# US 2025/0157584 A1 · System, method, and article for detecting abnormal cells using multi-dimensional analysis

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- Number: US 2025/0157584 A1
- Document ID: US20250157584A1
- Status: Published application
- Kind: A1
- Application number: 18/740,308
- Filed: 2024-06-11
- Published: 2025-05-15
- Earliest claimed: 2005-02-18
- Assignees: HematoLogics, Inc.
- Applicants: Hematologics, Inc.
- Inventors: Michael R. Loken; Sanjaya N. Joshi
- Web page: https://patentgrep.com/patent/US20250157584A1

## CPC

- G16B 40/10: Signal processing, e.g. from mass spectrometry [MS] or from PCR
- G01N 15/1456: {without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals}
- G01N 33/5091: {for testing the pathological state of an organism}
- G01N 33/56966: {Animal cells}
- G01N 33/56972: {White blood cells}
- G01N 33/575: for cancer
- G01N 33/5759: {involving compounds localised on the membrane of tumour or cancer cells}
- G06F 18/23: Clustering techniques
- G06F 18/41: {Interactive pattern learning with a human teacher}
- G06V 10/762: using clustering, e.g. of similar faces in social networks
- G06V 10/7788: {the supervisor being a human, e.g. interactive learning with a human teacher}
- G06V 20/698: {Matching; Classification}
- G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
- G01N 15/01: specially adapted for biological cells, e.g. blood cells (investigating sedimentation of particle suspensions in blood G01N15/05)
- G16B 25/00: ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
- G16B 45/00: ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- 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)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

A system, method, and article for diagnosing a test set of biological cells. For example, in one embodiment a normal set of cells is characterized using flow cytometry. A centroid and radius are defined for a set of clusters in an n-dimensional space corresponding to a normal maturation for a cell lineage in the normal set of cells. A test set of cells is characterized using flow cytometry and the characterization is compared to the set of clusters.

## Claims

### Claim 1

(canceled)

### Claim 2

A device, comprising:
memory; and
processing circuitry coupled to the memory, wherein the processing circuitry, in operation and using the memory:
defines a set of normal cell clusters in an n-dimensional space using a centroid line and radius, the radius originating on the line and a length of the radius being a function of a distance along the centroid line, the distance along the centroid line corresponding to a maturation level with a cell lineage, where n is greater than or equal to six;
compares an indication of a distribution of biological cells of a test set of biological cells along the centroid line in the n-dimensional space to an indication of a distribution of biological cells of the defined set of normal cell clusters along the centroid line in the n-dimensional space, the comparing including:
generating a histogram representing the indication of the distribution of biological cells of the defined set of normal cell clusters in a two-dimensional display having a first axis corresponding to a cell maturation level within a cell lineage and a second axis corresponding to a frequency of occurrence, wherein the histogram comprises a band corresponding to the centroid line and radius used to define the set of normal cell clusters; and
comparing frequencies of occurrence of biological cells along the centroid line in the set of normal cell clusters to frequencies of occurrence of biological cells along the centroid line in the test set of biological cells using the histogram;
characterizing the test set of biological cells based on the comparison of the indication of the distribution of biological cells of a test set of biological cells and the indication of the distribution of biological cells of the defined set of normal cell clusters in the histogram; and
diagnosing cancer in the test set of biological cells based on the characterization of the test set of biological cells.

### Claim 3 (depends on 2)

The device of claim 2, wherein,
each cell in a normal set of biological cells is exposed to a plurality of four or more reagents,
a corresponding plurality of fluorescence intensities of each cell in the normal set of biological cells is measured, and
the defining the set of normal cell clusters includes:
mapping each cell in the normal set of biological cells to a corresponding point in the n-dimensional space based at least in part on the measured plurality of fluorescence intensities of the cell in the normal set of biological cells, wherein the corresponding points form a normal set of points; and
defining the centroid line and radius based on the mapping of the normal set of points in the n-dimensional space.

### Claim 4 (depends on 3)

The device of claim 3, wherein,
each cell in the test set of biological cells is exposed to the plurality of reagents;
a corresponding plurality of fluorescence intensities of each cell in the test set of biological cells is measured, and
the generating the indication of the distribution of biological cells of the test set of biological cells includes:
mapping each cell in the test cell of biological cells to a corresponding point in the n-dimensional space based at least in part on the measured plurality of fluorescence intensities of the cell in the test set of biological cells, wherein the corresponding points form a test set of points.

### Claim 5 (depends on 4)

The device of claim 4, wherein the comparing the indication of the distribution of biological cells of a test set of biological cells and the indication of the distribution of biological cells of the defined set of normal cell clusters comprises:
identifying points in the test set of points which are outside of the set of normal cell clusters defined by the centroid line and radius.

### Claim 6 (depends on 5)

The device of claim 5, wherein the processing circuitry, in operation, clusters the identified points in the test set of points.

### Claim 7 (depends on 4)

The device of claim 4, wherein the processing circuitry, in operation, characterizes the test set of biological cells by determining frequencies of occurrence of cells of the identified points with respect to maturation levels.

### Claim 8 (depends on 7)

The device of claim 7, wherein determining frequencies of occurrence of cells of the identified points with respect to maturation levels includes determining frequencies of occurrence of cells of the identified points along the centroid line defining the set of normal clusters.

### Claim 9 (depends on 2)

The device of claim 2, wherein the indication of the distribution of biological cells of a test set of biological cells and the indication of the distribution of biological cells of the defined set of normal cell clusters are based on measuring a plurality of fluorescence intensities.

### Claim 10 (depends on 2)

The device of claim 2, wherein the biological cells of the defined set of normal cell clusters are a subset of a sample of normal biological cells.

### Claim 11 (depends on 2)

The device of claim 2, wherein the defined set of normal cell clusters corresponds to different stages of maturation within a cell lineage.

### Claim 12 (depends on 2)

The device of claim 2, wherein the radius is a distance to a closest point on the centroid line.

### Claim 13

A non-transitory computer-readable medium having contents which configure a processing device to perform a method, the method comprising:
(a) defining a set of normal cell clusters in an n-dimensional space using a centroid line and radius, the radius originating on the line and a length of the radius being a function of a distance along the centroid line, the distance along the centroid line corresponding to a maturation level with a cell lineage, where n is greater than or equal to six;
(b) comparing an indication of a distribution of biological cells of a test set of biological cells along the centroid line in the n-dimensional space to an indication of a distribution of biological cells of the defined set of normal cell clusters along the centroid line in the n-dimensional space, the comparing including:
(i) generating a histogram representing the indication of the distribution of biological cells of the defined set of normal cell clusters in a two-dimensional display having a first axis corresponding to a cell maturation level within a cell lineage and a second axis corresponding to a frequency of occurrence, wherein the histogram comprises a band corresponding to the centroid line and radius used to define the set of normal cell clusters;
(ii) superimposing a representation of the indication of the distribution of biological cells of a test set of biological cells on the histogram; and
(iii) comparing frequencies of occurrence of biological cells along the centroid line in the set of normal cell clusters to frequencies of occurrence of biological cells along the centroid line in the test set of biological cells using the superimposed representation on the histogram;
(c) characterizing the test set of biological cells based on the comparison of the indication of the distribution of biological cells of a test set of biological cells and the indication of the distribution of biological cells of the defined set of normal cell clusters in the histogram; and
(d) generating an indication of a diagnosis of cancer in the test set of biological cells based on the characterization of the test set of biological cells.

### Claim 14 (depends on 13)

The non-transitory computer-readable medium method of claim 13, wherein the contents comprise instructions executable by the processing circuitry.

### Claim 15 (depends on 13)

The non-transitory computer-readable medium of claim 13, wherein
each cell in a normal set of biological cells is exposed to a plurality of four or more reagents,
a corresponding plurality of fluorescence intensities of each cell in the normal set of biological cells is measured, and
the defining the set of normal cell clusters includes:
mapping each cell in the normal set of biological cells to a corresponding point in the n-dimensional space based at least in part on the measured plurality of fluorescence intensities of the cell in the normal set of biological cells, wherein the corresponding points form a normal set of points; and
defining the centroid line and radius based on the mapping of the normal set of points in the n-dimensional space.

### Claim 16 (depends on 13)

The non-transitory computer-readable medium of claim 13, wherein
each cell in the test set of biological cells is exposed to the plurality of reagents,
a corresponding plurality of fluorescence intensities of each cell in the test set of biological cells is measured, and
the method comprises generating the indication of the distribution of biological cells of the test set of biological cells by mapping each cell in the test cell of biological cells to a corresponding point in the n-dimensional space based at least in part on the measured plurality of fluorescence intensities of the cell in the test set of biological cells, wherein the corresponding points form a test set of points.