JP2007020449A - Screening method and screening apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To carry out the screening of medicines in high accuracy by using a proper morphological character. <P>SOLUTION: The screening method comprises the analysis of cell images photographed by a microscope, the evaluation of the parameterized value of the deviation of the contour of the cell from circles C<SB>I</SB>and C<SB>O</SB>as a morphological character representing the morphological character of each cell in the cell images and the screening of medicines based on the evaluation. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a screening method and a screening apparatus using image processing, and more particularly to a screening method and a screening apparatus for comparing morphological changes of cells with respect to a cell image acquired by a microscope.

  Evaluating the effects of various drugs and searching for particularly effective drugs is generally referred to as drug screening. In particular, in drug screening using living cells, after the drug is administered, an appropriate stimulus is applied to the cultured cells, and the difference in the cells from the cells that have not been stimulated is quantified to measure the drug effect. In these drug screenings, each treatment is usually performed by a human.

However, the stage of evaluating drug efficacy by observing cells in drug screening is usually carried out by human work. However, in screening that searches for a large amount of drugs, the burden on the experimenter is considerable, so it can be automated. It has become a challenge. A method for analyzing an image of a cell is disclosed in Patent Document 1, for example.
JP 2001-269195 A

Automation can be divided into a step of acquiring a cell image and a step of analyzing the acquired cell image. The analysis of the cell image is performed by extracting the feature amount of the cell using an appropriate image processing method and comparing the feature amount values in the cell images under different conditions.
However, there is a problem that the evaluation accuracy of the drug effect is often not high because noise is often not removed during the program processing.

  In the extraction of feature quantities of cell morphology, the first problem is to acquire feature quantities accurately and accurately. The accuracy is primarily the accuracy of the analysis stage for acquisition. This is often caused by analysis software programs, etc., and there is also an idea of accuracy for medicinal properties. Is not expressed well. In the case where there is no difference in the effect with the feature amount, although the effect should be originally a drug, it can be said that the accuracy is low, but this is the accuracy depending on how the experimental system is set.

  The main reason for the low accuracy of morphological features is the inclusion of image noise due to substances other than living cells contained in the cell image in the features. The following are examples of inappropriate choices.

  This invention is made | formed in view of the situation mentioned above, Comprising: It aims at providing the screening method and screening apparatus which can perform a more accurate chemical | medical agent screening using a suitable form feature-value.

In order to achieve the above object, the present invention provides the following means.
The present invention analyzes a cell image acquired by a microscope, evaluates a value obtained by parameterizing a deviation amount from a circle of a cell outline as a morphological feature amount representing a morphological feature of each cell in the cell image, A screening method for conducting drug screening based on this evaluation is provided.
In the present invention, as the morphological feature amount, a value obtained by parameterizing a deviation amount from at least one of an inscribed circle or a circumscribed circle of the outline of the cell may be evaluated.
By these, the size of the central part of the cell, the distortion of the whole shape, and the spatial spread of the cell can be grasped in a unified manner, and the morphological change of the cell can be expressed efficiently and accurately. .

  In addition, the present invention analyzes a three-dimensional image constructed from a plurality of cell images acquired by a microscope, and uses a morphological feature amount representing a morphological feature of each cell in the cell image as a deviation from the sphere of the cell outline. Provided is a screening method for evaluating a value obtained by parameterizing an amount and performing drug screening based on the evaluation.

In the above invention, as the morphological feature amount, a value obtained by parameterizing a deviation amount from at least one of the inscribed sphere or the circumscribed sphere of the cell outline may be evaluated.
Moreover, in the said invention, based on the said morphological feature-value, it is preferable to determine the cell in an image as either a living cell or a dead cell, and to use for evaluation.
In this determination, it goes without saying that the cells may be fixed before image acquisition.
Furthermore, in the above invention, analysis is performed on any region selected in the cell image, and these regions are classified into cell bodies, cell protrusions having a cyclic structure, and cells other than cells based on the parameterized values. It is preferable to classify into cell dead bodies or bubbles.

Moreover, in the said invention, it is preferable to quantify the image information other than the classified cell, and correct | amend the statistical result of the drug screening with respect to a cell using image information other than the quantified cell.
In fact, in a system that damages cells and kills some cells, not only the amount of living cells or the number of dead cells that preserve the shape of the cells to some extent, but also fragmented cells The accuracy of cell analysis is improved by quantifying image information other than cells existing in a cell image such as a dead body and using it as additional information for image analysis results targeting only cells.

Furthermore, in the said invention, it is good also as estimating that the change of the form of a cell originates in that the cell received damage, and quantifying the cytoprotective effect by a chemical | medical agent.
The main types of drugs that are targeted for cell-based drug screening are those that protect cells and reduce cell damage, control cell activation, inhibit division, and promote growth. There are drugs that have the effect of letting go.

In the process of damaging and dying cells, the shape generally becomes round and external organs such as protrusions contract. Furthermore, at the stage of complete death, it becomes considerably smaller than normal cells.
The medicinal properties of drugs that protect cells are the ratio of the number of dead cells to the number of surviving cells for a certain amount of damage, or the roundness of cells as a characteristic quantity that expresses more detailed medicinal effects. There is.

  On the other hand, cells activated by some effect of the drug, for example, the outer segment organ grows and grows, or the shape of the cell changes from a round shape to an ellipse shape due to the movement of the cell itself on the culture plate. A state of dripping is observed.

  Moreover, in the said invention, distortion from the circle | round | yen of a cell form may be interpreted as what originates in the motion of a cell, and it is good also as using the said form feature-value as a parameter | index which measures the activation with respect to the cell of a chemical | medical agent.

  Furthermore, in the above invention, in the screening method for nerve cells, information on the protrusions of each cell having a classified tubular structure is used as a morphological feature amount, and the total amount of the tubular structure correlates with damage taken by the cell. It is also possible to estimate and quantify the drug effect.

  Moreover, in the said invention, it is good also as using the cell sample comprised by several types.

  Furthermore, in the said invention, it is good also as performing similar evaluation about the cell type of interest and other cell types.

  Further, the present invention provides an illumination unit that irradiates a cell with illumination light, an image information input unit that detects light emitted from the cell and acquires image information, and image information acquired by the image information input unit. Image information processing means for parameterizing morphological feature quantities representing morphological features of each cell; evaluation means for evaluating morphological feature quantities parameterized by the image information processing means and performing drug screening on the cells; and There is provided a screening apparatus comprising output means for outputting and displaying a result of drug screening by an evaluation means.

In the above invention, it is preferable that the evaluation unit uses a deviation amount of a cell outline from a circle or a sphere as the morphological feature amount.
Moreover, in the said invention, it is preferable that the said evaluation means discriminate | determines the life or death of each cell based on the said form feature-value.
Furthermore, in the said invention, it is good also as performing the same evaluation about the cell type of interest and other cell types using a multiple types of cell sample.

  According to the present invention, it is possible to perform drug screening with higher accuracy using an appropriate morphological feature amount.

Hereinafter, a screening method and a screening apparatus according to an embodiment of the present invention will be described with reference to the drawings.
Before describing the screening method and apparatus according to this embodiment, a cell image analysis method will be described.

(Outline of cell analysis)
Consider a method of automating cell image analysis in an experimental system for observing cells such as drug screening.
The purpose of image analysis here is to identify the location of individual cells on the image, extract the feature quantities of each cell, and perform appropriate statistical processing on these feature quantities to create multiple cells. It is to provide means for comparing images.

  The flow of analysis processing will be described with reference to FIG. First, target cells are cultured (S1). Next, an appropriate pretreatment such as staining is performed to prepare for visualization (S2). The cells are fixed as necessary. These cell samples are set in an optical system such as a microscope and imaged (S3). The captured cell image is digitized and stored in a computer or the like (S4). These images are processed and analyzed on the computer (S5).

Next, each processing stage will be described.
(Preprocessing)
The cells cultured by an appropriate method are subjected to processing for imaging.
The processing for imaging is administration of a fluorescent substance. The cells are visualized by these processes.

(Optical system, imaging system, data storage)
In an optical system, observation is performed by applying light of an appropriate wavelength to cells. At this time, an appropriate camera is set in the optical system and photographing is performed. The imaging system usually uses a CCD or the like to digitize the image and store it in a personal computer or the like as data.

The cell image acquired by the above method is a color or monochromatic image. The image is stored as data having a width in the vertical and horizontal directions such as 1000 × 1000. The coordinates representing the position are assigned to each point on the image, and each point has the brightness of each color.
The brightness of the coordinates (x, y) is expressed as “230”, for example, and stored as digital data.

(Outline of image analysis)
Image analysis is a method of analyzing these digital data by performing appropriate processing with a software program on a personal computer.
In particular, in image analysis using cells, the primary purpose is to recognize cells, but cell recognition is usually performed directly by an experimenter.

  Although it depends on the type of experiment, in general, a microscope image (or field of view of the microscope) is observed, and in the image, “whether or not a cell is present”, “if a cell is present, where is the position of the cell? ”,“ The number of cells in the image ”,“ How many types of cells are in the image ”,“ How many cells of a particular type ”,“ How big are each cell? ” Recognize, record, and provide data for experiments.

  It is possible to perform statistical processing on these data and perform various interpretations in association with the imaging conditions of each cell image and the cell culture conditions. In particular, it is possible to screen for drugs such as compounds by detecting differences in form depending on drugs.

(Compound screening)
Experiments using cells are performed for various purposes. Here, the purpose and flow of the experiment will be briefly described, particularly using a cell-based compound screening as an example.

Cell-based compound screening aims to find effective drugs, and is performed by administering an appropriate compound or the like to a target cell and quantifying the influence of these compounds on the cell.
Furthermore, these quantified data are compared with the case of multiple compounds, and the purpose is to find out some of these compounds that have a significant effect on the cells and which are effective. .

(Screening procedure)
As shown in FIG. 2, the sample cells are usually classified into several groups (cell groups G1 to GN) (S11).
For example, in an experimental system for measuring the effect of a compound on a cell, the cell group G1 or the like to which a compound is added is divided into a cell group GN that is not.
An image is taken for each of these classified groups using an appropriate optical system such as a microscope (S12).
Usually, a plurality of images are taken for each group, and each image contains an appropriate number (several tens) of cells.

Next, the cell image imaged and stored by the above method is analyzed.
By analyzing the cell image, features such as the position of the cell present in the image, the amount of light emission of each cell, and the presence or absence of a size protrusion are extracted.
The cell features are averaged or analyzed for each group or image, and the difference between groups is detected and compared with the group conditions such as whether or not a compound is introduced. (S13).

(Details of the issue)
However, in the actual drug screening, however, there is a problem that the evaluation accuracy of the drug effect is often not high.

(Definition of feature extraction, examples of selection mistakes)
The first conceivable reason for this is that it is a low-accuracy analysis, although it is desired to perform a feature extraction process for cell morphology.

The reason why the accuracy of the morphological feature amount is low is that the definition / selection of the set feature amount is not appropriate as an amount representing the feature of the cell morphology.
For example, considering the case where the cell size is extracted as the cell morphology amount, an example in which the feature amount does not appropriately correspond to the cell morphology is given.
As the “cell size”, there is usually a method in which the distance L between two points having the largest distance on the boundary of the cell A is defined as the size. According to this method, for example, when the cell A as shown in FIG. 3 extends in a specific direction, it cannot be said that the size of the cell A is appropriately expressed.

  In particular, when the shape of the cell A is not close to a circle or many are distorted, it is difficult to accurately estimate the size of the cell A. Although the above example is considered to be applicable to such a case, in this experimental system, it can be said that the definition of the size of the cell A does not match the actual shape of the cell and is not appropriate.

(Accuracy problems caused by processing methods such as noise removal methods)
The fact that image noise caused by substances other than living cells contained in the cell image is included in the feature amount is cited as a second cause of reducing the measurement accuracy of the cell feature amount. This will be explained by taking an example of screening for a drug having an action of protecting cells.

As an example of such screening, a system that gives a stimulus to a cultured cell so that about half of the cells are killed can be considered. A method of evaluating the protective effect of the cells depending on how much the cell survival rate is increased by administering a drug to this cultured cell system is conceivable. Here, cell viability is performed by directly comparing the number of living cells.
The problem with this method is that some cells that have been killed by the stimulus may remain in the culture plate or medium.

In order to remove the dead bodies of these cells, for example, an operation such as washing before observing the cultured cells with a microscope is necessary.
In the actual experimental process, time and cost increase by adding such one process. This is not preferable in drug screening in which a large amount of drug samples are analyzed.
Under such circumstances, in the screening system as described above, it is necessary to consider a highly accurate analysis processing method on the assumption that living cells and cell dead bodies are mixed in the cell image.

As a method for solving the above problems, the screening method according to the present embodiment will be described below.
In the screening method according to the present embodiment, first, as the morphological feature amount expressing the morphology of the cell A, the deviation amount of the contour shape of the cell A from the circle or sphere is used.

  Although cell A dies by being stimulated, this process results in a continuous morphological change of cell A. In general, the cells A that are close to death after being stimulated are rounded for reasons such as loss of activity.

On the contrary, the shape of the actively active cell A usually has a considerable distortion with a circular or spherical shape as a standard.
Therefore, by adopting the deviation amount from the circle or sphere as the morphological feature amount of the cell A, it is considered that the life / death determination and the activity estimation can be performed.

Specifically, morphological feature amounts are extracted by the following method.
First, the image processing to extract the boundary of the cell A, further, as shown in FIG. 4, to obtain the circumscribed circle C _O of the maximum radius of the inscribed circle C _I and the minimum radius of the boundary of the cell A. Here, the radius of the circle, the area ratio of the cell region to the region included in the circle, and the like are used as the morphological feature amount of the cell A.
In particular, consider the case where cells are three-dimensionally overlapped (see FIG. 8). When a cell with an arrow in the figure is taken out and analyzed, it is necessary to analyze the cell in three dimensions.

When analyzing a three-dimensional cell A in three dimensions, the three-dimensional cell A image is obtained by changing the object itself, such as a plate, in the up-and-down direction and acquiring a two-dimensional image almost continuously. Configured based on data.
In such a case, as shown in FIG. 5, among the cross sections A _{1 to} A _N of the cell A, by analyzing the cross section passing through the center of the cell A by the above method, Quantification of the parameters described in (1) can be performed.

Here, the cross section passing through the center of the cell A is the vertical position where the inscribed circles C _{I1 to} C _IN are the largest with respect to the two-dimensional images obtained for the cross sections at different positions in the vertical direction of each cell A. Is defined as the horizontal cross section passing through.

(Characteristics of circles and cells)
From these morphological features, the size of the central portion of the cell A, that is, the size of the substantial cell A, the area ratio of the above area, the distortion of the overall shape, and the radius of the circumscribed circle The spatial extent of A can be grasped in a unified manner, and the morphological change of the cell A can be expressed efficiently and accurately.

This method, for example, can be identified as the central portion included in the inscribed circle C _I believed also that substantial portion against distorted cell A as shown in FIG. 4, simply long Compared with the case where the length L is taken, the activity of the cell A and the like can be evaluated at a value closer to the actual value.

Moreover, according to the screening method which concerns on this embodiment, the life and death of each cell A can be judged.
Furthermore, by using this method, it is possible to classify various types such as detection of specific cell organs such as protrusions, dead bodies of cells, fragments of dead bodies, and so-called noise such as bubbles.

  A specific method for dividing an image into a plurality of regions from the above method and classifying the region into a region corresponding to a cell body, a region corresponding to a cell protrusion, or a region not included in a living cell such as a cell dead body is as follows. It is as follows.

For example, many cell bodies have a shape close to an ellipse. In this case, the radius of the inscribed circle C _I and the circumscribed circle C _O can be determined because it falls within several times.
Further, for example, cells of the projections, generally although partial structure of a cell taking tubular structure more common, in this case, the inscribed circle C _I is small, since the circumscribed circle C _O is large, these radii ratio is large.

Also, in the process of cell death, the process of the cells gradually contracts and approaches a perfect circle as a whole. Therefore, a dead cell or a dying cell has a radius ratio between the inscribed circle C _I and the circumscribed circle C _O of approximately 1, and the radius of the inscribed circle C _I is also small.
By the method as described above, it becomes possible to classify the cells based on the feature amount defined using the inscribed circle C _I and the circumscribed circle C _O.

Furthermore, these feature quantities can be used as an index directly representing the effect of the drug by interpreting as follows.
Since cells have the characteristic of contracting when they are damaged by stimulation, if the distortion of the cell shape from the circle is interpreted as the damage received by the cells, it can be used as an indicator of the protective action of the drug.

  In addition, if the cell motility activity is high, it is considered that the degree of change in the shape of the cell boundary is large. Therefore, when the distortion of the cell shape from the circle is interpreted as being caused by cell movement, It can be used as an index for measuring activation.

There are various categories of drug screening. For example, an agent that protects cells, or an agent that activates cells to promote growth or promote division.
Although the screening method and the cell analysis method are different for each category of these drugs, the analysis method of the present invention can be applied in any case.

  In the case of a drug that protects cells, the ratio between the number of living cells and the number of dead cells is the primary indicator of drug efficacy. This can be measured by determining the life and death of the cells in the image by this method, classifying the number of each cell, and taking the ratio thereof.

  On the other hand, in the case of a drug that activates cells or suppresses cell activation, if there are many cells that die, it is not appropriate as a drug in the first place and is excluded from candidates. Here, for example, an index expressing the activity of a cell is such as how close a cell body or cell nucleus approaches an ellipse. Specifically, the following processing can be considered.

  This process first classifies the area in the image into a partial area that is estimated to be a cell and an area that is estimated to be a carcass fragment other than a cell, and if the dead body area is larger than the cell area, In the cell area, the cell body is classified into the cell body that exists at the center of the cell and constitutes the majority, and the outer segment area such as other protrusions. In particular, the ellipticity of the cell body area is obtained and averaged. Quantification is performed for each image and each experimental condition, and the efficacy of each is quantified.

  Therefore, the screening method described above can be applied to various drug screening systems such as the quantification of drug efficacy with cytoprotective action and the drug efficacy quantification of drug with cell activation activity.

  Further, in the present embodiment, the feature amount is corrected using image information other than cells that is not taken into consideration in normal cell image processing.

(Noise-containing image processing method)
In the system that damages the aforementioned cells, some of the cells die, but the dead bodies of these dead cells often remain in the image, causing noise inherent to the system, This is a cause of reducing the accuracy of feature quantity analysis.

  In normal analysis, image information other than cells, such as cell dead bodies, is usually removed by appropriate function processing or the like.

On the other hand, in the screening method according to the present embodiment, the feature amount is corrected using the image information that is normally removed.
For example, in the above-described system in which the number of cells is counted and used as an index of cytoprotective action, the number of cells is not always strictly controlled in advance. For this reason, a method of averaging the total number of cells by observing many cell images in the same category, that is, under similar conditions, and suppressing variations in the number of cells in the image is taken.

However, averaging and correcting by such a method in cell screening is not a preferable correction method because it increases the analysis time of the experiment.
In this embodiment, for example, by dividing the total number of cells by the number of dead cells, the proportion of cells that are dead or alive can be accurately estimated with respect to the number of cells before the stimulation.

In addition to correcting for the number as described above, for example, when evaluating cell damage using morphological distortion, the total number of dead cells or the total area of the dead cell area both corresponded to cell damage. It is a feature quantity.
Therefore, the amount of damage received by the cells can be corrected by comparing or averaging them, and a value closer to the actual cell damage can be given.

  As described above, it is expected that the accuracy of cell analysis can be improved by quantifying image information other than cells and using it as additional information of image analysis results targeting only cells.

In particular, when screening is performed using nerve cells, screening may be difficult because of the more specific form compared to normal cells.
For example, when considering a system in which the total length of protrusions having a tubular structure of nerve cells is a feature quantity expressing the form, the total length of protrusions varies greatly depending on the cell, or is easily affected by drugs, etc. It is considered that there are many cases where a large error is included in the result of the analysis process because it is difficult to detect in terms of image analysis compared to the body.

  In such a case, by using information such as cell dead bodies, two cell damage indices can be obtained, more appropriate values can be derived, and overall screening accuracy can be expected to increase. .

In such an experimental system for observing cells subjected to appropriate treatment such as drug administration, not only the type and amount of the drug, but also the culture conditions are often important factors affecting the results. it is conceivable that.
Cells are generally considered to be interacting with each other, and this interaction is considered not only between the same cell types but also between different cell types.

By the way, when observing a sample in which a plurality of cell types are cultured together, it is necessary to first perform a process of identifying the plurality of cell types.
As a method of classifying the cell type, a method of judging from a qualitative one such as a difference in the morphology or staining of each cell or a quantitative difference such as a fluorescence amount can be considered.

After performing these processes, feature amount extraction and the like are performed by the same procedure as the analysis performed on the single cell type described above, and changes to the drug are quantified.
By classifying sample cells into cell types, etc., and recording changes in the amount of features in each category, the data can be interpreted in more detail. For example, it can be effective by searching for effective drugs. Then you can expect.

In addition, when culturing a plurality of cell types, it is expected that the results will differ depending on the mixing ratio of the cells. Therefore, the information and the mixing ratio are also used.
Moreover, it can be expected that, for example, a more accurate drug search can be performed by comparing not only the cell ratio but also the difference in the response of each cell type to the drug.

The method of using these pieces of information is the same as the method of correcting using, for example, cell dead bodies.
For example, in a system including two cell types of the cell group G1 and the cell group G2, a result that 60% of the cell group G1 is killed and 10% of the cell group G2 is killed by applying a constant stimulus after drug administration. Suppose that In this case, for example, it can be interpreted that this drug has a role of selectively protecting the cell group G2.
In general, it can be expected that more detailed analysis can be performed by comparing results between different cell types.

Next, a screening apparatus according to an embodiment of the present invention will be described with reference to FIG.
FIG. 6 shows the overall configuration of the screening apparatus 1 according to this embodiment. The screening apparatus 1 according to the present embodiment includes an illumination optical system 3 including a light source 2 that generates excitation light, a positioning stage 5 on which a plate 4 on which a sample B including cells such as animals and plants to be observed is disposed, A light receiving optical system 7 including a CCD camera 6 that captures fluorescence emitted from the sample B, an image processing unit that processes an image acquired by the CCD camera 6 and extracts morphological features, and an extracted morphological And a screening unit that performs drug screening using the feature amount.

The illumination optical system 3 includes a condenser lens 9 that irradiates the sample B with excitation light from the light source 2.
The positioning stage 5 can move the plate 4 so as to focus on the sample B.

  The light receiving optical system 7 is provided with a filter 8 having optical characteristics that transmits fluorescence in a specific wavelength band. The filter 8 can be exchanged, and can be exchanged according to the wavelength band to be transmitted.

  As the image processing unit and the screening unit, a general-purpose processing device that is operated by a computer program, such as the computer 10, is used. The computer 10 has a computer program for causing it to function as an image processing unit, such as cell center extraction processing, center point examination processing, cell boundary extraction processing, individual cell feature extraction processing, total cell number extraction processing, and the like. The thing that realizes is installed. The computer 10 is also installed with a computer program for executing the screening method according to the present embodiment in order to function as a screening unit.

  In order to perform drug screening using the screening apparatus 1 according to the present embodiment, first, a sample B such as a cell sample is prepared on the plate 4 as shown in FIG. In the cell sample preparation step S21, the sample B is prepared under various conditions to be observed. Next, in the sample operation step S22 for staining and light emission, an appropriate staining method and an operation for causing light emission are performed on the sample B. In the sample setting step S23, the plate 4 prepared in this way is fixed to the positioning stage 5, and the positioning stage 5 is operated to perform observation position alignment and focus position alignment operation. Irradiate towards cell sample B.

  Since fluorescence is emitted from the sample B irradiated with the excitation light, the emitted fluorescence is collected by the objective lens 11, and only the fluorescence in a predetermined wavelength band is selected by the filter 8. In the image capturing step S24, the CCD camera 6 to take an image. Further, if necessary, various imaging conditions such as exchanging the filter 8 while the sample B is fixed are changed (S25) to perform imaging. Alternatively, the imaging position is changed as necessary (S26) and imaging is performed.

The fluorescence image information acquired by the CCD camera is sent to the image processing unit, and an image processing step S27 is performed.
In the image processing step S27, first, a point that becomes the center of each cell of each image is extracted (S271). Further, the extracted center point is examined, and an appropriate cell center point from which the inappropriate center point of the cell is removed is extracted (S272). Subsequently, the most appropriate cell boundary surrounding these cell center points is extracted (S273). Then, using the obtained cell boundary, the screening method described above, that is, extraction of the morphological feature amount of each cell and calculation of the total number of cells are performed (S28), and drug screening is performed based on this (S28). S29).

  Thus, according to the screening method and apparatus according to the present embodiment, there is an effect that drug screening using cells can be realized with high accuracy.

It is a flowchart which shows the flow of an image analysis process. It is a flowchart which shows the procedure of a screening. It is a figure explaining an example of the extraction method of the feature-value in the conventional screening. It is a figure explaining the extraction method of the feature-value in the screening method which concerns on one Embodiment of this invention. FIG. 5 is a diagram for explaining a feature amount extraction method when performing a three-dimensional analysis in the screening method of FIG. 4. It is a schematic diagram which shows the screening apparatus which concerns on one Embodiment of this invention. It is a flowchart explaining the screening procedure using the screening apparatus of FIG. It is a figure explaining the case where it is necessary to perform a three-dimensional analysis in the screening method of FIG.

Explanation of symbols

A cell _{C I,} C I1 ~C _IN inscribed circle _{C O,} C O1 ~C _ON circumcircle 1 screening device 3 illumination optical system (illumination means)
6 CCD camera (image information input means)
10 Computer (screening unit, evaluation unit, image processing unit, image information processing unit)

Claims (16)

Analyzing cell images acquired with a microscope,
As a morphological feature amount representing the morphological feature of each cell in the cell image, a value obtained by parameterizing the amount of deviation from the circle of the cell outline is evaluated,
A screening method for performing drug screening based on this evaluation.   The screening method according to claim 1, wherein a value obtained by parameterizing a deviation amount from at least one of an inscribed circle or a circumscribed circle of a cell outline is evaluated as the morphological feature amount. Analyzing a three-dimensional image constructed from a plurality of cell images acquired by a microscope,
As a morphological feature amount representing the morphological feature of each cell in the cell image, a value obtained by parameterizing the deviation amount of the cell outline from the sphere is evaluated,
A screening method for performing drug screening based on this evaluation.   The screening method according to claim 3, wherein a value obtained by parameterizing a deviation amount from at least one of an inscribed sphere or an circumscribed sphere of a cell outline is evaluated as the morphological feature amount.   The screening method according to any one of claims 1 to 4, wherein a cell in an image is determined as either a living cell or a dead cell based on the morphological feature amount and used for evaluation. Analyze one of the selected areas in the cell image,
6. The screening method according to claim 1, wherein these regions are classified into cell bodies, cell protrusions having a cyclic structure, dead bodies of cells other than cells, or bubbles based on parameterized values. Quantify image information other than the classified cells,
The screening method according to claim 6, wherein the statistical result of drug screening for cells is corrected using image information other than the quantified cells.   The screening method according to claim 7, wherein the change in cell morphology is estimated to be caused by damage of the cells, and the cytoprotective action by the drug is quantified. Interpret the distortion of the cell shape from the circle as a result of cell movement,
The screening method according to any one of claims 1 to 4, wherein the morphological feature amount is used as an index for measuring activation of a drug to cells. In the screening method for nerve cells,
Using information on the protrusions of each cell with a classified tubular structure as a morphological feature,
Estimating that the total amount of tubular structure correlates with the damage taken by the cells,
The screening method according to claim 6, wherein the drug effect is quantified.   The screening method according to any one of claims 1 to 10, wherein a cell sample composed of a plurality of types is used.   The screening method according to claim 11, wherein the same evaluation is performed for the cell type of interest and other cell types. Illumination means for illuminating cells with illumination light;
Image information input means for detecting light emitted from cells and acquiring image information;
In the image information acquired by the image information input means, an image information processing means for parameterizing a morphological feature amount representing a morphological characteristic of each cell;
An evaluation means for evaluating a morphological feature parameterized by the image information processing means, and performing drug screening on cells;
A screening apparatus comprising: output means for outputting and displaying a result of drug screening by the evaluation means.   The screening apparatus according to claim 13, wherein the evaluation unit uses a deviation amount of a cell outline from a circle or a sphere as the morphological feature amount.   The screening apparatus according to claim 13 or 14, wherein the evaluation unit determines whether each cell is live or dead based on the morphological feature amount.   The screening apparatus according to any one of claims 13 to 15, wherein a plurality of types of cell samples are used and the same evaluation is performed for a cell type of interest and other cell types.

Images