Methods for rapid, automated, high-throughput testing of biological samples and a system for performing said methods

Abstract

The methods and system of the invention are aimed at rapid, automated, high-throughput examination of biological samples. The system (300) is for performing the methods of the invention, wherein the system (300) comprises at least one microscope unit (310) comprising a microscope having a stage for holding at least one sample holder, and comprising an image acquisition unit arranged to be capable of taking a digital image of at least a portion of the at least one sample holder on the stage. The system (300) further comprises a storage unit (320) connected to the at least one microscope unit (310); at least one image analysis unit (330) connected to the storage unit (320); and at least one microdissection unit (340) comprising at least one sample holder unit for receiving the sample holder comprising at least one biological sample, and a visualization unit arranged to be able to take a digital image of at least a portion of the sample holder comprising at least one biological sample in the at least one sample holder unit, wherein the at least one microdissection unit (340) is connected to the at least one image analysis unit (330); and the system (300) further comprises at least one image correction unit (350) connected to the storage unit (320) and in operative relationship with the at least one microdissection unit (340) in a manner capable of controlling the operation of the at least one microdissection unit (340).

Description

[0001] M ethodsfor rapid, automated, high-throughput testing of biological samplesand a system for performing said methods

[0002] The invention relates to methods and a system for rapid, automated, high-throughput testing of biological samples for high-precision microdissection of objects to be excised in the biological sample.

[0003] The so-called "multi-omics" technologies such as transcriptom ics, metabolomics, proteomics, etc. that enable complex biological studies are suitable for analyzing the multi-level regulation of cell function and their relationships with each other, which usually requires the simultaneous examination of hundreds or thousands of cells. One branch of the " multi-omics" technology is the single-cell-based technology, which provides the opportunity for the phenotypic examination of a biological sample containing a multitude of cells, i.e. the identification and classification of individual cells or even cell compartments by their property. The result of the single-cell analysis must be projected onto the position of the cells in the original sample so that cells with different phenotypes can be identified according to their spatial localization, thus ensuring the sim ultaneous comparison of all parameters of individual cells in order to examine different levels of cell function and their relationships.

[0004] One method that can be used for "multi-omics" analysis is flow cytometry, including single-cell mass cytometry, which is a high-throughput method, however, the spatial position of the cells is not preserved during the procedure, so this information cannot be used for subsequent analyses. Another method could be the use of laser microdissection (LM D) microscopes, which are capable of isolating and dissecting cell groups, single cells, or subcellular cell particles in a manner that preserves their spatial position, however, LM D-based assays typically have low throughput, as they are suitable for examining only a few hundred cells. Another method for multi-omics analysis is the use of microscopes capable of high-content screening (HCS) / high- throughput screening (HT), which can take image-based recordings of thousands of slides containing biological samples per day, where the si ide contain Ing biological samples can contain up to several m illion cells. For further analysis of a biological sample, it is preferable to select a few thousand cells out of several million, so the first challenge is to reliably identify and isolate these cells.

[0005] A combination of the LM D-based method and the high-throughput microscopy method can be used to identify and isolate individual cells in microscopic images, in which the analysis of the image data can be done either by manual, small-element microdissection isolation, where the excision of the selected cells is usually accurate, but the number of cells to be excised is limited due to manual identification and isolation. The isolation and identification of individual cells can also be performed using an automated, high-throughput method, which allows the isolation of a large number of cells per sample compared to traditional methods, but the isolation and excision of cells is typically imprecise, so without user supervision this method is not suitable for proper isolation and excision while preserving the true spatial position of the cells. The degree of inaccuracy of cell isolation and sectioning using this automatic method may arise, on the one hand, from the fact that the param etersof the imagestaken by LM D-based and high-throughput microscopes differ from each other, typically due to the different properties of the camera and lens used, so the image data may differ greatly, which makes it difficult to accurately identify individual cells in different image recordings. Another problem can be caused by deformation and change in shape of the biological samples on the plate, which can occur during the transportation of the plates containing the biological samples; treatment with chemicals; exposure to heat, such as laser exposure; cutting of the samples; moving or removing the coverslip placed on the sample; or possibly due to drying of the sample itself over time, which physical deformation occurs in most cases in the period between the two images taken using different procedures, so due to the deterioration in quality, it is difficult to identify individual cells with sufficient accuracy. Furthermore, the excision of selected cells during microdissection can lead to deformation of biological samples, as physical impact at a given point can lead to a change in the state of a given part or all of the membrane, thus affecting the other cells of the biological sample to be excised. An additional difficulty may arise if the individual cells to be examined are located far from each other on the slide, so that it is not possible to isolate and cut out individual cells to be examined from a single field of view without moving the stage holding the slide, which may lead to additional positioning errors in different image recordings taken with different devices.

[0006] Depending on the requirements of a given analysis of biological samples, reducing processing time may be essential, for example due to RNA degradation, so in this case, it is necessary to maximize throughput while minimizing processing time in all of the above methods in such a way that the identification of individual cells is carried out with sufficient accuracy.

[0007] EP 2235578 describes a laser microdissection system and method suitable for taking a digital image of a part of a slide containing a biological sample containing cells to be examined, with the aim of identifying individual cells to be examined on a biological sample and in the digital image thereof and cutting out the cells with a different unit. Although the solution preserves the original spatial position of each cell by transforming the corresponding coordinates of the cells to be examined in the digital image into coordinates readable by the cutting unit, where the accuracy of the cutting can be improved by cross-correlation of the coordinates, this system and method are only suitable for correcting alignment errors resulting from displacement. The system according to this patent document is not suitable for correcting alignment errors resulting from possible physical deformationsthat traditionally occur in the case of samples, for improving the alignment with high precision, or for simultaneously examining all cells to be examined on the entire slide, since the identification and cutting of the cells to be examined is carried out exclusively in the image according to the currently displayed field of view of the given microscope.

[0008] US9, 217,694 describes a laser microdissection method for automatically creating cutting lines by controlling the relative motion between a laser beam and a sample, wherein at least one object to be excised is automatically determined, the cutting line of which is excised by controlling the laser beam . The correction step of the proposed method can only serve to correct distortion caused by lighting and shading, but not to correct errors resulting from physical deformation of individual samples. The method according to the solution is also not suitable for sim ultaneously examining the cells of the entire slide, since the method is limited to the area to be examined on the stage in a given position.

[0009] US6,787,301 discloses a method and apparatusfor laser microdissection, which is used to excise a cell in a sample with a focused laser beam of a defined cutting width, where the cell is excised with a cutting line that cuts the cell to be excised from the surrounding cells in such a way that the excised cell can fall into a collection container under the influence of gravity. The goal of the solution is to determine the cutting width of the laser beam for microdissection in such a way that the selected cell can be properly isolated and excised from the surrounding cells. The user can manually correct the appropriate size of the sample to be cut out using the cutting tool, i.e. based on its single field of view image.

[0010] None of the above solutions enables automated, high-throughput microdissection of objects, i.e. cells or cell compartments, in a biological sample by highly accurate alignment of at least two different digital images containing the given object, where the contours of each object are aligned with unlimited degrees of freedom distortion correction prior to excision. Furthermore, none of the above solutions allows for simultaneous, high-precision cutting of objects using the above method for the entire sample holder containing the biological sample. The aim of the solution according to the invention is to implement a system and method that enables the high-precision, fast, automatic, high-throughput identification, isolation, cutting out, and optionally further analysis of individual objects by improving the alignment of the contours indicating the spatial position of the objects. The solution according to the invention further enables simultaneous examination of the objects to be examined in the above manner for the entire plate containing the biological sample.

[0011] The objects set forth by the invention are realized by a method for improving the microdissection of objects in a sample holder comprising a biological sample, wherein during the method

[0012] - In step S100, providing at least one microscope unit, which includes a microscope with an object stage and an image capture unit;

[0013] - In step S110, placing a sample holder comprising at least one biological sample on the object stage;

[0014] - In step S120a, taking a first digital image with the image capture unit of at least one part of the sample holder comprising at least one biological sample placed on the object stage;

[0015] - In step S130, transmitting the first digital image to a storage unit;

[0016] - In step S140, identifying the objects in the first digital image stored in the storage unit using at least one image analysis unit;

[0017] - In step S150, selecting at least one part of the identified objects using the at least one image analysis unit and transmitting them to the storage unit;

[0018] - In step S160, generating the original contours of the selected objects using the at least one image analysis unit;

[0019] - In step S170, providing at least one microdissection unit, which includes at least one sample holder unit for receiving at least one sample holder comprising a biological sample and includes a visualization unit for creating a second digital image of the sample holder comprising at least one biological sample;

[0020] - In step S180, placing the sample holder comprising at least one biological sample in at least one sample holder unit of the microdissection unit in such a way that the visualization unit is used to create a second digital image of the sample holder comprising the given biological sample; - in step S190, transmitting the original contours to the storage unit and the at least one microdissection unit ;

[0021] - In step S200, fitting the original contours to the second digital image of the at least one microdissection unit and creating a third digital image,

[0022] - In step S210, providing at least one image correction unit and transmitted the first digital image, the second digital image and the original contours to the at least one image correction unit,

[0023] - In step S220, aligning the first digital image and the second digital image with each other using the at least one image correction unit, and adjusting the original contours according to the alignment, thereby creating current contours;

[0024] - In step S230, transmitting the current contours to the at least one microdissection unit, adjusting the contours of the third digital image to the position corresponding to the current contours, thereby creating a fourth digital image;

[0025] - In step S240, cutting out the objects based on the fourth digital image using the at least one microdissection unit.

[0026] Preferably, in step S120a, the image capturing unit takes multiple first digital I mages of individual parts of the given sample holder comprising a biological sample from multiple fields of view, where the multiple first digital images taken from individual parts of the given sample holder correspond to the individual fields of view, and by combining the multiple first digital images, a first digital image is created that presents the entire given sample holder.

[0027] Preferably, in the case of using multiple microscope units, steps S100-120a are performed per microscope unit.

[0028] The objects set forth by the invention are further achieved by a method for improving the microdissection of objects in a sample holder comprising a biological sample, wherein the method comprises:

[0029] - in step S120b, taking at least one first digital image of at least one part of the sample holder comprising at least one biological sample;

[0030] - in step S130, transmitting the at least one first digital image to a storage unit ;

[0031] - in step S140, identifying the objects in the at least one first digital image stored in the storage unit by at least one image analysis unit; - in step S150, selecting at least one part of the identified objects by the at least one image analysis unit and transmitting the at least one part of the identified objectsto the storage unit;

[0032] - in step S160, generating original contours of the selected objects by the at least one image analysis unit;

[0033] - In step S170, providing at least one microdissection unit, which includes at least one sample holder unit for receiving the sample holder comprising at least one biological sample and a visualization unit for creating a second digital image of the sample holder comprising at least one biological sample;

[0034] - In step S180, placing the sample holder comprising at least one biological sample in at least one sample holder unit of the microdissection unit in such a way that the second digital image is created with the visualization unit;

[0035] - In step S190, transmitting the original contours to the storage unit and the at least one microdissection unit;

[0036] - In step S200, fitting the original contours onto the second digital image of the at least one microdissection unit and creating a third digital image;

[0037] - In step S210, providing at least one image correction unit and transmitting to the at least one image correction unit the first digital image, the second digital image and the original contours;

[0038] - In step S220, aligning the first digital image and the second digital image with each other using the at least one image correction unit, then adjusting the original contours according to the alignment, thereby creating current contours;

[0039] - In step S230, transmitting the current contours to the at least one microdissection unit and adjusting the contours of the third digital image to the position corresponding to the current contours, thereby creating a fourth digital image;

[0040] - In step S240, cutting out the objects based on the fourth digital image by the at least one microdissection unit.

[0041] Preferably, in step S120b, multiple first digital images are taken from multiple fields of view of individual parts of the sample holder comprising the given biological sample, where the first digital images taken from the individual partsof the sample holder correspond to the individual fields of view, and by combining the multiple first digital images, a first digital image is created that presents the entire given sample holder. The multiple first digital images corresponding to multiple fields of view of individual parts of the sample holder comprising the given biological sample may originate from multiple microscope units.

[0042] Conveniently, during the identification of objects according to step S140, a phenotypic classification of the objects is performed.

[0043] Preferably, during the selection of the identified objects according to step S150, the number of objects is reduced to a value between several thousand and several hundred objects.

[0044] Preferably, during step S180, several second digital images are taken from several fields of view of individual parts of the sample holder comprising the given biological sample, where the second digital images taken from the individual parts of the given sample holder correspond to the individual fieldsof view, and by combining the several second digital images, a second digital image is created that presents the entire given sample holder.

[0045] Conveniently, after starting step S190, the procedural steps preceding step S190, but at least steps S140-S160, are performed on a further sample holder comprising the biological sample.

[0046] Preferably, the sample holder is provided with marker points that can be identified in both the first digital image and the second digital image, where step S200 is performed based on the alignment of the marker points in the first digital image and the second digital image.

[0047] Step S220 may include the following steps:

[0048] - In step S221 , taking the first digital image, the second digital image and the original contours;

[0049] - In step S222, perform ing segmentation on both the first digital image and the second digital image, thereby identifying the objects;

[0050] - in step S223, if the individual objects can be identified in both the first digital image and the second digital image, then merging the f irst and second digital images based on the identified objects by transforming the first digital image according to the second digital image, or vice versa; or

[0051] - if the individual objects cannot be identified properly in the first digital image or the second digital image, then in step S223ba, transforming the style of the first digital image and / or the second digital image so as to obtain a first digital image and a second digital image of the same or similar style, then in step S223bb, identifying marker points in the first digital image and the second digital image of the same or similar image style, then in step S223bc, merging the first digital image and the second digital image based on the marker points by transforming the first digital image according to the second digital image, or vice versa;

[0052] - In step S224, transforming the original contours according to the transformation applied when the first digital image and the second digital image are combined to thereby create the current contours.

[0053] Preferably, based on the combination of the first digital image and the second digital image, creating the current contours by correcting the original contours with an arbitrary degree of freedom, if necessary.

[0054] Preferably, in the method according to the invention:

[0055] - in step S250, at least one microdissection unit comprises at least one collection vessel for collecting the cut objects, in which the cut objects cut in step S240 are placed;

[0056] - in step S260, the cut objects in the at least one collection vessel are transmitted to at least one object analysis unit; and

[0057] - in step S270, the molecular composition and / or specific physical properties of each cut object are analyzed by the at least one object analysis unit.

[0058] Preferably, in step S280, the information relating to the objects according to step S140, according to step S230 and according to step S270 is combined and analyzed.

[0059] Preferably, the objects in the sample holder comprising at least one biological sample are subcellular units, tissue sections, preferably single-cell units.

[0060] The first digital image, the second digital image, the third digital image and the fourth digital image may be 2-dimensional images.

[0061] The method is preferably performed automatically or semi-automatically, preferably by unsupervised or supervised machine learning.

[0062] The objects set forth by the invention are f urther achieved by implementing a system for carrying out the method according to the invention, which system comprises:

[0063] - at least one microscope unit comprising a microscope having a stage for holding at least one sample holder and comprising an image capturing unit arranged to be able to take a digital image of at least one part of the at least one sample holder on the stage;

[0064] - a storage unit connected to the at least one microscope unit ; - at least one image analysis unit connected to the storage unit;

[0065] - at least one m icrodissection unit comprising at least one sample holder unit for receiving the sample holder comprising at least one biological sample and a visualization unit arranged to be able to take a digital image of at least a portion of the sample holder comprising at least one biological sample in the at least one sample holder unit, wherein the at least one microdissection unit is connected to the at least one image analysis unit; wherein the system further comprises

[0066] - at least one image correction unit connected to the storage unit and in operative relationship with the at least one microdissection unit in such a way that it is able to control the operation of the at least one microdissection unit.

[0067] Preferably, the at least one microscope unit and the at least one microdissection unit are designed in an integrated manner.

[0068] Preferably, the at least one image analysis unit and the at least one image correction unit are designed in an integrated manner.

[0069] The system according to the invention may advantageously further comprise at least one object analysis unit, which is connected to the at least one microdissection unit and the at least one image analysis unit.

[0070] In the following, exemplary preferred embodiments of the invention are described with the aid of the accompanying drawings, in which

[0071] Figure 1 shows a flow chart illustrating certain essential process steps of the methods according to the invention,

[0072] Figure 2 shows an example of a possible combination of a first digital image and a seco nd digital image in step S220 of a method according to the invention, and

[0073] Figure 3 shows a schematic representation of a preferred embodiment of a system according to the invention.

[0074] The present invention is defined by the appended claims. The present description describes certain aspects and features of certain preferred embodimentswith the aid of the drawings, but they should not be considered as limiting the scope of the protection scope.

[0075] The objects of the invention can be achieved by met hods according to independent, main claims, some of the process steps of which may be identical. Fig. 1 shows a flowchart showing the process steps S130-S240 of the methods according to the independent main claims. The methods according to the invention relate to improving the microdissection of objects in a sample holder comprising a biological sample.

[0076] In the present invention, a biological sample with objects is understood to mean a sample comprising a given biological material, preferably a tissue sample, including collected or cultured tissue samples, blood smears, cell cultures, etc., which may contain several, even several million objects, i.e. cell groups, single cells, and cell compartments. The biological sample is stored in a suitable sample holder that is suitable for handling by the units used in the method. Such a sample holder may be, for example, a slide, an assay, such as a microassay or immunoassay, etc., or any other suitable storage element for receiving a sample.

[0077] M icrodissection is a method used in biology and medicine, by which a given piece can be cut out of a generally flat biological sample using a laser beam, where the cut piece, for example a cut single cell, is available independently of the rest of the sample for further, primarily biological, studies.

[0078] The method according to main claim 1 is characterized by the following method steps, of which steps S100-S120a are not shown in Figure 1.

[0079] In step S100, at least one microscope unit 310 is purchased, which includes a microscope with an object stage and an image acquisition unit.

[0080] In step S1 10, a sample holder comprising at least one biological sample is placed on the stage of the at least one microscope unit 310, which is thus positioned in a suitable position for the image capture unit to take a digital image of the biological sample in the sample holder. The placement on the stage may be done manually or automatically, for example using a robotic arm. The at least one microscope unit 310 may be a microscope unit 310 suitable for taking a digital image of the sample holder comprising at least one biological sample, for example a light microscope, a fluorescent microscope, etc. The sample holder comprising at least one biological sample may also be a sample holder suitable for storing one or more biological samples separated from each other. Furthermore, the at least one microscope unit 310 may be suitable for handling multiple sample holders, each containing biological material, for example, four sample holders, for example four slides, may be placed on the stage of a given microscope unit 310, however, the given microscope unit 310 may also be suitable for receiving a different number of sample holders. In step S120a, a first digital image is taken by the image capture unit of at least one part of a sample holder having at least one biological sample placed on the stage. In this case, the image capture unit generally takes a first digital image from a field of view, which may typically represent a part of the given sample holder, but in the case of certain types of sample holders, such as m ultiwell plates, it may even represent the entire sample holder. Alternatively, in step S120a, the image capture unit can take multiple first digital images from multiple fields of view of individual parts of the given sample holder having a biological sample, where multiple first digital images taken from individual parts of the given sample holder correspond to each field of view, and by combining the multiple first digital images, a first digital image can be created that presents the entire given sample holder, thereby providing a digital image of all objects in the biological sample. In step S120a, the imaging according to the different fields of view can be performed by moving the image capture unit or the sample holder. The above procedural step can be performed on all sample holders containing biological samples, thusobtaini ng a complete digital image of each sample holder.

[0081] The following describes a possible way of obtaining a first digital image of a single sample holder. M ultiple first digital images corresponding to multiple fields of view can be obtained from individual parts of a sample holder comprising a biological sample using a single microscope unit 310 or multiple microscope units 310. If multiple microscope units 310 are used, process steps S100-S120a are performed for each microscope unit 310. The multiple microscope units 310 can be of the same or different types of microscope units 310.

[0082] The execution of the process steps S100-S120a per microscope unit 310 may mean, on the one hand, that the same process steps are performed several times on a single sample holder comprising a biological sample with the plurality of microscope units 310, i.e., the individual steps above are repeated per m icroscope unit 310. The steps S100-S120a repeated for a single sample holder comprising the plurality of microscope units 310 may occur immediately one after the other in time, which corresponds to essentially the same condition in terms of the state of the biological sample in the given sample holder, so that the properties of the objects in the biological sample may typically have nearly the same parameters in each first digital image. The advantage of this is that the quality of the first digital images taken with each microscope unit 310 can be checked by comparing the f irst digital images taken with each independent microscope unit 310 with each other.

[0083] The steps S100-S120a repeated for a single sample holder per multiple microscope units 310 may also occur with a given time difference, so that the properties of the objects of the biological sample in the given sample holder may differ to a given extent in each first digital image based on the change in time. The advantage of this is that the change in the characteristics of the objects in the first digital images taken at different times can be tracked, so that the further process steps can be performed based on the current state of the objects, thereby parameters changing due to the physical change of the sample can also be identified in the first digital images.

[0084] On the other hand, performing the process steps S100-S120a with multiple microscope units 310 may also mean that steps S100-S120a are performed separately on multiple sample holders with biological samples simultaneously and in parallel using multiple microscope units 310, i.e. each of the above steps is performed once with a separate microscope unit 310 on a given sample holder comprising a given biological sample. The ad vantage of this is that the throughput of the process is increased by the fact that multiple sample holders with biological samples can be examined simultaneously and in parallel with the multiple microscope units 310. This is particularly advantageous in the case of time-sensitive examinations, where the given examination can only be performed with sufficient reliability within a specific time frame.

[0085] The method according to main claim 4, in contrary to the above, comprises a method step S120b, during which at least one first digital image is taken of at least one part of the sample holder comprising at least one biological sample. In this case, the first digital image is already available, which is essentially at least one first digital image taken with a microscope unit 310 of at least one part of a sample holder comprising a biological sample, preferably of the entire sample holder. Step S120b is also not shown in FIG. 1 .

[0086] Subsequently, the method according to both main claims 1 and 4 may comprise the method steps S130-S240, which are shown in FIG. 1 .

[0087] After the process steps S100-S120a or after the process step S120b, in step S130, the first digital image is transmitted to a storage unit 320. The storage unit may be any conventional data storage unit suitable for receiving and storing data, in this case digital image data.

[0088] In step S140, the objects in the first digital image stored in the storage unit 320 are identified by at least one image analysis unit 330. The identification of the object in the given first digital image may be carried out based on methods known in the art, for example by segmenting the digital image recording and then identifying the individual objects based on predetermined criteria, essentially by classifying certain properties of the individual objects, for example based on cell morphology and / or intensity, etc. During step S140, the classification of the objects based on phenotypic characteristics can be advantageously performed during the identification of the objects.

[0089] In step S150, at least a portion of the objects identified in step S140 are selected by at least one image analysis unit 330 and transmitted to the storage unit 320. The selection of the objects is preferably based on the classification of the objects in step S140, such that all objects classified in certain classes are selected. After the selection, the number of objects to be further processed in the process is typically reduced, preferably the number of objects is reduced from, for example, one or more million objects to several thousand or several hundred objects. The advantage of reducing the number of objects by selection is that the individual selected objects can generally be easily separated and examined in subsequent process steps.

[0090] In step S160, the original contours of the selected objects are generated by the at least one image analysis unit 330. By the original contours of the objects is meant the contours of the objects according to the first digital image, i.e. the contours of the objects in the first, original Im age taken by the image acquisition unit of the at least one microscope unit 310, are generated. The steps performed by the at least one image analysis unit 330, i.e. steps S140-S160, can be performed in a fully automatic or semi-automatic manner. Preferably, all steps of the methods according to the invention are performed automatically or semi-automatically. Automatic execution is possible, for example, using unsupervised machine learning, while semi-automatic execution is possible, for example, using supervised machine learning, but any other suitable automatic or semi-automatic method can be used.

[0091] In step S170, at least one m icrodissection unit 340 is taken, which includes at least one sample holder unit for receiving at least one sample holder comprising a biological sample and a visualization unit for generating a second digital image of the sample holder comprising the at least one biological sample, wherein the second digital image is essentially a digital image generated by the at least one microdissection unit 340 of the placed sample holder. The at least one microdissection unit 340 typically has a plurality of sample holder units, for example four sample holder units.

[0092] In step S180, the sample holder comprising at least one biological sample is placed in at least one sample holder unit of the given microdissection unit 340 in such a way that the second digital image of the sample holder comprising the given biological sample is prepared with the visualization unit. In step S108, the sample holder comprising the given biological sample is understood to mean a sample holder of which a first digital image was prepared in the previous process steps, and on which the objects were identified, at least a part of them were selected, and then the contours of the objects were determined. The second digital image prepared with the visualization unit of the at least one microdissection unit 340 is essentially a digital image of the sample holder comprising the given biological sample placed in the at least one sample holder unit in real time, according to a given field of view. The placement of the sample holder comprising the at least one biological sample in the at least one sample holder unit of the at least one microdissection unit 340 can be done manually or automatically, for example with the help of a robotic arm.

[0093] In step S180, multiple second digital Im ages may be taken from multiple fields of view of portions of the sample container containing the biological sample, where the second digital I mages taken from portions of the sample container correspond to the multiple fields of view, and a second digital image may be created by combining the multiple second digital images to present the entire sample container. A first digital image and a second digital image may then be available, each of which is a digital representation of the entire sample container, and which were taken with different units.

[0094] In step S190, the original contours created in step S160 are transmitted to the storage unit 320 and to the at least one microdissection unit 340.

[0095] After starting step S190, the process steps preceding step S190, but at least steps S140-S160, can be performed on a further sample holder comprising a biological sample. The process steps preceding step S190 can be the process steps between S100-S180 on the one hand, and the process steps between S120b-S180 on the other hand. Preferably, at least steps S140 and S160 can be performed after starting step S190, which has the advantage that an examination of a further sample holder comprising a biological sample can be performed with the at least one image analysis unit 330 while the at least one microdissection unit 340 performs the cutting of the objects. Typically, the execution of the process steps between S190-S240 is more timeconsuming than the execution of the steps preceding step S190, thus it is particularly advantageousto execute the individual st epsof the process simultaneously, in parallel with each other.

[0096] In step S200, the original contours created in step S160 are applied to the second digital image of the at least one microdissection unit 340, thereby creating a third digital image, where the third digital image is essentially the second digital image with contours, where the contours are created based on the first digital image by the at least one image analysis unit 330, and where the second digital image is created by the at least one microdissection unit 340. The third digital image according to step S200 is a digital image based on which the at least one microdissection unit 340 could perform the cutting of the objects, however, in this case, the position of the objectswould not be checked and corrected, if necessary, i.e. the microdissection processwould not be improved.

[0097] The sample holder used in the method according to the invention is provided with marker points that can be identified in both the first digital image and the second digital image. The sample holder is preferably provided with at least three marker points, which are preferably arranged at a distance from each other and evenly distributed. This essentially means that the membrane of the sample holder has marker points that are visible in the individual digital images after the individual digital images have been taken, so that they can be suitable for positioning the individual digital images relative to each other. Step S200 is thus performed based on the alignment of the marker points in the first digital image and the second digital image. During step S200, the original contours created in step S160 are aligned on the second digital image in such a way that the marker points in the same position in the first digital image and the second digital image are aligned before the alignment, which essentially also results in an approximate, “raw” alignment of the first digital image and the second digital image. Since the original contours are created based on the first digital image, the original contours also carry information corresponding to the marker points of the first digital image, so the created third digital image is essentially a second digital image that contains the original contours in an approximately positioned position.

[0098] In step S210, at least one image correction unit 350 is taken, to which the first digital image, the second digital image and the original contours are transmitted. In step S220, the first digital image and the second digital image are aligned with each other using the at least one image correction unit 350, and then the original contours are aligned according to the alignment of the first and second digital images, thereby creating actual contours. By actual contours, we mean that the at least one image correction unit 350 also “finely” aligns the first and second digital images so that the original contours determined in the first digital image are aligned to the position corresponding to the real contours of the objects in the second digital image. The execution of step S220 is shown in detail based on Fig. 2.

[0099] Step S220 may include following process steps: in step S221 , the first digital image, the second digital image and the original contours are taken. Subsequently, in step S222, segmentation is performed in both the first and second digital images to identify objects. The first digital image and the second digital image then represent the same sample holder, where the objects in the biological sample carried by the sample holder can be identified by segmenting the first and second digital images, where the identification is preferably based on the characteristics of the objects, in particular the contours and / or regions of the objects.

[0100] In step S223a, if the individual objects can be identified in both the first and second digital images, the first and second digital images are combined based on the identified objects, preferably the first digital image and the second digital image are combined based on the contours or regions of the individual objects by transforming the first digital image according to the second digital image, i.e. the coordinates of the first digital image are transformed to a position that corresponds to the coordinates of the second digital image, so that the positions of the corresponding objects identified in the individual digital images are also overlapped. Snce the first digital image and the second digital image represent the same sample holder, the objects identified in given, nearly identical positions in the individual digital images correspond to the same object. The transformation can also be done in reverse, i.e. the coordinates of the second digital image can also be transformed into a posit ion that corresponds to the coordinates of the first digital image.

[0101] Alternatively, in step S223, if the individual objects cannot be properly identified in the first digital image or the second digital image, the style of the first digital image and / or the second digital image is converted to obtain a first digital image and a second digital image of the same or sim ilar style. By properly identifying the objects, we mean that preferably all objects in the first digital image and the second digital image representing the same sample holder can be identif ied based on the characteristics of the objects, preferably their contours and / or regions. If the identification is not proper in at least one of the first digital image and the second digital image, the style of the first digital image and / or the second digital image isconverted. The image style conversion is preferably performed by converting the style of the first digital image to the style of the second digital image. The image style transformation can also be done in reverse, i.e. the style of the second digital image is transformed into the style of the first digital image. It is also conceivable that the style of the f irst and second digital images is transformed into a third image style different from the first and second image styles. During step S223bb, in the first and second digital images transformed into a uniform image style, identification points are determined, which are essentially characteristics of the image style, for example, specific pixel points, or regions or contours of objects, or any visually identifiable feature. Based on the identification points, during step S223bc, the first digital image and the second digital image are merged by transforming the first digital image according to the second digital image, i.e. the coordinates of the first digital image are transformed to positions that correspond to the coordinates of the second digital image, so that the positions of the identification points according to each digital image also overlap. Snce the first digital image and the second digital image represent the same sample holder, the identification points at given, nearly identical positions in each digital image can be assigned to the same region of the biological sample. The transformation can also be done in reverse, i.e. the coordinatesof the second digital image can be transformed to the position corresponding to the coordinatesof the first digital image.

[0102] In the case of S223a or S223ba-S223bc, the merging of the first digital image and the second digital image based on the identified objects or identification points essentially means that one of the first digital image and the second digital image istransformed to a position such that the objects or identification points identified in the first and second digital images overlap each other. The transformation may be rigid or non-rigid, or linear or nonlinear.

[0103] In step S224, the original contours are transformed according to the transformation applied when the first digital image and the second digital image are combined to create the current contours. This essentially means that while in step S200 the original contours are only placed based on the combination of the marker points of the first and second digital images, in step S224 the “fine” matching of the original contours is also performed, which is based on the transformation of the first and second images. The transformation applied when the first and second images are combined can be performed based on a transformation matrix, based on which the original contours can also be aligned to the current contours of the objects. Based on the combination of the first and second digital images, the current contours are created - if necessary - by correcting the original contours, preferably by correcting the distortion of any degree of freedom of the original contours. If no transformation is required during the merging step of steps S223a or S223ba-S223bc, or if the transformation is at a level such that the correction of the original contours is essentially negligible, then the position of the current contours is completely or essentially the same as the position of the original contours. The current contours in the fourth digital image essentially allow for further processing of individual objectswith corrected contours during the process.

[0104] Following step S220, in step S230, the current contours are transmitted to the at least one microdissection unit 340, and the contours of the third digital image are aligned to the current contours, thereby creating a fourth digital image. The third digital image essentially represents the original contours placed on the second digital image, while the fourth digital image representsthe current contours placed on the second digital image, i.e., optionally, containsthe corrected, aligned contours of the individual objects.

[0105] In step S240, the objects are cut out based on the fourth digital image using at least one microdissection unit 340. The physical cutting of the objects is performed on the sample holder comprising at least one biological sample, which was placed in step S180 at the microdissection unit 340. The cutting is typically performed with a laser based on the current, updated contours of the objects, so that the given object is cut out very precisely in such away that it can be clearly distinguished from other objects in the biological sample.

[0106] After step S240, optionally further process steps can be performed in both the method according to main claim 1 and the method according to main claim 4. These process steps are not shown in FIG. 1.

[0107] After step S240:

[0108] - during step S250, where the at least one microdissection unit 340 comprises at least one collection vessel for collecting the cut objects, the cut objects in step S240 are placed in the at least one collection vessel. The placement in the at least one collection vessel can be done manually or automatically, preferably based on the positioning of the at least one collection vessel, where the at least one collection vessel is located below the sample holder containing the objects to be cut, so that after cutting, the cut object falls into the at least one collection vessel under the influence of gravity. Optionally, the at least one microdissection unit 340 may comprise several collection vessels, for example for cut objects with given characteristics.

[0109] - in step S260, the cut objects in the at least one collection container are transmitted to at least one object analysis unit 360, and

[0110] - in step S270, the molecular composition and / or specific physical properties of each cut object are analyzed with at least one object analysis unit 360.

[0111] In a preferred embodiment, following process step S270, step S280 may be performed, in which the information on the objects according to step S140, according to step S230 and according to step S270 is combined and analyzed. The information according to step S140 may essentially include phenotypic characteristics of the objects, the information according to step S230 may essentially be information on the current contours of each object, which may determine the spatial position of the objects on the given sample holder. The information according to step S270 may essentially be information on the molecular composition and / or specific physical properties of the objects. Combining the above information with each other may enable a “ multi-omicS’ study to be performed with respect to each biological sample and each object.

[0112] The objects in the sample holder comprising at least one biological sample may preferably be subcellular units, tissue sections, preferably single-cell units.

[0113] The first digital image, second digital image, third digital image and fourth digital image according to the method of the invention may be 2-dimensional images.

[0114] Next, Figure 2 is described, which shows an example of a possible combination of a first digital image and a second digital image in step S220 of a method according to the invention. In step S221 of Figure 2, a first digital image, a second digital image and the original contours are taken, where the image styles of the first and second digital images are different from each other in this case, and the original contours are not separately depicted in Figure 2. Due to the images with different image styles, the identification of individual objectswas not done properly during the segmentation according to step S222, not depicted in Figure 2, therefore, the image style of the first digital image and / or the second digital image needs to be transformed. In step S223ba of Figure 2, the style of the first digital image is transformed into a first digital image with the same style as the style of the second digital image. Subsequently, in step S223bb, identification points are identified in the images with the same image style, which are marked with white circles in the figure. Although the number of white circles is the same in the first and second digital images with the same image style, their location is not exactly the same. In step S223bc, the first digital image and the second digital image are merged based on the identification points by transforming the coordinates of one digital image to the coordinates of the other digital image, while the identification points defined in each digital image overlap each other. The degree and direction of the transformation were illustrated by sliding the first digital image and the second digital image relative to each other in step S223bc. The transformation can have any degree of freedom and extent. After the transformation, in step S224, not shown in Figure 2, the original contours are taken and the original contours are transformed based on the transformation applied when merging the first and second digital images, thereby creating the current contours. The current contours essentially mean the improved position of the original contours based on the transformation described above, which provides an opportunity to properly delimit the real contours of the objects before cutting them out. Figure 3 shows a preferred embodiment of the system according to the invention. The system 300 according to the invention is used to perform the methods according to the invention, i.e. to improve the microdissection of objects in a sample holder comprising a biological sample. The detailed description of the methods according to the invention has been given previously, so the description of the system 300 is limited to the structural arrangement of the system 300.

[0115] The system 300 comprises at least one microscope unit 310, which in the case of the system 300 according to FIG. 3 is a microscope unit 310 comprising a microscope having a st age on which at least one sample holder can be placed, and comprising an image capturing unit adapted to take a first digital image of at least one part of the at least one sample holder on the stage. The at least one microscope unit 310 may be any microscope unit 310 having a microscope and an image capturing unit, for example a light microscope, a fluorescent microscope, etc. The stage is preferably suitable for receiving several sample holders, even of different types, from which the image capturing unit can take a first digital image. The image capture unit can advantageously take several first digital images, which cover the entire surface of the sample holder according to different fields of view, so that the biological sample in the given sample holder is presented in its entirety, in digital form, after the individual first digital images are combined, with the objects contained therein. The first digital image of the given, complete sample holder is taken either by moving the image capture unit relative to the sample holder, or vice versa, by moving the given sample holder relative to the image capture unit.

[0116] The system of FIG. 3 further comprises a storage unit 320, which is connected to the microscope unit 310, for receiving and storing a digital image produced therewith, which is a digital image produced during the methods of the invention. The storage unit 320 may be any unit suitable for storing data.

[0117] The system 300 further comprises at least one image analysis unit 330, in the embodiment of FIG. 3, an image analysis unit 330, which is connected to the storage unit 320 in a manner suitable for sending and receiving data. The at least one image analysis unit 330 operates in the manner described in the methods of the invention.

[0118] Furthermore, the system 300 comprises at least one microdissection unit 340, in the embodiment of FIG. 3 a microdissection unit 340 comprising at least one sample holder unit for receiving a sample holder comprising at least one biological sample and a visualization unit for generating a digital image of the sample holder comprising at least one biological sample, wherein the microdissection unit 340 is connected to an image analysis unit 330 for receiving information therefrom. The at least one microdissection unit 330 operates in a manner suitable for carrying out the methods of the invention.

[0119] The system 300 further includes at least one image correction unit 350, in the embodiment of FIG. 3 , an image correction unit 350 that is connected to the storage unit 320 and is in operative relationship with the at least one microdissection unit 340 such that it can control the operation of the at least one microdissection unit 340. The at least one image correction unit 350 controls the operation of the at least one microdissection unit 340 in accordance with the methods of the invention.

[0120] The at least one microscope unit 310 and the at least one microdissection unit 340 of the system 300 according to the invention may also be designed in an integrated manner.

[0121] The at least one image analysis unit 330 and the at least one image correction unit 350 of the system 300 according to the invention may also be designed in an integrated manner.

[0122] The system 300 according to the invention may further comprise at least one object analysis unit 360, which is connected to the at least one microdissection unit 340 and the at least one image analysis unit 330, wherein the operation of the at least one object analysis unit 360 is carried out in a manner corresponding to the implementation of the methods according to the invention.

[0123] The plurality of objects in the sample holder comprising at least one biological sample used in the system 300 according to the invention may be subcellular units, tissue parts, preferably single-cell units, i.e. objects treated with the methods according to the invention.

[0124] The system 300 according to the invention may comprise one or more of the following: 310 microscope unit, 330 image analysis unit, 340 microdissection unit, 350 image correction unit and 360 object analysis unit, where the advantage of the several units listed above is that the number of biological samples that can be handled by the system 300 and the speed of analysis of the biological samples can be increased by being able to handle multiple biological samples sim ultaneously and in parallel. If the system 300 comprises one of each of the aforementioned units, it is also possible to handle m ultiple sample holders simultaneously and in parallel, since the system 300 may start performing the process steps prior to steps S180 on another sample holder after performing the process step S180 according to the process.

[0125] The advantage of the methods and system according to the invention is that, unlike previously used microdissection methods, it is suitable for correcting the contours of objects according to the entire sample holder and not only according to a single field of view of the microdissection unit.

[0126] The methods according to the invention can be automated and can even be performed using unsupervised machine learning, thus greatly reducing the time required for analysis and the number of operators.

[0127] The solution according to the invention al lows for the correct ion of the distortion of the contours of objects with any degree of freedom, thus any damage or change to the sample in a given sample holder becomes manageable.

Claims

Claims1. M ethod for improving microdissection of objects in a sample holder containing a biological sample, comprising the steps of- providing (S100) at least one microscope unit (310) comprising a microscope with an object stage and an image capture unit ;- placing (S1 10) a sample holder comprising at least one biological sample on the object stage;- taking (S120a) a first digital image by the image capture unit of at least a part of the sample holder placed on the object stage and comprising the at least one biological sample;- transmitting (S130) the first digital image to a storage unit (320);- identifying (S140) objects in the first digital image stored in the storage unit (320) using at least one image analysis unit (330);- selecting at least a portion of the identified objects by the at least one image analysis unit (330) and transmitting (S150) them to the storage unit (320);- generating (S160) original contours of the selected objects by the at least one image analysis unit (330);- providing (S170) at least one microdissection unit (340) comprising at least one sample holder unit for receiving at least one sample holder com prising the biological sample and a visualization unit for taking a second digital image of the sample holder comprising the at least one biological sample;- arranging (S180) the sample holder comprising the at least one biological sample in at least one sample holder unit of the microdissection unit (340) in a way that enables the visualization unit to take a second digital image of the sample holder comprising the given biological sample; characterized in that the method further comprises- transmitting (S190) the original contours to the storage unit (320) and the at least one microdissection unit (340);- fitting the original contours to the second digital image of the at least one microdissection unit (340) and generating (S200) a third digital image;- providing at least one image correction unit (350) and transmitting (S210) the first digital image, the second digital image and the original contours to the image correction unit (350);- matching the first digital image and the second digital image by means of the at least one image correction unit (350), then aligning the original contours according to the matching, thereby creating current contours (S220);- transferring the current contours (S220) to the microdissection unit (340), and aligning the contours of the third digital image to the position corresponding to the current contours, thereby creating a fourth digital image (S230);- by means of the at least one microdissection unit (340) cutting out the objects (S240) based on the fourth digital image.

2. The method according to claim 1 , characterized in that during step S120a, multiple first digital images are taken from m ultiple fields of view by the image capturing unit of individual parts of the given sample holder comprising the biological sample, where the multiple first digital images taken from the individual parts of the given sample holder correspond to the individual fields of view, and by combining the multiple first digital images, a first digital image is created that presents the entire given sample holder.

3. The method according to claim 1 or 2, wherein in the case of using multiple microscope units (310), steps S100-120a are performed for each microscope unit (310).

4. A method for improving microdissection of objects in a sample holder comprising a biological sample, comprising the steps of- receiving (S120 b) at least one first digital image of at least one part of the sample holder having at least one biological sample;- transmitting (S130) the at least one first digital image to a storage unit (320);- identifying (S140) objects in at least one f irst digital image stored in the storage unit by means of at least one image analysis unit (330);- selecting at least a part of the identified objects by means of the at least one image analysis unit (330) and transmitting them (S150) to the storage unit (320);- generating (S160) the original contours of the selected objects with the at least one image analysis unit (330);- providing at least one microdissection unit (340), which comprises at least one sample holder unit for receiving the sample holder comprising the at least one biological sample, andcomprising a visualization unit for generating a second digital image of the sample holder comprising the at least one biological sample (S170);- placing the sample holder comprising at least one biological sample in at least one sample holder unit of the microdissection unit (340) in such a way that the second digital image is produced with the visualization unit (S180); characterized in that the method further comprises- transmitting (S190) the original contours to the storage unit (320) and the at least one microdissection unit (340);- fitting the original contours to the second digital image of the at least one microdissection unit (340) and creating (S200) a third digital image;- providing at least one image correction unit (350), transmitting (S210) the first digital image, the second digital image and the original contours at least one image correction unit (350);- aligning the first digital image and the second digital image with the at least one image correction unit (350), and then aligning the original contoursaccording to the alignment, thereby creating current contours (S220);- transmitting the current contours to the at least one microdissection unit (340), aligning the contours of the third digital image to a position corresponding to the current contours, thereby creating a fourth digital image (S230);- cutting out the objects (S240) by the at least one microdissection unit (340) based on the fourth digital image.

5. The method according to claim 4, characterized in that during step S120b, multiple first digital Im ages are taken from multiple fields of view of individual parts of the sample holder comprising the given biological sample, where the first digital images taken from the individual parts of the given sample holder correspond to the individual fields of view, and by combining the multiple first digital images, a first digital image is created that presents the entire given sample holder.

6. The method according to claim 4 or 5, characterized in that the plurality of first digital images corresponding to the plurality of fields of view of the individual parts of the sample holder comprising the given biological sample are obtained from a plurality of microscope units (310).

7. The method according to any one of claims 1 -6, characterized in that during the identification of the objects according to step S140, a phenotypic classification of the objects is performed.

8. The method according to any one of claims 1 -7, characterized in that during the selection of the identified objects according to step S150, the number of objects is reduced to a value between several thousand and several hundred objects.

9. The method according to any one of claims 1 -8, characterized in that during step S180, multiple second digital images are created from multiple fields of view of individual partsof the sample holder comprising the given biological sample, where the second digital images created from the individual parts of the given sample holder correspond to the individual fields of view, and by combining the multiple second digital images, a second digital image is created that presents the entire given sample holder.

10. The method according to any one of claims 1 -9, characterized in that after starting step S190, the method steps preceding step S190, but at least steps S140-S160, are performed on a sample holder comprising a further biological sample.

11. The method according to any one of claims 1 -10, characterized in that the sample holder is provided with marker pointsthat can be identified in both the first digital image and the second digital image, wherein step S200 is performed based on the alignment of the marker points in the first digital image and the second digital image.

12. The method according to any one of claims 1 -11 , characterized in that step S220 comprises the following steps:- taking (S221 ) the first digital image, the second digital image and the original contours;- performing segmentation on both the first digital image and the second digital image, thereby identifying the objects (S222);- if the individual objectscan be properly identified in both the first digital image and the second digital image, then based on the identified objects, merging the first and second digital images by transforming the first digital image according to the second digital image, or vice versa, (S223a); or- if the individual objects cannot be properly identified in the first digital image or the second digital image, transforming the style of the first digital image and / or the second digital image to obtain a first digital image and a second digital image of the same or similar style (S223ba), then identifying the marker points in the first digital image and the second digital image of the same or similar image style (S223bb), then merging thefirst digital image and thesecond digital imagebased on the marker pointsby transforming the first digital image according to the second digital image, or vice versa (S223bc);- transforming the original contours according to the transformation applied when merging the first digital image and the second digital image to thereby create the current contours (S224).

13. The method according to claim 12, characterized in that, based on the alignment of the first digital image and the second digital image, if necessary, the current contours are created by correcting the original contours with an arbitrary degree of freedom.

14. The method according to any one of claims 1 -13, characterized in that:- the at least one microdissection unit (340) comprises at least one collection container for collecting the cut objects, into which the objects cut in step S240 are placed (S250);- transmitting (S260) the cut objects in the at least one collection container to at least one object analysis unit (360); and- analyzing (S270) the molecular composition and / or specific physical properties of each cut object by the at least one object analysis unit (360).

15. The method according to any one of claims 1 -14, further comprising the steps of combining and analyzing (S280) the information regarding the objects according to step S140, according to step S230 and according to step S270.

16. The method according to any one of the preceding claims, characterized in that the objects in the sample holder comprising at least one biological sample are subcellular units, tissue parts, preferably single-cell units.

17. The method according to any one of the preceding claims, characterized in that the first digital image, the second digital image, the third digital image and the fourth digital image are 2-dimensional images.

18. The method according to any one of the preceding claims, characterized in that the method is performed automatically or semi-automatically, preferably by unsupervised or supervised machine learning.

19. A system (300) for performing the method according to any one of the preceding claims, the system (300) comprising:- at least one microscope unit (310) comprising a microscope having a st age for holding at least one sample holder and comprising an image capturing unit arranged to be able to take a digital image of at least a part of the at least one sample holder on the stage;- a storage unit (320) connected to the at least one microscope unit (310);- at least one image analysis unit (330) connected to the storage unit (320);- at least one microdissection unit (340) comprising at least one sample holder unit for receiving the sample holder comprising at least one biological sample and a visualization unit arranged to be able to take a digital image of at least a part of the sample holder comprising at least one biological sample in the at least one sample holder unit, wherein the at least one microdissection unit (340) is connected to the at least one image analysis unit (330); characterized in that it further comprises- at least one image correction unit (350) connected to the storage unit (320) and operatively connected to the at least one m icrodissection unit (340) in a manner capable of controlling the operation of the at least one microdissection unit (340).

20. The system according to claim 19, characterized in that the at least one microscope unit (310) and the at least one microdissection unit (340) are designed in an integrated manner.

21. The system according to claim 19 or 20, characterized in that the at least one image analysis unit (330) and the at least one image correction unit (350) are designed in an integrated manner.

22. The system of any one of claims 19-21 , further comprising at least one object analysis unit (360) connected to the at least one microdissection unit (340) and the at least one image analysis unit (330).

Images