Methods and systems for applying a liquid sample to a substrate for image analysis

Abstract

This disclosure relates to an automated method for applying a liquid sample (1) onto a substrate (2) for image analysis and an automated system (100) for performing the automated method. The automated method includes: providing data corresponding to the characteristics of the liquid sample (1) from a characteristic measurement unit (20) to a workflow management unit (90); having the workflow management unit (90) select a sample preparation operation based on the characteristics of the liquid sample (1); having the workflow management unit (90) set operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample (1); and controlling the sample preparation unit (10) to prepare the liquid sample (1) for image analysis by performing the sample preparation operation selected by the workflow management unit (90) and using the operating parameters set by the workflow management unit (90).

Description

Technical Field

[0001] This disclosure relates to an automated method and system for applying liquid samples onto a substrate for image analysis. This disclosure further relates to a computer program product including instructions for instructing the automated system to perform the automated method. The automated method, automated system, and computer program product according to this disclosure can be used in the field of hematology. However, other application areas are also possible. Background Technology

[0002] There is a general trend towards automating sample preparation and analysis in hematology. For example, complete blood count (CBC), one of the most frequently performed laboratory tests in hematology, can be assessed using automated devices such as flow cytometry employing impedance measurement, fluorescence measurement, and / or light scattering-based measurement techniques. These devices allow for the determination of various properties of biological samples, such as red blood cell (RBC) count, white blood cell (WBC) count, platelet count, hemoglobin (Hb), and hematocrit (Het). Furthermore, they allow for the characterization of the morphological features of RBCs, WBCs, and platelets through indirect measurements based on light absorption and light scattering techniques and / or cytochemical measurements.

[0003] Whenever an abnormality is detected in a biological sample by flow cytometry analysis (which may be an indication of a disease, such as an abnormally high WBC count or suspected infection in WBCs), the standard procedure is to further investigate the sample to complete the evaluation of the morphological composition of CBCs. In a typical hematology workflow, an in vitro diagnostic (IVD) system identifies biological samples in which abnormalities have been detected to indicate to laboratory technicians that further investigation is required. Such further evaluation is still commonly performed manually, involving placing a portion of the biological sample on a substrate (e.g., a microscope slide), smearing the sample onto the substrate to form a wedge smear, drying and staining the sample, and visually examining the sample under a microscope. This challenging manual process is cost-intensive and time-consuming and typically requires skilled laboratory technicians. Advances have been made in automating this procedure in recent years. Currently, various products are available on the market designed to apply liquid samples onto microscope slides using automated wedge preparation techniques. However, a major drawback of wedge smear preparation is that it produces samples with highly variable thickness and blood component distribution. Wedge smears typically have only a single narrow band with an appropriate cell density for examination and analysis. The positioning and shape of this band vary depending on the slide. Furthermore, these products are usually stand-alone units, resulting in samples having to be manually transported from the automated sample preparation unit to a microscope for visual examination. US 2008 / 0050511 A1 discloses an automated slide preparation apparatus and a method for processing biological samples by quantifying the residue left in the tube by a blood sample propelled through the tube, and controlling the movement profile of the blood smear member of the automated slide preparation apparatus in response to the quantification.

[0004] Other automated sample preparation methods and systems have been developed to overcome the drawbacks of wedge smears in order to produce uniform, high-quality samples, thereby making visual evaluation of the samples easier and more accurate. For example, US 10,764,538 discloses a system and method for applying a monolayer of sample cells onto a substrate using an improved technique to produce a uniform distribution of cells on the substrate, and further discloses an integrated digital microscope for automated visual inspection. This system uses an applicator rather than a coating component to deposit the sample onto the substrate. The physical characteristics of the sample material, such as viscosity or consistency, influence the fluid behavior of the sample as it is applied to the substrate by the applicator and how it is distributed on the substrate after application. The system of US 10,764,538 combines a predetermined optimized sample flow rate through the applicator tip with a predetermined relative applicator speed and height of the tip above the substrate. However, sample characteristics such as the viscosity, consistency, and density of components can vary from sample to sample and become particularly prominent between different types of sample materials. This poses a challenge to systems designed to process different types of sample materials, such as whole blood, serum, plasma, and other bodily fluids like urine, cerebrospinal fluid (CSF), and bone marrow. The system described in US 10,764,538 involves analyzing images of the sample and determining whether further dilution or concentration is needed based on the number of cells counted in the image. If so, the system dilutes or concentrates a portion of the sample before retesting. In either case, the system will need to repeat the entire sample preparation workflow on the same sample again. This reduces system throughput and increases the time to produce results, ultimately placing a financial burden on the laboratory. Summary of the Invention

[0005] In contrast to the background art described above, aspects of the present invention according to this disclosure offer certain non-obvious advantages and advancements over the prior art. In particular, it is recognized that there is a need for an improved method and system for preparing liquid samples for image analysis.

[0006] While the aspects of the invention according to this disclosure are not limited to specific advantages or functionalities, it should be noted that certain aspects of this disclosure can realize automated methods and systems for applying liquid samples to a substrate to produce improved samples for subsequent image analysis. In particular, for different liquid samples with different physical properties, certain aspects of this disclosure can realize the formation of a sample particle monolayer on the substrate while ensuring a sufficient number of particles on the substrate and a uniform distribution of the particles.

[0007] Certain aspects of this disclosure enable an improved method for applying liquid samples to a substrate by selecting a sample preparation operation and setting operating parameters based on previously determined properties of each individual liquid sample. The methods and systems according to certain aspects of this disclosure further provide a simple and cost-effective technique for determining the properties of liquid samples. Other aspects of this disclosure provide a faster and less resource-intensive sample processing workflow compared to solutions known in the art. Furthermore, the methods and systems according to certain aspects enable sample preparation procedures adaptable to a wide variety of different sample materials.

[0008] In particular, this disclosure relates to an automated method for applying a liquid sample to a substrate for image analysis. The automated method includes providing data corresponding to the characteristics of the liquid sample from a characterization unit to a workflow management unit. The automated method further includes the workflow management unit selecting a sample preparation operation based on the characteristics of the liquid sample. The automated method further includes the workflow management unit setting operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample. The automated method further includes controlling the sample preparation unit to prepare the liquid sample by performing the sample preparation operation selected by the workflow management unit and using the operating parameters set by the workflow management unit, wherein the selected sample preparation operation includes at least: applying the liquid sample to the substrate by controlling the applicator to translate relative to the substrate while applying the liquid sample via an applicator, causing particles in the liquid sample to settle onto the substrate.

[0009] As used herein, the term "liquid sample" is a broad term and can refer to any liquid material that can undergo diagnostic procedures, such as in vitro diagnostic (IVD) analysis, to determine its physical, chemical, physiological, or immunological properties, or to detect one or more target analytes suspected of being present therein, such as peptides (e.g., antigens, antibodies), nucleic acids, electrolytes, cells, cell surface proteins, coagulation factors, etc. The term can refer to biological samples, quality control solutions, calibrator solutions, reference solutions, or mixtures of one or more biological samples with one or more reagents and / or diluents, or mixtures of quality control solutions or calibrator solutions with one or more reagents and / or diluents. Liquid samples can be derived from any biological source, such as physiological fluids, including blood, cerebrospinal fluid (CSF), urine, synovial fluid, peritoneal fluid, pleural fluid, tissue, bone marrow, etc. Liquid samples can be used directly from the source or after pretreatment to alter the characteristics of the sample (e.g., preparing plasma from blood, diluting viscous fluids, lysis, etc.). Processing methods can involve filtration, distillation, concentration, centrifugation, inactivation of interfering components, and addition of reagents. Initially solid or semi-solid biological materials (e.g., tissues) can be made into liquids by dissolving or suspending them in a suitable liquid medium. According to certain aspects of this disclosure, the liquid sample can be a blood sample, such as whole blood, plasma, or serum. Alternatively, and according to further aspects of this disclosure, the liquid sample can be a body fluid sample, such as cerebrospinal fluid, synovial fluid, pleural fluid, ascites, or bone marrow aspirate.

[0010] As used herein, the term "reagent" can be any kind of liquid solution containing reactants, typically chemical compounds or agents capable of binding to or chemically transforming one or more suspected structures of a sample component or analyte in a liquid sample. Together with the corresponding detection method, the reagent enables the detection of these structures or analytes. Examples of reactants include enzymes, enzyme substrates, dyes, conjugated dyes, protein-binding molecules, nucleic acid-binding molecules, antibodies, chelating agents, promoters, inhibitors, epitopes, antigens, etc. In particular, reagents may include dyes or mixtures of dyes, wherein dye mixtures are also commonly referred to as staining agents.

[0011] As used herein, the term "dye" can refer to a detectable portion of cellular structures in a liquid sample suitable for staining, for example, bright-field microscopy or fluorescence microscopy. Examples of dyes include chromogenic dyes, metallographic dyes, chromophore-containing dyes, fluorescent dyes, phosphorescent dyes, and nanomaterials (such as quantum dots). The term "staining agent" can refer to a solution containing multiple dyes. A well-known example is the Romanowski type staining agent, a metachromatic staining agent that can be used to stain cytological samples, wherein the staining agent contains cationic thiazide dyes (such as polychromatic methylene blue, azure A, azure B, azure C, azure IV, p-dimethylthionine, thionine, methylene violet burnsin, methyl thionine, toluidine blue, and combinations thereof) and anionic halofluorescein dyes (such as eosin A, eosin Y, eosin G, and combinations thereof). Other examples include Malachowski stain, Giemsa stain, May-Gruenwald stain, May-Gruenwald-Giemsa (MGG) stain, Jenner stain, Wright stain, Leishman stain, and DIFF-QUICK (a proprietary modified Wright stain).

[0012] As used herein, the term "substrate" can refer to any type of support material that has the property of allowing a liquid sample to be applied thereon and allowing the liquid sample to be imaged and / or analyzed, for example, by means of a microscope. Typically, a substrate has a flat receiving surface on which a liquid sample can be applied. Substrates can include, but are not limited to, glass or plastic microscope slides, polished or mirrored ceramic slides, polished metal substrates, plastic or other flexible sample films, and / or any other reflective material capable of supporting the sample. Substrates can be plates exhibiting rectangular or circular form.

[0013] As used herein with respect to liquid samples, the term "characteristics" can refer to any physical, chemical, physiological, or immunological feature of a liquid sample. Examples include sample type, the number and / or type of particles in the sample, sample viscosity, sample density, sample color, turbidity, pH, etc., one or more of which can be determined by a dedicated functional unit, namely, a characteristic measurement unit. In particular, and according to one aspect of this disclosure, the characteristics of a liquid sample include any or a combination of liquid sample type, hematocrit, hematocrit range, sample viscosity, sample density, or particle count. Examples of possible sample types have been mentioned above.

[0014] As used herein, the term "hematocrit" can refer to the volume percentage (vol%) of red blood cells (RBCs) in blood. Various methods exist for determining hematocrit, some of which are performed by fully automated devices. Most automated methods are indirect methods, where hematocrit is derived from other measured parameters, i.e., calculated. For example, when applying a measurement method using the Coulter principle, the number of RBCs in a known volume of blood sample and the mean cell volume of the RBCs are determined. The RBC count is then multiplied by the mean cell volume and correlated with the known sample volume to obtain the hematocrit as a volume percentage. Alternative methods include estimating hematocrit by calculating using the measured amount of hemoglobin. As used herein, the term "hematocrit range" can refer to a predetermined range of hematocrit levels. For example, a hematocrit range can correspond to a well-known reference range defined for use in laboratory diagnostics. One or more hematocrit ranges can be defined. For example, a "normal" hematocrit range can include all hematocrit levels considered "normal" in a medical context, such as between 35% and 51%. A “low” hematocrit range can be defined, including hematocrit levels below 35%, and a “high” hematocrit range can be defined, including hematocrit levels above 51%. Hematocrit ranges can be determined based on the patient's sex; for example, the “normal range” for women can be between 36% and 45%, and for men, it can be between 40% and 51%. Further ranges can be determined using higher resolution. Hematocrit ranges can be determined and implemented by the manufacturer or by the operator.

[0015] As used herein, the term "sample viscosity" generally refers to a measure of a liquid sample's resistance to deformation at a given rate. It quantifies the internal friction between adjacent fluid layers in relative motion. Various factors can affect the viscosity of a liquid sample. One example is sample temperature. Another example is the amount of components contained in the liquid sample. For example, blood samples contain components such as cells (e.g., RBCs, white blood cells (WBCs), platelets) or molecules (e.g., proteins, electrolytes, carbohydrates, fatty acids). Of these components, RBCs have the greatest impact on the viscosity of blood samples. For example, the relative viscosity of blood can be four times that of water. In bone marrow aspirates, viscosity may be affected by, for example, the amount of hematopoietic cells, adipose tissue (adipocytes), and supporting stromal cells present. In yet another example, cerebrospinal fluid samples may contain small amounts of WBCs, carbohydrates, electrolytes, and proteins, affecting the sample's viscosity. The viscosity of a liquid sample can be measured, for example, by a viscometer or rheometer.

[0016] The term "sample density" can refer to the mass per unit volume of a liquid sample, similar to how sample viscosity can be affected by the composition of the liquid sample. For example, according to... Kenner, T. "The measurement of blood density and its meaning." Basic research in cardiology Volume 84, 2 (1989): 111-24. Blood density is proportional to hematocrit or total protein concentration in the blood.

[0017] The term "particle count" refers to the number of particles of a given type in a liquid sample. Typically, the reported number of particles is related to a defined volume of the liquid sample. Therefore, the term "particle" can refer to any kind of particle in a liquid sample or a component of the liquid sample. Particles in a blood sample can be any component smaller than 50 µm, less than 30 µm according to one example, or less than 20 µm according to another example, such as cellular components (e.g., RBCs, WBCs, platelets, bacteria, parasitic protozoa, etc.) or other structures (e.g., artifacts). In a clinical setting, the number of RBCs and / or WBCs can be determined in a predetermined volume of, for example, a patient's blood or urine sample to detect potential irregularities indicating an underlying medical condition. In another example, a cerebrospinal fluid sample can be analyzed by counting the number of WBCs it contains, where an elevated WBC count can, for example, indicate inflammation or infection of the brain or spinal cord. Particle counts can be determined using conventional methods based on the Coulter principle (e.g., impedance-based flow cytometry) or (digital) microscopy.

[0018] As used herein, "unit" can refer to a functional entity specifically designed to perform a particular set of operations, typically as part of a workflow. Therefore, the unit is constructed and configured in a way that optimally performs such operations. It can operate autonomously as a standalone device, collaboratively with other units, or as a sub-unit / module of a more complex device. Thus, in the IVD field, a unit can refer to a standalone IVD analyzer that can connect to or collaborate with one or more other IVD analyzers, or it can refer to a part or module within an IVD analyzer or IVD system. For example, a unit can be a conveyor for transferring sample containers within or between diagnostic devices. It can be a gripper, centrifuge, pipetting unit, incubation unit, analysis (measurement) unit, imaging unit, results display unit, etc.

[0019] As used herein, the term "characteristic measurement unit" is a broad term and can refer to any kind of device, module, or functional unit configured to automatically measure the characteristics or multiple characteristics of a liquid sample. A characteristic measurement unit can be designed as a standalone device that is communicatively connected to other devices via a network (e.g., via an intranet or the Internet). Alternatively and preferably, a characteristic measurement unit can be a module or functional unit forming a cluster of functional units within a larger device (e.g., an IVD device) and can be communicatively connected to other functional units within that larger device. A characteristic measurement unit can be configured to measure the characteristics of a liquid sample using some measurement method. According to certain aspects of this disclosure, providing data corresponding to the characteristics of a liquid sample includes controlling the characteristic measurement unit to measure the characteristics of the liquid sample by impedance measurement, or conductivity measurement, or resistance measurement, or electrochemical measurement, or optical measurement, or pressure measurement, or viscosity measurement, or any combination thereof. For example, a characteristic measurement unit can be an impedance-based flow cytometer that uses the Coulter principle to measure certain characteristics of the liquid sample. The Coulter principle is well known in the art and will therefore not be described in further detail. In another example, the characterization unit can be a blood gas analyzer capable of performing conductivity or electrochemical measurements to determine the properties of a liquid sample. Conductivity is the ability of a solution to transmit (conduct) electrical current. The current will increase proportionally to the number of ions (or charged particles) found in the solution, their charge, and their mobility (i.e., how easily ions can move in the solution). In electrochemical measurements, a chemical reaction is converted into an electrical signal, which can then be measured. In another example, the characterization unit can be a photometer or spectrophotometer that measures the transmission or absorption of light (potentially of different wavelengths) through a liquid sample. According to one aspect of this disclosure, optical measurements are light scattering measurements (e.g., in a flow cell) or interferometry measurements. For example, the characterization unit can be a laser-based flow cytometer that measures forward scattered light (FSC) signals, side scattered light (SSC) signals, and / or dye-specific fluorescence signals. Alternatively, the flow cytometer can be based on laser interferometry, as described, for example, below: Zhao, Y. et al., Self-Mixing Interferometry- Based Micro Flow Cytometry System for Label-Free Cells Classification. Appl. Sci. 2020, 10, 478. https: / / doi.org / 10.3390 / app10020478In yet another example, the characteristic measurement unit may be a viscometer or a rheometer. Typical viscometers used in the art are capillary viscometers or rotational viscometers. Another technique for determining the viscosity of a liquid is by measuring the rate at which a magnetic ball moves back and forth within the liquid sample by a magnetic field. In another example, and according to one aspect of this disclosure, pressure measurement includes controlling a pipette probe to aspirate a portion of a liquid sample from a sample container. While aspirating the liquid sample, the method includes measuring the pressure inside the pipette probe via a pressure sensor operatively coupled to the pipette probe. The method further includes correlating the measured pressure with a hematocrit range and storing the measured pressure and the associated hematocrit range as characteristics of the liquid sample in a data storage device. Examples of hematocrit ranges to which the measured pressure may be associated are described below. Alternatively, and according to another aspect of this disclosure, the method may include correlating the measured pressure with any one of a sample viscosity range, a sample density range, or a particle count range. The method may further include storing the measured pressure and the associated viscosity range, sample density range, or particle count range as characteristics of the liquid sample in a data storage device, respectively. Examples of corresponding ranges to which the measured pressure may be associated are described below.

[0020] As used herein, the term "pipette probe" is a broad term and can refer to a functional unit configured to perform pipetting operations. For example, a pipetting probe can be configured to aspirate a liquid sample or a predetermined portion thereof from a sample container. Typically, a pipetting probe includes a tubular segment having an internal channel in at least one opening at or near the tip of the probe and at least one other opening at the opposite end of the tubular segment. The pipetting probe further includes a pump fluidly connected to the tubular segment and allowing negative pressure to be generated within the internal channel to aspirate liquid into the internal channel. Additionally or alternatively, the pump allows positive pressure to be generated within the channel to dispense any present liquid from the internal channel. The tubular segment may be at least partially tapered, for example at the tip. The tubular segment of the pipetting probe may be designed as a hollow needle with a sharpened tip to facilitate aspiration of a liquid sample from a closed sample container. The tubular segment of the pipetting probe can be operated with a reusable tip that requires periodic cleaning to prevent cross-contamination. Alternatively, it can be operated using single-use tips, which are interchangeable between pipetting operations of different liquid samples.

[0021] As used herein, the term "pressure sensor" can refer to any type of sensor configured to measure pressure within a vessel or compartment. According to one aspect of this disclosure, a pressure sensor is operatively connected to a pipette probe, enabling the measurement of pressure within the pipette probe. Pressure measurements can be performed during aspiration of a liquid sample into the pipette probe and / or during the dispensing of the liquid sample. Therefore, pressure measurements can be performed and recorded as continuous measurements over time, e.g., from the start to the end of the aspiration operation, thus producing a pressure profile. Alternatively, it can be performed and recorded once or multiple times at predetermined time intervals during the aspiration operation. For example, pressure can be measured at the start of the aspiration operation and again at the end of the aspiration operation. Alternatively, pressure can be measured at time intervals in any range between 0.05 seconds and 1 second. For example, pressure measurements can be performed and recorded every 0.1 seconds, every 0.2 seconds, or every 0.5 seconds. Various types of pressure sensing technologies are known in the art. Pressure sensors can be resistive sensors, capacitive sensors, piezoelectric sensors, MEMS (microelectromechanical systems) based sensors, etc. The recorded pressure curve or pressure measurement result can be compared with a reference curve or reference value. Depending on the deviation of the recorded pressure curve or pressure measurement result from the reference curve or reference value, calculations can be performed regarding certain properties of the liquid sample, such as the viscosity, density, or hematocrit of the liquid sample. In this way, and according to one aspect of this disclosure, the measured pressure can be correlated with hematocrit or a range of hematocrit values. For example, when aspirating a liquid sample from a closed sample container, a negative pressure is generated inside the pipette probe to draw the liquid sample into the pipette probe. If the liquid sample has a high hematocrit and therefore a high viscosity compared to a liquid sample with a normal hematocrit, it is necessary to further reduce the negative pressure to aspirate the same volume of liquid sample within the same time period. Pressure measurements inside the pipette probe can detect such changes in negative pressure.

[0022] Measurement data generated by the characterization unit is typically stored electronically, such as in a data storage device. As used herein, the term "data storage device" refers to any kind of storage medium configured to digitally store data or information, such as computer memory, network storage, or cloud storage. Therefore, the characterization unit may include a data storage device, or it may be communicatively connected to a remote data storage device, such as a computer network or the cloud. Data "corresponding to the characteristics of the liquid sample" may include any raw and / or processed data that reflects the characteristics of the liquid sample in any way, examples of which have been described above. Data processing may include conversion steps. For example, depending on the measurement method, measurement parameters may be converted from analog signals to digital signals, such as by an analog-to-digital converter (ADC), before the data can be processed and / or stored. In another example, data may be processed by converting the measured values ​​to other units, such as from g / L to mg / dL. In yet another example, data may be processed by stratification, such as by correlating or grouping one or a set of measurements into predefined categories. Examples of predefined categories include hematocrit ranges, such as: a "normal" hematocrit range, which may include all hematocrit measurements between 35% and 51%; or a "high" hematocrit range, which includes hematocrit levels above 51%, etc. (see also more examples above). As mentioned above, the characterization unit may be communicatively connected to other devices or functional units (e.g., workflow management units) via wired or wireless direct connections or indirectly through communication networks to enable data transmission or exchange, or via transmission or exchange through other data management units (such as computers). Communication means and protocols for transferring data between two or more digital entities are well known in the art and will therefore not be further described herein.

[0023] As used herein, the term "workflow management unit" is a broad term and can refer to a hardware and / or software implementation system configured to manage the workflow of one or more functional units, such as those operating within an IVD device or across multiple IVD devices. A workflow may include a series of operational steps that may require synchronization across different functional units. The workflow management unit may include a programmable logic controller or processor running a computer-readable program equipped with instructions to perform the operational steps according to the methods described herein. The workflow management unit may be integrated into an IVD device; it may be integrated into a unit, subunit, or module of the IVD device, or it may be a separate logical entity that communicates with the IVD device or its units, subunits, or modules via a wired or wireless direct connection or indirectly via a network interface device, either wired or wirelessly, through a communication network such as a wide area network (e.g., the Internet) or a healthcare provider's local area network or intranet. In some respects, the workflow management unit can be integrated with the controller or data management unit, for example, implemented on a computing device (such as a desktop computer, laptop, smartphone, tablet, personal digital assistant (PDA), etc.), or it can be included in a server computer and / or distributed / shared across / among multiple IVD devices. For example, the workflow management unit can be configured to determine processing orders for a batch of liquid samples based on its corresponding test orders. In another example, the workflow management unit can instruct functional units (such as conveyors) to transport sample containers containing liquid samples to a specific location within the IVD device and instruct second functional units (such as pipette probes) to aspirate the liquid sample or a portion thereof from the sample container. Therefore, the workflow management unit can synchronize the operational steps performed by the conveyor with those performed by the pipette probe to achieve workflow efficiency and prevent certain risks, such as collisions between the pipette probe and the sample container.

[0024] According to this disclosure, the workflow management unit selects sample preparation operations based on the characteristics of the liquid sample. As used herein, the term "sample preparation operation" can refer to any kind of operational step performed to prepare a liquid sample for subsequent analytical evaluation or diagnostic testing. Examples of sample preparation operations include diluting the liquid sample, concentrating the liquid sample, mixing, dispersing, aliquoting, transferring (e.g., from a sample container to a reaction vessel or from a sample container to a substrate), staining the liquid sample, etc. For the processing of each liquid sample, the workflow management unit typically selects a series of sample preparation operations, wherein the selected sample preparation operations may depend at least in part on the characteristics of the liquid sample. In particular, sample preparation operations may be selected based on whether data or data points corresponding to the characteristics of the liquid sample fall within a predetermined range, are above or below a predetermined threshold, or correspond to a predetermined category or reference value. For example, if the liquid sample's characteristic is an abnormally high hematocrit level (which can be defined as being above a predetermined upper threshold (e.g., above 55%) or falling within a predetermined range (e.g., between 55% and 60%)), the workflow management unit can select the following sample preparation operations: diluting the liquid sample, applying the diluted liquid sample to a substrate, staining the diluted liquid sample, and fixing the diluted liquid sample. Alternatively, if the characteristic corresponding to the liquid sample is high sample viscosity, sample density, or particle count, the same sample preparation operations can be selected. In another example, if the liquid sample's particle count is low (which can be defined as the particle count being below a predetermined lower threshold or falling within a predetermined range), for example, if the red blood cell count is less than 3.5 cells per pL or if the red blood cell count is between 2.5 and 3.5 cells per pL, the workflow management unit can select the following sample preparation operations: concentrating (e.g., by centrifuging the liquid sample and removing the supernatant) the liquid sample, applying the concentrated liquid sample to a substrate, staining the concentrated liquid sample, and fixing the concentrated liquid sample. According to alternatives, if the characteristics corresponding to the liquid sample refer to low hematocrit, hematocrit range, sample viscosity, or sample density, the same sample preparation operation can be selected. In another example, if the characteristics of the liquid sample are hematocrit, sample viscosity, sample density, or particle count within the normal range, the workflow management unit can select sample preparation operations for applying the liquid sample to the substrate and for staining and / or fixing the liquid sample on the substrate. The selected sample preparation operation is then transmitted as an instruction from the workflow management unit to the sample preparation unit for the selection of the sample preparation operation.

[0025] According to this disclosure, the workflow management unit sets operating parameters based on the selected sample preparation operation and / or the characteristics of the liquid sample. As used herein, the term "operating parameter" can refer to any kind of operating parameter used to perform any operational step, particularly a sample preparation operation. The operating parameters set by the workflow management unit can be transmitted as instructions to the sample preparation unit, which uses these operating parameters to perform the sample preparation operation. Examples of operating parameters include the centrifuge rotation speed and / or centrifugation time, the volume of diluent to be pipetted to the liquid sample, the distance between the applicator and the substrate, the type and / or volume of the staining agent to be used for staining, etc. In devices known in the art, operating parameters can be fixed, i.e., they can be predetermined by the manufacturer and therefore not adjustable during operation of the device. In other devices, operating parameters can be manually set by the device operator. However, the operating parameters according to this disclosure are automatically and dynamically adjustable based on variable factors, such as the characteristics of the liquid sample. The characteristics of liquid samples (examples of which are outlined in more detail above) have a significant impact on the uniformity of liquid sample distribution on the substrate, so it is advantageous to be able to flexibly select and adjust sample preparation operations and corresponding operating parameters.

[0026] According to aspects of this disclosure, the operating parameters include at least one parameter selected from the group consisting of: the distance between the applicator and the substrate, and / or the movement pattern of the applicator relative to the substrate, and / or the speed pattern of the applicator relative to the substrate, and / or the liquid sample dispensing volume (which is a portion of the aspirated liquid sample), and / or the dispensing rate, and / or the distance between rows of liquid samples on the substrate.

[0027] As used herein, the term "distance between applicator and substrate" refers to the distance between the tip of the applicator and the substrate during the liquid sample dispensing procedure, and influences the uniformity of liquid sample distribution on the substrate due to capillary forces within the sample adjacent to the sample dispensed from the applicator. Therefore, the sample preparation unit is configured to adjust the distance between the applicator and the substrate. For example, if the substrate is placed in the sample preparation unit with a horizontal orientation, the applicator can be moved vertically relative to the substrate, for example, by a stepper motor or pneumatic actuator. Depending on the characteristics of the liquid sample, the distance between the applicator and the substrate can be determined to be in the range of 8 to 20 µm (e.g., 10, 12, 14, 16, or 18 µm). For example, if the liquid sample has a high hematocrit (e.g., a hematocrit greater than 52%) or alternatively has high sample viscosity, high sample density, or high particle count, the workflow management unit can determine the distance between the applicator and the substrate to be a value in the range of 8 to 12 µm (e.g., 10 µm) to ensure uniform particle deposition onto the substrate. In another example, if the liquid sample is measured to have a low viscosity (e.g., less than 3 centipoise (cP)) or alternatively a low hematocrit, low sample density, or low particle count, the workflow management unit can determine the distance between the applicator and the substrate to be a value in the range of 16 to 20 μm (e.g., 18 μm) to allow for the application of a larger volume of liquid sample to the substrate. Once the distance between the applicator and the substrate is determined, the distance remains nearly constant throughout the liquid sample application procedure, for example, varying by no more than 2 µm.

[0028] As used herein, the term "movement pattern" refers to the direction of movement of the applicator relative to the substrate over a period of time (e.g., during the application of a liquid sample). Those skilled in the art will recognize that the movement pattern thus also determines the sedimentation pattern of the liquid sample and, consequently, any particles included therein, on the substrate. According to one aspect of this disclosure, the method includes controlling the translational movement of the substrate and / or the applicator relative to each other. Thus, the applicator may be movably coupled to rails that enable translational movement of the applicator relative to the substrate in the xy Cartesian plane, while the substrate remains in a fixed position. Alternatively, the applicator may be mounted in a fixed position, and the substrate may be movable relative to the applicator in the xy Cartesian plane. In another alternative, both the applicator and the substrate may be movable relative to each other in the xy Cartesian plane. The movement pattern is selected such that the sample particles are distributed as uniformly as possible on the substrate. For example, the liquid sample may be applied to the substrate in a linear alignment, forming a row. It may be applied in multiple rows close to each other. Multiple rows close to each other can be formed in a single consecutive application step, for example, to form a boustrophedon pattern. Therefore, the applicator can be positioned, for example, at the lower left corner of the application area on the substrate. As the liquid sample is applied through the tip of the applicator, the applicator moves in the x-direction to the lower right corner of the application area on the substrate to create a first row. From here, while still applying the liquid sample, the applicator moves a predetermined distance in the y-direction, i.e., creating a distance between rows, and then moves back in the negative x-direction to the left side of the application area on the substrate to create a second row adjacent to the first row. The applicator again moves in the y-direction by the same distance as before, and moves in the x-direction to the right side of the application area on the substrate to create a third row adjacent to the second row. This procedure can be continued until the entire application area is covered by the liquid sample or until a predetermined volume of liquid sample has been applied, thus creating a zigzag application pattern. In another example, the liquid sample can be applied in a concentric circle or a spiral pattern.

[0029] As used herein, the term "distance between lines" refers to a parameter that determines how far apart the lines are when a movement pattern contains multiple lines. In the example described above, the distance between lines is determined by a parameter for movement along the y-direction, and this distance can be in the range of 10 to 1000 µm, for example, in the range of 30 to 800 µm, or, according to another example, in the range of 50 to 500 µm.

[0030] As used herein, the term "liquid sample preparation volume" refers to the volume of liquid sample to be prepared and applied to the substrate (particularly to the dispensing region on the substrate). Typically, a liquid sample is provided in a sample container, from which only a portion or aliquot of the liquid sample is required for further processing. According to one aspect of this method, the liquid sample preparation volume is determined to be a value between 0.1 and 10 µL. According to another aspect, the liquid sample preparation volume is determined to be a value between 0.3 and 8 µL. According to yet another aspect, the liquid sample preparation volume is determined to be a value between 0.5 and 1.5 µL. According to yet another aspect, the liquid sample preparation volume is determined to be approximately 1 µL.

[0031] As used herein, the term "velocity mode" refers to the rate of the applicator relative to the substrate and its adjustment during the application of a liquid sample. The rate may remain constant or it may vary during the application process. For example, and relative to the ox-plowing path movement mode mentioned above, the applicator may move relative to the substrate in the x-direction at a certain rate. As it approaches either side of the application area on the substrate, the rate of the applicator relative to the substrate may be continuously reduced to ensure a smooth transition from movement in the x-direction to movement in the y-direction, thereby preventing potential splashing of the liquid sample (which could occur in the event of a sudden stop in applicator movement). Therefore, the velocity mode may include variables such as the rate of the applicator relative to the substrate in the x-direction, the rate of the applicator relative to the substrate in the y-direction, and the deceleration and / or acceleration rates.

[0032] As used herein, the term "dispensing rate" refers to the volume of liquid sample dispensed from the tip of the applicator per unit time. The dispensing rate can be determined in relation to the velocity or velocity pattern of the applicator relative to the substrate. For example, the dispensing rate can be determined to be 0.1 µL per second while the applicator tip moves over the substrate at a velocity of 30 mm per second. According to one aspect of this method, the dispensing rate can be set to a value between 0.01 µL / s and 1 µL / s, particularly between 0.03 µL / s and 0.8 µL / s, and more particularly between 0.05 µL / s and 0.5 µL / s.

[0033] As used in this disclosure, "sample preparation unit" is a broad term and can refer to any kind of device, module, or functional unit configured to automatically prepare liquid samples for subsequent analytical evaluation or diagnostic testing. The sample preparation unit may be designed as a standalone device that may be operationally and / or communicatively connected to other devices. Alternatively, the term may include multiple standalone devices that are operationally and communicatively connected to each other and possibly to other devices (e.g., analytical devices). Alternatively and preferably, the sample preparation unit may be included in an IVD device, wherein the sample preparation unit may include one or more modules or functional units. The sample preparation unit may be configured to perform any kind of sample preparation operation or combination of sample preparation operations. According to this disclosure, the sample preparation unit prepares a liquid sample by performing a sample preparation operation selected by a workflow management unit and by using operating parameters set by the workflow management unit, wherein the sample preparation operation includes: applying the liquid sample to the substrate by controlling the translational movement of the applicator relative to the substrate when the liquid sample is applied to the substrate via an applicator, such that particles in the liquid sample settle onto the substrate; staining the liquid sample on the substrate; and / or fixing the liquid sample on the substrate. Therefore, the sample preparation unit includes an applicator for dispensing a liquid sample onto a substrate. The applicator can be a hollow needle-shaped or syringe-shaped element with an opening at its tip. The applicator can be operatively connected to a pump, such as a peristaltic pump or syringe pump, which allows small volumes of liquid sample to be dispensed onto the substrate through the tip of the applicator. According to one aspect of this disclosure, the tip can have an outer diameter of 2 to 5 mm and an inner diameter of about 0.5 mm. According to another aspect, the tip can have an outer diameter of 0.5 to 1.5 mm and an inner diameter of 0.1 to 0.45 mm. The tip can be disposable or washable. The tip can be rounded to facilitate insertion and cleaning. Translation of the applicator relative to the substrate can refer to translating the applicator relative to the substrate, translating the substrate relative to the applicator, or translating both the applicator and the substrate relative to each other. The sample preparation unit may further include a staining unit for staining the liquid sample on the substrate. The staining unit is configured to apply a staining agent or dye to a liquid sample on a substrate and may therefore include one or more applicators, which may be, for example, a peristaltic pump. Examples of compatible staining agents are Romanowski stain, reticular cell stain, staining agents using specific antibodies, hematoxylin and eosin, immunocytochemical staining agents, histochemical staining agents for viewing cellular components, and / or staining agents based on antibodies, aptamers, or other staining agents that bind ligands to antigens (further examples of staining agents mentioned above). The staining agent may be mixed with a diluent before being applied to the substrate. For example, a diluent that can be used to dilute whole blood may include a saline solution or a protein solution.The range of salt solutions extends from "physiological saline" (0.9N) to complex salt mixtures. The range of protein solutions extends from simple bovine albumin solutions to commercial formulations containing selected human plasma proteins. Alternatively or additionally, the sample preparation unit may include a fixation unit for fixing liquid samples on a substrate. Fixing liquid samples may include exposing the liquid sample on the substrate to a fixative (e.g., 85% methanol) and / or to a buffer solution. For some staining agents, ethanol- or formaldehyde-based fixatives may be used. Therefore, the fixation unit may include an applicator for dispensing the appropriate fixative to the liquid sample. Examples of staining and fixation units are disclosed in US 8,454,908. Alternatively, the substrate carrying the liquid sample may be immersed in one or more baths of staining and fixation solutions. In another alternative, capillary action may be used to move the staining and / or fixation solutions across the substrate.

[0034] According to one aspect of this disclosure, the automated method further includes: controlling an imaging unit to generate a digital microscope image of one or more particles on a substrate; analyzing the one or more particles in the digital microscope image to generate an analysis result for a liquid sample; and displaying data and / or analysis results corresponding to the characteristics of the liquid sample on a display device.

[0035] As used herein, the term "imaging unit" refers to any kind of device, module, or functional unit configured to generate digital microscopic images of one or more particles on a substrate. An imaging unit may be designed as a standalone device that can be operationally and / or communicatively connected to other devices, such as via an intranet or the Internet. Alternatively and preferably, an imaging unit may be a module or functional unit within a cluster of functional units forming a larger device (e.g., an IVD device) and may be operatively and communicatively connected to other functional units within that larger device. To generate digital microscopic images, an imaging unit may include a light emitting device, a microscope, and a light receiving device. The light emitting device, as mentioned herein, can be any kind of device configured to emit light within any of the visible, infrared, or ultraviolet spectral ranges to illuminate a liquid sample on a substrate. The light emitting device may be configured to emit light having a single wavelength or may be configured to simultaneously emit light with different wavelengths. The light emitting device may, for example, include a white light source or other multispectral light sources, such as halogen bulbs, fluorescent bulbs, or incandescent bulbs. The light emitting device may further include, for example, a filter in the form of a filter wheel, to filter multispectral light into a single wavelength or a narrowband wavelength. Alternatively or additionally, the light emitting device may include one or more lasers or light-emitting diodes (LEDs). Lasers and LEDs typically produce narrow-band illumination. The advantage of using narrowband illumination instead of broadband illumination is that it increases the sharpness of the image generated by the light receiving device. The microscope, as mentioned herein, can be any kind of device including at least one optical element configured to receive light generated by a liquid sample on a substrate in response to illumination and / or to receive light transmitted through the liquid sample on the substrate, and to focus the incident light rays to produce an image. The microscope may include at least one lens, such as at least one imaging lens and / or at least one objective lens. The microscope may include multiple lenses, such as a lens system. The microscope may be configured, for example, in conjunction with a lens system, to project an image of a liquid sample on a substrate or a magnified image of a region of a liquid sample on a substrate onto a light receiving device. The magnification of the microscope may be in the range of 4x to 100x. For example, the magnification may be 10x, or 20x, or 50x. Microscopes may include at least one zoom lens and / or at least one zoom lens system. Examples of microscopes include bright-field microscopes, fluorescence microscopes, phase-contrast microscopes, spectroscopic microscopes, dark-field microscopes, Fourier transform imaging microscopes, etc. As used herein, a light-receiving device can be any kind of device configured to receive light to record or capture optical data or information and to convert said optical data or information to form a digital image. Therefore, a light-receiving device may include a camera that includes an image sensor. As an example, the image sensor may be a CCD chip and / or a CMOS chip.The resulting digital microscope images of one or more particles on the substrate can then be stored in a data storage device.

[0036] Digital microscope images can be transmitted to or accessed by a functional unit (e.g., an image processor) configured to analyze one or more particles in the digital microscope image to generate analytical results for a liquid sample. Therefore, as used herein, the term "analysis" can include identifying (i.e., in the sense of localization) one or more target particles within a digital microscope image, possibly determining the localization of particles in the digital microscope image or the coordinates of their localization on a substrate, and identifying the type of one or more particles, for example, based on certain characteristics of the particles displayed in the digital microscope image. To perform such analysis in an automated manner, appropriate computer-readable instructions, such as image analysis algorithms, are provided to a controller. Examples of image analysis algorithms are described in US 7,689,038, US 7,881,532, US 2023028525A1, and WO2023118586A1. For example, in the field of hematology, the target particles can be cellular components of blood, namely RBCs, WBCs, and platelets. When executed by an image processor, one or more image analysis algorithms enable the image processor to locate RBCs, WBCs, and platelets in or from the background of a digital microscope image and to distinguish RBCs, WBCs, and platelets from other particles. They further enable the controller to identify specific cell types, namely RBCs, WBCs, or platelets, and to further differentiate cell subtypes based on certain morphological features displayed in the digital microscope image. For example, WBC subtypes may include: neutrophils, lymphocytes, atypical lymphocytes, hematopoietic progenitor cells, monocytes, and immature granulocytes; granulocytes, including basophils, eosinophils, neutrophils (such as segmented neutrophils and band neutrophils), mast cells, primitive cells, promyelocytes, metamyelocytes, leukocytes with inclusion bodies (such as Oswald rod bodies or Dürer bodies), etc. RBC subtypes can include normal red blood cells, nucleated red blood cells, polychromatic cells, reticulocytes, immature reticulocytes, schizoblasts, spherocytes, stomatoblasts, red blood cells with inclusion bodies (such as Hojo bodies, Hein bodies, and Papenheimer bodies), and red blood cells with inclusion bodies (such as Plasmodium or Babesia).

[0037] As used herein, the term "generating analytical results" refers to producing analytical results based on data or information generated by the imaging unit in an image analysis procedure. Therefore, analytical results can include one or more numerical values, any kind of descriptive information, or any kind of visual information about the target analyte in the tested liquid sample, or any combination thereof. For example, complete blood count (CBC) is one of the most frequently performed laboratory test suites in hematology. CBC analysis results typically include measurements of RBC count, WBC count, platelet count, hemoglobin concentration, hematocrit, and measurements of mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular hemoglobin (MCH), and red blood cell distribution width (RDW). In another example, white blood cell differential (another frequently performed laboratory test) analysis results can include the absolute count and relative percentage of WBC subtypes (such as neutrophils, lymphocytes, monocytes, eosinophils, and basophils). In another example, the analysis results may include a digital microscope image generated by an imaging unit and possibly processed by an imaging algorithm to make certain features in the digital microscope image visible to a human observer. In yet another example, the analysis results may include a measure of fluorescence emitted by an analyte in the liquid sample, such as color and / or intensity. Other examples of analysis results are the number and / or relative percentage of nucleated red blood cells (NRBCs), mean platelet volume (MPV), the number and / or relative percentage of reticulocytes, or the mean reticulocyte hemoglobin content. In many IVD devices known in the art, the analysis results are presented on a display device to healthcare professionals, such as laboratory personnel or physicians. Thus, a “display device” can be any kind of device configured to display data or information in a human-readable manner. Examples of displaying analysis results, particularly images of cells, are disclosed in US 11,047,791. According to one aspect of this disclosure, an automated method includes the method steps of displaying data and / or analysis results corresponding to the properties of a liquid sample on a display device. For example, for a given liquid sample, an analysis result for the sample viscosity and CBCs may be displayed. In another example, the analysis results of CBC generated from digital microscope images can be viewed close to the particle counts measured by the characterization unit, which includes counts for RBCs, WBCs, and platelets.

[0038] According to one aspect of this disclosure, the automated method further includes generating an output value using the analytical results and the characteristics of the liquid sample, which can allow for more accurate and reliable analytical results. The characteristics of the liquid sample and the analytical results may refer to the same parameter, such as the hematocrit of the liquid sample. In such cases, the method includes comparing a parameter measured by a characterization unit with a parameter determined by analysis of microscopic images. This allows the analytical results generated by a controller based on microscopic images to validate or verify the parameter measured by the characterization unit, and vice versa. The “output value” can be generated by a computational operation using the analytical results and the characteristics of the liquid sample. For example, the output value may result in the subtraction of the analytical results from the characteristics of the liquid sample, or vice versa, or the output value may refer to the relative difference between two values. Alternatively, the output value can be generated by comparing a value calculated using the analytical results and the characteristics of the liquid sample with a threshold or reference value. Alternatively, the output value may be a descriptive statement, such as indicating that the analytical results and the characteristics of the liquid sample are the same or sufficiently similar. In another example, the output value may indicate that the two results are significantly different and that there may be a quality problem in the sample preparation procedure. It can issue and display alarms or warning messages to inform the device operator of quality issues.

[0039] According to aspects of this disclosure, the operating parameters include dilution parameters and / or concentration parameters, and the sample preparation operation further includes diluting or concentrating the liquid sample according to the dilution parameters or concentration parameters, respectively, before applying the liquid sample to the substrate. As used herein, "dilution parameters" can refer to any kind of setting related to the sample preparation operation of diluting the liquid sample, particularly an adjustable setting. A typical operating step in the dilution operation may be, for example, producing aliquots of a predetermined volume of liquid sample by pipetting a predetermined volume of liquid sample into a sample vessel. Another operating step may include pipetting a predetermined volume of diluent into aliquots of the liquid sample. Yet another operating step may include mixing or vortexing the diluted liquid sample. Therefore, the dilution parameters may include any or a combination of the following: liquid sample volume, diluent volume, the ratio between the liquid sample volume and the diluent volume, the number of aliquots to be produced, a measure of mixing intensity (e.g., the operating speed of the mixer), mixing time (duration), a measure of vortexing intensity, etc. For example, dilution parameters may include a liquid sample to diluent volume ratio of 1:1, indicating that a predetermined volume of liquid sample is diluted in an equal volume of diluent. Therefore, dilution parameters may include any liquid sample to diluent volume ratio in the range of 1:0.05 to 1:20 (liquid sample: diluent). For example, dilution parameters may include a volume ratio between 1:0.1 and 1:10, or it may include a volume ratio between 1:0.5 and 1:8. According to the method steps of this disclosure described in further detail above, operating parameters are set by the workflow management unit based on the selected sample preparation operation and / or based on the characteristics of the liquid sample. For example, if the characteristics of the liquid sample refer to a highly elevated hematocrit level, such as above a predetermined threshold, the workflow management unit may select a sample preparation operation that includes diluting the liquid sample. The workflow management unit then sets operating parameters, wherein the operating parameters include the dilution parameters. Since the liquid sample is characterized by a highly elevated hematocrit level, the workflow management unit can set dilution parameters in a manner that achieves high dilution, for example, including a volume ratio of 1:5 (liquid sample: diluent), and may also include a high mixing intensity for mixing the diluted liquid sample. In another example, where the liquid sample is characterized by a moderately elevated hematocrit level (e.g., between a predetermined lower and upper threshold), the workflow management unit can set dilution parameters in a manner that achieves lower dilution than in the previous example, for example, including a volume ratio of 1:1 (liquid sample: diluent), and may include a low mixing intensity for mixing the diluted liquid sample.

[0040] As used herein, “concentration parameters” can refer to any kind of setting, particularly adjustable settings, related to the sample preparation operation of concentrating liquid samples. In the context of this disclosure, “concentration” refers to the process of bringing a target analyte or particle present in solution at a certain concentration to a higher concentration (e.g., by removing the liquid portion of the solution that does not contain the target analyte or particles). Typical steps in a concentration operation may include, for example, producing aliquots of a predetermined volume of liquid sample by pipetting a predetermined volume of liquid sample into a sample vessel. Another step may include rotating or centrifuging the sample vessel containing the liquid sample so that the target particles settle to the bottom of the sample vessel. Yet another step may include, for example, removing the supernatant using an automated pipette. Yet another step may include mixing the concentrated liquid sample. Therefore, concentration parameters may include any or a combination of the following: the volume of liquid sample used to produce aliquots, preferably in the range of 1 µL to 1000 µL; the number of aliquots to be produced; the rotational speed of the centrifuge or sample vessel rotator; the centrifugation time (duration); the volume of supernatant to be removed; the mixing intensity, etc. For example, if the liquid sample's characteristics refer to parameters below a predetermined threshold or within a range considered low, such as a low particle count, the workflow management unit can select a sample preparation operation that includes concentrating the liquid sample. The workflow management unit then sets operating parameters, which include concentration parameters. For example, the workflow management unit can set concentration parameters such that it includes a centrifuge rotation speed of approximately 1500 to 2000 rpm for a duration of 10 to 15 minutes, and a supernatant volume to be removed after centrifugation, for example, 500 µL. In another example, if the liquid sample's characteristics refer to moderately reduced parameters (e.g., moderately reduced hematocrit levels), the workflow management unit can set concentration parameters such that it includes a centrifuge rotation speed of approximately 1000 to 1500 rpm and a supernatant volume to be removed after centrifugation of 250 µL.

[0041] This disclosure further relates to an automated system for preparing liquid samples for image analysis according to the automated method described above. The automated system includes a sample preparation unit comprising: an applicator for dispensing a liquid sample onto a substrate; a staining unit for staining the liquid sample on the substrate; and / or a fixation unit for fixing the liquid sample on the substrate. The automated system further includes a workflow management unit configured to: receive data corresponding to the characteristics of the liquid sample from a characteristic measurement unit; select a sample preparation operation based on the characteristics of the liquid sample; set operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample; and control the sample preparation unit to prepare the liquid sample by performing the sample preparation operation selected by the workflow management unit and by using the operating parameters set by the workflow management unit, wherein the sample preparation operation includes: applying the liquid sample onto the substrate by controlling the applicator to translate relative to the substrate while dispensing the liquid sample onto the substrate via the applicator, such that particles in the liquid sample settle onto the substrate.

[0042] As used herein, the term "automated system" can refer to any kind of automated pre-analytical, analytical device, or combination thereof. The analytical device is configured to obtain analytical measurements or results from a patient's sample in vitro to provide information about the patient's health status. Analytical measurements or results can be qualitative, semi-quantitative, and / or quantitative measurements of the analyte or particle. It is designed to automatically perform a set of processing operations optimized for the corresponding type of analysis (e.g., hematological analysis, coagulation analysis, clinical chemistry, immunochemistry) and may include operations such as pipetting, incubation, delivery, mixing, heating, cooling, measurement, detection, cleaning, etc. The automated system can be or may include an IVD device. The pre-analytical device is configured to prepare liquid samples or sample containers holding liquid samples in such a way that they can subsequently be processed by the analytical device. This may include processing steps such as loading / unloading of sample containers and / or consumables, opening caps, preliminary verification of sample quality, fill level verification, pipetting, aliquoting, centrifugation, dilution, labeling, sorting, incubation, etc. Automated systems can operate as standalone devices or in conjunction with one or more other devices (such as IVD devices). Automated systems typically comprise multiple functional units, each dedicated to a specific task, that work together to automate sample handling and analysis. These functional units can include pipetting units, pumps, valves, transfer devices, clamps, incubation units, analytical measurement units, temperature control units, controllers, and so on.

[0043] According to one aspect of this disclosure, the automated system further includes: an imaging unit configured to generate digital microscopic images of one or more particles on a substrate; a display device; and an image processor configured to analyze one or more particles in the digital microscopic images to generate analytical results for a liquid sample, wherein a workflow management unit controls the automated system to display the properties and / or analytical results of the liquid sample on the display device.

[0044] As used herein, the term "image processor" can refer to a programmable logic controller or processor running a computer-readable program equipped with instructions for operating according to an operational plan. The term can refer to a central processing unit, microprocessor, microcontroller, reduced instruction set circuit (RISC), application-specific integrated circuit (ASIC), logic circuit, and any other circuit or processor capable of performing the functions / methods described herein. Regardless of the type of processor, it is configured to perform one or more of the methods described herein. The image processor can be integrated into a unit, subunit, or module of an automation system that communicates with other units, subunits, or modules of the automation system via a direct wired or wireless connection or indirectly through a wired or wireless communication network. In some aspects, the controller can be integrated with a data management unit, for example, implemented on a computing device (such as a desktop computer, laptop, smartphone, tablet, PDA, etc.), or it can be included in a server computer and / or distributed / shared across / among multiple automation systems. Furthermore, the system may include remote devices, servers, and cloud-based components that communicate via wired or wireless (e.g., infrared, cellular, Bluetooth®) or remote PC / server or cloud-based systems. Specifically, the image processor is configured to analyze particles in digital microscope images of liquid samples and generate analytical results specific to the liquid samples.

[0045] According to aspects of this disclosure, the automated system further includes a characteristic measurement unit configured to determine the characteristics of a liquid sample by any one of impedance measurement, conductivity measurement, resistance measurement, electrochemical measurement, optical measurement, pressure measurement, or viscosity measurement.

[0046] According to one aspect of this disclosure, the characterization unit further includes a pipette probe operatively coupled to a pressure sensor, wherein the controller is configured to: control the pipette probe to aspirate a portion of a liquid sample from a sample container; measure the pressure inside the pipette probe via the pressure sensor while aspirating the liquid sample; correlate the measured pressure with a hematocrit range; and store the measured pressure and the correlated hematocrit range as characteristics of the liquid sample in a data storage device.

[0047] According to aspects of this disclosure, the sample preparation unit includes a dilution module and / or a concentration module, each configured to dilute or concentrate a liquid sample according to operating parameters set by a workflow management unit, wherein the operating parameters include a dilution factor and / or a concentration factor. An example of the concentration module may be a centrifuge for centrifuging a liquid sample and thereby concentrating particles in the liquid sample or separating different types of components of the liquid sample, such as fractionating a whole blood sample. The dilution, suspension, or dispersion of the liquid sample may be performed in water or a suitable buffer solution, such as PBS (phosphate-buffered saline), physiological sodium chloride solution, or other buffer solutions known to those skilled in the art. Therefore, the sample preparation unit may include corresponding functional units, such as pipettes or applicators for applying a diluent or buffer solution to the liquid sample or vice versa. The sample preparation unit may further include suitable reaction dishes, for example, for mixing and incubating the liquid sample with reagents. An example of the dilution and / or concentration module is an automated system for handling particles as described in US 10,436,685.

[0048] This disclosure further relates to a computer program product including instructions for causing an automation system as described above to perform the automation method as described above. Attached Figure Description

[0049] Figure 1 shows a flowchart of an automated method for applying a liquid sample onto a substrate for image analysis according to the present disclosure; Figure 2 shows a flowchart of an automated method for applying a liquid sample onto a substrate for image analysis according to a further aspect of this disclosure; Figure 3 shows a flowchart of an automated method for applying a liquid sample onto a substrate for image analysis according to a further aspect of this disclosure; Figure 4 shows a flowchart of an automated method for applying a liquid sample onto a substrate for image analysis according to a further aspect of this disclosure; Figure 5 shows a schematic illustration of an automated system according to the present disclosure; Figure 6 shows a schematic illustration of an automated system according to a further aspect of this disclosure; Figure 7 shows a schematic illustration of an automated system according to a further aspect of this disclosure; Figures 8A and 8B show microscopic images of particles in a liquid sample on a substrate.

[0050] Those skilled in the art should understand that the components in the figures are shown schematically for simplicity and clarity and are not necessarily drawn to scale. For example, the dimensions of some components may be enlarged relative to other components to aid in understanding aspects of this disclosure. Furthermore, portions that do not contribute to the teachings of this disclosure have been omitted. Detailed Implementation

[0051] Figure 1 A flowchart is shown of an automated method for applying a liquid sample to a substrate for image analysis. The automated method includes providing data corresponding to the characteristics of the liquid sample from a characterization unit to a workflow management unit 90 (step 102). For example, the characterization unit may be an impedance-based flow cytometer, using the Coulter principle to determine the characteristics of the liquid sample. Positively measured characteristics of the liquid sample may refer to, for example: particle counts in the liquid sample, particularly the number of red blood cells (RBCs), white blood cells (WBCs), and platelets; and hematocrit, which can be calculated from the number of RBCs multiplied by the mean cell volume of the RBCs and correlated with a known sample volume. Any characteristics of the liquid sample measured in this manner are typically stored electronically, for example, in a data storage device. Therefore, the characterization unit may include a data storage device (not shown), or it may be communicatively connected to a remote data storage device (not shown), such as a computer network or the cloud. From here, data corresponding to the characteristics of the liquid sample is provided to the workflow management unit 90 via well-known electronic data transfer means, such as wired or wireless methods. Information about the identity of the liquid sample, such as the ID number, can be provided to the workflow management unit 90 along with data corresponding to the characteristics of the liquid sample, or it can be provided independently of that data, for example, by a local laboratory information system (LIS) (not shown).

[0052] Once data corresponding to one or more properties of the liquid sample has been provided to the workflow management unit 90, the workflow management unit 90 selects a sample preparation operation based on that data (step 104). According to a specific aspect of this disclosure, the sample preparation operation includes at least: applying the liquid sample to the substrate by controlling the translation of the applicator relative to the substrate when applying the liquid sample via the applicator, causing particles in the liquid sample to settle onto the substrate; and staining and / or fixing the liquid sample on the substrate. Other examples of the sample preparation operation include mixing, dispersing, aliquoting, transferring, diluting, or concentrating the liquid sample.

[0053] Workflow management unit 90 sets operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample (step 106). According to one aspect of the invention, the operating parameters include dilution parameters and / or concentration parameters. According to another aspect of the disclosure, the operating parameters include at least one or a combination of parameters selected from the group consisting of: the distance between the applicator and the substrate, the movement pattern of the applicator relative to the substrate, the speed pattern of the applicator relative to the substrate, the liquid sample dispensing volume, the dispensing rate, and / or the distance between rows of liquid sample on the substrate.

[0054] The selected sample preparation operation and the operation parameters set by the workflow management unit 90 are transmitted as instructions to the sample preparation unit to prepare a liquid sample by performing the sample preparation operation selected by the workflow management unit 90 and using the operation parameters set by the workflow management unit 90 (step 108).

[0055] Figure 2 A flowchart of an automated method for applying a liquid sample to a substrate for image analysis, according to one aspect of this disclosure, is shown. Step 202, which provides data corresponding to the properties of the liquid sample, corresponds to... Figure 1 Step 102 in the text. Therefore, for a detailed description of step 202, refer to the... Figure 1 The description.

[0056] Step 204 corresponds to Figure 1 Step 104 of the selection process based on the characteristics of the liquid sample is shown, but further sub-steps of the selection process according to one aspect of this disclosure are illustrated. Generally, the workflow management unit 90 selects the sample preparation operation by determining whether data or data points corresponding to the characteristics of the liquid sample are above or below a predetermined threshold, whether they are within a predetermined range, or whether they correspond to a predetermined category or reference value. Figure 2In the example shown, workflow management unit 90 determines which predetermined hematocrit range, such as normal, high, or low, corresponds to the data corresponding to the characteristics of the liquid sample (step 2042). The hematocrit range can depend on the sex and age of the sample donor. For example, the normal range for adult women can be between 36% and 45%, and for adult men, it can be between 40% and 51%. Therefore, the sex of the sample donor can be considered when determining the hematocrit range of the liquid sample. Depending on the verification results in step 2042, workflow management unit 90 selects the appropriate sample preparation operation. For example, if workflow management unit 90 determines in step 2042 that the hematocrit of the liquid sample is within the normal range, it selects the following sample preparation operations: applying the liquid sample to the substrate by controlling the translation of the applicator relative to the substrate when applying the liquid sample to the substrate via the applicator, causing particles in the liquid sample to settle onto the substrate, staining the liquid sample on the substrate, and fixing the liquid sample on the substrate (step 2044). In another example, and according to one aspect of the invention, if the workflow management unit 90 determines in step 2042 that the hematocrit of the liquid sample is in an abnormally high range, which can be defined as, for example, between 55% and 60% or above a predetermined upper limit threshold of 55%, then it selects the following sample preparation operations: diluting the liquid sample, applying the liquid sample to a substrate, staining the liquid sample on the substrate, and fixing the liquid sample on the substrate (step 2046). In yet another example, and according to one aspect of the invention, if the workflow management unit 90 determines in step 2042 that the hematocrit of the liquid sample is in an abnormally low range, which can be defined as, for example, between 20% and 30% or below a predetermined lower limit threshold of 30%, then it selects the following sample preparation operations: concentrating the liquid sample, applying the liquid sample to a substrate, staining the liquid sample on the substrate, and fixing the liquid sample on the substrate (step 2048).

[0057] Further, the workflow management unit 90 sets operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample (step 206). In the example mentioned above, when the characteristics of the liquid sample are within the normal range of hematocrit, the workflow management unit 90 sets one or more operating parameters selected from the group consisting of: the distance between the applicator and the substrate, the movement mode of the applicator relative to the substrate, the speed mode of the applicator movement relative to the substrate, the liquid sample dispensing volume (which is a portion of the aspirated liquid sample), the dispensing rate, and the distance between rows of liquid samples on the substrate. Specifically, the workflow management unit 90 may set the distance between the applicator and the substrate to 12 µm, the dispensing rate to 0.055 µL / s, and the speed mode to 65 mm / s relative to the movement of the applicator in the x-direction (step 2064). According to another aspect, the operating parameters may include the volume and type of staining agent to be used to stain the liquid sample. In another example, when the liquid sample has a hematocrit in an abnormally high range and a dilution operation is selected, the workflow management unit 90 sets the dilution parameters to, for example, a volume ratio of 1:5 (liquid sample: diluent) (step 2066). Further operating parameters, similar to those mentioned in the previous examples, can be set in step 2066 (step 2064). In yet another example, when the liquid sample has a hematocrit in an abnormally low range and a concentration operation is selected, the workflow management unit 90 sets the concentration parameters, for example, setting the volume of the aliquot sample to 500 µL, the centrifuge speed for a 10-minute duration to approximately 2000 rpm, and the volume of the supernatant to be removed after centrifugation to 250 µL (step 2068). Further operating parameters, similar to those mentioned relative to the previous examples (steps 2064 and 2066), can be set in step 2068.

[0058] Step 208 corresponds to Figure 1Step 108 refers to transmitting the selected sample preparation operation and the operating parameters set by the workflow management unit 90 as instructions to the sample preparation unit to prepare the liquid sample accordingly. As a result, the substrate (e.g., a glass microscope slide) carries the liquid sample, wherein the particles of the liquid sample (e.g., RBCs, WBCs, and platelets) are uniformly distributed across the substrate in a monolayer. Furthermore, a sufficient number of particles on the substrate are available for subsequent image analysis, thereby ensuring the generation of reliable analytical results. According to one aspect of this disclosure, the automated method further includes controlling the imaging unit to generate digital microscope images of one or more particles on the substrate, analyzing one or more particles in the digital microscope images to generate analytical results for the liquid sample, and displaying data and / or analytical results corresponding to the characteristics of the liquid sample on a display device (step 210).

[0059] Figure 3 A flowchart of an automated method for applying a liquid sample to a substrate for image analysis, according to a further aspect of this disclosure, is shown. Step 302 involves providing data corresponding to the characteristics of the liquid sample from a characterization unit to a workflow management unit 90. According to one aspect of this disclosure, providing the data includes controlling the characterization unit to determine the characteristics of the liquid sample by any one of impedance measurement, conductivity measurement, resistance measurement, electrochemical measurement, optical measurement, pressure measurement, or viscosity measurement, and subsequently transmitting the measurement data to the workflow management unit 90. For example, Figure 3 The characteristic measurement unit in the example can be a module or functional unit within the automated system of this disclosure, such as a photometer, spectrophotometer, or pressure sensor operatively coupled to a pipette probe (further examples described above). The data can be raw data, such as photometric information in the form of transmission or absorption data, which needs to be interpreted or converted by the workflow management unit 90 to derive information about the properties of the liquid sample. Alternatively, the characteristic measurement unit can include a separate processor for processing the raw data before providing it to the workflow management unit 90.

[0060] exist Figure 3 In the first example of step 304, a moderate increase in hematocrit was found compared to the normal range, for example, within the range of 51% to 55% (step 3042). In another example, a moderate decrease in hematocrit was found compared to the normal range, for example, within the range of 30% to 35% (step 3042). In yet another example, a hematocrit was found to be within the normal range, for example, within the range of 35% to 51%. Figure 3In the aspects of the invention shown, the workflow management unit 90 selects the following sample preparation operations when the hematocrit in the liquid sample is only moderately increased or decreased: applying the liquid sample to the substrate by controlling the translation of the applicator relative to the substrate when applying the liquid sample to the substrate via the applicator, causing particles in the liquid sample to settle onto the substrate, staining the liquid sample on the substrate, and fixing the liquid sample on the substrate (steps 3046 and 3048). The selected sample preparation operation is the same as the sample preparation operation selected for liquid samples with normal hematocrit (step 3044). When the parameter is only moderately increased or decreased, it is not necessary to perform the following operations. Figure 2 The example describes the specified dilution or concentration operation.

[0061] The workflow management unit 90 then sets operating parameters based on the selected sample preparation operation and the characteristics of the liquid sample (step 306) to generate an improved sample for subsequent image analysis. Specifically, this is done to ensure a sufficient number of particles and uniform particle distribution on the substrate, while also enabling the formation of a sample particle monolayer. In an example where the liquid sample has a moderately elevated hematocrit, the workflow management unit 90 can set the distance between the applicator and the substrate to 12 µm, the liquid sample application volume to 1 µL, the application rate to a value between 0.01 mL / s and 0.055 µL / s (e.g., 0.04 µL / s), and the distance between rows of liquid samples to a range between 0.37 mm and 0.6 mm (e.g., 0.5 mm) (step 3066). In an example where the liquid sample has a moderately reduced hematocrit, the workflow management unit 90 can set the distance between the applicator and the substrate to 12 µm, the liquid sample application volume to 4 µL, the application rate to a value within the range of 0.1 mL / s to 0.4 µL / s, for example, 0.22 µL / s, and the distance between the rows of liquid samples to a range of 0.1 mm to 0.37 mm, for example, 0.123 mm (step 3068). In an example where the liquid sample has a normal hematocrit, the workflow management unit 90 can set the distance between the applicator and the substrate to 12 µm, the liquid sample application volume to 1 µL, the application rate to a value within the range of 0.04 mL / s to 0.08 µL / s, for example, 0.055 µL / s, and the distance between the rows of liquid samples to a range of 0.3 mm to 0.5 mm, for example, 0.37 mm (step 3064).

[0062] Other examples of possible operating parameter settings based on experimental investigations are shown in Table 1. These examples illustrate possible combinations of settings that depend on the properties of the liquid sample to achieve monolayer formation of sample particles on the substrate and ensure a sufficient number and uniform distribution of particles on the substrate.

[0063] Table 1: Examples of Operating Parameter Settings .

[0064] exist Figure 8A Microscopic images of cells in the synovial fluid sample applied to the substrate can be seen. To achieve sufficient cell quantity and uniform distribution, the liquid sample application volume was set to 9 µL, the application rate to 0.495 µL / s, and the row spacing to 0.053 mm. In comparison, Figure 8B The same synovial fluid sample applied to the substrate with the same operating parameters is shown, except that a liquid sample application volume of 1 µL was used instead of 9 µL. It can be seen that... Figure 8B The number of cells in it is lower than Figure 8A The number of cells in the sample is insufficient for reliable analysis. Therefore, and according to an aspect of the invention, if the characteristics of the liquid sample are determined to be those of a slick sample and / or if the characteristics of the liquid sample are determined to be a viscosity or density below a predetermined threshold, then the workflow management unit 90, according to... Figure 8A Use the examples in the document to set the operation parameters.

[0065] Continue to refer to Figure 3 Steps 308 and 310 correspond to Figure 2 Steps 208 and 210 in the above. Therefore, for a detailed description of steps 308 and 310, refer to... Figure 2 The description.

[0066] Figure 4 A flowchart is shown of an automated method for applying a liquid sample to a substrate for image analysis, according to another aspect of this disclosure. Figure 4 The characteristic measurement unit in the example can be a device for generating data corresponding to the sample type of the liquid sample, such as a photometer or spectrophotometer. The generated data corresponding to the characteristics (i.e., sample type) of the liquid sample is provided from the characteristic measurement unit to the workflow management unit 90 (step 402).

[0067] The automation method further includes selecting a sample preparation operation (step 404) based on the characteristics of the liquid sample by the workflow management unit 90. Figure 4In the illustrated aspect, the workflow management unit 90 determines the sample type of the liquid sample based on data received by the characteristic measurement unit, which in this example is either a whole blood sample or a cerebrospinal fluid sample (step 4042). In the example related to a whole blood sample, the workflow management unit 90 selects a sample preparation operation that includes applying the liquid sample to a substrate, staining the liquid sample on the substrate, and fixing the liquid sample on the substrate (step 4044). In the example of a cerebrospinal fluid sample that typically contains a small number of cells or particles, the workflow management unit 90 selects a sample preparation operation that includes applying the liquid sample to a substrate, staining the liquid sample on the substrate, fixing the liquid sample on the substrate, and concentrating the liquid sample in comparison with a whole blood sample (step 4048) to increase its concentration relative to the volume of cellular material in the liquid sample.

[0068] The workflow management unit 90 then sets the operating parameters based on the selected sample preparation operation and the characteristics of the liquid sample (step 406). In the example related to whole blood samples and sample preparation operations such as applying a liquid sample to a substrate as selected in step 4044, the workflow management unit 90 sets the operating parameter defining the distance between the applicator and the substrate to 0.7 μm, the operating parameter regarding the liquid sample application volume to 1 μL, and the operating parameter regarding the application rate to 0.1 μL / s (step 4064). In the example related to cerebrospinal fluid samples and sample preparation operations such as applying a liquid sample to a substrate as selected in step 4048, the workflow management unit 90 sets the operating parameter defining the distance between the applicator and the substrate to 0.7 μm, the operating parameter regarding the liquid sample application volume to 4 μL, and the operating parameter regarding the application rate to 0.4 μL / s (step 4068). This allows more liquid sample material to be applied to the substrate, thereby compensating for the smaller amount of cellular material in the liquid sample. For the concentration operation selected in step 4048, the workflow management unit 90 sets the corresponding operating parameters, including, for example, the centrifuge speed (step 4068) and / or the volume of supernatant to be removed.

[0069] Steps 408 and 410 correspond to Figure 2 Steps 208 and 210 in the middle and Figure 3 Steps 308 and 310 in the above. Therefore, for a detailed description of steps 408 and 410, refer to... Figure 2 and Figure 3 The description.

[0070] Figure 5A schematic diagram of an automated system 100 according to the present disclosure is shown, wherein the automated system 100 includes a sample preparation unit 10 and a workflow management unit 90. The sample preparation unit 10 includes an applicator 12, which may be a hollow needle-shaped or syringe-shaped element, through which a liquid sample 1 is applied to a substrate 2. For the process of applying the liquid sample 1 to the substrate 2, the substrate 2 is placed on a substrate holder 4. The applicator 12 and the substrate 2 on the substrate holder 4 can be configured to translate relative to each other in the x, y, and z directions. This can be achieved by moving the applicator 12 relative to the static substrate holder 4, by moving the substrate holder 4 relative to the static applicator 12, or by moving the applicator 12 and the substrate holder 4 simultaneously. The sample preparation unit 10 further includes a staining unit 14 for staining the liquid sample 1 on the substrate 2.

[0071] The workflow management unit 90 can be a separate entity, physically separate from the automation system 100 but communicatively connected to it. The workflow management unit 90 is configured to receive data corresponding to the characteristics of the liquid sample 1 from the characteristic measurement unit 20. Based on the received data, the workflow management unit 90 is configured to select a sample preparation operation and set operating parameters, which it then transmits to the sample preparation unit 10 to prepare the liquid sample 1 by performing the sample preparation operation selected by the workflow management unit 90 and using the operating parameters set by the workflow management unit 90. The sample preparation operation includes applying the liquid sample 1 to the substrate 2 by controlling the translational movement of the applicator 12 relative to the substrate 2 when the liquid sample 1 is applied to the substrate 2 via the applicator 12, causing particles 3 in the liquid sample 1 to settle onto the substrate 2. According to one aspect of this disclosure, the liquid sample can be a whole blood sample, and the particles can be any type of cell component, such as RBCs, WBCs, or platelets.

[0072] Figure 5 The characteristic measurement unit 20 is an independent physical entity, such as a laser-based flow cytometer, which measures forward scattered light (FSC) signals, side scattered light (SSC) signals and / or dye-specific fluorescence signals, and is communicatively connected to the automation system 100, particularly to the workflow management unit 90 of the automation system 100.

[0073] Figure 6A schematic diagram of an automated system 100 according to a further aspect of this disclosure is shown. A characteristic measurement unit 20 is implemented as a module or functional unit in the automated system 100 and is communicatively connected to a workflow management unit 90. It can be, for example, a photometer or spectrophotometer, measuring the transmission or absorption of light of different wavelengths through a liquid sample.

[0074] Figure 6 The sample preparation unit 10 in the middle corresponds to Figure 5 The sample preparation unit is shown. Therefore, for a detailed description of the sample preparation unit 10, please refer to... Figure 5 The description.

[0075] Figure 6 The automated system 100 further includes: an imaging unit 30 configured to generate digital microscopic images of one or more particles 3 in a liquid sample 1 on a substrate 2; and a display device 40. Therefore, the imaging unit 30 may include a light emitting device (not shown), a microscope 32, and a light receiving device 34 (such as a camera). An image processor 92 is configured to analyze one or more particles 3 in the digital microscopic image to generate an analysis result for the liquid sample 1, and to display the characteristics 41 and / or analysis result 42 of the liquid sample on the display device 40. Therefore, the image processor 92 may be communicatively connected to the imaging unit 30 and the display device 40 via a workflow management unit 90. The displayed characteristics 41 and analysis result 42 of the liquid sample may refer to different parameters. For example, the characteristics of the liquid sample may refer to the hematocrit of the liquid sample, while the analysis result may refer to the number and type (based on their morphology) of white blood cells (WBCs) in the liquid sample. According to an alternative aspect of the invention, the characteristics of the liquid and the analysis result may refer to the same parameter, such as hematocrit. The workflow management unit 90 may, for example, compare the hematocrit measured by the characteristic measurement unit 20 with the hematocrit determined based on the analysis of microscopic images, as part of a quality assessment. The analytical results and the characteristics of the liquid sample are then used to generate an output value, which is displayed 41, 42 on the device 40. The output value may, for example, indicate that the two hematocrit values ​​are the same or sufficiently similar. Alternatively, if the two hematocrit values ​​differ by a predetermined factor, the output value may indicate that the two results are significantly different and that there may be a quality problem in the sample preparation procedure. Alarms or warning messages 41, 42 may also be displayed, alternatively, to inform the device operator.

[0076] Figure 7 The automated system 100 in the figure illustrates a further aspect of the invention. Figure 7The characterization unit 20 in the automated system 100 includes a pipette probe 22 operatively coupled to a pressure sensor 24. A controller 90 is configured to control the pipette probe 22 to aspirate a portion of liquid sample 1 from a sample container 26. During aspiration of liquid sample 1, the pressure inside the pipette probe 22 is measured by the pressure sensor 24, and the measured pressure is correlated with a hematocrit range. As described above, the characterization via pressure measurement is based on the principle that the negative pressure required to aspirate the same volume of liquid sample into the pipette probe 22 within the same time period depends on the viscosity and / or density of the liquid sample. Measuring the pressure during liquid sample aspiration allows estimation of the viscosity and / or density of the liquid sample, and thus allows the pressure measurement results to be correlated with, for example, low, normal, or high hematocrit ranges. The measured pressure and the associated hematocrit range are then stored as characteristics of the liquid sample in a data storage device 80. The data storage device 80 is communicatively connected to a workflow management unit 90.

[0077] Figure 7 The sample preparation unit 10 of the automated system 100 includes a dilution module 16 and / or a concentration module 16, which are respectively configured to dilute or concentrate the liquid sample 1 according to operating parameters set by the workflow management unit 92, wherein the operating parameters include dilution parameters and / or concentration parameters. Examples of dilution module 16, concentration module 16, dilution parameters, and concentration parameters are mentioned above.

[0078] The foregoing description details apparatuses and methods according to various aspects. These apparatuses and methods may be embodied in many different forms and should not be construed as limited to the aspects set forth and described herein. Therefore, it should be understood that the apparatuses and methods are not limited to the specific aspects disclosed, and modifications and other aspects are intended to be included within the scope of the appended claims. Although specific terminology is used herein, it is used only in a general and descriptive sense and not for limiting purposes. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. While any methods and materials similar to or equivalent to those described herein may be used in the practice or testing of the methods, preferred methods and materials are described herein.

[0079] Furthermore, the use of the indefinite article "a" or "an" to refer to an element does not preclude the possibility of more than one element, unless the context explicitly requires exactly one element. Therefore, the indefinite article "a" or "an" generally means "at least one / a kind." Similarly, the terms "have," "contain," or "include," or any arbitrary grammatical variations thereof, are used in a non-exclusive manner. Thus, these terms can refer either to a situation where no other features exist in the entity described in the context besides those introduced by these terms, or to a situation where one or more other features exist. For example, expressions such as "A has B," "A contains B," and "A includes B" can refer either to a situation where no other elements exist in A besides B (i.e., A consists solely and exclusively of B), or to a situation where one or more other elements (such as element C, element C+D, or even other elements) exist in A besides B.

[0080] Furthermore, throughout this specification, the terms "an aspect," "an aspect," "an instance," or "an instance" refer to a specific feature, structure, or characteristic described in connection with that aspect or instance that is included in at least one aspect. Therefore, the phrases "in an aspect," "in a aspect," "an instance," or "an instance" appearing throughout this specification do not necessarily refer to the same aspect or instance.

[0081] Furthermore, specific features, structures, or characteristics may be combined in any suitable combination and / or sub-combination in one or more embodiments or examples.

Claims

1. An automated method for applying a liquid sample (1) onto a substrate (2) for image analysis, the automated method comprising: - Data corresponding to the characteristics of the liquid sample (1) is provided from the characteristic measurement unit (20) to the workflow management unit (90); - The workflow management unit (90) selects the sample preparation operation based on the characteristics of the liquid sample (1); - The workflow management unit (90) sets the operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample (1); - The sample preparation unit (10) is controlled to prepare the liquid sample (1) for image analysis by executing the sample preparation operation selected by the workflow management unit (90) and by using the operation parameters set by the workflow management unit (90), wherein the selected sample preparation operation includes at least: - The liquid sample (1) is applied to the substrate (2) by controlling the translation of the applicator (12) relative to the substrate (2) when the liquid sample (1) is applied to the substrate (2) via the applicator (12), such that the particles (3) in the liquid sample (1) settle onto the substrate (2), and - To stain the liquid sample (1) on the substrate (2) and / or to fix the liquid sample (1) on the substrate (2).

2. The automation method according to claim 1, further comprising: - The imaging unit (30) is controlled to generate digital microscope images of one or more particles (3) on the substrate (2); - Analyze the one or more particles (3) in the digital microscope image to generate analytical results for the liquid sample (1); as well as - Display the data and / or the analysis results corresponding to the characteristics of the liquid sample (1) on the display device (50).

3. The automated method of claim 2, further comprising using the analytical results and the properties of the liquid sample to generate an output value.

4. The automated method according to any one of the preceding claims, wherein the operating parameters include dilution parameters and / or concentration parameters, and wherein the sample preparation operation further includes: Before applying the liquid sample (1) to the substrate (3), the liquid sample is diluted or concentrated according to the dilution parameter or the concentration parameter, respectively.

5. The automation method according to any one of the preceding claims, wherein the operating parameters include at least one parameter selected from the group consisting of: - The distance between the applicator (12) and the substrate (2), and / or - The movement pattern of the applicator (12) relative to the substrate (2), and / or - The velocity pattern of the applicator (12) relative to the substrate (2), and / or - Liquid sample (1) application volume, and / or - Application rate, and / or - The distance between rows of liquid samples (1) on the substrate (2).

6. The automated method according to any one of the preceding claims, wherein the characteristics of the liquid sample (1) include any one or a combination of liquid sample type, hematocrit, hematocrit range, sample viscosity, sample density, or particle count.

7. The automated method according to any one of the preceding claims, wherein providing data corresponding to the characteristics of the liquid sample (1) comprises: The characteristic measurement unit (20) is controlled to determine the characteristics of the liquid sample (1) by any one of impedance measurement, conductivity measurement, resistance measurement, electrochemical measurement, optical measurement, pressure measurement, or viscosity measurement.

8. The automated method of claim 7, wherein the pressure measurement comprises: - Control the pipetting probe (22) to aspirate a portion of the liquid sample (1) from the sample container (26); - When aspirating the liquid sample (1), the pressure inside the pipetting probe (22) is measured by a pressure sensor (24) operably coupled to the pipetting probe (22); - To correlate the measured pressure with the range of hematocrit; as well as - The measured pressure and the associated hematocrit range are stored in the data storage device (80) as characteristics of the liquid sample (1).

9. An automated system (100) for preparing a liquid sample (1) for image analysis according to any one of claims 1 to 8, said automated system (100) comprising: - Sample preparation unit (10), comprising: - An applicator (12) for applying the liquid sample (1) to the substrate (2), and - A staining unit (14) for staining the liquid sample (1) on the substrate (2) and / or a fixing unit (14) for fixing the liquid sample (1) on the substrate (2); - Workflow management unit (90), which is configured to: - Receive data corresponding to the characteristics of the liquid sample (1) from the characteristic measurement unit (20). - Select the sample preparation operation based on the characteristics of the liquid sample (1). - Set the operating parameters based on the selected sample preparation operation and / or based on the characteristics of the liquid sample (1). - Control the sample preparation unit (10) to prepare the liquid sample (1) by performing the sample preparation operation selected by the workflow management unit (90) and by using the operation parameters set by the workflow management unit (90), wherein the sample preparation operation includes: applying the liquid sample (1) to the substrate (2) by controlling the applicator (12) to move translationally relative to the substrate (2) when the liquid sample (1) is applied to the substrate (2) via the applicator (12), such that particles (3) in the liquid sample (1) settle onto the substrate (2).

10. The automation system (100) according to claim 9, further comprising: - Imaging unit (30), which is configured to generate digital microscope images of one or more particles (3) on the substrate (2); - Display device (40); and - An image processor (92) configured to analyze one or more particles (3) in the digital microscope image to generate analysis results for the liquid sample (1), wherein the workflow management unit (90) controls the automation system (100) to display the properties of the liquid sample (1) and / or the analysis results on the display device (40).

11. The automated system (100) according to claim 9 or 10, further comprising the characteristic measurement unit (20), the characteristic measurement unit (20) being configured to determine the characteristics of the liquid sample (1) by any one of impedance measurement, or conductivity measurement, or resistance measurement, or electrochemical measurement, or optical measurement, or pressure measurement, or viscosity measurement.

12. The automation system (100) of claim 11, wherein the characteristic measurement unit (20) includes a pipetting probe (22) operatively coupled to a pressure sensor (24), wherein the workflow management unit (90) is configured to: - Control the pipetting probe (22) to aspirate a portion of the liquid sample (1) from the sample container (26); - When the liquid sample (1) is aspirated, the pressure inside the pipetting probe (22) is measured by the pressure sensor (24); - To correlate the measured pressure with the range of hematocrit; as well as - The measured pressure and the associated hematocrit range are stored in the data storage device (80) as characteristics of the liquid sample (1).

13. The automated system (100) according to any one of claims 9 to 12, wherein the sample preparation unit (20) further comprises a dilution module (16) and / or a concentration module (16), wherein the dilution module (16) and / or the concentration module (16) are respectively configured to dilute or concentrate the liquid sample (1) according to the operating parameters set by the workflow management unit, wherein the operating parameters respectively include dilution parameters and / or concentration parameters.

14. A computer program product comprising instructions for causing an automation system (100) according to any one of claims 9 to 13 to perform an automation method according to any one of claims 1 to 8.

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