Infrared imaging of biological material

Abstract

A method of mapping a tissue characteristic in a tissue sample comprises gathering infrared absorption data from the sample at selected wavelengths, and determining, from the infrared absorption data, a first measure of the amount of power or energy absorbed attributable to an amide moiety and a second measure of the amount of power or energy absorbed attributable to a phosphate moiety. A ratio of the first measure and the second measure is used to establish a histological index. The histological index may be used to indicate a malignancy grade of tumour in the tissue.

The invention claimed is:  
     
         1 . A method of mapping a tissue characteristic in a tissue sample comprising, for each of a plurality of pixels in a two dimensional array:
 gathering infrared absorption data from the sample at selected wavelengths;   determining, from the infrared absorption data, a first measure of the amount of energy or power absorbed attributable to an amide moiety and a second measure of the amount of energy or power absorbed attributable to a phosphate moiety, and   determining a ratio of the first measure and the second measure to establish a histological index, to thereby generate a dataset corresponding to pixel values of a spatial map of the sample wherein the histological index, PA, is derived according to the expression PA=[|M(λ3)−M(λ4)|]/[|M(λ1)−M(λ2)|] or PA=[X M(λ3)−M(λ4)]/[X M(λ1)−M(λ2)], where: M(λn) is a measure of the absorbed energy or power at λn; λ1 is a wavelength corresponding to a peak absorption value attributable to an amide moiety; λ2 is a wavelength corresponding to a baseline absorption value attributable to an amide moiety; λ3 is a wavelength corresponding to a peak absorption value attributable to a phosphate moiety; λ4 is a wavelength corresponding to a baseline absorption value attributable to a phosphate moiety; X is numerical factor ≥1 which is set to a value sufficient to ensure that the measure M for a peak absorption values λ3 and λ1 is always greater than the measure M for the corresponding baseline absorption values λ4 and λ2 for all measurements; and   λ1=6.0±0.1 microns; λ2=6.5±0.1 microns; λ3=a number selected from a group consisting of 8.13±0.1 microns and 9.26±0.1 microns; λ4=a number selected from a group consisting of 8.57±0.1 microns and 10.0±0.1 microns.   
     
     
         2 . The method of  claim 1  in which the value X is set according to the signal-to-noise ratio of the measurement system. 
     
     
         3 . The method of  claim 1  in which the value of X lies in the range 1.2 to 1.5. 
     
     
         4 . The method of  claim 1  in which each of the first and second measures is obtained from: sample data S; environment data Es; background data B; and background environment data Eb, the method further comprising compensating the sample data S using Es, B, Eb, where:
 (i) sample data S is taken with the sample loaded in the machine on the sample stage and the shutter open/removed; 
 (ii) environment data Es is taken with the sample loaded in the machine and the shutter in/closed; 
 (iii) background data B is taken with the sample out of the apparatus and the shutter open/removed; and 
 (iv) background environment data Eb is taken with the sample out and the shutter in/closed. 
 
     
     
         5 . The method of  claim 4  wherein each of the first and second measures M is obtained from one or more measurements M according to the expression M=[S−Es]/[B−Eb]. 
     
     
         6 . The method of  claim 1  further including performing a bad pixel replacement procedure comprising:
 deriving a at least one histogram of a measured absorption value selected from a group consisting of measured absorption values λ1, λ2, λ3, and λ4 in the array; 
 identifying pixels having the lowest frequency of occurrence of the measured absorption values; and  
 replacing the absorption value of each of the identified pixels with a substitute value comprising an average value of one or more adjacent pixels to the identified pixel. 
 
     
     
         7 . The method of  claim 6  further including performing the bad pixel replacement procedure for each of the wavelengths λ1, λ2, λ3, and λ4. 
     
     
         8 . The method of  claim 1  further including plotting spatial variations in the histological index in at least two dimensions. 
     
     
         9 . The method of  claim 7  further including classifying each pixel as indicative of first, second or third tissue type based on the histological index for each pixel. 
     
     
         10 . The method of  claim 7  further including classifying each pixel as indicative of a non-cancerous tissue candidate type or a cancerous tissue candidate type. 
     
     
         11 . The method of  claim 10  applied to breast tissue. 
     
     
         12 . The method of  claim 1  further including using the histological index to derive a cancer grading. 
     
     
         13 . The method of  claim 12  in which the cancer grading is breast cancer. 
     
     
         14 . Apparatus for mapping a tissue characteristic in a tissue sample comprising:
 a detector configured to obtain infrared absorption data from a tissue sample at selected wavelengths;   a processing module configured to process said infrared absorption data;   the apparatus being configured to carry out the method of  claim 1 .   
     
     
       15. A method of determining a tissue characteristic in a tissue sample, the method comprising:
 gathering infrared absorption data from the sample;   determining, from the infrared absorption data at selected wavelengths for a first pixel, a first measure of the amount of energy or power absorbed attributable to an amide moiety and a second measure of the amount of energy or power absorbed attributable to a phosphate moiety; and   determining a ratio of the first measure and the second measure to establish a histological index for the first pixel, wherein the histological index, PA, is derived according to the expression PA=[|M(λ3)−M(λ4)|]/[|M(λ1)−M(λ2)|]or PA=[X M(λ3)−M(λ4)]/[X M(λ1)−M(λ2)], where: M(λn) is a measure of the absorbed energy or power at λn; λ1 is a wavelength corresponding to a peak absorption value attributable to an amide moiety; λ2 is a wavelength corresponding to a baseline absorption value attributable to an amide moiety; λ3 is a wavelength corresponding to a peak absorption value attributable to a phosphate moiety; λ4 is a wavelength corresponding to a baseline absorption value attributable to a phosphate moiety; X is numerical factor ≥1 which is set to a value sufficient to ensure that the measure M for a peak absorption values λ3 and λ1 is always greater than the measure M for the corresponding baseline absorption values λ4 and λ2 for all measurements; and λ1=6.0±0.1 microns; λ2=6.5±0.1 microns; λ3=a number selected from a group consisting of 8.13±0.1 microns and 9.26±0.1 microns; λ4 =a number selected from a group consisting of 8.57±0.1 microns and 10.0±0.1 microns.   
     
     
       16. The method of  claim 15 , further comprising:
 determining from the infrared absorption data at selected wavelengths for each of a plurality of additional pixels in a two-dimensional array with the first pixel, a first measure of the amount of energy or power absorbed attributable to an amide moiety and a second measure of the amount of energy or power absorbed attributable to a phosphate moiety; and   determining a ratio of the first measure and the second measure to establish a histological index for each one of the plurality of additional pixels, wherein the histological index, PA, is derived according to the expression PA=[|M(λ3)−M(λ4)|]/ [|M(λ1)−M(λ2)|]or PA=[X M(λ3)−M(λ4)]/ [X M(λ1)−M(λ2)], where: M(λn) is a measure of the absorbed energy or power at λn; λ1 is a wavelength corresponding to a peak absorption value attributable to an amide moiety; λ2 is a wavelength corresponding to a baseline absorption value attributable to an amide moiety; λ3 is a wavelength corresponding to a peak absorption value attributable to a phosphate moiety; λ4 is a wavelength corresponding to a baseline absorption value attributable to a phosphate moiety; X is numerical factor ≥1 which is set to a value sufficient to ensure that the measure M for a peak absorption values λ3 and λ1 is always greater than the measure M for the corresponding baseline absorption values λ4 and λ2 for all measurements; and λ1=6.0±0.1 microns; λ2=6.5±0.1 microns; λ3=a number selected from a group consisting of 8.13±0.1 microns and 9.26±0.1 microns; λ4=a number selected from a group consisting of 8.57±0.1 microns and 10.0±0.1 microns.   
     
     
       17. The method of  claim 16 , further comprising generating a histological map of the sample using the histological indices for each pixel. 
     
     
       18. The method of  claim 16 , further including performing a bad pixel replacement procedure comprising:
 deriving a histogram of a measured pixel values selected from a group consisting of measured absorption values λ1, λ2, λ3, and λ4 in the two-dimensional array;   identifying pixels having the lowest frequency of occurrence of the measured absorption values; and   replacing the absorption value of each of the identified pixels with a substitute value comprising an average value of one or more adjacent pixels to the identified pixel.   
     
     
       19. A method of determining a tissue characteristic in a tissue sample, the method comprising:
 gathering infrared absorption data from the sample;   determining from the infrared absorption data at selected wavelengths, a first measure of the amount of energy or power absorbed attributable to an amide moiety and a second measure of the amount of energy or power absorbed attributable to a phosphate moiety; and   determining a ratio of the first measure and the second measure to establish a histological index PA derived according to the expression PA=[|M(λ3)−M(λ4)|]/[|M(λ1)−M(λ2)|] or PA=[X M(λ3)−M(λ4)]/[X M(λ1)−M(λ2)], where: M(λn) is a measure of the absorbed energy or power at λn; λ1 is a wavelength corresponding to a peak absorption value attributable to an amide moiety; λ2 is a wavelength corresponding to a baseline absorption value attributable to an amide moiety; λ3 is a wavelength corresponding to a peak absorption value attributable to a phosphate moiety; λ4 is a wavelength corresponding to a baseline absorption value attributable to a phosphate moiety; X is numerical factor ≥1 which is set to a value sufficient to ensure that the measure M for a peak absorption values λ3 and λ1 is always greater than the measure M for the corresponding baseline absorption values λ4 and λ2 for all measurements; and λ1=6.0±0.1 microns; λ2=6.5±0.1 microns; λ3=a number selected from a group consisting of 8.13±0.1 microns and 9.26±0.1 microns; λ4=a number selected from a group consisting of 8.57±0.1 microns and 10.0±0.1 microns.   
     
     
       20. The method of  claim 19  in which the value X is set according to the signal-to-noise ratio of the measurement system. 
     
     
       21. The method of  claim 19  in which the value of X lies in the range 1.2 to 1.5. 
     
     
       22. The method of  claim 19  in which each of the first and second measures is obtained from: sample data S; environment data Es; background data B; and background environment data Eb, the method further comprising compensating the sample data S using Es, B, Eb, where:
 (i) sample data S is taken with the sample loaded in the machine on the sample stage and the shutter open/removed; 
 (ii) environment data Es is taken with the sample loaded in the machine and the shutter in/closed; 
 (iii) background data B is taken with the sample out of the apparatus and the shutter open/removed; and 
 (iv) background environment data Eb is taken with the sample out and the shutter in/closed. 
 
     
     
       23. The method of  claim 19 , wherein the infrared absorption data are gathered from the sample at selected wavelengths. 
     
     
       24. The method of  claim 19  further including using the histological index to derive a cancer grading. 
     
     
       25. The method of  claim 24  in which the cancer grading is breast cancer. 
     
     
       26. Apparatus for determining a tissue characteristic in a tissue sample comprising:
 a detector configured to obtain infrared absorption data from a tissue sample;   a processing module configured to process said infrared absorption data, the apparatus being configured to carry out the method of claim 15.   
     
     
       27. The apparatus of  claim 26 , wherein the detector is configured to obtain the infrared absorption data at selected wavelengths. 
     
     
       28. A method of mapping a tissue characteristic in a tissue sample, the method comprising:
 gathering infrared absorption data from the sample;   determining a first measure of the amount of energy or power absorbed attributable to an amide moiety and a second measure of the amount of energy or power absorbed attributable to a phosphate moiety from the infrared absorption data at selected wavelengths for each of a plurality of pixels in a two-dimensional array; and   determining a ratio of the first measure and the second measure to establish a histological index PA derived according to the expression PA=[|M(λ3)−M(λ4)|]/[|M(λ1)−M(λ2)|]or PA=[X M(λ3)−M(λ4)]/[X M(λ1)−M(λ2)], where: M(λn) is a measure of the absorbed energy or power at λn; λ1 is a wavelength corresponding to a peak absorption value attributable to an amide moiety; λ2 is a wavelength corresponding to a baseline absorption value attributable to an amide moiety; λ3 is a wavelength corresponding to a peak absorption value attributable to a phosphate moiety; λ4 is a wavelength corresponding to a baseline absorption value attributable to a phosphate moiety; X is numerical factor ≥1 which is set to a value sufficient to ensure that the measure M for a peak absorption values λ3 and λ1 is always greater than the measure M for the corresponding baseline absorption values λ4 and λ2 for all measurements; and λ1=6.0±0.1 microns; λ2=6.5±0.1 microns; λ3=a number selected from a group consisting of 8.13±0.1 microns and 9.26±0.1 microns; λ4=a number selected from a group consisting of 8.57±0.1 microns and 10.0±0.1 microns.   
     
     
       29. The method of  claim 28 , further including performing a bad pixel replacement procedure comprising:
 deriving a histogram of a measured absorption value selected from a group consisting of measured absorption values λ1, λ2, λ3, and λ4 in the array;   identifying pixels having the lowest frequency of occurrence of the measured absorption values; and   replacing the absorption value of each of the identified pixels with a substitute value comprising an average value of one or more adjacent pixels to the identified pixel.   
     
     
       30. The method of  claim 29 , further including performing the bad pixel replacement procedure for each of the wavelengths λ1, λ2, λ3, and λ4. 
     
     
       31. The method of  claim 28  further including plotting spatial variations in the histological index in at least two dimensions. 
     
     
       32. The method of  claim 28  further including classifying each pixel as indicative of first, second or third tissue type based on the histological index for each pixel. 
     
     
       33. The method of  claim 28  further including classifying each pixel as indicative of a non-cancerous tissue candidate type or a cancerous tissue candidate type. 
     
     
       34. The method of  claim 33  applied to breast tissue.