# US RE50,871 E1 · Infrared imaging of biological material

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- Number: US RE50,871 E1
- Document ID: USRE50871E1
- Status: Granted
- Kind: E1
- Application number: 17/940,624
- Filed: 2022-10-31
- Granted: 2026-04-21
- Earliest claimed: 2015-04-29
- Assignees: Digistain Inc.
- Applicants: Digistain Inc.
- Inventors: Christopher Clement Phillips; Hemmel Amrania
- Web page: https://patentgrep.com/patent/USRE50871E1

## CPC

- G01N 21/3563: for analysing solids; Preparation of samples therefor
- A61B 5/0075: {by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy (A61B5/0071 takes precedence)}
- G01J 3/42: Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry (beam switching arrangements G01J3/08)
- G01N 21/314: {with comparison of measurements at specific and non-specific wavelengths (dual wavelength spectrometry G01J3/427)}
- G01N 21/35: using infrared light (G01N21/39 takes precedence)
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G01J: MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY (light sources F21, H01J, H01K, H05B; investigating properties of materials by optical means G01N)

## 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.

## Claims

### Claim 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.

### Claim 2 (depends on 1)

The method of claim 1 in which the value X is set according to the signal-to-noise ratio of the measurement system.

### Claim 3 (depends on 1)

The method of claim 1 in which the value of X lies in the range 1.2 to 1.5.

### Claim 4 (depends on 1)

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.

### Claim 5 (depends on 4)

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].

### Claim 6 (depends on 1)

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.

### Claim 7 (depends on 6)

The method of claim 6 further including performing the bad pixel replacement procedure for each of the wavelengths λ1, λ2, λ3, and λ4.

### Claim 8 (depends on 1)

The method of claim 1 further including plotting spatial variations in the histological index in at least two dimensions.

### Claim 9 (depends on 7)

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.

### Claim 10 (depends on 7)

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.

### Claim 11 (depends on 10)

The method of claim 10 applied to breast tissue.

### Claim 12 (depends on 1)

The method of claim 1 further including using the histological index to derive a cancer grading.

### Claim 13 (depends on 12)

The method of claim 12 in which the cancer grading is breast cancer.

### Claim 14 (depends on 1)

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.

### Claim 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.

### Claim 16 (depends on 15)

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.

### Claim 17 (depends on 16)

The method of claim 16, further comprising generating a histological map of the sample using the histological indices for each pixel.

### Claim 18 (depends on 16)

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.

### Claim 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.

### Claim 20 (depends on 19)

The method of claim 19 in which the value X is set according to the signal-to-noise ratio of the measurement system.

### Claim 21 (depends on 19)

The method of claim 19 in which the value of X lies in the range 1.2 to 1.5.

### Claim 22 (depends on 19)

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.

### Claim 23 (depends on 19)

The method of claim 19, wherein the infrared absorption data are gathered from the sample at selected wavelengths.

### Claim 24 (depends on 19)

The method of claim 19 further including using the histological index to derive a cancer grading.

### Claim 25 (depends on 24)

The method of claim 24 in which the cancer grading is breast cancer.

### Claim 26 (depends on 15)

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.

### Claim 27 (depends on 26)

The apparatus of claim 26, wherein the detector is configured to obtain the infrared absorption data at selected wavelengths.

### Claim 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.

### Claim 29 (depends on 28)

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.

### Claim 30 (depends on 29)

The method of claim 29, further including performing the bad pixel replacement procedure for each of the wavelengths λ1, λ2, λ3, and λ4.

### Claim 31 (depends on 28)

The method of claim 28 further including plotting spatial variations in the histological index in at least two dimensions.

### Claim 32 (depends on 28)

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.

### Claim 33 (depends on 28)

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.

### Claim 34 (depends on 33)

The method of claim 33 applied to breast tissue.