RU2803847C1 - Accounting for errors in optical measurements - Google Patents

Abstract

FIELD: measurement equipment.

SUBSTANCE: identifying, within the microscopic image, candidates for a given formation within a blood sample, wherein the given formation is selected from the group consisting of: platelets, leukocytes, erythrocytes, circulating tumour cells, reticulocytes, and Howell-Jolly bodies; confirming at least that the candidate group is these entities by performing additional analysis of the candidates; determining the ratio between the number of candidates of the given formation with the number of confirmed candidates of the given formation and excluding the sample from use for performing at least a group of measurements on the sample, based on the ratio between the number of candidates and the number of confirmed candidates.

EFFECT: ensuring identification of errors in measurements and accounting for such errors.

8 cl, 8 dwg

Description

This Application claims priority to U.S. Provisional Patent Application No. 62/924,229, Pecker, filed October 22, 2019, entitled "Accounting for Errors in Optical Measurements."

This Application relates to the scope of the PCT filed as of the even date hereunder entitled "Accounting for Errors in Optical Measurements", Pecker, claiming priority to US Provisional Patent Application No. 62/924,229, Pecker, filed October 22, 2019.

The above Applications are incorporated herein by reference.

FIELD OF TECHNOLOGY TO WHICH THE INVENTION RELATES

Some applications of the currently disclosed subject matter relate generally to the analysis of bodily samples and, in particular, to optical density and microscopic measurements that are performed on blood samples.

BACKGROUND OF THE ART

In some optical-based methods (eg, diagnostic and/or analytical methods), a property of a biological sample, such as a blood sample, is determined by performing an optical measurement. For example, the density of a component (eg, the amount of a component per unit volume) can be determined by counting the component within a microscopic image. Likewise, the concentration and/or density of a component can be measured by performing optical absorption, transmittance, fluorescence and/or luminescence measurements on the sample. Typically, the sample is placed in a sample holder and measurements are made on a portion of the sample that is contained within the sample holder chamber. Measurements made on a portion of the sample that is contained within the sample holder chamber are analyzed to determine the properties of the sample.

SUMMARY OF THE INVENTION

In accordance with some applications of the present invention, a biological sample (eg, a blood sample) is placed in a sample holder. While the sample is positioned in the sample holder, optical measurements are performed on the sample by one or more optical measurement devices. For example, optical measurement devices may comprise a microscope (eg, digital microscope), spectrophotometer, photometer, spectrometer, camera, spectral camera, hyperspectral camera, fluorometer, spectrofluorometer, and/or photodetector (eg, photodiode, photoresistor, and/or phototransistor). For some applications, optical measurement devices contain special light sources (such as light-emitting diodes, incandescent light sources, etc.) and/or optical elements to control light collection and/or light emission (such as lenses, diffusers, filters, and etc.). For some applications, a microscope system is used that is substantially similar to the microscope system described in US 2014/0347459, Greenfield, which is incorporated herein by reference.

A computer processor typically receives and processes optical measurements made by an optical measurement device. Additionally, typically a computer processor controls the acquisition of optical measurements that are performed by one or more optical measurement devices. For some applications, the optical measurement device is located within the optical measurement unit. To perform optical measurements on a sample, the sample holder is placed within the optical measurement unit. Typically, the optical measurement unit contains a microscope system configured to perform microscopic imaging of a portion of a sample. For some applications, the microscope system includes a set of bright-field light sources (eg, light-emitting diodes) that are configured to be used for bright-field imaging of the sample, a set of fluorescent light sources (eg, light-emitting diodes) that are configured to be used for fluorescent imaging of the sample, and a camera (such as a CCD camera and/or a CMOS camera) configured to acquire an image of the sample. Typically, the optical measurement unit also includes an optical density measurement unit configured to perform optical density measurements (eg, optical absorption measurements) on a second portion of the sample. For some applications, the optical density measurement unit comprises sets of optical density measuring light sources (eg, light emitting diodes) and light detectors that are configured to perform optical density measurements on a sample. For some applications, each of the above sets of light sources (i.e., a set of brightfield light sources, a set of fluorescent light sources, and a set of optical density light sources) comprises a group of light sources (e.g., a group of light-emitting diodes), each of which is configured with the ability to emit light at a suitable wavelength or range of wavelengths.

In accordance with some applications of the present invention, various techniques are performed (typically by a computer processor) to determine whether various errors have occurred, and possibly identify the source of the error if an error has occurred. Such errors may arise from preparing the entire sample. For example, the sample may have been left in the sample holder for too long before measurements were taken (which could cause the sample to deteriorate and/or prevent dyes that were mixed with one or both portions of the sample from becoming overly absorbed into the formations inside sample). Alternatively, errors may arise as a result of preparing a special portion of the sample. Alternatively or additionally, errors may result from an error with the sample holder (e.g., the sample holder material itself is unclean, and/or dirt or spilled blood on the sample holder), and/or an error with the microscope system itself, such as illumination (e.g. the light-emitting diode that is used for brightfield imaging, and/or the light-emitting diode that is used during fluorescence imaging of the sample), and/or errors associated with the optical path, and/or the motor and stage components or controllers, and/or errors received from the environment in which the device is placed (for example, relative humidity, temperature, pressure, bulk concentration or any other environmental factors). Additionally, alternatively or additionally, there may be a problem inherent to the sample (for example, a very low amount or a very high amount of a particular formation, or too much time has passed since the sample was collected), which means that the computer processor is not able to perform certain measurements with a sufficient degree of accuracy , and/or what it means that the computer processor should indicate it to the user.

For some applications, in response to identification of an error, the computer processor outputs a message indicating the error and/or indicating the source of the error. For some applications, the computer processor does not perform certain measurements on the blood sample in response to the identification of an error. For some applications, in response to identifying an error, the computer processor does not perform any measurements on the sample, and/or indicates that the sample is unusable, and/or instructs the user to repeat sample preparation with a new test kit, and/or recollect the blood sample. Alternatively or additionally, certain parameters of the blood sample are determined by the computer processor by calibrating the measurements made on the blood sample to account for error.

For some applications, one or more of the following errors are taken into account, for example, in one or more of the ways described above:

Errors in the microscopy device, such as:

- loss of steps in the motor that moves the microscope stage

- changes in the play of movement of the microscope stage

- changes in synchronization between the microscope camera and the microscope stage

- alignment between the microscope camera and the microscope stage (for example, due to relative rotation between these elements)

- problems with the optical system (for example, changes in focusing quality over time, for example caused by samples, or caused by a part of the microscope stage (for example, a scratched part))

- changes in leveling in the microscope system

- change in expected focal position along the z-axis (i.e., optical axis)

- loss of connection between elements

- changes in linear camera response

Errors caused by environmental factors, for example:

- the device is outside the permissible temperature, humidity, height level, etc.

- specific components are outside the target values

Common errors caused by factors such as:

- scanning time

- device startup time

- available working memory/storage device

Some examples of technologies for identifying errors and accounting for such errors are described below in this document.

Thus, in accordance with some applications of the present invention, a method is established, comprising the steps of:

prepare a blood sample for analysis:

placing a blood sample within the sample chamber; And

placing a sample chamber with a blood sample placed therein within the microscopy unit;

obtaining one or more microscopic images of a sample chamber with a blood sample placed therein through a microscope of the microscopy unit;

based on the one or more images, determining the number of one or more types of cells within the sample chamber that have already settled within the sample chamber before obtaining the one or more microscopic images; And

determine the properties of the sample at least partly in response thereto.

In some applications, preparing a blood sample for analysis further comprises staining the blood sample with one or more dyes.

In some applications:

determining the number of one or more cell types within the sample chamber that have already settled within the sample chamber, before obtaining one or more microscopic images, comprises determining whether more than a threshold number of red blood cells have already settled within the sample chamber sample, before taking one or more microscopic images, and

determining a property of the sample comprises, in response to determining that more than a threshold number of red blood cells within the sample chamber have already settled within the sample chamber before acquiring one or more microscopic images, excluding at least a portion of the sample from use to perform at least a number of measurements on the sample.

In some applications, the method further comprises the steps of:

after positioning the sample chamber with the blood sample placed therein within the microscopy unit, allowing one or more cell types within the sample chamber to form a monolayer of cells;

obtain a set of one or more additional microscopic images of a monolayer of cells; And

perform one or more measurements on a sample by analyzing a set of one or more additional microscopic images.

In some applications, the method further comprises determining an indication of how long the blood sample has been in the sample chamber before acquiring one or more microscopic images, based on the number of one or more cell types that have already settled within the sample chamber before obtaining one or more several microscopic images.

In some applications

the method further comprises the step of performing one or more measurements on the sample,

determining the number of one or more types of cells within the sample chamber that have already settled within the sample chamber, before obtaining one or more microscopic images, comprises determining whether more than a threshold number of red blood cells have already settled within the sample chamber within the sample chamber , before acquiring one or more microscopic images, and

making one or more measurements on the sample comprises, in response to determining that more than a threshold number of red blood cells within the sample chamber have already settled within the sample chamber, before obtaining one or more microscopic images, calibrating the measurements.

In some applications, preparing a blood sample for analysis further comprises staining the blood sample with one or more dyes; calibrating the measurement comprises calibrating the measurement to account for the amount of staining to which formations within the blood sample have undergone, as indicated by exceeding a threshold number of red blood cells within the sample chamber already deposited in within the sample chamber, before acquiring one or more microscopic images.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing a portion of the blood sample within the sample chamber;

obtaining microscopic images of red blood cells within the blood sample as the red blood cells within the blood sample settle within the sample chamber;

determine the property of the dynamics of sedimentation of a blood sample by image analysis; And

create an output signal in response to this.

In some applications, placing a portion of a blood sample within a sample chamber comprises placing an undiluted portion of a blood sample within a sample chamber, and obtaining microscopic images of red blood cells within a blood sample comprises obtaining microscopic images of red blood cells within an undiluted blood sample.

In some applications, determining the sedimentation dynamics property of a blood sample by image analysis comprises determining the sedimentation dynamics property of the blood sample in real time with respect to the sedimentation of red blood cells within the blood sample.

In some applications, determining the sedimentation dynamics property of a blood sample by image analysis comprises determining the sedimentation dynamics property of a blood sample while red blood cells within the blood are still settling.

In some applications, determining the sedimentation dynamics property of a blood sample by image analysis comprises determining the erythrocyte sedimentation rate of the blood sample by image analysis.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing a first portion of a blood sample within the first sample chamber;

placing a second portion of the blood sample within the second sample chamber;

obtain microscopic images of the first portion of the blood sample;

perform optical density measurements on the second portion of the blood sample;

discover that the concentration of this formation inside the sample exceeds a threshold value; And

determine the reason for exceeding the threshold value of the concentration of a given formation in comparison with the parameter determined from microscopic images of the first portion of the blood sample, with the parameter determined from the optical density measurement performed on the second portion of the blood sample.

In some applications, determining the cause of the concentration of a given entity exceeding a threshold value includes determining that the blood sample itself is causing the concentration of a given entity within the sample to exceed a threshold value, determining that the concentration of the entity, as indicated by microscopic images, is similar to the concentration of the entity, as determined from measurements optical density.

In some applications, determining why a threshold concentration of a given entity is exceeded includes determining that the preparation of one portion of a blood sample causes the concentration of a given entity within the sample to exceed a threshold, determining that the concentration of the entity as indicated by microscopic images is different from the concentration of the entity, as determined from absorbance measurements.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber;

obtain microscopic images of a portion of a blood sample;

identifying, within the microscopic image, at least one type of formation selected from the group consisting of: echinocytes, spherocytes and serrated erythrocytes;

measure the amount of the selected type of education; And

create an output signal in response to this.

In some applications, identifying at least one type of formation comprises identifying echinocytes. In some applications, identifying at least one type of formation comprises identifying spherocytes. In some applications, identifying at least one type of formation comprises identifying jagged red blood cells.

In some applications, generating an output signal comprises excluding at least a portion of the blood sample from use for performing at least a group of measurements on the blood sample based at least in part on the amount of a selected type of formation exceeding a threshold value. In some applications, creating an output signal includes creating a quantity indication for the user. In some applications, generating the output signal comprises generating an indication of the age of the sample portion to the user.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber;

obtain microscopic images of a portion of a blood sample;

identifying, within the microscopic images, at least one type of formation selected from the group consisting of: echinocytes, spherocytes and serrated erythrocytes;

measure the amount of the selected type of education; And

determining an indication of the age of the sample portion based at least in part on the quantity.

In some applications, the method further comprises measuring a sample parameter by analyzing microscopic images, and measuring the sample parameter comprises performing a measurement on the microscopic images and calibrating the measurement based on determining an indication of the age of a portion of the sample.

In some applications, the method further comprises measuring a sample parameter by performing an optical density measurement on a second portion of the blood sample, and measuring the sample parameter comprises calibrating the optical density measurement based on a particular indication of the age of the sample portion.

In some applications, identifying at least one type of formation comprises identifying echinocytes. In some applications, identifying at least one type of formation comprises identifying spherocytes. In some applications, identifying at least one type of formation comprises identifying jagged red blood cells.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber, which is a cavity that contains a base surface;

allowing cells in the cell suspension to settle on the base surface of the holder to form a monolayer of cells on the base surface of the holder;

obtaining at least one microscopic image of at least a portion of a monolayer of cells;

identify, within the microscopic image, hemolyzed red blood cells;

measuring the number of identified hemolyzed red blood cells; And

creating an output signal based on the number of identified hemolyzed red blood cells.

In some applications, the method further comprises, based on the number of identified hemolyzed red blood cells, estimating the total number of hemolyzed red blood cells within the blood sample that is greater than the number of identified hemolyzed red blood cells, and generating an output signal comprises providing an indication of the estimated total hemolyzed red blood cell count to the user.

In some applications, generating an output signal comprises excluding a sample portion from use to perform at least a group of measurements on the sample based at least in part on the number of said hemolyzed red blood cells exceeding a threshold value.

In some applications, excluding a sample from use to perform at least a group of measurements on the sample comprises, based on the number of identified hemolyzed red blood cells, an estimate of the total number of hemolyzed red blood cells within the sample that is greater than the number of identified hemolyzed red blood cells.

In some applications, the method further comprises staining a blood sample, and identifying at least partially hemolyzed red blood cells comprises distinguishing hemolyzed red blood cells from non-hemolyzed red blood cells by identifying red blood cells that are stained with the dye as hemolyzed.

In some applications, staining the blood sample comprises staining the blood sample with a Hoechst reagent.

In some applications, obtaining at least one microscopic image of at least a portion of a monolayer of cells comprises obtaining at least one bright-field microscopic image of at least a portion of the monolayer of cells, and identifying red blood cells that are stained with a dye comprises identifying red blood cells having an outline that is visible in within the bright field microscopic image, and having an interior that is similar to the background of the bright field microscopic image.

In some applications, obtaining at least one microscopic image of at least a portion of a monolayer of cells comprises obtaining at least one fluorescent microscopic image of at least a portion of the monolayer of cells, and identifying red blood cells that are stained with a dye comprises identifying red blood cells that appear as bright circles in within the image.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing the biological sample in a sample chamber that has a group of areas, each of which defines corresponding different heights;

measuring a parameter that indicates the transmission of light through the sample chamber in appropriate areas; And

use a computer processor:

a normalizing parameter, which is measured in the corresponding areas in relation to each other;

detecting that there is a bubble within the sample chamber, at least in part in response thereto; And

performing an action in response to detection that there is a bubble within the sample chamber.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing the blood sample in a sample chamber that has a group of areas, each of which defines corresponding different heights;

measuring a parameter that indicates the transmission of light through the sample chamber in appropriate areas; And

use a computer processor:

based on the absolute value of the parameter in selected areas, calculating the hemoglobin concentration inside the sample;

a normalizing parameter, which is measured in the corresponding areas in relation to each other; And

confirming the calculated hemoglobin concentration based on the normalized parameter.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber;

obtain microscopic images of a portion of a blood sample;

identifying within the microscopic image candidates for a given formation within the blood sample;

confirm at least that the group of candidates is these entities by performing additional analysis of the candidates;

compare the number of candidates for a given education with the number of confirmed candidates for a given education; And

eliminating at least a portion of the sample from use for performing at least a group of measurements on the sample based at least in part on the relationship between the number of candidates and the number of confirmed candidates.

In some applications:

identifying, within a microscopic image, candidates for a given formation within a blood sample comprises identifying, within a microscopic image, candidates for platelets within a blood sample;

confirming that at least a group of candidates are these entities, performing additional analysis of the candidates, contains confirmation that at least a group of the candidate platelets are platelets, performing additional analysis of the candidates; And

excluding at least a portion of the sample from use to perform at least a group of measurements on the sample comprises excluding at least a portion of the sample from use to perform at least a group of measurements on the sample based at least in part on the relationship between the number of platelet candidates and the amount confirmed platelet candidates.

In some applications:

identifying, within a microscopic image, candidates for a given formation within a blood sample comprises identifying, within a microscopic image, candidate leukocytes within a blood sample;

confirming that at least a group of candidates are these entities, performing additional analysis of the candidates, contains confirmation that at least a group of the candidates for leukocytes are leukocytes, performing additional analysis of the candidates; And

excluding at least a portion of the sample from use to perform at least a group of measurements on the sample comprises excluding at least a portion of the sample from use to perform at least a group of measurements on the sample based at least in part on the relationship between the number of leukocyte candidates and the number confirmed leukocyte candidates.

In some applications, excluding at least a portion of a sample from use to perform at least a group of measurements on the sample comprises excluding at least a portion of the sample from use to perform at least a group of measurements on the sample based on the ratio of the number of confirmed candidates to the number of candidates in excess of a maximum threshold value.

In some applications, excluding at least a portion of a sample from use to perform at least a group of measurements on the sample comprises excluding at least a portion of the sample from use to perform at least a group of measurements on the sample based on a ratio of the number of confirmed candidates to the number of candidates that is less minimum threshold value.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber;

obtain microscopic images of a portion of a blood sample;

identify, within the microscopic image, candidate leukocytes within the blood sample;

confirm that at least some of the leukocyte candidates are given types of leukocytes by performing additional analysis of the leukocyte candidates;

comparing the number of leukocyte candidates with the number of leukocyte candidates confirmed to be the given leukocyte types; And

excluding at least a portion of the sample from use for performing at least a group of measurements on the sample based at least in part on the relationship between the number of leukocyte candidates and the number of leukocyte candidates confirmed to be the given leukocyte types.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

staining the blood sample with one or more dyes;

obtaining at least one microscopic image of a blood sample;

identifying contaminants within the sample by identifying colored objects having irregular shapes;

count one or more formations located inside the sample by performing microscopic analysis on the sample; And

exclude from the calculation areas of the sample located within these distances from the identified pollutants.

In some applications, staining a blood sample with one or more dyes comprises staining the blood sample with acridine orange and Hoechst's reagent, and identifying foreign substances comprises identifying colored objects that have irregular shapes and that are stained with both acridine orange and Hoechst's reagent.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber;

perform optical measurements on the sample;

based on the optical measurements, determining that one or more air bubbles are present within the sample chamber;

generating an output signal at least in part based on determining that one or more air bubbles are present within the sample chamber.

In some applications, the method further comprises determining one or more sample parameters based on optical measurements, and excluding at least a group of optical measurements from use to determine one or more sample parameters based on determining that one or more air bubbles are present within the chamber .

In some applications, generating an output signal comprises excluding a portion of the blood sample from being used to perform at least a group of measurements on the sample based on determining that one or more air bubbles are present within the sample chamber.

In some applications, determining that one or more air bubbles are present within the sample chamber involves analyzing the optical absorption profile of the sample along a given direction along the sample chamber.

In some applications, making optical measurements on a sample comprises taking one or more optical absorption measurements at a wavelength at which hemoglobin does not absorb light, and determining that one or more air bubbles are present within the sample chamber comprises analyzing one or more measurements optical absorption at a wavelength at which hemoglobin does not absorb light.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within the sample chamber, which is a cavity that contains a base surface;

allowing cells in the cell suspension to settle on the base surface of the holder to form a monolayer of cells on the base surface of the holder;

obtaining at least one microscopic image of at least a portion of a monolayer of cells;

identify, within the microscopic image, an area in which the sample is not present; And

eliminate the use of at least the identified region in microscopic analysis of a portion of the sample.

In some applications, identifying the region in which the sample is not present comprises identifying the interface between the wet region and the dry region on the base surface of the sample chamber.

In some applications, identifying a region in which a sample is not present comprises discriminating between a region in which a sample is not present and one or more regions in which a sample is present and the sample has a low cell density.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within a sample chamber, which is a cavity that contains a base surface and a top cover;

allowing cells in the cell suspension to settle on the base surface of the holder to form a monolayer of cells on the base surface of the holder;

obtaining at least one microscopic image of at least a portion of a monolayer of cells while the microscope is focused on the focal plane of the monolayer, and the portion of the monolayer of cells is located within the focal plane of the monolayer;

identifying that the dirt is located on the top coating or on the back side of the base surface by identifying an area in which the formation is visible on a focal plane that is different from the focal plane of the monolayer; And

eliminate the use of at least the identified region in microscopic analysis of a portion of the sample.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

placing at least a portion of the blood sample within a sample chamber, which is a cavity that contains a base surface and a top cover;

allowing cells in the cell suspension to settle on the base surface of the holder to form a monolayer of cells on the base surface of the holder;

obtaining at least one microscopic image of at least a portion of a monolayer of cells while the microscope is focused on the focal plane of the monolayer, and the portion of the monolayer of cells is located within the focal plane of the monolayer;

identifying an area in which the background intensity of the microscopic image is indicative that dirt is located on the top coating or on the back of the base surface; And

eliminate the use of at least the identified region in microscopic analysis of a portion of the sample.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

staining at least a portion of the blood sample with a fluorescent dye;

identifying stained cells within the blood sample by obtaining a group of fluorescent microscopic images of a portion of the blood sample through a microscopy unit, illuminating the portion of the sample with a light source that emits light in a given spectral range;

identifying that one or more fluorescent areas that are visible within the microscopic image obtained when illuminated by a light source other than the stained cells; And

determine a property of the light source based on the identified fluorescent regions.

In some applications, determining a property of the light source based on the identified fluorescent regions comprises determining whether the spatial distribution of illumination of the fluorescent light source has changed since a previous measurement.

In some applications, determining a property of a light source based on the identified fluorescent regions comprises determining whether the spatial uniformity of illumination of the fluorescent light source has changed since a previous measurement.

In some applications, determining a property of the light source based on the identified regions comprises determining whether the spatial position of illumination by the fluorescent light source has changed since a previous measurement.

In some applications, determining a property of the light source based on the identified regions comprises determining whether the vignetting effects of the fluorescent light source illumination have changed since a previous measurement.

In some applications, determining a property of the light source based on the identified regions comprises determining whether the spectral distribution of illumination of the fluorescent light source has changed since a previous measurement.

In some applications, determining a property of the light source based on the identified regions comprises determining whether the illumination intensity of the fluorescent light source has changed since a previous measurement.

In some applications, the method further comprises determining a parameter of the blood sample by performing measurements on stained cells, and normalizing the measurement based on a determined property of the light source.

In some applications, the method further comprises excluding at least a group of measurements from being performed on the blood sample based on a particular property of the light source.

In some applications, identifying one or more fluorescent regions that are visible within a microscopic image that is obtained when illuminated by a light source other than stained cells comprises identifying intercellular regions within the blood sample.

In some applications, identifying one or more fluorescent regions that are visible within a microscopic image that is obtained when illuminated by a light source other than stained cells comprises identifying one or more fluorescent regions of the microscopy unit.

In some applications, obtaining a group of fluorescent microscopic images of a portion of a blood sample comprises obtaining a group of fluorescent microscopic images of a portion of a blood sample while the blood sample is placed in a sample holder, and identifying one or more fluorescent regions that are visible within the microscopic image that is obtained. when illuminated by a light source other than stained cells, contains the identification of one or more fluorescent regions of the sample holder.

In some applications, the sample holder contains glass and plastic layers that are bonded to each other through a pressure-sensitive adhesive that fluoresces, and identification of one or more fluorescent areas that are visible within a microscopic image that is obtained when illuminated by a light source other than colored cells, contains identification of a pressure-sensitive adhesive.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

staining at least a portion of the blood sample with a fluorescent dye;

identifying stained cells within the blood sample by obtaining a group of fluorescent microscopic images of a portion of the blood sample, illuminating the portion of the sample with a light source that emits light in a given spectral range;

identifying that one or more fluorescent areas that are visible within the microscopic image obtained when illuminated by a light source other than the stained cells; And

normalize the fluorescence of the stained cells based on the identified fluorescent regions.

In some applications, identifying one or more fluorescent regions that are visible within a microscopic image that is obtained when illuminated by a light source other than stained cells comprises identifying intercellular regions within the blood sample.

In some applications, identifying one or more fluorescent regions that are visible within a microscopic image that is obtained when illuminated by a light source other than stained cells comprises identifying one or more fluorescent regions of the microscopy unit.

In some applications, obtaining a group of fluorescent microscopic images of a portion of a blood sample comprises obtaining a group of fluorescent microscopic images of a portion of a blood sample while the blood sample is placed in a sample holder, and identifying one or more fluorescent regions that are visible within the microscopic image that is obtained. when illuminated by a light source other than stained cells, contains the identification of one or more fluorescent regions of the sample holder.

In some applications, the sample holder contains glass and plastic layers that are bonded to each other through a pressure-sensitive adhesive that fluoresces, and identification of one or more fluorescent areas that are visible within a microscopic image that is obtained when illuminated by a light source other than colored cells, contains identification of a pressure-sensitive adhesive.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

identifying formations within the blood sample by obtaining a group of bright-field microscopic images of at least a portion of the blood sample, illuminating the portion of the blood sample with light from a bright-field light source;

analyzing the bright field regions of light emitted by the bright field light source in the absence of a blood sample; And

determine the property of the bright-field light source based on the analysis of the bright-field regions of the light.

In some applications, determining a property of a light source based on the identified brightfield regions comprises determining whether the spatial distribution of illumination by the brightfield light source has changed from a previous measurement.

In some applications, determining a property of a light source includes determining whether the spatial uniformity of illumination by a brightfield light source has changed from a previous measurement.

In some applications, determining a property of a light source includes determining whether the spatial position of the illumination of the brightfield light source has changed from a previous measurement.

In some applications, determining a property of a light source includes determining whether the vignetting effects of the brightfield light source have changed from a previous measurement.

In some applications, determining a property of the light source comprises determining whether the spectral distribution of illumination by the brightfield light source has changed since a previous measurement.

In some applications, determining a property of a light source includes determining whether the illumination intensity of the brightfield light source has changed since a previous measurement.

In some applications, analyzing brightfield regions of light emitted by the brightfield light source in the absence of a blood sample comprises periodically analyzing brightfield regions of light emitted by the brightfield light source in the absence of a blood sample at fixed time intervals.

In some applications, the analysis of brightfield regions of light emitted by the brightfield light source in the absence of a blood sample comprises analysis of brightfield regions of light emitted by the brightfield light source after a predetermined number of blood samples have been imaged by the brightfield light source.

In some applications, the method further comprises determining a parameter of the blood sample by performing a measurement on structures within the blood sample, and normalizing the measurement based on a determined property of the bright field light source.

In some applications, the method further comprises excluding at least a group of measurements from being performed on the blood sample based on a particular property of the bright field light source.

Additionally, in accordance with some applications of the present invention, a method is provided, comprising the steps of:

staining portions of the respective blood samples with at least one type of fluorescent dye;

using the microscopy unit, fluorescent microscopic images of portions of the corresponding blood samples are obtained by illuminating the sample portion with a group of light sources, each of which emits light in the corresponding spectral range;

discovering that there is an error in at least a group of microscopic images; And

classify the source of the error:

in response to detecting that an error has been introduced from a given point in time, identifying a fluorescent dye as being the source of the error;

in response to detecting that the error has gradually increased over time, identifying dirt within the microscopy unit as being the source of the error; And

in response to detecting that the error is present only in images obtained when illuminated by one of the light sources, identifying one of the light sources as being the source of the error.

The present invention will be fully understood from the following detailed description of embodiments thereof taken in conjunction with the drawings, in which:

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a block diagram showing components of a biological sample analysis system in accordance with certain applications of the present invention;

Fig. 2A, 2B and 2C are schematic illustrations of respective views of a sample holder that is used to perform both microscopic and optical density measurements in accordance with certain applications of the present invention;

Fig. 3A, 3B and 3C are microscopic images of a blood sample that contains hemolyzed red blood cells obtained in accordance with certain applications of the present invention; And

Fig. 4 is a graph showing profiles of normalized light transmittance intensity recorded along the length of a sample chamber, in accordance with some applications of the present invention.

DETAILED DESCRIPTION OF IMPLEMENTATION OPTIONS

Reference is now made to FIG. 1, which is a block diagram showing components of a biological sample analysis system 20 in accordance with some applications of the present invention. Typically, a biological sample (eg, a blood sample) is placed in a sample holder 22. While the sample is positioned in the sample holder, optical measurements are performed on the sample by one or more optical measurement devices 24. For example, optical measurement devices may comprise a microscope (eg, digital microscope), spectrophotometer, photometer, spectrometer, camera, spectral camera, hyperspectral camera, fluorometer, spectrofluorometer, and/or photodetector (eg, photodiode, photoresistor, and/or phototransistor). For some applications, optical measurement devices contain special light sources (such as light-emitting diodes, incandescent light sources, etc.) and/or optical elements to control light collection and/or light emission (such as lenses, diffusers, filters, and etc.). For some applications, a microscope system is used that is substantially similar to the microscope system described in US 2014/0347459, Greenfield, which is incorporated herein by reference.

Computer processor 28 typically receives and processes optical measurements made by the optical measurement device. Additionally, typically a computer processor controls the acquisition of optical measurements that are performed by one or more optical measurement devices. The computer processor interacts with the memory 30. A user (eg, a laboratory technician, or the person from whom the sample was taken) sends commands to the computer processor through the user interface 32. For some applications, the user interface includes a keyboard, a mouse, a joystick, a touch screen device (such such as a smartphone or tablet computer), touchpad, trackball, voice command interface, and/or other types of user interfaces that are known in the art. Typically, the computer processor produces an output signal through the output device 34. Additionally, typically, the output device includes a display such as a monitor, and the output signal includes an output signal that is displayed on the display. For some applications, the processor produces an output signal to another type of visual, text, graphics, tactile, audio, and/or video output device, such as speakers, headphones, a smartphone, or a tablet computer. For some applications, user interface 32 acts as both an input interface and an output interface, that is, it acts as an input/output interface. For some applications, the processor creates an output signal on a computer-readable medium (eg, a computer-readable medium for non-transitory storage of information), such as a disk or portable USB storage device, and/or creates an output signal on a printer.

For some applications, the optical measurement device 24 (and/or the computer processor 28 and memory 30) is located within the optical measurement unit 31. To perform optical measurements on a sample, the sample holder 22 is placed within the optical measurement unit. Typically, the optical measurement unit contains a microscope system configured to perform microscopic imaging of a portion of a sample. For some applications, the microscope system includes a set of bright-field light sources (eg, light-emitting diodes) that are configured to be used for bright-field imaging of the sample, a set of fluorescent light sources (eg, light-emitting diodes) that are configured to be used for fluorescent imaging of the sample, and a camera (such as a CCD camera or a CMOS camera) configured to acquire an image of the sample. Typically, the optical measurement unit also includes an optical density measurement unit configured to perform optical density measurements (eg, optical absorption measurements) on a second portion of the sample. For some applications, the optical density measurement unit comprises a set of optical density measurement light sources (eg, light emitting diodes) and light detectors that are configured to perform optical density measurements on a sample. For some applications, each of the above sets of light sources (i.e., a set of brightfield light sources, a set of fluorescent light sources, and a set of optical density light sources) comprises a group of light sources (e.g., a group of light-emitting diodes), each of which is configured with the ability to emit light at a suitable wavelength or range of wavelengths.

Reference is now made to FIG. 2A and 2B, which are schematic illustrations of respective views of a sample holder 22, in accordance with certain applications of the present invention. Fig. 2A shows a top view of the sample holder (with the top cover of the sample holder shown as opaque in FIG. 2A for purposes of illustration), and FIG. 2B shows a bottom view (in which the sample holder is rotated around its short edge in relation to the view shown in FIG. 2A). Typically, the sample holder includes a first set 52 of one or more cameras that are used to perform microscopic analysis on the sample, and a second set 54 of one or more cameras that are used to perform absorbance measurements on the sample. Typically, the sample holder chambers are filled with a bodily sample, such as blood, through the sample introduction ports 38. For some applications, the chambers define one or more outlet openings 40. The outlet openings are configured to facilitate filling of the chambers with a bodily sample by allowing air that is present in the chambers to be released from the chambers. Typically, as shown, the outlet ports are positioned longitudinally opposite the inlet ports (with respect to the sample chamber of the sample holder). Thus, for some applications, exhaust ports provide a more efficient air removal mechanism than if the exhaust ports were located closer to the intake ports.

Reference is made to FIG. 2C, which shows an exploded view of a sample holder 22 in accordance with some applications of the present invention. For some applications, the sample holder includes at least three components: a molded component 42, a glass sheet 44, and an adhesive layer 46 configured to adhere the glass sheet to the back of the molded component. The molded component is typically made from a polymer (eg, plastic) that is molded (eg, injection molding) to provide the chambers with the desired geometric shape. For example, as shown, the molded component is typically molded to define sample entry holes 38, outlets 40, and grooves 48 that surround a central portion of each of the chambers. The grooves typically facilitate filling the chambers with the solid sample by allowing air to flow into the outlets, and/or allowing the solid sample to flow around the central portion of the chamber.

For some applications, the sample holder as shown in FIG. 2A-C are used when performing a complete blood count on a blood sample. For some applications, a first portion of a blood sample is placed within a chamber of a first set of chambers 52 (which are used to perform microscopic analysis on the sample), and a second portion of a blood sample is placed within a chamber of a second set of chambers 54 (which are used to perform optical density measurements on the sample). For some applications, the first camera set 52 contains a group of cameras, and the second camera set 54 contains only a single camera, as shown. However, the scope of the present applications includes the use of any number of cameras (eg, a single camera or a group of cameras) within either a first set of cameras, or within a second set of cameras, or any combination thereof. The first portion of the blood sample is typically diluted relative to the second portion of the blood sample. For example, the diluent may contain pH buffers, dyes, fluorescent dyes, antibodies, sphere-forming agents, lysing agents, etc. Typically, the second portion of the blood sample, which is housed within the chamber of the second set of chambers 54, is a natural, undiluted blood sample. Alternatively or additionally, the second portion of the blood sample may be a sample that has undergone some modification, including, for example, one or more dilutions (eg, controlled dilution), addition of a component or reagent, or fractionation.

For some applications, one or more staining agents are used to stain a first portion of a blood sample (which is placed within a chamber of the first set of chambers 52) before the sample is imaged microscopically. For example, the staining agent may be configured to stain DNA preferentially over staining other cellular components. Alternatively, the staining agent may be configured to stain all cellular nucleic acids in preference to staining other cellular components. For example, the sample may be stained with acridine orange reagent, Hoechst reagent, and/or any other staining agent that is configured to preferentially stain DNA and/or RNA within the blood sample. The staining agent may be designed to stain all cellular nucleic acids, but DNA and RNA staining is more noticeable under certain lighting and filtering conditions, as is known for example with acridine orange. Images of the sample can be obtained through imaging conditions that allow the detection of cells (eg, bright field) and/or imaging conditions that allow the visualization of stained bodies (eg, appropriate fluorescent lighting). Typically, the first portion of the sample is stained with acridine orange and Hoechst reagent. For example, the first (diluted) portion of a blood sample can be prepared using techniques that are described in US 2015/0316477, Pollak, which is incorporated herein by reference, and which describes a method for preparing blood samples for analysis that includes a dilution step, wherein the step dilution facilitates identification and/or counting of components within microscopic images of a sample.

Typically, prior to microscopic imaging, the first portion of blood (which is housed in the first set of 52 chambers) is allowed to settle so as to form a monolayer of cells, for example, through techniques that are described in US 9,329,129, Pollak, which is incorporated herein by reference. For some applications, microscopic analysis of the first portion of the blood sample is performed on a monolayer of cells. Typically, the first portion of the blood sample is imaged under bright-field imaging, i.e., under illumination from one or more light sources (for example, one or more light-emitting diodes, which typically emit light in the appropriate spectral ranges). Additionally, typically the first portion of the blood sample is further visualized by fluorescence imaging. Typically, fluorescence imaging is performed by exciting colored objects (i.e., objects that have absorbed dye(s)) within a sample by directing light toward the sample at known excitation wavelengths (i.e., wavelengths at which the colored objects are known to be objects emit fluorescent light if excited by light at these wavelengths), and detection of fluorescent light. Typically, for fluorescence imaging, a separate set of light sources (eg, one or more light-emitting diodes) is used to illuminate the sample at known excitation wavelengths.

It should be noted that in the context of this Application, the term "monolayer" is used to refer to a layer of cells that have settled, for example, to be located within the single focus field of a microscope. There may be some overlap of cells within a monolayer, for example, within certain areas there are two or more overlapping layers of cells. For example, red blood cells may overlap each other within a monolayer, and/or platelets may overlap or be positioned above red blood cells within a monolayer.

As described with reference to US 2019/0302099, Pollack, which is incorporated herein by reference, for some applications, the chambers belonging to set 52 (which are used for microscopic measurements) have different heights from each other to facilitate the measurement of different measured quantities by microscopic images of the relevant cameras, and/or the use of different cameras used for microscopic analysis of the relevant sample types. For example, if the blood sample and/or the monolayer formed by the sample has a relatively low red blood cell density, then measurements may be made within a sample holder chamber having a higher height (i.e., a sample holder chamber having a higher height relative to another chamber, having a relatively low height) such that there is sufficient cell density, and/or so that there is sufficient cell density within the monolayer formed by the sample to provide statistically reliable data. Such measurements may include, for example, measurements of red blood cell density, measurements of other cellular characteristics (such as numbers of abnormal red blood cells, red blood cells that contain intracellular bodies (eg, pathogens, Howell-Jolly bodies), etc.), and/or concentrations hemoglobin. Conversely, if the blood sample and/or the monolayer formed by the sample has a relatively high density of red blood cells, then such measurements can be made on a sample holder chamber having a relatively low height, for example such that there is sufficient sparseness of the cells, and/or such that there is sufficient sparseness of cells within the monolayer of cells formed by the sample so that the cells can be identified within the microscopic images. For some applications, such methods are performed even without precisely knowing the difference in height between the chambers belonging to set 52.

For some applications, based on the quantity being measured, a chamber is selected within the sample holder on which optical measurements are to be made. For example, a sample holder chamber having a greater height may be used to perform white blood cell counting (eg, to reduce statistical errors that may result from a low count in a smaller area), differentiating white blood cells, and/or detecting rarer forms of white blood cells. Conversely, to determine mean erythrocyte hemoglobin (MCH), mean cell volume (MCV), red cell distribution by volume (RDW), morphological features of red blood cells and/or red blood cell abnormalities, microscopic images can be obtained from a sample chamber having a relatively low height , since in such chambers the cells are relatively sparsely distributed over the area, and/or form a monolayer in which the cells are relatively sparsely distributed. Likewise, for platelet counting, platelet classification, and/or extraction of any other characteristics (such as volume) of platelets, microscopic images can be obtained from a sample chamber having a relatively low height, since within such chambers there are fewer red blood cells that overlap (completely or partially) with platelets in microscopic images, and/or in a monolayer.

According to the above examples, it is preferable to use a sample holder chamber having a lower height for performing optical measurements to measure some measurable quantities inside a sample (such as a blood sample), while it is preferable to use a sample holder chamber having a higher height for performing optical measurements to measure other measurable quantities within such a sample. Thus, for some applications, a first measurable quantity within a sample is measured by making a first optical measurement on (eg, taking microscopic images of) a portion of the sample that is located within a first chamber belonging to the sample holder set 52, and a second measurable quantity of the same sample is measured by making a second optical measurement on (eg, by obtaining microscopic images) a portion of the sample that is located within the second chamber of the sample holder assembly 52. For some applications, the first and second measured values are normalized to each other, for example, through techniques such as those described in US 2019/0145963, Zait, which is incorporated herein by reference.

In general, to perform absorbance measurements on a sample, it is desirable to know the optical path length, volume, and/or thickness of the portion of the sample on which the optical measurements were performed as accurately as possible. Typically, absorbance measurements are performed on a second portion of the sample (which is typically placed in a second set of 54 chambers in undiluted form). For example, the concentration and/or density of a component can be measured by performing optical absorption, transmittance, fluorescence and/or luminescence measurements on a sample.

Referring again to FIG. 2A, for some applications, cameras belonging to array 54 (which are used to measure optical density) typically define at least a first region 56 (which is typically deeper) and a second region 58 (which is typically shallower) wherein the height of the chambers varies between the first and second regions in a predetermined manner, for example as described in WO 17/195205, Pollack, which is incorporated herein by reference. The heights of the first region 56 and the second region 58 of the sample chamber are limited by a lower surface that is limited by the glass sheet and an upper surface that is limited by the molded component. The upper surface in the second region is stepped in relation to the upper surface in the first region. The step between the top surface in the first and second regions provides a given height difference Δh between the regions, such that even if the absolute height of the regions is known to a reasonable degree of accuracy (for example, due to tolerances in the manufacturing process), the height difference Δh is known to a sufficient degree of accuracy for sample parameter determination, through the technologies described herein, and as described in US 2019/0302099, Pollack, which is incorporated herein by reference. For some applications, the height of the chamber varies from the first region 56 to the second region 58, and the height then varies again from the second region to the third region 59, so that along the sample chamber, the first region 56 delimits the maximum height region, the second region 58 delimits the average height region, and the third area 59 limited the area of minimum height. For some applications, additional height variations occur along the length of the chamber, and/or the height varies gradually along the length of the chamber.

As described herein above, a sample is placed in a sample holder and optical measurements are performed on the sample by one or more optical measurement devices 24. Typically, the sample is observed by an optical measurement device through a glass layer, the glass being transparent at least to the wavelengths typically used by the optical measurement device. Typically, the sample holder is inserted into the optical measurement unit 31, which accommodates the optical measurement device while performing optical measurements. Typically, the optical measurement unit accommodates the sample holder such that the molded layer is located above the glass layer, and so that the optical measurement unit is located below the glass layer of the sample holder, and is capable of performing optical measurements on the sample through the glass layer. The sample holder is formed by gluing a glass sheet to the molded component. For example, the glass sheet and the molded component may be bonded to each other during manufacturing or assembly (eg, by thermal bonding, solvent bonding, ultrasonic bonding, laser bonding, thermal bonding, adhesive, mechanical clamping, and/or additional substrates). For some applications, the glass layer and the molded component are bonded to each other during manufacture or assembly via an adhesive layer 46. For some applications, due to manufacturing process tolerances, the absolute heights of the sample chambers are not known. As described above, the step between the top surface in the first and second regions provides a predetermined height difference Δh between the regions, such that even if the absolute height of the regions is known to a reasonable degree of accuracy (for example, due to tolerances in the manufacturing process), the height difference Δh is known to a sufficient degree of accuracy to determine the sample parameter. Alternative or additional variations in height (e.g., step variations in height or gradual variations in height) along the length of the chamber may be used as an alternative to or in addition to the step between the first and second regions, for example, through techniques described herein. and as described in US 2019/0302099, Pollack, which is incorporated herein by reference.

For some applications, a portion of the sample holder 22 is configured to fluoresce at least under certain conditions. For example, the sample holder portion may be configured to fluoresce when exposed to light emitted by the optical measurement device 24 (eg, bright field light or fluorescent light that is emitted by the microscope system). Or, the sample holder portion may be configured to fluoresce when placed within the optical measurement unit 31 in which the optical measurement device 24 is located. As described hereinabove, for some applications, sample holder 22 includes an adhesive layer 46. For some applications, the adhesive layer or portion thereof is configured to fluoresce in the manner described above (e.g., with an adhesive material within the adhesive layer configured to fluoresce, an adhesive layer comprising additional material that is configured to fluoresce, and/or an adhesive layer coated with such material). For some applications, the adhesive layer is a pressure-sensitive adhesive, at least a portion of which is configured to fluoresce. For example, the pressure-sensitive adhesive may be an acrylic-based pressure-sensitive adhesive, at least a portion of which is configured to fluoresce.

In accordance with some applications of the present invention, various techniques are performed (typically by a computer processor) to determine whether various errors have occurred, and possibly identify the source of the error if an error has occurred. Such errors may arise from preparing the entire sample. For example, the sample may have been left in the sample holder for too long before measurements were taken (which could cause the sample to deteriorate and/or prevent dyes that were mixed with one or both portions of the sample from becoming overly absorbed into the formations inside sample). Alternatively, errors may arise as a result of preparing a particular portion of the sample. For example, there could be an error in the preparation of the first portion (which is typically diluted and placed within the first set of 52 chambers to be microscopically analyzed), such as an error in diluting the first portion of the sample, air bubbles entering the first set of 52 chambers, or contamination of this sample portions. Alternatively or additionally, there could have been an error in the preparation of the second portion (which is typically undiluted and placed within the chamber of the chamber set 54 to be analyzed via absorbance measurements), such as contamination of that portion, or air bubbles entering the second set of 54 chambers. .

Alternatively or additionally, errors may result from an error with the sample holder (e.g., the sample holder material (e.g., the substrate) itself is unclean, and/or dirt or spilled blood on the sample holder), and/or an error with the microscope system itself, e.g. , illumination (for example, the light-emitting diode that is used for brightfield imaging and/or the light-emitting diode that is used during fluorescence imaging of the sample), and/or errors associated with the optical path, and/or motor and stage components or controllers, and /or errors received from the environment in which the device is placed (for example, relative humidity, temperature, pressure, bulk concentration or any other environmental factors). Additionally, alternatively or additionally, there may be a problem inherent to the sample (for example, a very low amount or a very high amount of a particular formation, or too much time has passed since the sample was collected), which means that the computer processor is not able to perform certain measurements with a sufficient degree of accuracy , and/or what it means that the computer processor should indicate it to the user.

For some applications, in response to identification of an error, the computer processor outputs a message indicating the error and/or indicating the source of the error. For some applications, the computer processor does not perform certain measurements on the blood sample in response to the identification of an error. For some applications, in response to identifying an error, the computer processor does not perform any measurements on the sample, and/or indicates that the sample is unusable, and/or instructs the user to repeat sample preparation with a new test kit, and/or recollect the blood sample. Alternatively or additionally, certain parameters of the blood sample are determined by the computer processor by calibrating the measurements made on the blood sample to account for error.

For some applications, one or more of the following errors are taken into account, for example, in one or more of the ways described above:

Errors in the microscopy device, such as:

- loss of steps in the motor that moves the microscope stage

- changes in the movement play of the microscope stage (for example, as described in further detail in this document below)

- changes in timing between the microscope camera and the microscope stage (for example, as described in further detail herein below)

- alignment between the microscope camera and the microscope stage (for example, due to relative rotation between these elements)

- problems with the optical system (for example, changes in focusing quality over time, for example caused by samples, or caused by a part of the microscope stage (for example, a scratched part), for example, as described in further detail below in this document)

- changes in leveling in the microscope system

- change in expected focal position along the z-axis (i.e., optical axis)

- loss of connection between elements

- changes in linear camera response

Errors caused by environmental factors, for example:

- the device is outside the permissible temperature, humidity, height level, etc.

- specific components are outside the target values

Common errors caused by factors such as:

- scanning time

- device startup time

- available working memory/storage device

Some examples of technologies for identifying errors and accounting for such errors are described below in this document.

As described herein above, typically, the first portion of the blood sample was analyzed microscopically while it was located within the first set of 52 sample chambers. Typically, prior to microscopic imaging, the first portion of blood (which is housed in the first set of 52 chambers) is allowed to settle so as to form a monolayer of cells, for example, through techniques that are described in US 9,329,129, Pollak, which is incorporated herein by reference.

For some applications, the computer processor is configured to determine whether one or more cell types (eg, red blood cells) have already settled within the sample chamber before the sample holder has been placed in the microscopy unit, obtaining one or more microscopic images of the sample after the sample holder has been placed in the microscopy unit, and one or more images are analyzed.

Typically, if it is determined that all red blood cells have settled before microscopy images are acquired, this indicates that the blood sample was left within the sample chamber for too long before the sample holder was placed in the microscopy unit. It should be noted that although microscopic image analysis has typically been performed on a monolayer of settled cells, it is nevertheless desirable for the sample holder to be placed in the microscopy unit while some red blood cells are still settling, as this indicates that the sample was not left in the sample holder for too long before being placed in the microscopy unit. Conversely, if all the red blood cells (or a sufficiently large portion of red blood cells) have already settled, the sample may have deteriorated and/or the dyes may have been excessively absorbed by formations within the sample. Thus, the extent to which cells are still settling can be used as a measure of how recently the sample was collected from the subject and/or how recently the sample was placed in the sample holder or sample chamber (i.e., sample freshness ). Thus, for some applications, in response to determining that more than a threshold number of red blood cells within the sample chamber have already settled within the sample chamber before one or more microscopic images are acquired, the sample (or portion thereof) is excluded from use to perform at least least group of measurements on the sample.

For some applications, an indication of the age of a blood sample is determined at least in part based on determining whether one or more cell types have already settled within the sample chamber within the sample chamber, prior to obtaining one or more microscopic images. For some applications, an indication of the age of a blood sample is determined at least in part based on the number (or proportion) of one or more cell types within the sample chamber that have not yet settled within the sample chamber, prior to obtaining one or more microscopic images.

For some applications, an analysis substantially similar to that described in the paragraphs above (to determine how recently the sample was collected from the subject and/or how recently the sample was placed in the sample holder or sample chamber) is performed on the second portion of the sample. (which is typically housed in the second set of 54 chambers in undiluted form).

It should be noted that, typically, after the computer processor has determined an indication of how recently a sample was collected from a subject and/or how recently the sample was placed in a sample holder or sample chamber (e.g., through the assay technology described above), the holder The sample is left in place within the microscopy unit for several minutes (eg, 2 to 10 minutes, eg, approximately 5 minutes) before additional imaging of the first portion of the blood sample is performed (wherein additional imaging is performed for the purpose of microscopic analysis of the blood sample). This is done to give time for the first portion of the blood sample to settle into a monolayer.

For some applications, measurements that are made on a sample are calibrated in response to determining that more than a threshold number of red blood cells within the sample chamber have already settled within the sample chamber, prior to acquiring one or more microscopic images. For example, such measurements may be calibrated to account for the amount of staining that has occurred within the blood sample, as indicated by more than a threshold number of red blood cells within the sample chamber already deposited within the sample chamber, prior to the acquisition of one or more microscopic images. For some applications, measurements made on a sample are calibrated based on the number (or proportion) of one or more cell types within the sample chamber that have not yet settled within the sample chamber, before one or more microscopic images are taken.

For some applications, microscopic images of red blood cells within a blood sample are obtained while the red blood cells within the blood sample are sedimented within a sample chamber, and the sedimentation dynamics property of the blood sample (eg, erythrocyte sedimentation rate) is determined by a computer processor by image analysis. Typically, the sedimentation dynamics property of a blood sample (eg, erythrocyte sedimentation rate) is determined by a computer processor in real time with respect to erythrocyte sedimentation (ie, while the erythrocytes are still settling). This differs from other technologies for determining the sedimentation dynamics property of a blood sample (eg, erythrocyte sedimentation rate), which measure the total time it takes for erythrocytes to settle. It should be noted that if such measurements are performed on a diluted portion of a blood sample, the effect of proteins on erythrocyte sedimentation time is weakened. Thus, for some applications, such measurements are performed on an undiluted portion of the blood sample.

For some applications, the above-described assays for determining an indication of how recently a sample was collected from a subject and/or how recently a sample was placed in a sample holder, and/or to determine sedimentation dynamics properties are adjusted by information on each sample, such as a red blood cell or platelet, mean cell volume, mean cell hemoglobin concentration, or other such indicators indicative of the sample. Alternatively or additionally, assays to determine an indication of how recently a sample was collected from a subject and/or how recently a sample was placed in a sample holder, and/or to determine properties of sedimentation dynamics were adjusted for single-cell level information (i.e. , extracting data associated with individual cells and adjusting certain properties of sedimentation dynamics based on that data).

For some applications, in response to determining that the concentration of a given entity within a blood sample exceeds a threshold value, the computer processor determines the cause of the concentration of the entity exceeding the threshold value by comparing a parameter determined from microscopic images of the first portion of the blood sample with a parameter determined from the measurement optical density performed on the second portion of the blood sample. For example, in response to detecting that the first sample portion (which is typically diluted and placed within a chamber of the first set of chambers 52) has a very high red blood cell count or a very low red blood cell count, the computer processor may make a comparison to determine whether this is the case that the blood sample initially had a very high red blood cell count, or a very low red blood cell count, or was caused by an error in sample preparation (for example, dilution of the first portion). The computer processor typically determines that the blood sample itself is causing the concentration of a given species within the sample to exceed a threshold value by determining that the concentration of the species, as indicated by microscopic images, is similar to the concentration of the species, as determined from optical density measurements. Additionally, typically, the computer processor determines that the preparation of a portion of the blood sample causes the concentration of a given species within the sample to exceed a threshold value by determining that the concentration of the species, as indicated by the microscopic images, is different from the concentration of the species, as determined from optical density measurements.

For some applications, an analysis similar to that described in the paragraphs above is performed using sample parameters other than concentration (eg, mean cell volume, mean cell hemoglobin, etc.). For some applications, in response to identifying that there is a difference between the parameters measured on the respective sample portions, it is determined that the respective sample portions are likely to be portions of two different samples (eg, from two different patients).

For some applications, parameters that are determined from corresponding sample portions are used to correct each other. For example, if the parameter values that are measured in each sample portion are different from each other, but it is determined that there is a third parameter value (or range of values) that lies within the error range for both values that are measured in each sample portion, then it can be determined that a third value (or range of values) is likely to be correct.

For some applications, in response to one or more sample parameters being outside the normal range, the computer processor compares those parameters to other sample parameters. In response to all parameters being outside the normal range (or even erroneous in a way that correlates with an error in one or more parameters), the computer processor may determine that this is due to a calculation error that affects all of them. options.

For some applications, the computer processor is configured to identify echinocytes, spherocytes, and/or serrated red blood cells within the microscopic images of the first portion of the sample. Typically, the presence of such a formation is an indication that the sample portion has deteriorated due to the age and/or storage conditions of the sample. For some such applications, a computer processor measures the amount of such growths and excludes at least a portion of the blood sample from use to perform at least a group of measurements on the blood sample based at least in part on the number of the selected type of growths exceeding a threshold value. For some applications, the computer processor generates an indication of quantity and/or associated clinical condition for the user. Alternatively or additionally, the computer processor determines the age indication of the sample portion based at least in part on the quantity. For some applications, to determine a sample parameter, a measurement is performed on microscopic images, and the measurement is calibrated based on a specific indication of the age of the sample portion and/or based on the number of the aforementioned formations. For some applications, the sample parameter is determined by performing an absorbance measurement on a second portion of the blood sample (which is typically located within a chamber of the second set of sample chambers 54), and calibrating the absorbance measurements based on a specific indication of the age of the sample portion, and/or based on the number of the above-mentioned formations. (For some applications, absorbance measurements are calibrated based on one or more other factors, such as red blood cell morphology, red blood cell volume, platelet count, level of foreign matter within the sample, and/or the presence or quantity of any objects or characteristics that may affect scattering) .

For some applications, the computer processor estimates the volumes of echinocytes, spherocytes and/or serrated red blood cells. For some such applications, the volumes of such cells are included in the overall measure of the average volume of red blood cells within the sample.

Reference is now made to FIG. 3A and 3B, which are bright-field microscopic images taken under violet and green LED illumination, respectively, in accordance with certain applications of the present invention. As described above herein, microscopic images of a first portion of a blood sample are typically obtained and the monolayer of cells within the first portion is analyzed. Typically, spherification technologies are not applied to the red blood cells in a sample before imaging a portion of the sample. The inventors of the present application have discovered that when a sample portion is microscopically imaged using the techniques described herein, some hemolyzed red blood cells are visible in the microscopic images. Typically, after a sample is stained with Hoechst reagent (or any fluorescent or non-fluorescent dye that has an affinity for the cell membrane) in brightfield imaging, the outline of the cell is visible and the rest of the cell appears as the background of the image. This effect can be observed in Fig. 3A and 3B, which show red blood cells 60 and outlines of hemolyzed red blood cells 62, and the interior of the cells appears similar to the background so that the outlines appear as “empty” cells. "Empty" cells tend to have essentially similar shapes and sizes to red blood cells.

Reference is also made to FIG. 3C, which is fluoroscopic microscopic images obtained in accordance with certain applications of the present invention. The image was recorded after the blood sample was stained with Hoechst reagent and excited by UV illumination centered at approximately 360 nm. It can be noted that unlike red blood cells 60, which appear as dark circles, hemolyzed red blood cells 62 appear as light circles, having generally similar shapes and sizes to red blood cells. It is believed that hemolyzed erythrocytes become stained with Hoechst reagent associated with residues that remain on the membrane of hemolyzed erythrocytes. This causes hemolyzed red blood cells to appear as "empty" cells in brightfield images, and/or appear as bright circles in fluorescence images. It is further suggested that the reason why red blood cells appear as darkened circles in the fluorescence image is that there is background radiation from the free Hoechst reagent throughout the sample, but this radiation is attenuated by the hemoglobin in the red blood cells so that they appear darker than the background.

Thus, in accordance with some applications of the present invention, hemolyzed red blood cells are identified within an unspherified blood sample. Typically, the sample is stained with a dye such as Hoechst reagent (or any fluorescent or non-fluorescent dye that has an affinity for the cell membrane). Hemolyzed red blood cells are identified within bright-field images of a stained sample by identifying cells whose outlines are visible and whose interiors appear substantially similar to the background (so that the outlines appear as “blank” cells). Alternatively or additionally, hemolyzed red blood cells are identified within the fluorescent images of the stained sample. Typically, hemolyzed RBCs have essentially similar shapes and sizes to the RBCs within the images.

For some applications, the hemolyzed RBCs that are visible form only a fraction of the total hemolyzed RBCs that are present within the sample portion, since this is typically the case when the hemolyzed RBC portion is not visible. For some applications, a computer processor identifies visible hemolyzed red blood cells and measures the number of identified hemolyzed red blood cells within a portion of the sample. Typically, based on the number of identified hemolyzed red blood cells, the computer processor estimates the total number of hemolyzed red blood cells within the sample portion to be greater than the number of identified hemolyzed red blood cells. Alternatively or additionally, based on the number of hemolyzed red blood cells identified, the computer processor estimates the ratio of hemolyzed red blood cells to non-hemolyzed red blood cells within the sample. Typically, this ratio is calculated by estimating the total number of hemolyzed red blood cells within a portion of the sample, which is greater than the number of identified hemolyzed red blood cells. For some applications, the computer processor provides the user with an indication of the estimated total number of hemolyzed red blood cells within the blood sample, or the ratio of hemolyzed red blood cells to non-hemolyzed red blood cells. Alternatively or additionally, the computer processor excludes the sample from use for performing at least a group of measurements on the sample based at least in part on the number of identified hemolyzed red blood cells exceeding a threshold value or based on the above-mentioned ratio exceeding a threshold value. For some applications, sample exclusion is based on an estimate of the total number of hemolyzed RBCs within a sample portion that is greater than the number of hemolyzed RBCs identified.

For some applications to identify a given entity within a blood sample (such as platelets, red blood cells, white blood cells, etc.), the computer processor first identifies candidates for a given entity within a blood sample by analyzing microscopic images of a first portion of the blood sample. The computer processor then confirms that at least some of the candidates are these entities by performing additional analysis of the candidates.

For some applications, a computer processor compares the number of candidates of a given formation to count confirmed candidates of a given formation and removes at least a portion of the sample from use to perform at least a group of measurements on the sample based at least in part on the relationship between the number of candidates and the number of confirmed candidates. For example, if the ratio of the number of confirmed candidates to the number of candidates exceeds a maximum threshold, then the computer processor may exclude at least a portion of the sample from use to perform at least a group of measurements on the sample as an indication of too many candidates that have been confirmed. indicating an error. Alternatively or additionally, if the ratio of the number of confirmed candidates to the number of candidates is below a minimum threshold, the computer processor may exclude at least a portion of the sample from being used to perform at least a group of measurements on the sample as an indication that the number of candidates is too small. which were confirmed, indicating an error. For some applications, if the ratio of the number of confirmed platelets to the number of platelet candidates is below a minimum threshold value, the computer processor excludes at least a portion of the sample from use for performing a platelet count, as this is an indication that too few platelet candidates have been confirmed as platelets, indicating an error. For example, this error may be caused by foreign substances (or other contaminants) misidentified as platelets or as platelet candidates. It should be noted that the source of error may be in the preparation of the sample portion, in the sample holder, in areas of the microscopy unit and/or in the blood itself. For some applications, similar techniques are performed on red blood cells, white blood cells, and/or other entities within the sample (eg, abnormal white blood cells, embolic tumor cells, red blood cells, reticulocytes, Howell-Jolly bodies, etc.).

For some applications, the computer processor is configured to identify white blood cell candidates within a blood sample, and is also configured to confirm at least a group of white blood cell candidates as being given types of white blood cells (e.g., neutrophils, lymphocytes, eosinophils, monocytes, blasts, undifferentiated cells, atypical lymphocytes and/or basophils), by performing additional analysis of candidate leukocytes. For some applications, a computer processor compares the number of leukocyte candidates with the number of leukocyte candidates confirmed to be the given types of leukocytes, and removes at least a portion of the sample from use to perform at least a group of measurements on the sample, at least in part, based on the ratio between the number of leukocyte candidates and the number of leukocyte candidates confirmed to be the given leukocyte types. For example, if the ratio of the number of white blood cell candidates confirmed to be given types of white blood cells to the number of white blood cell candidates exceeds a maximum threshold value, then the computer processor may exclude at least a portion of the sample from use for performing at least a group of measurements on the sample because this is an indication that too few candidates have been confirmed, indicating an error. Alternatively or additionally, if the ratio of the number of leukocyte candidates confirmed to be the given leukocyte types to the number of leukocyte candidates is below a minimum threshold, then the computer processor may exclude at least a portion of the sample from use for performing at least a group of measurements on the sample , as this is an indication that too few candidates have been confirmed, indicating an error. It should be noted that the source of error may be in the preparation of the sample portion, in the sample holder, in areas of the microscopy unit and/or in the blood itself.

For some applications, the computer processor is configured to identify foreign substances (or other contaminants) within a sample, identifying colored objects that have irregular shapes (eg, fibrous shapes, non-round shapes, and/or elongated shapes). As described herein above, typically a computer processor performs a count of one or more entities located within a sample by performing a microscopic analysis on the sample. For some applications, the computer processor excludes areas of the sample located within given distances from identified foreign substances (or other contaminants). Typically, foreign substances are stained with dyes, and additionally, usually foreign substances are stained with both acridine orange and Hoechst reagent. For some applications, the computer processor identifies foreign substances (or other contaminants) by identifying objects that are irregularly shaped and/or that are colored with a dye (eg, both acridine orange and Hoechst reagent).

Reference is now made to FIG. 4, which is a graph showing normalized log light transmittance intensity profiles measured along the length of a sample chamber belonging to a second set of sample chambers 54, in accordance with certain applications of the present invention. As described hereinabove, typically the computer processor is configured to perform optical measurements (eg, optical density measurements) on a second sample portion that is located in a second set of sample chambers 54. For some applications, light (such as light from an LED) is passed through a chamber in the spectral range in which hemoglobin absorbs light, and the intensity of the transmitted light is detected by a photodetector. The amount of light that is absorbed is interpreted as an indicator of the hemoglobin concentration within the second portion of the sample, in accordance with the Beer-Lambert law.

For some applications, the computer processor determines that one or more air bubbles are present within one second set of sample chambers based on optical measurements. For example, due to regions having different heights within a sample chamber, the normalized profile of the logarithm of light transmittance intensity (which is related to the hemoglobin absorption profile) along the length of the chamber is expected to have a given shape, for example, regions along which the logarithm of light transmittance intensity is essentially constant with differences between areas (due to steps in chamber height). This is indicated by the solid curve 70 in FIG. 4, which is a collection of the normalized logarithm of the transmittance intensity recorded along the length of the sample chamber for several different samples. As shown, along the sample chamber minimum height region 56, the logarithm of the transmittance intensity is substantially constant. (In fact, there is a slight slope along the length of this region, which is due to the variation in height along the length of the region due to tolerances in the fabrication of the sample holder, as described above herein.) There is then a drop in the logarithm of the transmittance intensity as the distance along the sample chamber increases. transitions to a mid-height region 58 (in which hemoglobin absorption is greater and light transmission is thus lower), before further drop occurs as the distance along the sample chamber progresses to a maximum height region 59 (in which absorption there is even more hemoglobin, and thus light transmission is even lower). It should be noted that the method by which transmittance was normalized was to take the average of the logarithm of light transmission intensity within a given region of maximum height and assign it a value of 1, taking the average of the logarithm of light transmission intensity within a given region of minimum height and assigning it a second values and then normalizing other values with respect to those two values. (In some cases, the value of the logarithm of the light transmission intensity within a given region of the minimum height region is assigned the value of the Euler number (i.e., 2.718), although in the example shown in Fig. 4 this is not the case.) One would expect that the normalized profile of any sample that fills the sample chamber will have a similar profile regardless of the absolute hemoglobin absorption of the sample, since the shape of the profile depends on the relative absorption along different regions of the sample chamber.

Thin curve 72 in FIG. 4 shows the normalized logarithm of the transmittance intensity recorded along the length of the sample chamber for a given sample. It can be observed that within the region of minimum height there is a relatively flat portion of the curve (which is below curve 70) and then a peak (which is above curve 70). Additionally, along the mid-height region, curve 72 is below curve 70. Typically, such a profile is indicative of the fact that there is a bubble (eg, an air bubble, and/or the presence of another substance) within the minimum height region. At the bubble position, light transmission is greater, resulting in a peak in curve 72 at this position. At other positions (eg, within other portions of the minimum height region) and along the entire average height region, the presence of a bubble within the minimum height region results in a decrease in the normalized logarithm of transmittance values relative to the values of a sample that does not contain a bubble. Likewise, when there are bubbles within other regions of the sample chamber (or along the entire region), this will result in different normalized log transmittance profiles. For example, if the bubble were along the entire minimum height region, this would result in a decrease in the normalized log transmittance within the mid height region relative to the normalized log transmittance of a sample that does not contain the bubble. For some applications, the chamber height varies in different ways, but in general the same techniques are followed with appropriate modifications.

Thus, in accordance with some applications of the present invention, in addition to measured absolute values of a parameter that represents the transmittance of light along the length of the sample chamber, normalized values of a parameter that represents the transmittance of light (e.g., the normalized logarithm of the transmittance intensity) are determined along the sample chamber. Based on the normalized parameter values, the computer processor determines that a bubble (eg, an air bubble or the presence of another substance) is likely within the sample chamber. For some applications, in response to determining that there is likely to be a bubble within the sample chamber, the computer processor generates an output signal. For example, the computer processor may generate an error message (eg, a message indicating that the sample chamber must be refilled), may exclude the sample, and/or may exclude a measurement site being performed on the sample.

For some applications, a computer processor makes optical absorption measurements, but only uses areas of the chamber where no bubble is present. Thus, for some applications, based on the absolute value of a parameter, which is a measure of the light transmittance of at least some areas within the sample chamber, the computer processor calculates the hemoglobin concentration within the sample. In addition, the computer processor normalizes the parameter measured in the corresponding areas within the sample chamber with respect to each other. At least in part in response to the normalized parameter, the computer processor determines which region to use to calculate the hemoglobin concentration within the sample. Alternatively, the computer processor may exclude the sample from use for calculating the hemoglobin concentration within the sample, and/or may generate an error message (eg, a message indicating that the sample chamber must be refilled).

Along the width of the chamber, the sample is expected to have an absorption profile that is substantially constant. For some applications, the computer processor is configured to interpret an unexpectedly low level of absorption (which does not correspond to the profiles described above) as indicative of the presence of an air bubble. For some applications, to determine whether air bubbles are present, one or more optical absorption measurements are performed at a wavelength at which hemoglobin does not absorb light (eg, through green light). Alternatively or additionally, a camera (eg, a CCD camera or a CMOS microscope camera) is used to image a second portion of the blood sample, and a computer processor determines whether air bubbles are present based on the image(s).

Typically, one or more sample parameters are determined by a computer processor based on optical measurements. For some applications, at least some optical measurements are eliminated from use in determining one or more sample parameters based on a determination that one or more air bubbles are present within the chamber. For some applications, the computer processor generates an output signal indicating that a portion of the blood sample has been excluded from use for performing at least a group of measurements on the sample based on determining that one or more air bubbles are present within the sample chamber.

For some applications, substantially similar techniques are performed on a first portion of a blood sample that is housed in a first set of sample chambers 52. For example, a computer processor may be configured to identify a region in which a sample is not present within a microscopic image of a sample chamber, and exclude at least the identified region from use in microscopic analysis of a portion of the sample. For some applications, the computer processor is configured to identify such an area by identifying the interface between a wet area and a dry area on the base surface of the sample chamber. Typically, when identifying such an area, the computer processor is configured to discriminate between areas in which the sample is not present and areas in which the sample is present and the sample has a low cell density.

For some applications, the computer processor is configured to identify the presence of dirt (eg, spilled blood) on the outer surface of the sample holder. As described herein above, typically at least one microscopic image is obtained of a monolayer of cells that have settled on the base surface of the sample holder. Typically, the image is acquired while the microscope is focused on the focal plane of the monolayer, with the monolayer of cells located within the focal plane of the monolayer. For some applications, the computer processor identifies that the dirt is located on the top cover of the sample holder or on the back of the base surface by identifying the area in which the formation is visible on a focal plane that is different from the focal plane of the monolayer. Alternatively or additionally, the computer processor identifies a region in which the background intensity of the microscopic image (which was acquired at the focal plane of the monolayer) is indicative of dirt that is located on the top coating or on the back of the base surface. For some applications, in response, the computer processor excludes at least the identified region from use in microscopic analysis of a portion of the sample.

As described herein above, typically the first portion of a blood sample is imaged under bright-field imaging, i.e., under illumination from one or more bright-field light sources (for example, one or more light-emitting diodes, which typically emit light in appropriate spectral ranges). Additionally, typically the first portion of the blood sample is further visualized by fluorescence imaging. Typically, fluorescence imaging is performed by exciting colored objects within a sample by directing light toward the sample at known excitation wavelengths (i.e., wavelengths at which colored objects are known to emit fluorescent light if excited by light at those wavelengths), and detection of fluorescent light. Typically, for fluorescence imaging, a separate set of one or more fluorescent light-emitting diodes is used to illuminate the sample at known excitation wavelengths.

For some applications, a computer processor analyzes the light that is emitted by the brightfield light source and determines a property of the brightfield light source. For example, the computer processor may periodically determine whether the spatial distribution of illumination by the bright-field light source has changed from a previous measurement (e.g., whether the spatial uniformity of the illumination has changed, or whether the spatial position has changed from a previous measurement), whether the vignetting effects of the illumination by the bright-field light source have changed from a previous measurement, whether the spectral distribution of illumination by the bright-field light source has changed since the previous measurement, and/or whether the intensity of illumination by the bright-field light source has changed since the previous measurement. As described herein above, typically, a computer processor determines a blood sample parameter by performing measurements on lesions that are identified within microscopic images of the blood sample. For some applications, such measurements are normalized based on a specific property of the brightfield light source. For some applications, at least some measurements are excluded from being performed on a blood sample based on a particular property of the bright field light source.

For some applications, to determine the properties of the brightfield light source, a computer processor analyzes the light that is emitted by the brightfield light source in the absence of a sample holder. Alternatively or additionally, a computer processor analyzes light that is emitted by a bright field light source that passes through the intercellular regions within the blood sample.

For some applications, a computer processor analyzes the light that is emitted by a fluorescent light source and determines a property of the fluorescent light source. For example, the computer processor may periodically determine whether the spatial distribution of the illumination of the fluorescent light source has changed from a previous measurement (e.g., whether the spatial uniformity of the illumination has changed, or whether the spatial position has changed from a previous measurement), whether the vignetting effects of the illumination of the fluorescent light source have changed from the previous measurement, whether the spectral distribution of illumination by the fluorescent light source has changed since the previous measurement, and/or whether the intensity of illumination by the fluorescent light source has changed since the previous measurement. As described herein above, typically, a computer processor determines a blood sample parameter by performing measurements on lesions that are identified within microscopic images of the blood sample. For some applications, such measurements are normalized based on a specific property of the fluorescent light source. For some applications, at least some measurements are excluded from being performed on a blood sample based on a particular property of the fluorescent light source.

For some applications, to determine a property of a fluorescent light source, a computer processor identifies one or more fluorescent regions that are visible within a microscopic image produced by illumination with a fluorescent light source other than stained cells, and determines a property of the fluorescent light source based on the identified fluorescent regions. regions. For example, such fluorescent regions may comprise intercellular regions within the blood sample, one or more fluorescent regions of a microscopy unit, and/or one or more fluorescent regions of a sample holder (eg, the pressure-sensitive sample holder adhesive described herein above). For some applications, the sample holder is placed on a stage within the microscopy unit, and the stage contains fluorescent areas to perform the measurements described above. Alternatively or additionally, the sample holder includes a fluorescent region (eg, a fluorescent spot) for performing the above-described measurements.

For some applications, the computer processor is configured to detect whether areas of the microscopy unit (such as the CCD camera, CMOS camera, lenses, and/or sample holder holding stage) have dirt or scratches on them, obtaining microscopic images in the absence of any sample holder , and identification of dirt or scratches in such images. For some applications, such images are acquired periodically (eg, at fixed time intervals) to determine whether the microscopy unit, or areas of the microscopy unit, have dirt or scratches on them. For some applications, in response to the detection of such dirt and/or scratches, this is indicated to the user. Alternatively or additionally, areas within the images that correspond to positions in which dirt and/or scratches are present are not contained in at least some image analyzes of the samples. Additionally, alternatively or additionally, measurements taken in areas within the images that correspond to positions in which dirt and/or scratches are present are calibrated to account for dirt and/or scratches.

For some applications, the computer processor is configured to detect whether there is dirt or scratches on portions of the sample holder, through techniques generally similar to the above-mentioned techniques. For example, a sample holder can be visualized without a sample in it. For some applications, the computer processor is configured to detect whether portions of the sample holder fluoresce non-uniformly, for example, by imaging the sample holder without a sample present therein.

For some applications, in response to detecting that there is an error in at least some of the fluorescence microscopy images, the computer processor classifies the source of the error as follows. In response to detecting that an error has been introduced at this point in time, the computer processor identifies the dye as being the source of the error, as this indicates that the error has been introduced as a result of using a new batch of dye. In response to detecting that the error is gradually increasing over time, the computer processor identifies dirt within the microscopy unit as being the source of the error, since such dirt typically causes gradual deterioration over time. In response to detecting that the error is present only in images illuminated by one of the light sources (eg, light emitting diodes), the computer processor identifies that one of the light sources as being the source of the error.

For some applications, the optical measurement unit contains a microscope, which contains a microscope stage on which a sample holder is typically placed. Typically, a computer processor drives the microscope stage to move through one or more motors that are used to drive the movement of mechanical elements. In some cases, there is a degree of play associated with the movement of mechanical elements. For example, when the direction of movement is initiated or reversed, there may be a delay between the issuance of computer-implemented commands to the motors and the implementation of movement of the mechanical elements. For some applications, the computer processor takes this effect into account when performing any movement (eg, by assuming that there is a given fixed delay, or by periodically measuring the delay and taking the delay as the most recently measured). For some applications, the amount of play is quantified by a microscopic system, and the amount of play is interpreted as being indicative of the condition of the mechanical components and/or motor(s). For example, the amount of backlash can be quantified by observing how many motor steps are required to produce appreciable movement in the microscope system and/or repeating the same measurements in two different directions of movement, and the correlation between the images or metrics is extracted from the images associated with movement in two different directions. For some applications, based on the measurements described above, the condition of mechanical components and/or motor(s) is determined. For some applications, an output signal is generated in response to a certain state of mechanical elements and/or motor(s). For example, at least some images of the sample (and/or data associated with the sample) may be rejected from analysis, the microscope and/or other areas of the optical measurement unit may be blocked so that they cannot be used, and/or there may be an alert has been generated (for example, an alert may be generated indicating that maintenance is required and/or an alert indicating that preventative maintenance is recommended).

For some applications, microscopic images (and/or other signals) are acquired while the stage is moving. For some such applications, there may be temporary timing discrepancies between the reported or interpolated stage position at a given time and the actual timing of the received camera or sensor position at that location. This may lead to an error in the intended position where a given image (or data) was acquired, and may subsequently lead to additional error if that position is used for other purposes (for example, if this image (or this data) and the corresponding position are used as input signal for focusing the microscope). For some applications, such timing mismatch is measured using two measurements of the same target, for example, as follows. A first target image (or a set of data associated with the target) is acquired through static acquisition along a mechanical axis, and a second target image (or a set of data associated with the target) is acquired through acquisition while moving the stage. Detects differences between images or metrics extracted from images (and/or differences between two sets of data), if such differences are detected, then the computer processor uses them as an input signal to determine that there is a timing mismatch and/or to correct the mismatch synchronization For some applications, such measurements are made periodically and used as an input signal to determine the status of portions of the optical measurement system (such as portions of the microscope system containing the imaging portion, mechanical components, and/or motors). For some applications, an output signal is generated in response to detecting that there is a timing mismatch and/or a difference relative to a previous measurement. For example, at least some images of the sample (and/or data associated with the sample) may be rejected from analysis, the microscope and/or other areas of the optical measurement unit may be blocked so that they cannot be used, and/or there may be an alert has been generated (for example, an alert may be generated indicating that maintenance is required and/or an alert indicating that preventative maintenance is recommended).

For some applications, the condition of the optical measurement unit (eg, the microscope of the optical measurement system, and/or the optical absorption measurement section of the optical measurement unit) is assessed by imaging a target that is installed in the optical measurement unit itself (or is typically inserted into the optical measurement unit). For example, a scratched glass surface, a printed glass surface, one or more fluorescent or non-fluorescent beads, pinholes, or any other resolving target may be used. For some applications, by acquiring and analyzing images of such a target (and/or data related thereto), the computer processor outputs optical characteristics of the optical measurement unit, such as aberration, resolution, contrast, scattering, and attenuation. For some applications, the computer processor performs this analysis periodically and compares certain characteristics with specified values. For some applications, an output signal is generated in response to detecting that there is a difference between one or more specified characteristics and specified values. For example, at least some images of the sample (and/or data associated with the sample) may be rejected from analysis, the microscope and/or other areas of the optical measurement unit may be blocked so that they cannot be used, and/or there may be an alert has been generated (for example, an alert may be generated indicating that maintenance is required and/or an alert indicating that preventive maintenance is recommended). For some applications, based on certain characteristics, the computer processor adjusts the features of the extracted image, the measured values (in the case of a non-imaging measurement), and/or the measured values of the sample. For example, absorption measurements can be corrected by changing the apparent contrast in the target.

For some applications, the sample that is described herein is a sample that contains blood or its components (for example, a sample of diluted or undiluted whole blood, a sample containing predominantly red blood cells, or a diluted sample containing predominantly red blood cells), and the parameters are determined relative to components in the blood, such as platelets, white blood cells, abnormal white blood cells, embolic tumor cells, red blood cells, reticulocytes, Howell-Jolly bodies, etc.

In general, it should be noted that although some applications of the present invention have been described in relation to a blood sample, the scope of the present invention includes the application of the apparatus and methods described herein to various samples. For some applications, the sample is a biological sample, such as blood, saliva, semen, sweat, sputum, vaginal fluid, feces, breast milk, bronchoalveolar lavage, gastric lavage, tears and/or nasal discharge. The biological sample can be from any living creature, and usually from warm-blooded animals. For some applications, the biological sample is a sample from a mammal, such as a human body. For some applications, a sample is taken from any domestic animal, zoo animals, and farm animals, including, but not limited to, dogs, cats, horses, cows, and sheep. Alternatively or additionally, a biological sample is taken from animals that act as disease vectors containing deer or rats.

For some applications, technologies similar to those described herein above are applied to a non-body sample. For some applications, the sample is an environmental sample, such as a water sample (eg, groundwater), a surface swab, a soil sample, an air sample, or any combination thereof. In some embodiments, the sample is a food sample, such as a meat sample, a dairy sample, a water sample, a wash fluid sample, a beverage sample, and/or any combination thereof.

The applications of the invention described herein may take the form of a computer program product accessible from a computer-used or computer-readable medium (e.g., a non-transitory storage medium) providing program code for use by or in connection with a computer, or any command execution system , such as a computer processor 28. For purposes of this description, a computer or computer readable medium may be any device that can contain, store, transmit, distribute, or carry a program for use by or in connection with an instruction execution system, device, or apparatus. The medium may be an electronic, magnetic, optical, electromagnetic, infrared or semiconductor system (or device or apparatus) or distribution medium. Generally, a computer usable or machine readable medium is a non-transitory computer usable or machine readable medium.

Examples of computer readable media include semiconductor or solid state memory, magnetic tape, removable computer floppy disk, random access memory (RAM), read only memory (ROM), hard magnetic disk, and optical disk. Modern examples of optical discs include compact optical disc (CD-ROM), compact disc rewritable (CD-R/W), and DVD.

A data processing system suitable for storing and/or executing program code will include at least one processor (eg, computer processor 28) coupled directly or indirectly to memory elements (eg, memory 30) via a system bus. The memory elements may include local memory that operates while the program code is actually executing, a mass storage device, and high-speed buffer memories that provide temporary storage of at least some program code to reduce the number of times code must be retrieved from the mass storage device during lead time. The system can read instructions of the invention on program storage devices, and follow these instructions to carry out the methodology of embodiments of the invention.

Network adapters may be connected to the processor to allow the processor to communicate with other processors or remote printers or storage devices over intermediate private or public networks. Modems, cable modems, and Ethernet cards are just a few of the types of network adapters currently available.

The computer program code for performing the operations of the present invention may be written in any combination of one or more programming languages comprising an object-oriented programming language such as Java, Smalltalk, C++, or the like, and traditional procedural programming languages such as the C or C programming language. similar programming languages.

It will be appreciated that the algorithms described herein may be implemented by computer program instructions. These computer program instructions may be provided to a general purpose computer processor, a special purpose computer, or other programmable data processing device to obtain the machine, such that the instructions that are executed through the computer processor (e.g., computer processor 28) or other programmable data processing device create the means to implement the functions/actions specified in the algorithms described in this Application. These computer program instructions may also be stored in a computer-readable medium (e.g., a computer-readable medium for non-transitory information storage), which can direct a computer or other programmable data processing device to operate in a particular manner such that the instructions stored on the computer-readable medium produce an article of manufacture. , containing a command tool that implements the function/action specified in the flowchart blocks and algorithms. Computer program instructions may also be loaded into a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce computer-implemented processes such that instructions that are executed on the computer or other programmable device , provide a process for implementing the functions/actions specified in the algorithms described in this Application.

The computer processor 28 is typically a hardware device that is programmed by a computer program command to provide a special purpose computer. For example, when programmed to perform the algorithms described herein, computer processor 28 typically acts as a special purpose computer processor for sample analysis. In general, the operations described herein, which are performed by the computer processor 28, convert the physical state of the memory 30, which is an actual physical article, to have a different magnetic polarity, electrical charge, or the like, depending on the memory technology that is used.

The apparatus and methods described herein may be used in connection with the apparatus and methods described in any of the following Patent Applications, all of which are incorporated herein by reference:

US 2012/0169863 to Bachelet;

US 2014/0347459 to Greenfield;

US 2015/0037806 to Pollak;

US 2015/0316477 to Pollak;

US 2016/0208306 to Pollak;

US 2016/0246046 to Yorav Raphael;

US 2016/0279633 to Bachelet;

US 2018/0246313 to Eshel;

WO 16/030897 to Yorav Raphael;

WO 17/046799 to Eshel;

WO 17/168411 to Eshel;

WO 17/195205 to Pollack;

US 2019/0145963 to Zait; and

WO 19/097387 to Yorav-Raphael.

One skilled in the art will appreciate that the present invention is not limited to what has been specifically shown and described herein above. Rather, it is the scope of the present invention to include both sets and subsets of the various features described hereinabove, as well as variations and modifications thereof not found in the prior art that may occur upon reading the foregoing description by one skilled in the art.

Claims (34)

1. A method for accounting for errors in optical measurements, including stages in which: placing a blood sample within the sample chamber; obtaining at least one microscopic image of a blood sample; identifying within the microscopic image candidates for a given formation within a blood sample, wherein the given formation is selected from the group consisting of: platelets, leukocytes, erythrocytes, circulating tumor cells, reticulocytes and Howell-Jolly bodies; confirming at least that the candidate group is a given entity by performing additional analysis of the candidates; determine the ratio between the number of candidates of a given education with the number of confirmed candidates of a given education; And eliminating the sample from use for performing at least a group of measurements on the sample based on the relationship between the number of candidates and the number of confirmed candidates. 2. The method of claim 1, wherein excluding a sample from use to perform at least a group of measurements on the sample includes excluding the sample from use to perform at least a group of measurements on the sample based on the quantity ratio between confirmed candidates and quantity candidates exceeding the maximum threshold. 3. Method according to any one of paragraphs. 1, 2, wherein excluding a sample from use to perform at least a group of measurements on the sample includes excluding the sample from use to perform at least a group of measurements on the sample based on the ratio of the number of confirmed candidates and the number of candidates that is less than the minimum threshold value. 4. A method for accounting for errors in optical measurements, including stages in which: placing a blood sample within the sample chamber; obtaining at least one microscopic image of a blood sample; identifying, within the microscopic image, candidate leukocytes within the blood sample; confirming at least that the group of leukocyte candidates are given types of leukocytes by performing additional analysis of the leukocyte candidates; determining the relationship between the leukocyte candidates and the number of leukocyte candidates confirmed to be the given leukocyte types; And excluding the sample from use for performing at least a group of measurements on the sample based at least in part on the relationship between the number of leukocyte candidates and the number of leukocyte candidates confirmed to be the given leukocyte types. 5. Device for recording errors in optical measurements, including: a sample chamber configured to receive a blood sample; a microscope configured to obtain at least one microscopic image of a blood sample; And at least one computer processor configured to: identifying, within a microscopic image, candidates for a given formation in a blood sample, wherein the formation is selected from the group consisting of: platelets, leukocytes, erythrocytes, circulating tumor cells, reticulocytes and Howell-Jolly bodies; confirming that at least some of the candidates are a given entity by performing further analysis of the candidates; determining the ratio between the number of candidates of a given education to the number of verified candidates of a given education; And eliminating the use of the sample to perform at least some measurements of the sample based on the relationship between the number of candidates and the number of candidates tested. 6. The apparatus of claim 5, wherein the computer processor is configured to exclude the sample from use to perform at least some measurements on the sample based on the ratio of the number between confirmed candidates and the number of candidates exceeding a maximum threshold. 7. Device according to any one of paragraphs. 5, 6, wherein the computer processor is configured to exclude the sample from use to perform at least some measurements on the sample based on the ratio between the number of candidates tested and the number of candidates tested that is less than a minimum threshold. 8. Device for recording errors in optical measurements, including: a sample chamber configured to receive a blood sample; a microscope configured to obtain at least one microscopic image of a blood sample; And at least one computer processor configured to: identifying within a microscopic image candidate leukocytes within a blood sample; confirming that at least some of the leukocyte candidates are the desired leukocyte types by further analyzing the leukocyte candidates; determining the relationship between the candidate leukocytes and the number of candidate leukocytes confirmed as given types of leukocytes; And excluding the sample from use to perform at least some measurements on the sample based at least in part on the relationship between the number of leukocyte candidates and the number of leukocyte candidates confirmed to be the given leukocyte types.