WO2025196261A1

WO2025196261A1 - Automated method for microscopic analysis of a biological sample

Info

Publication number: WO2025196261A1
Application number: PCT/EP2025/057788
Authority: WO
Inventors: Mirko Mario KLINGAUF; Jaclyn Mary RUHL
Original assignee: Roche Diagnostics International AG
Current assignee: Roche Diagnostics International AG
Priority date: 2024-03-22
Filing date: 2025-03-21
Publication date: 2025-09-25
Anticipated expiration: 2026-09-22

Abstract

The present invention relates to an automated method for microscopic analysis of a biological sample suspected to comprise cells, comprising the following steps: a) mounting a biological sample suspected to comprise cells on a microscopic slide; b)contacting the sample mounted on the microscopic slide with a first staining solution comprising a single first dye and a fixative for a time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed; c) analyzing the microscopic slide by automated microscopic imaging; d) determining the cells in the sample; e) comparing the determined cells to a reference; f) depending on the comparison, contacting the sample with a second or further staining solution; and g) repeating steps c) to e). The invention further relates to an automated microscopic device adapted for performing the method of the invention.

Description

Automated method for microscopic analysis of a biological sample

Technical Field

Background art

Analyzing body fluids provides an important diagnostic tool for assessing a subject’s health. Body fluids display a wide range of cell concentration, highly variable viscosity and specific features like cell aggregates or even bone splinters. On-Slide body fluid analysis, unlike analysis by flow cytometry, necessitates multiple staining and washing steps, which can lead to significant cell loss making accurate counts difficult. However, on-slide analysis allows for automation of cell determination, such as determination of extended white blood cell differentials which is currently done manually. Despite existing tools, developing new devices and methods is still a focus of ongoing research and development.

EP2424589A1 discloses systems and methods analyzing body fluids containing cells utilizing an improved technique for applying a monolayer of cells to a slide and generating a substantially uniform distribution of cells on the slide. Additionally, aspects of EP2424589A1 relate to systems and method for utilizing multi-color microscopy for improving the quality of images captured by a light receiving device. The automated counting of cells in blood samples in multi-color microscopy is disclosed.

EP2972208A1 relates to particle contrast agents generally and more specifically to particle contrast agent compositions for use to discriminate and quantify particles such as blood cells in a blood fluid sample by imaging in an automated particle analysis system.

Problem to be solved

None of these known methods and devices provide means for cost and time-efficient but accurate automated microscopic analysis of a biological sample suspected to comprise cells, specifically a sample of a body expected to comprise a low number of cells; in particular the prior art provide no means for cost and time-efficient but accurate automated determination of cell numbers and cell types in a sample of a body expected to comprise a low number of cells.

It is therefore desirable to overcome at least partially the above mentioned shortcomings of the known methods and devices of this kind and address the above mentioned problems and needs.

Summary

This problem is addressed by an automated method and a device for microscopic analysis of a biological sample suspected to comprise cells with the features of the independent claims. Advantageous embodiments which might be realized in an isolated fashion or in any arbitrary combinations are listed in the dependent claims as well as throughout the specification.

As used in the following, the terms “have”, “comprise” or “include” or any arbitrary grammatical variations thereof are used in a non-exclusive way. Thus, these terms may both refer to a situation in which, besides the feature introduced by these terms, no further features are present in the entity described in this context and to a situation in which one or more further features are present. As an example, the expressions “A has B”, “A comprises B” and “A includes B” may both refer to a situation in which, besides B, no other element is present in A (i.e. a situation in which A solely and exclusively consists of B) and to a situation in which, besides B, one or more further elements are present in entity A, such as element C, elements C and D or even further elements.

Further, it shall be noted that the terms “at least one”, “one or more” or similar expressions indicating that a feature or element may be present once or more than once typically will be used only once when introducing the respective feature or element. In the following, in most cases, when referring to the respective feature or element, the expressions “at least one” or “one or more” will not be repeated, non-withstanding the fact that the respective feature or element may be present once or more than once.

Further, as used in the following, the terms "preferably", "more preferably", "particularly", "more particularly", "specifically", "more specifically, “typically”, “more typically" or similar terms are used in conjunction with optional features, without restricting alternative possibilities. Thus, features introduced by these terms are optional features and are not intended to restrict the scope of the claims in any way. The invention may, as the skilled person will recognize, be performed by using alternative features. Similarly, features introduced by "in an embodiment of the invention" or similar expressions are intended to be optional features, without any restriction regarding alternative embodiments of the invention, without any restrictions regarding the scope of the invention and without any restriction regarding the possibility of combining the features introduced in such way with other optional or non-optional features of the invention.

The present invention proposes an automated method for microscopic analysis of a biological sample suspected to comprise cells.

The method comprises the following method steps which, specifically, may be performed in the given order. Still, a different order is also possible. It is further possible to perform two or more of the method steps fully or partially simultaneously. Further, one or more or even all of the method steps may be performed once or may be performed repeatedly, such as repeated once or several times. Further, the method may comprise additional method steps which are not listed.

The automated method comprises the following steps: a) mounting a biological sample suspected to comprise cells on a microscopic slide; b) contacting the sample mounted on the microscopic slide with a first staining solution comprising a single first dye and a fixative for a time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed; c) analyzing the microscopic slide by automated microscopic imaging; d) determining the cells in the sample; e) comparing the determined cells to a reference; f) depending on the comparison, contacting said sample with a second or further staining solution; and g) repeating steps c) to e).

The automated method according to the invention may provide advantageous means for microscopic analysis of a biological sample. In particular, it may provide an accurate microscopic determination of cell numbers, utilizing a simplified staining process which typically reduces the analysis time and work load and thereby enhances cost-efficiency. The determination of cell number may typically be an absolute quantification resulting in an accurate count of cells present in a sample.

The term “automated” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to a process which is performed completely by means of at least one computer and/or computer network and/or machine, in particular without manual action and/or interaction with a user. The method may be performed completely automatically also referred to as fully automated. Alternatively selected steps of the method may be fully automated.

The method may be computer-implemented or partially computer-implemented. The term “computer-implemented” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to a process which is fully or partially implemented by using a data processing means, such as data processing means comprising at least one processor. The term “computer”, thus, may generally refer to a device or to a combination or network of devices having at least one data processing means such as at least one processing unit. The computer, additionally, may comprise one or more further components, such as at least one of a data storage device, an electronic interface or a human-machine interface.

The term “microscopic analysis” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to the analysis of a sample mounted onto a substrate, e.g. on a microscopic slide, by microscopic imaging. In particular, the term may relate to the process of image data acquisition of said sample, more particularly acquisition of a microscopic image, and, may typically include determining cells in said sample.

The term “microscopic slide” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to a substrate which is designated for a sample to be mounted thereon for microscopic analysis. The substrate may be mechanically stable. The substrate may comprise any material which provides sufficient mechanical stability. The substrate may exhibit a surface which is configured to be compatible with biological material. By way of example, the microscopic slide is a glass slide. However, further kinds of materials for the slides may also be feasible. The microscopic slide may be a plate having a 2D extension and a thickness. The 2D extension of the plate may exhibit a rectangular or circular form. The thickness of the plate may be small compared to a size of the extension, preferably 20 %, more preferred 10 %, in particular 5 %, or less than a measure for a linear extent of the 2D extension of the plate. The microscopic slide may have a shape which may enable imaging of the sample mounted on the microscopic slide. Typically, the substrate typically comprises or consists of glass.

The term “microscopic imaging” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to generating and/or providing a two-dimensional (2D) representation of at least one property of the sample using a microscope, also denoted by the term “microscopic image”. The image can typically be processed and displayed on a screen for being regarded by eyes of a viewer, preferably, without any further aids, apart from eyeglasses of the viewer. The microscopic imaging may comprise generating and/or providing a digital image. The term “digital image” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to a discrete and discontinuous representation of the image. The term “digital image” may refer to a two-dimensional function, f(x,y), wherein intensity and/or color values are given for any x, y-position in the digital image, wherein the position may be discretized corresponding to recording pixels of the digital image. Methods and devices for microscopic imaging are known in the art. Devices for automated microscopic imaging particularly suitable for the method of the present invention are known in the art and for example disclosed for example in PCT/EP2023/084735, US2018/012062 Al, US2016/0026852 Al, US2012262705 Al and US 2012194729 Al. The term “microscopic image” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to an image of at least one area of the microscopic slide generated by using at least one microscope, more specifically an image scanner, e.g. a scanning microscope. The microscopic scanning may be performed using at least one microscope, typically at least one scanning microscope.

The term “image data acquisition” or “image acquisition” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to at least one process of generating at least one image, for example a plurality of images. As outline above, the microscopic images may be generated as digital images, e.g. as image data. In the method according to the invention, the microscopic imaging typically comprises at least one light microscope, typically at least one bright field microscope or at least one fluorescence microscope as known in the art. Typically, the microscope is a scanning microscope. It is also noted that the method described herein may be used in connection with microscope slide scanning instrument architectures and techniques for image capture, stitching and magnification as described in US 2008/0240613 Al and US 10061107 B2 which are incorporated herein by reference, including features in connection with reconstituting an image.

The term “biological sample” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to a sample derived from a biological entity, such as a cell, a tissue, a body, an excrement, of any type of organisms. The term in particular refers to a sample suspected to comprise cells, more particular nucleated cells. Typically, the biological sample is a sample of a body fluid, specifically a sample of a body fluid expected to comprise a low number of cells, more specifically a body fluid derived from a subject of interest. Samples of blood or samples of whole blood are typically excluded from the analysis by the method according to the invention. Commonly said blood samples comprise more than one million cells per pl and are hence typically not understood as comprising a low number of cells. The terms “sample” and “biological sample” are used interchangeably herein. As referred to herein, the term “sample” may relate to any sub-portion or sub sample or aliquot of the biological sample. A sub-portion or subsample or aliquot of the sample may typically be obtained by dividing the sample into portions by techniques in known to the person of skill in the art such as pipetting portions, e.g. pipetting predetermined volumes, of a liquid sample into vessels or onto microscopic slides.

More typically, a body fluid expected to comprise a low number of cells (i.e. a sample of a body fluid suitable for the analysis in the method according to the invention) comprises less than 10000 cells/pl of sample, less than 1000 cells/pl of sample, less than 500 cells/pl of sample, less than 100 cells/pl of sample, or less than 10 cells/pl of sample. Even more typically, a body fluid expected to comprise a low number of cells comprises an amount of 0 to 10 cells/ pl of sample.

Body fluids suitable for automated microscopic analysis in the method according to the invention are specifically selected from the group consisting of: cerebrospinal fluid, synovial fluid, urine, saliva, pleural fluid, lacrimal fluid, peritoneal fluid, pericardial fluid, and bone marrow. More specifically, said body fluids are selected from the group consisting of: cerebrospinal fluid, even more specifically said body fluid is cerebrospinal fluid.

Samples of body fluids can be obtained by well-known techniques. These techniques include, preferably, punctures, scrapes, swabs or biopsies. Such samples can be obtained by use of needles, syringes, brushes, (cotton) swabs, spatulas, rinse/wash devices, punch biopsy devices, puncture devices for cavities, such as needles or lances, or by other surgical instrumentation. Typically, samples may be obtained from body fluids, or tissues or organs by separating techniques such as filtration, centrifugation, or cell sorting. Most typically, the sample is a body fluid as defined elsewhere herein. The sample may in particular be a cerebrospinal fluid, synovial fluid, urine, saliva, pleural fluid, lacrimal fluid, peritoneal fluid, pericardial fluid, or bone marrow. The sample typically is a liquid sample; a sample of tissue or organ may be dispersed or diluted using an appropriate buffer to obtain a liquid sample.

The method comprises mounting a biological sample on a microscopic slide. The term “mounting” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may specifically refer without limitation, to placing the sample, in particular the sample of a body fluid, onto the microscopic slide. This may typically comprise dispensing a defined amount or the entire of the sample volume to the microscopic slide. The dispensing may involve an automated liquid dispenser or an automated pipetting device, such as known in the art. Alternatively, a defined amount of the sample may be dispensed or pipetted manually. Moreover, for non-liquid or viscous samples, “mounting” may refer to applying the sample onto the microscopic slide by means of a spatula or a swab.

Typically, the sample mounted on the microscopic slide has a predefined volume of 0.5 pl to 10 pl. More typically, a predefined volume of 1 to 5 pl of sample is mounted on the microscopic slide.

Samples obtained from body fluids expected to comprise a low number of cells are commonly difficult to obtain. Often only a few pl can be obtained from said body fluids and hence only limited sample volume is available for analysis. The method according to the invention is advantageous as it requires little sample volumes. Volumes of 0.5 to 10 pl are usually sufficient for an accurate determination of cells, in particular for determination of the number of cells. Moreover, the analysis makes an absolute quantification of the sample possible, in particular of the number of cells present in the sample.

The method according to the invention further comprises contacting the sample mounted onto the microscopic slide with a first staining solution. The term “contacting” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to establishing a contact of a biological sample mounted onto a microscopic slide with a first staining solution by any means known to the skilled artisan such as: immersing the microscopic slide in the first staining solution; spraying the staining solution on top of the sample; wetting the sample with the first staining solution, and the like.

Typically, the single first dye of the first staining solution is a nucleic acid staining dye. More typically, said single first dye is selected from the group consisting of eosin, chlorazol black E, toluidine blue, neutral red, methylene blue, azure B, ethyl green, hematoxylin, even more typically said dye is azure B.

The term “first staining solution comprising a single first dye and a fixative” as used herein refers to a first staining solution that exclusively comprises a single dye. Further said staining solution comprises a fixative. However, besides said single first dye there are no other dyes present in said first staining solution. Preferably, the first staining solution exclusively comprises a nucleic acid staining dye as specified elsewhere herein in more detail. The fixative comprises, typically is, methanol, ethanol or an aldehyde or a combination thereof. The fixative may be chosen by the person of skill in the art depending on the specific single first dye and the sample. Suitable combinations of dyes and fixatives are known in the art. A preferred first dye in line with the present invention is azure B. More preferably, the first staining solution may comprise or consist of a solution of 0.01 % to 0.5 (w/v) of azure B in methanol more preferably 0.1 % (w/v) of azure B in methanol.

Said contacting the sample mounted onto the microscopic slide with a first staining solution typically results in staining and fixing of the sample in a single step, in other words it typically provides a stained and fixed sample in a single step.

Staining and fixing with a single dye in a single step as in the method according to the invention is advantageous as it reduces loss of cells caused by wash-off commonly seen in staining procedures involving multiple steps of staining, fixing and washing that are required when staining with multiple dyes. In the method according to the invention, a washing step for removing the staining solution is typically not performed. Hence wash-off from the sample can completely be avoided. Reducing potential wash-off has a major impact on accuracy of the cell determination, in particular for biological samples suspected to comprise a low number of cells. With the method according to the invention, a level of quantification of lower than 1 can be achieved, typically the level of quantification is approaching 0, more typically, the level of quantification is lower than 0.5, lower than 0.25, lower than 0.1, or even lower than 0.01. The low level of quantification is advantageous as it means that even if only one cell is present in the biological sample, said cell can be determined with sufficient accuracy The term "level of quantification" as used herein also is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to the detection limit, i.e. the number of cells per sample, at which the cells in the sample may still be determined with a sufficient degree of confidence or statistical significance. It may particularly refer to with lowest quantity of cells to be determined in a sample with a sufficient degree of confidence or statistical significance.

According to the present invention, the first staining solution further may comprise a surfactant and/or ethylene glycol. The surfactant may preferably be selected from the group consisting of non-ionic, cationic, anionic, and zwitterionic surfactants, more preferably the surfactant is a non-ionic surfactant such as a polysorbate. Typically, the surfactant may be present in an amount from 0.05 to 0.5 % (w/v) of the staining solution. The sample mounted on the microscopic slide is contacted with said first staining solution comprising a single first dye and a fixative for a time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed. Suitable staining and fixing times are known to the skilled artisan and typically depend on the dye, the fixative and the sample involved. According to the present invention, the time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed is typically less than 2 minutes, more typically less than 60 seconds, more typically between 20 seconds and 60 seconds, even more typically around 40 seconds. The claimed method is advantageous as the time needed for staining and fixing can be minimized while a reliable determination of cells is still possible. Preferably, the staining and fixing is performed in an automated Stainer wherein the residual staining solution is removed automatically by means of a suction device or the like. Automated strainers and staining platforms are known in the art and disclosed for example in WO 2020/104538 and US2016018302.

The method according to the invention comprises a step of determining the cells in the sample. The term “determining” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may, without limitation, encompass any kind of qualitative or quantitative determinations of the cells. A qualitative determination aims at determining the presence or the absence of cells, in particular discriminating between different type of cells in the sample; whereas quantitative determination aims at determining the amount of number of the cells in the sample. The quantitative determination, i.e. the determination of the amount, includes determining the absolute numbers (e.g. the total number of cells present in the sample) or a relative amount (e.g., an amount relative to the sample volume (concentration) or a classification such as a score (e.g., “high amount”, “low amount” and the like). Typically, said step of determining the cells comprises at least determining the absolute number of the cells in the sample. More typically, said step of determining the cells comprises determining the absolute number of cells in the sample and the type of cells in the sample. Determining the cells comprises determining the absolute number of polynucleated and the absolute number of mononucleated cells of the same type in the sample, for example of poly- and mononucleated white blood cells.

Typically, the step of determining the cells in the sample of the method according to the invention comprises automated determining of the number of cells. Said automated determining can be achieved by an automated comparison algorithm implemented on a data processing device such as a computer. Means and methods for automated determination of cell numbers on a microscopic slide are known in the art and for example described in PCT/EP2023/084735, US2009269799, US2015355078 and WO 2020104538.

More typically, the step of determining the cells in the sample of the method according to the invention comprises automated determining of the type of cells. In general, the type of cell to be determined is not particularly limited. All types of cells suspected to be present in the sample may be determined. Even more typically, the step of determining the cells in the sample determines the accumulated count of the cells in the biological sample. Automated cell recognition systems are known in the art and for example disclosed in PCTZEP2023/084735, US2018012062 Al and US2016026852 Al. Typically, automated determining of cells, also referred to as cell recognition herein, may comprise image segmentation by an image segmentation algorithm as known in the art and described for example in US2007036436 Al and US2010150443 Al, which are enclosed herein in their entirety by reference.

Typically, the type of cells to be determined include mononucleated white blood cells and/or polynucleated white blood cells such as granulocytes, lymphocytes and monocytes; red blood cells; cancer cells; platelets; bacterial cells; cells of parasites; mesothelial cells; particularly the type of cells to be determined include mononucleated white blood cells, polynucleated white blood cells, red blood cells, cancer cells.

More particularly, the step of determining the cells in the sample comprises discriminating be-tween mono- and polynucleated cells of the same type.

Even more particularly, determining the cells in the sample comprises discriminating between mono- and polynucleated white blood cells and determining their amounts, such as determining the amount of mononucleated white blood cells and the amount of polynucleated white blood cells in the sample. Even more particularly, determining the cells in the sample comprises performing a two-type differential analysis for white blood cells.

Further types of differential analysis such as three-, or five-type differential analysis, may be performed in cases and/or under conditions as known in the art. However, advantageously with the method according to the present invention, higher type differential analysis is possible. Higher type differential analysis refers to more than 6 type differential, typically more than 10-type, eve more typically 14-type differential analysis is possible; wherein neutrophils, lymphocytes, monocytes, eosinophils, basophils and subtypes thereof are determined. Advantageously, it has been found by the present inventors that staining with a single first dye is sufficient in order to analyze most biological samples suspected to comprise cells. Depending on a comparison to a reference the biological sample may be contacted with a second or further staining solution; and the steps of analyzing the microscopic slide by automated microscopic imaging, determining the cells in the sample, and comparing the determined cells to a reference are repeated.

The term “reference” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to a predefined value regarding the cells suspected to be comprised in the biological sample. Said value may in particular depend on the cells and/or type of cells suspected to be comprised in the biological sample and/or on the biological sample itself. More specifically, the reference represents an expected value of cells per volume of the sample, typically an expected number of cells, more typically an expected number for each cell type per volume of the sample. The reference typically relates to a reference value derived from a biological sample of healthy subj ect or object, typically to a normalized range derived from a biological sample of healthy subject or object or any average thereof. The type and value of the reference typically depends on the sample type. Relevant reference values relating to particular sample types are known in the art and can immediately be chosen and applied by a person of skill in the art as required.

Typical values of references to be applied in line with the present invention include the following: a maximum of five white bloods cells per pl of cerebrospinal fluid.

Source: *Galagan, K. A. (2006). Color atlas of body fluids: an illustrated field guide based on proficiency testing. Northfield, IL: College of American Pathologists.

** Sysmex Educational Enhancement and Development SEED Body Fluids. (2017, April). Retrieved from https://www.sysmex.ch/akademie/literatur/documents/detail/sysmex-seed- synovial-fluid-part- 1 -main-characteristics.html.

*** Heron M, Gratters JC, ten Dam-Molenkamp KM, Hijdra D, van Heugten-Roeling A, Claessen AM, Ruven HJ, van den Bosch JM, van Velzen-Blad H. Bronchoalveolar lavage cell pattern from healthy human lung. Clin Exp Immunol. 2012 Mar;167(3):523-31.

The term "subject" as used herein relates is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to any kind of living being, in particular animals and, more particularly, to mammals. In particular, the subject is a primate and, most typically, a human. A “healthy subject” according to the present invention, particularly refers to a subject not displaying any aberrations in or of the cells determined in the method of the invention. The biological sample to be analyzed in the present invention is typically derived from a subject suspected to display aberrations in or of the cells determined. The term “aberrations” in this respect typically refers to the number or shape or any other characteristics, such as number of nuclei, of the determined cells.

The step of comparing the determined cells to a reference can be achieved by an automated comparison algorithm, or classification algorithm, such as known in the art, typically a comparison algorithm, more typically a thresholding algorithm, implemented on a data processing device such as a computer. Compared to each other are typically the determined cells and a reference representing an expected value for said cells or said type of cells in said biological sample. Suitable devices with appropriate software such as thresholding processes are known in the art and for example described in US2007036436 Al and US2010150443 Al.

Typically, the term “depending on the comparison” means a dependency on the result of the comparison, i.e. the result achieved in the comparison, a negative or a positive result.

Specifically a positive result is achieved if the determined cells meet the reference and a negative result is achieved if the determined cells do not meet the reference. Typically, a positive result means that the determined cells are below or equal to the reference. More typically, a positive result means that the number of the determined cells is lower than or equal to the reference value; while a negative result means that number of the determined cells is higher than the reference value. More typically, a negative result of the comparison means that the determined cells are above the reference. More typically, a negative result of the comparison means that a number of the determined cells is higher than the reference value. Even more typically, a negative result of the comparison means that a number of a certain type of determined cells is higher than the reference value.

In case the comparison gives a positive result, contacting said sample with a second or further staining solution and repeating of steps c) to e) is not necessary and not performed.

In case the comparison gives a negative result, the sample is contacted with a second or further staining solution and steps c) to e) are repeated.

The result from the comparison may be assigned to further information on the sample and/or on the sample type and/or information relating to the subject the sample may be derived from including for example age of the subject, sex of the subject, and/or health of the subject.

Alternatively, the sample is contacted with a second or further staining solution and steps c) to e) are repeated if in the comparison the determined cells differ significantly from the reference. A “significant difference” refers to a statistical difference, in particular to a statistically significant difference in the number of the determined cells and the reference.

The step of comparing the determined cell with a reference is typically performed automatically. It may more typically involve the use of a computer or may be controlled by a computer or computer network.

The method according to the invention further comprises depending on the comparison, contacting said sample with a second or further staining solution. The method typically comprises a step of selecting the sample for contacting with a second or further staining solution based on the comparison. The selection may typically be automated or performed manually, more typically, the selection is fully automated. Even more typically, the method may comprise automatically selecting the sample for contacting with a second or further staining solution based on the comparison and automatically contacting said sample with a second or further staining solution based on the comparison.

The sample selected for contacting with a second or further staining solution may be identical with the sample contacted with the first staining solution. In this case, the step of mounting the sample to a microscopic slide is typically not required; i.e. the sample is already mounted. However, alternatively, the sample selected for contacting with a second or further staining solution may refer to a new aliquot of the sample contacted with the first staining solution; then the step of mounting the sample to a microscopic slide is typically required.

The second or further staining solution typically comprises one or more than one dye different from the single first dye and a fixative. The fixative may be a fixative as described for the first staining solution elsewhere herein. The dye may be a dye as described for the first staining solution elsewhere herein as long as it is not identical with the single first dye used in the first staining solution. Particular suitable dyes or stains for the second or further staining solution are selected from the group consisting of Romanowsky, Romanowsky-Giemsa, Wright, Wright-Giemsa and May-Grunwald stain.

The contacting may be performed as described elsewhere herein for the first staining solution. Following the contacting with the second or further staining solution, the method comprises repeating steps c) to e).

Preferably, the second or further staining solution comprises Romanowsky, Romanowsky- Giemsa, Wright, Wright-Giemsa or May-Grunwald stain. These stains and dyes are known in the art. A suitable fixative may be used depending on the stain or dye.

In the method according to the invention, preferably, steps b) to e) are fully automated, typically steps b) to g) are fully automated.

Preferably, the automated microscopic imaging comprises automated cell recognition by a classification algorithm. More preferably, the automated microscopic imaging and the automated determining comprises the classification algorithm. The classification algorithm may typically classify cells into cell types, for example mononucleated white blood cells and/or polynucleated white blood cells such as granulocytes, lymphocytes and monocytes, red blood cells, cancer cells, platelets, bacterial cells, cells of parasites, mesothelial cells. Linear discriminant analysis (LDA) based classification and/or non-LDA classification, such as Bayesian classification may be used. Processes and devices to classify cells are known in the art and for examples described in US 2016026852 Al.

Cells may typically be classified as known in the art, namely based on feature vectors representing one or more features of the objects, such as cell area, cell shape, cell color, cell optical density, cell texture, and other features of the cells and described for example in US 2016026852 Al, which is enclosed herein in its entirety by reference.

Alternatively, the classification algorithm uses at least one classification algorithm selected from the group consisting of at least one convolutional neural network (CNN) technology, deconvolutional neural network (DNN) technology, machine learning algorithm, decision trees, point vector, random forest, K-Nearest-Neighbor. A typical classification algorithm suitable for use in the method according to the invention is disclosed in PCT/EP2023/084735.

Moreover the present invention contemplates an automated microscopic device adapted for performing the method of any of the preceding claims, comprising at least one automated microscopic image scanner equipped with at least one microscopic slide holder; at least one automated Stainer comprising a first staining solution for staining a biological sample mounted on a microscopic slide; at least one processing device configured for determining the cells in the sample by comparing the determined cells to a reference; at least one controlling device configured for contacting said sample with a second or further staining solution and repeating the imaging of said microscopic slide depending on the comparison.

The term “automated microscopic imaging” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to the microscopic analysis of a biological sample, typically a biological sample mounted onto a microscopic slide, by use of an automated microscope, as known in the art; in particular, a microscope comprising an automated microscopic image scanner.

The term “automated microscopic image scanner” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to a device or system configured for automatically scanning the sample and thereby generating microscopic images. It is further equipped with at least one microscopic slide holder. For example, the image scanner may comprise at least one light microscope. Image scanners are known in the art and commercially available. Examples thereof are given below.

Automated microscopic image scanners and automated microscopic devices are known in the art such as cobas m 511 from Roche and described for example in EP2638381 Al, EP2424589 Al and/or WO 2020/104538 Al. An automated Stainer suitable for use in the present invention is disclosed in WO 2020/104538 Al.

The image scanner may comprise at least one image sensor. The term "image sensor" as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to at least one sensor device having at least one imaging element configured for recording or capturing spatially resolved one-dimensional, two-dimensional or even three-dimensional optical data or information. The image sensor may be a camera, e.g. a pixelated camera. As an example, the imaging sensor may comprise at least one camera chip, such as at least one CCD chip and/or at least one CMOS chip. The image sensor may comprise at least one camera, wherein the camera is a charge-coupled device (CCD) and/or a complimentary metal-oxide semiconductor (CMOS) image sensor. However, further kinds of imaging devices may also be feasible.

The term “processing device” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term specifically may refer, without limitation, to an arbitrary logic circuitry configured for performing basic operations of a computer or system, and/or, generally, to a device which is configured for performing calculations or logic operations. The processing device may be configured for processing basic instructions that drive the computer or system. As an example, the processing device may comprise at least one arithmetic logic unit (ALU), at least one floating-point unit (FPU), such as a math co-pro- cessor or a numeric co-processor, a plurality of registers, specifically registers configured for supplying operands to the ALU and storing results of operations, and a memory, such as an LI and L2 cache memory. The processing device may be a multi-core processor. The processing device may be or may comprise a central processing unit (CPU). Additionally or alternatively, the processing device may be or may comprise a microprocessor. The processing device’s elements may be contained in one single integrated circuitry (IC) chip. Ad- ditionally or alternatively, the processing device may be or may comprise one or more application-specific integrated circuits (ASICs) and/or one or more field-programmable gate arrays (FPGAs) and/or one or more tensor processing unit (TPU) and/or one or more chip, such as a dedicated machine learning optimized chip, or the like. The processing device specifically may be configured, such as by software programming, for performing one or more evaluation operations. For example, the processing device is a control logic of the image scanner and/or a remote device to which the image scanner is connected. The processing device may be at least one element or at least one unit of the image scanner. However, other embodiments are feasible, e.g. in which the processing device is embodied at least partially as external and/or remote processing device.

The term “controlling device” as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art and is not to be limited to a special or customized meaning. The term may, specifically, refer, without limitation, to an arbitrary device, that may also be referred to as controller, configured for performing the named operations, e.g. by using at least one data processing device, e.g. the processing device described above or as described in more detail below, and, for example, by using at least one processor and/or at least one application-specific integrated circuit. As an example, the at least one controlling device may comprise at least one data processing device having a software code stored thereon comprising a number of computer commands. The controlling device may provide one or more hardware elements for performing one or more of the named operations and/or may provide one or more processors with software running thereon for performing one or more of the named operations. The controlling device may comprise one or more programmable devices such as one or more computers, application-specific integrated circuits (ASICs), Digital Signal Processors (DSPs), or Field Programmable Gate Arrays (FPGAs). Additionally or alternatively, however, the controlling device may also fully or partially be embodied by hardware. Further, the controlling device may comprise at least one volatile or non-volatile data storage. The controlling device may comprise at least one interface, such as a human-device interface, configured for entering commands and/or for outputting information. The at least one interface may comprise a wired interface and/or a wireless interface for uni-directionally or bi-directionally exchanging data or commands, specifically between the image scanner and at least one further device and/or units of the image scanner. For example, the controlling device may comprise at least one computer and/or at least one processor. The controlling device may be or may comprise a centralized control device and/or one or more decentralized control devices. Further contemplated according to the present invention is the use of a single first dye for automated microscopic analysis of cells in a biological sample suspected to comprise cells.

Summarizing and without excluding further possible embodiments, the following embodiments may be envisaged:

1. An automated method for microscopic analysis of a biological sample suspected to comprise cells, comprising the following steps: a) mounting a biological sample suspected to comprise cells on a microscopic slide; b) contacting the sample mounted on the microscopic slide with a first staining solution comprising a single first dye and a fixative for a time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed; c) analyzing the microscopic slide by automated microscopic imaging; d) determining the cells in the sample; e) comparing the determined cells to a reference; f) depending on the comparison, contacting said sample with a second or further staining solution; and g) repeating steps c) to e).

2. The method according to embodiment 1, wherein the biological sample is a sample of a body fluid, specifically a sample of a body fluid expected to comprise a low number of cells.

3. The method according to any of the preceding embodiments, wherein a low number of cells refers to less than 10000, less than 1000, less than 500, less than 100, less than 10 cells/pl of sample.

4. The method according to any of the preceding embodiments, wherein the body fluid is selected from the group consisting of: cerebrospinal fluid, synovial fluid, urine, saliva, pleural fluid, lacrimal fluid, peritoneal fluid, pericardial fluid, and bone marrow.

5. The method according to any of the preceding embodiments, wherein the step of determining the cells in the sample comprises automated determining of the number of cells. The method according to any of the preceding embodiments, wherein the step of determining the cells in the sample comprises automated determining of the type of cells. The method according to any of the preceding embodiments, wherein the step of determining the cells in the sample comprises discriminating between mono- and polynucleated cells of the same type. The method according to any of the preceding embodiments, wherein the automated microscopic imaging comprises automated cell recognition by a classification algorithm. The method according to any of the preceding embodiments, wherein the reference represents an expected value of the cells, typically an expected number of cells, more typically an expected number for each cell type. The method according to any of the preceding embodiments, wherein the single first dye is a nucleic acid staining dye, typically selected from the group consisting of eosin, chlorazol black E, toluidine blue, neutral red, methylene blue, azure B, ethyl green, hematoxylin. The method according to any of the preceding embodiments, wherein the first staining solution comprises a single first dye and a fixative. The method according to the preceding embodiment, wherein the first staining solution consists of a single first dye and a fixative. The method according to embodiment 11, wherein the first staining solution consists of a single first dye, a fixative and at least one of the following: a surfactant, ethylene glycol. The method according to the preceding embodiment, wherein the fixative comprises, typically is, methanol, ethanol or an aldehyde or a combination thereof. The method according to any of the preceding embodiments, wherein the time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed is less than 2 minutes, typically less than 60 seconds, more typically around 40 seconds. The method according to any of the preceding embodiments, wherein the sample is contacted with a second or further staining solution and steps c) to e) are repeated if in the comparison the determined cells differ significantly from the reference. The method according to any of the preceding embodiments, wherein the first dye is azure B. The method according to any of the preceding embodiments, wherein the first staining solution comprises 0.1 % (w/v) azure B in methanol. The method according to any of the preceding embodiments, wherein the first staining solution further comprises a surfactant and/or ethylene glycol. The method according to any of the preceding embodiments, wherein the second or further staining solution comprises Romanowsky, Romanowsky-Giemsa, Wright, Wright-Giemsa or May-Grunwald stain. The method according to any of the preceding embodiments, wherein the automated microscopic imaging and the automated determining comprises the classification algorithm. The method according to any of the preceding embodiments, wherein the microscopic imaging comprises at least one light microscope, typically at least one bright field microscope or at least one fluorescence microscope. The method according to any of the preceding embodiments 6 to 21 , wherein the type of cells to be determined include mononucleated white blood cells and/or polynucleated white blood cells such as granulocytes, lymphocytes and monocytes, red blood cells, cancer cells, platelets, bacterial cells, cells of parasites, mesothelial cells; typically mononucleated white blood cells, polynucleated white blood cells, red blood cells, cancer cells. The method according to any of the preceding embodiments, wherein steps b) to e) are fully automated, typically wherein steps b) to g) are fully automated. 25. The method according to any of the preceding embodiments, wherein the step of determining the cells in the sample comprises automated determining of the absolute numbers of the cells in the sample.

26. An automated microscopic device adapted for performing the method of any of the preceding embodiments, comprising: at least one automated microscopic image scanner equipped with at least one microscopic slide holder; at least one automated Stainer comprising a first staining solution for staining a biological sample mounted on a microscopic slide; at least one processing device configured for determining the cells in the sample by comparing the determined cells to a reference; at least one controlling device configured for contacting said sample with a second or further staining solution and repeating the imaging of said microscopic slide depending on the comparison.

All references cited throughout this specification are herewith incorporated by reference with respect to their entire disclosure content and with respect to the specific disclosure contents mentioned in the specification.

Figure legends

Figure 1 is a schematic depiction of the workflow in line with the invention. (1) Workflow depicting the one step staining and fixing procedure of a sample of body fluid. (2) contacting the sample mounted to a microscopic slide with a first staining solution comprising a single first dye and a fixative. The mounted sample is dried and the cells are determined and compared to a reference: (4) shows a mononucleated, (5) shows a polynucleated white blood cell in microscope image of a sample fixed with methanol containing 0.05% azure blue and imaged using a lOx, NA 0.5 objective (6). (3) Depending on the comparison with the reference, said sample is reflexed to further staining such as depicted in workflow (7). (7) exemplifies a full Romanowsky staining procedure for an extended differential analysis. (8) Fixing the sample with a fixative, contacting the sample with a first (9) and second (10) staining solution, (11) rinsing of the sample. (12) microscope image for accurate redetermination of cells and 5-part differential analysis based on re-stained sample.

Examples

The following Examples shall merely illustrate the invention. They shall not be construed, whatsoever, to limit the scope of the invention.

In a first procedure, a first aliquot of a sample is printed onto a glass slide, air dried and subsequently fixed using methanol containing 0.05% azure blue. The slide is then imaged using a lOx NA 0.5 objective for determination of cell numbers and an initial 2-part differential (mono- vs polynucleated WBCs). In case of a conspicuous result, a reflex process would be triggered (either automatically or by the user) in which the sample would be undergo a second staining procedure. The second procedure includes applying a second aliquot of the sample onto a glass slide, air drying the sample and fixing it with fixative, which may be the same as in the first procedure. The second procedure further includes staining the sample with a Romanowsky stain, followed by a rinsing step. The imaging step and image analysis then allow for a determination of the quantity of different cell types and a 5-part differential.

In a first example, a whole blood sample was applied and processed according to the first procedure (s. microscope image 6, Fig. 1). Mono- and polynucleated WBCs were found in the sample. After triggering a reflex test, the same whole blood sample was applied onto a microscope slide again and was processed according to the second procedure, i.e. staining, washing and imaging. An image of a microscope image of the whole blood sample after the second procedure is shown on the right (s. microscope image 12, Fig. 1). Optionally, the same microscope slide as used in the first procedure can be reused in the second procedure and only undergo additional staining and washing steps (sample application, air drying and fixation would not be required in this scenario).

In a second experiment, an ascites body fluid sample was processed according to the first procedure, in order to demonstrate that the sample processing according to the first procedure also works with larger sample volumes (6 pL instead of 1 pL). Cited literature

Galagan, K. A. (2006). Color atlas of body fluids: an illustrated field guide based on proficiency testing. Northfield, IL: College of American Pathologists.

Sysmex Educational Enhancement and Development SEED Body Fluids. (2017, April). Retrieved from https://www.sysmex.ch/akademie/literatur/documents/detail/sysmex-seed-syn- ovial-fluid-part-l-main-characteristics.html. Heron M, Gratters JC, ten Dam-Molenkamp KM, Hijdra D, van Heugten-Roeling A, Claessen AM, Ruven HJ, van den Bosch JM, van Velzen-Blad H. Bronchoalveolar lavage cell pattern from healthy human lung. Clin Exp Immunol. 2012 Mar;167(3):523-31.

Claims

2. The method according to claim 1, wherein the biological sample is a sample of a body fluid, specifically a sample of a body fluid expected to comprise a low number of cells.

3. The method according to any of the preceding claims, wherein a low number of cells refers to less than 10000, less than 1000, less than 500, less than 100, less than 10 cells/pl of sample.

4. The method according to any of the preceding claims, wherein the body fluid is selected from the group consisting of: cerebrospinal fluid, synovial fluid, urine, saliva, pleural fluid, lacrimal fluid, peritoneal fluid, pericardial fluid, and bone marrow.

5. The method according to any of the preceding claims, wherein the step of determining the cells in the sample comprises automated determining of the number of cells.

6. The method according to any of the preceding claims, wherein the step of determining the cells in the sample comprises automated determining of the type of cells.

7. The method according to any of the preceding claims, wherein the step of determining the cells in the sample comprises discriminating between mono- and polynucleated cells of the same type.

8. The method according to any of the preceding claims, wherein the automated microscopic imaging comprises automated cell recognition by a classification algorithm.

9. The method according to any of the preceding claims, wherein the single first dye is a nucleic acid staining dye, typically selected from the group consisting of eosin, chlorazol black E, toluidine blue, neutral red, methylene blue, azure B, ethyl green, hematoxylin

10. The method according to any of the preceding claims, wherein the first staining solution comprises a single first dye and a fixative.

11. The method according to the preceding claim, wherein the first staining solution consists of a single first dye and a fixative.

12. The method according to any of the preceding claims, wherein the time sufficient to allow the cells suspected to be comprised in the sample to be stained and fixed is less than 2 minutes, typically less than 60 seconds, more typically around 40 seconds.

13. The method according to any of the preceding claims, wherein the sample is contacted with a second or further staining solution and steps c) to e) are repeated if in the comparison the determined cells differ significantly from the reference.

14. The method according to any of claims 6 to 13, wherein the type of cells to be determined include mononucleated white blood cells and/or polynucleated white blood cells such as granulocytes, lymphocytes and monocytes, red blood cells, cancer cells, platelets, bacterial cells, cells of parasites, mesothelial cells; typically mononucleated white blood cells, polynucleated white blood cells, red blood cells, cancer cells.

15. The method according to any of the preceding claims, wherein steps b) to e) are fully automated, typically wherein steps b) to g) are fully automated.

16. The method according to any of the preceding claims, wherein the step of determining the cells in the sample comprises automated determining of the absolute numbers of the cells in the sample.

17. An automated microscopic device adapted for performing the method of any of the preceding claims, comprising: at least one automated microscopic image scanner equipped with at least one microscopic slide holder; at least one automated Stainer comprising a first staining solution for staining a biological sample mounted on a microscopic slide; at least one processing device configured for determining the cells in the sample by comparing the determined cells to a reference;

-at least one controlling device configured for contacting said sample with a second or further staining solution and repeating the imaging of said microscopic slide de- pending on the comparison.