wherein said validating step (5) employs manual interpretation of the spectra of said additional samples compared to the training set.

26. A method according to claim 25, wherein said validating step (5) employs a statistical method to compare the property predicted in step (4) to the property independently quantified in step (2).

27. A method for analyzing a property of whole animal blood having a water content, the whole animal blood comprising a first compartment related to the property to be analyzed and a second compartment having a proportionally larger or smaller amount of water than the first compartment, the method comprising:

(a) irradiating with near infrared light multiple samples of the whole animal blood;

(b) detecting the near infrared spectrum of each of said multiple samples as spectral data consisting of absorbance intensities;

(c) applying a pre-processing technique to the spectral data of absorbance intensities of the spectrum of each of said multiple samples;

(d) independently quantifying the property to be analyzed for each of said multiple samples;

(e) independently quantifying a value proportional to the percentage oxygen saturation in the whole animal blood for each of said multiple samples;

(f) establishing a training set from said near infrared spectra of step (c) of said multiple samples using processed spectral data comprising a near infrared wavelength absorbance peak of the water content; and

(g) statistically identifying the nature of a best two compartment mathematical correlation between the property to be analyzed in the first compartment and the water content in the whole animal blood (1) by correlating values obtained during step (d) and step (e) with values obtained during step (f) and (2) by selecting at least a wavelength absorbance intensity that is a near infrared wavelength absorbance peak of the water content.

28. The method according to claim 27, further comprising the steps of:

(h) irradiating an unknown sample of whole animal blood with near infrared light;

(i) detecting near infrared spectrum of said unknown sample as spectral data consisting of absorbance intensities;

(j) applying said pre-processing technique using each wavelength selected in step (g) to the spectral data of absorbance intensities of said spectrum of said unknown sample;

(k) determining a value proportional to the percent oxygen saturation of the unknown sample; and

(l) predicting the property to be analyzed in said unknown sample by utilizing said best two compartment mathematical correlation obtained in said statistically identifying step (g).

29. A method according to claim 28, wherein the property of the first compartment to be analyzed is hematocrit.

30. A method according to claim 28, wherein the property of the first compartment to be analyzed is the hemoglobin concentration in the whole blood.

31. A method according to claim 28, wherein said detecting step (b) and said detecting step (i) use spectral analysis instrumentation which records said absorbance spectra of said multiple samples and said unknown sample in the dynamic condition of the whole animal blood flowing through the spectral analysis instrumentation.

32. A method according to claim 31, wherein detecting step (b) and said detecting step (i) use transmittance detection components in said spectral analysis instrumentation.

33. A method according to claim 31, wherein detecting step (b) and said detecting step (i) use reflectance detection components in said spectral analysis instrumentation.

34. A method according to claim 28, wherein said multiple samples are of at least one known organism of a given biological species;

and wherein said unknown sample is of the same biological species as said multiple samples.

35. A method according to claim 28, wherein said determining step (k) comprises using a pulse oximeter to measure the percent oxygen saturation of the unknown sample.

36. A method according to claim 28, wherein said determining step (k) comprises using a co-oximeter to measure the percent oxygen saturation of the unknown sample.

37. A method according to claim 28, wherein said determining step (k) comprises using the ratio of the absorbances of two wavelengths where the ratio of extinction coefficients for oxyhemoglobin and deoxyhemoglobin at one wavelength is different than that ratio at the second wavelength.

38. A method according to claim 37, wherein said absorbance of deoxyhemoglobin is in the range from about 680 nm to about 720 nm and wherein said absorbance of the combination of oxyhemoglobin and deoxyhemoglobin is in the range of about 780 nm to about 830 nm.

39. A method according to claim 38, wherein said validating step (6) employs a statistical method to compare the property predicted in step (5) to the property independently quantified in step (2).

40. A method according to claim 27, wherein said statistically identifying step (g) uses multiple linear regression analysis.

41. A method according to claim 40, wherein said statistically identifying step (g) uses the independently quantified percent oxygen saturation in said multiple samples as a regression variable in said multiple linear regression analysis to determine said mathematical correlation.

42. A method according to claim 40, wherein said statistically identifying step (g) uses multiple stepwise regression analysis with the independently quantified percent oxygen saturation in said multiple samples as a regression variable to determine said mathematical correlation.

43. A method according to claim 40, wherein said statistically identifying step (g) uses partial least squares regression analysis with the independently quantified percent oxygen saturation in said multiple samples as a regression variable to determine said mathematical correlation.

44. A method according to claim 27, wherein said mathematical correlation in said statistically identifying step (g) comprises a linear function related to a near infrared absorbance peak of water in the absorbance spectra of said multiple samples subjected to said pre-processing technique and the percent oxygen saturation in said multiple samples.

45. A method according to claim 28, wherein said mathematical correlation in said statistically identifying step (g) comprises a linear function related to a near infrared absorbance peak of water in the absorbance spectra of said multiple samples subjected to said pre-processing technique and the percent oxygen saturation in said multiples samples.

46. A method according to claim 45, wherein said pre-processing technique comprises transforming said spectra of said multiple samples of said training set by computing a multiple derivative of said multiple samples.

47. A method according to claim 46, wherein said multiple derivative is the second derivative.

48. A method according to claim 46, wherein said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers.

49. A method according to claim 48, wherein the property to be analyzed is hematocrit and said mathematical correlation solves the equation:

space="preserve" listing-type="equation">C=B.sub.0 +B.sub.1 (A.sub.1)+B.sub.2 (A.sub.2)

where C is the Hematocrit;

B₀ ranges from about -31 to about 32;

where A₁ is a value proportional to the percent oxygen saturation and B₁ is the regression coefficient for the percent oxygen saturation and ranges from about -0.4 to about 36;

where A₂ is the second derivative transformation of said absorbance peak of water and ranges from about 1160 to about 1175 nm and B₂ is the regression coefficient of the second derivative transformation of said absorbance peak of water and ranges from about 439 to about 496.

50. A method according to claim 48, wherein the property to be analyzed is concentration of hemoglobin and said mathematical correlation solves the equation:

space="preserve" listing-type="equation">C=B.sub.0 +B.sub.1 (A.sub.1)+B.sub.2 (A.sub.2)

where C is the concentration of hemoglobin;

B₀ ranges from about -11 to about 11;

where A₁ is a value proportional to the percent oxygen saturation and B₁ is the regression coefficient for the percent oxygen saturation and ranges from about -0.08 to about 13;

where A₂ is the second derivative transformation of said absorbance peak of water and ranges from about 1160 to about 1175 nm and B₂ is the regression coefficient of the second derivative transformation of said absorbance peak of water and ranges from about 147 to about 169.

51. The method according to claim 45, wherein said pre-processing technique comprises applying a ratio consisting of absorbance intensities of a near infrared absorbance peak of the water content in said training set to another near infrared wavelength absorbance measuring point in said source spectra set to obtain a multiplicity of ratio wavelength pairs, wherein said training set is established using the multiplicity of wavelength pairs, wherein the selecting of step (g) comprises selecting a ratio wavelength pair consisting of absorbance intensities in which one wavelength is a near infrared wavelength absorbance peak of the water content and in which the second wavelength of the ratio wavelength pair is another near infrared wavelength absorbance measuring point, and wherein step j applies a ratio pre-processing technique using the ratio wavelength pair selected in step (g).

52. A method according to claim 51, wherein said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers, and said another near infrared wavelength absorbance measuring point is the isosbestic point of oxyhemoglobin and deoxyhemoglobin.

53. A method according to claim 52, wherein the property to be analyzed is hematocrit and said mathematical correlation solves the equation:

space="preserve" listing-type="equation">C=B.sub.0 +B.sub.1 (A.sub.1)+B.sub.2 (A.sub.2)

where C is the Hematocrit;

B₀ ranges from about -106 to about -134;

where A₁ is a value proportional to the percent oxygen saturation and B₁ is the regression coefficient for the percent oxygen saturation and ranges from about -15 to about 0.1;

where A₂ is the ratio of the Absorbance at said Isosbestic Point to the Absorbance at said Absorbance Peak of Water and B₂ is the regression coefficient of said absorbance peak of water and ranges from about 116 to about 121.

54. A method according to claim 52, wherein the property to be analyzed is hemoglobin concentration and said mathematical correlation solves the equation:

space="preserve" listing-type="equation">C=B.sub.0 +B.sub.1 (A.sub.1)+B.sub.2 (A.sub.2)

where C is the concentration of hemoglobin;

B₀ ranges from about -46 to about -36;

where A₁ is a value proportional to the percent oxygen saturation and B₁ is the regression coefficient for the percent oxygen saturation and ranges from about -5 to about 0.02;

where A₂ is the ratio of the Absorbance at said Isosbestic Point to the Absorbance at said Absorbance Peak of Water and B₂ is the regression coefficient of said absorbance peak of water and ranges from about 40 to about 42.

55. A method according to claim 45, wherein said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers.

56. A method according to claim 44, wherein said pre-processing technique comprises transforming said spectra of said multiple samples of said training set by computing a multiple derivative of said multiple samples.

57. A method according to claim 56, wherein said multiple derivative is the second derivative.

58. A method according to claim 56, wherein said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers.

59. The method according to claim 44, wherein said pre-processing technique comprises applying a ratio consisting of absorbance intensities of a near infrared absorbance peak of the water content in said training set to another near infrared wavelength absorbance measuring point in said source spectra set to obtain a multiplicity of ratio wavelength pairs, wherein said training set is established using the multiplicity of wavelength pairs, and wherein the selecting of step (g) comprises selecting a ratio wavelength pair consisting of absorbance intensities in which one wavelength is a near infrared wavelength absorbance peak of the water content and in which the second wavelength of the ratio wavelength pair is another near infrared wavelength absorbance measuring point.

60. A method according to claim 59, wherein said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers, and said another near infrared wavelength absorbance measuring point is the isosbestic point of oxyhemoglobin and deoxyhemoglobin.

61. A method according to claim 44, wherein said absorbance peak of water occurs in the near infrared spectra from about 1150 to about 1190 nanometers.

62. A method according to claim 27, wherein the property of the first compartment to be analyzed is hematocrit.

63. A method according to claim 27, wherein the property of the first compartment to be analyzed is the hemoglobin concentration in the whole blood.

64. A method according to claim 27, wherein said mathematical correlation statistically identified in step (g) indicates a complementary relationship between the property to be analyzed and the water content.

65. A method according to claim 27, wherein said multiple samples are of at least one known organism of a given biological species.

66. A method according to claim 27, further comprising the steps of:

(1) observing additional samples of biological matter in a dynamic condition;

(2) independently quantifying the property to be analyzed for each of said additional samples;

(3) independently quantifying a value proportional to the percentage oxygen saturation in the whole animal blood for each of said additional samples;

(4) performing steps (a), (b), and (c) with respect to said additional samples;

(5) predicting the property to be analyzed in said additional samples by utilizing said mathematical correlation obtained in said statistically identifying step (g); and

(6) validating said mathematical correlation by comparing the property predicted in step (5) to the property independently quantified in step (2).

67. A method of monitoring a property of interest in whole blood of a live patient, nearly simultaneously with flow of the whole blood in the patient, the whole blood approximated to comprise a first compartment related to the property of interest and a second compartment having a proportionally larger or smaller mount of water, comprising:

(a) establishing a blood flow loop having a diversion section departing from the patient terminating at a flow cell, a return section returning to the patient beginning at a flow cell, and a bypass section between the diversion section and the return section;

(b) flowing the whole blood through the blood loop;

(c) using near infrared detecting means to monitor the property of interest in the whole blood flowing through the blood loop;

(d) identifying the value of the property of interest using a method of correlation of a linear functional relationship;

wherein said linear functional relationship is established by;

(1) observing multiple samples of whole blood in a dynamic condition;

(2) irradiating with near infrared light said multiple samples of the whole blood;

(3) detecting the near infrared adsorption spectrum of each of said multiple samples as spectral data consisting of absorbance intensifies;

(4) applying a ratio pre-processing technique to the spectral data of absorbance intensities of the spectrum of each of said multiple samples to identify a multiplicity of ratio wavelength pairs;

(5) independently quantifying the property of interest for each of said multiple samples;

(6) establishing a training set from said near infrared adsorption spectra of step (4) of said multiple samples using the multiplicity of ratio wavelength pairs; and

(7) statistically identifying the nature of a best two compartment mathematical correlation between the property to be analyzed in the first compartment and the water content in he whole blood (i) by correlating values obtained during step (5) with values obtained during step (6) and (ii) by selecting a ratio wavelength pair of absorbance intensities in which one wavelength is a strong near infrared wavelength absorbance peak of the water content and in which the second wavelength of the ratio wavelength pair is another near infrared wavelength absorbance measuring point having absorbances in the first compartment which minimize variability in the property of interest.

68. A method according to claim 67, wherein said identifying step (d) comprises determining the property of interest in the whole blood flowing through the blood by applying said mathematical correlation to a near infrared spectrum of the whole blood flowing in the blood loop.

69. A method according to claim 67, wherein the property of interest is hematocrit.

70. A method according to claim 67, wherein the property of interest is hemoglobin.