Quality control methods and quality control products for immunohistochemical staining

Abstract

The present invention discloses a quality control method and a quality control product for immunohistochemical staining. The quality control method comprises the following processes: obtaining an animal or a commercially available organ or tissue, making a quality control wax block with the organ or tissue, slicing the quality control wax block to obtain a quality control section, wherein the quality control section comprises at least two parts with different proliferating cell antigen densities; synchronously performing immunohistochemical staining on a human sample to be detected and the quality control section, respectively obtaining a pathological image of the human sample to be detected after immunohistochemical staining and a quality control image of the quality control section; extracting proliferating cell antigen indexes of at least two parts with different proliferating cell antigen densities from the quality control image; comparing the proliferating cell antigen indexes of each part with their corresponding proliferating cell antigen standard indexes respectively to judge the quality of the immunohistochemical staining. The present invention can evaluate the quality of immunohistochemical staining more accurately, objectively, comprehensively, qualitatively and quantitatively.

Description

Technical Field

[0001] The present invention relates to the field of pathological examinations, and more specifically, to a quality control method and a quality control product for immunohistochemical staining. Background Art

[0002] Immunohistochemical staining applies the basic principle of immunology - the antigen-antibody reaction, that is, the principle of specific binding of an antigen to an antibody. By means of a chemical reaction, a chromogenic agent (fluorescein, enzyme, metal ion, isotope) labeled with an antibody is made to develop color to determine antigens (polypeptides and proteins) in tissue cells, and to conduct research on their localization, qualitative and relative quantitative analysis, which is called immunohistochemistry or immunocytochemistry. Immunohistochemical staining is increasingly widely used in surgical pathology and other morphological fields, and has become an indispensable tool for disease diagnosis in pathology.

[0003] The quality of immunohistochemical staining operation directly affects the pathological diagnosis result. Therefore, quality control is an essential procedure for testing the quality of immunohistochemical operation and a prerequisite for ensuring the accuracy of test results. A series of inspection and control measures taken within a laboratory or between laboratories to monitor and evaluate the working quality within the laboratory or between laboratories in order to decide whether to issue a test report are called the quality control methods for in-house / inter-laboratory immunohistochemical staining.

[0004] In the prior art, standardized quality control products have been very widespread and popular for general blood detection methods. However, for quality control products for histological sample detection, they are relatively rare in clinical applications at present, and the existing quality control methods only give negative or positive results, lacking quantitative evaluation. Not only are the evaluation results inaccurate, but also it is impossible to determine what causes improper operation, which is not conducive to improving the operation process. Summary of the Invention

[0005] The object of the present invention is to overcome the above-mentioned defects existing in the prior art, and to provide a quality control method and a quality control product for immunohistochemical staining to improve the quality control quality of immunohistochemical staining.

[0006] To achieve the above object, the technical solution of the present invention is as follows:

[0007] A quality control method for immunohistochemical staining, comprising the following process:

[0008] Obtain an animal or a commercially available organ or tissue, make a quality control wax block with the organ or tissue, section the quality control wax block to obtain a quality control section, and the quality control section includes at least two parts with different proliferating cell antigen densities;

[0009] The sample of the person to be tested and the quality control slide are synchronously subjected to immunohistochemical staining, and the pathological image of the sample of the person to be tested after immunohistochemical staining and the quality control image of the quality control slide are respectively obtained;

[0010] The proliferation cell antigen index of the parts with at least two different proliferation cell antigen densities is extracted from the quality control image;

[0011] The proliferation cell antigen index of each part is respectively compared with its corresponding proliferation cell antigen standard index to judge the quality of the immunohistochemical staining.

[0012] The present invention also provides a quality control product for immunohistochemical staining, including a quality control slide, which is obtained by making a quality control wax block with an animal or a commercially available organ or tissue and slicing the quality control wax block, and the quality control slide includes parts with at least two different proliferation cell antigen densities.

[0013] Implementing the embodiments of the present invention will have the following beneficial effects:

[0014] During the immunohistochemical process, normal antigens (i.e., cell antigens that have not undergone proliferation and division) and proliferation cell antigens are respectively marked with different colors. The proliferation cell antigen index represents the ratio of the proliferation cell antigen to the total number of antigens, and the total number of antigens is equal to the sum of the normal antigen and the proliferation cell antigen. The process of extracting the proliferation cell antigen index from the quality control image is the process of identifying the normal antigen and the proliferation cell antigen marked with different colors. If the identified proliferation cell antigen index is close to the proliferation cell antigen standard index corresponding to this part (within a certain allowable error range), it is judged that the staining of both the normal antigen and the proliferation cell antigen is qualified, and the process of identifying the quantity (including manual visual identification and computer AI identification) is also qualified.

[0015] The density of the proliferation cell antigen determines the density value of the color points of the proliferation cell antigen. The density of the color points directly affects the proliferation cell antigen index. If the staining is too deep, the extracted proliferation cell antigen index will be larger than the proliferation cell antigen standard index. For tissues or parts with a large density, the obtained proliferation cell antigen index will deviate more from the proliferation cell antigen standard index. If the staining is too light, the extracted proliferation cell antigen index will be smaller than the proliferation cell antigen standard index. For tissues or parts with a small density, the obtained proliferation cell antigen index will deviate more from the proliferation cell antigen standard index. The present invention can accurately evaluate whether the staining depth is qualified by extracting the proliferation cell antigen indices of parts with at least two different proliferation cell antigen densities and respectively comparing them with their corresponding standard indices. If the indices of different proliferation cell antigen densities are all close to the corresponding standard indices, it is not only judged that the staining depth is qualified, but also judged that the staining of the normal antigen and the proliferation cell antigen and the process of identifying the quantity are all qualified.

[0016] In addition, the proliferating cell antigen index is a quantitative value that can reflect the degree of deviation from the standard index. Different levels of quality control evaluations such as excellent, good, and poor can be given according to the degree of deviation from the standard index, enabling quantitative evaluation of the quality control quality. Moreover, according to the degree of deviation from the standard index, the reasons for unqualified staining can also be known, facilitating the operator to improve the operation process. Most of the existing technologies use positive or negative evaluations for quality control quality, lacking quantitative evaluations. Not only are the evaluation results inaccurate, but it is also impossible to determine the reasons for improper operation, which is not conducive to improving the operation process.

[0017] In summary, the quality control method of the present invention can evaluate the quality of immunohistochemistry more accurately, objectively, comprehensively, qualitatively and quantitatively, ensuring that the proliferating cell antigen index extracted from the pathological images of the samples to be tested is reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Among them:

[0020] Figure 1 is a schematic flow chart of the quality control method for immunohistochemical staining in a specific embodiment of the present invention.

[0021] Figure 2 is a schematic structural diagram of a quality control wax block in a specific embodiment of the present invention.

[0022] Figure 3 is a schematic structural diagram of a quality control product in a specific embodiment of the present invention.

[0023] Figure 4 is a schematic diagram of a quality control image after staining of a quality control slide in a specific embodiment of the present invention.

[0024] Figure 5 is Figure 4 a schematic diagram of the proliferating cell antigen density in regions A, B, C, and D in

[0025] Figure 6 is a quality control image after staining for Ki67 antigen in a specific embodiment of the present invention.

[0026] Figure 7 is in a specific embodiment of the present invention for Figure 6 the schematic diagram of the interpretation result of the quality control image shown by using the medical image processing method of deep learning.

[0027] Figure 8 is the result diagram of the fusion of Figure 7 and Figure 6 .

[0028] Figure 9 is the distribution diagram of the M value in a specific embodiment of the present invention. Specific Embodiments

[0029] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0030] Refer to Figure 1 , the present invention discloses a quality control method for immunohistochemical staining, including the following steps:

[0031] S1: Obtain an animal or a commercially available organ or tissue, use the organ or tissue to make a quality control wax block 10, refer to Figure 2 , section the quality control wax block to obtain a quality control slide 20, and the quality control slide includes at least two parts with different proliferating cell antigen densities.

[0032] In this step, for the animal or commercially available organ or tissue, the animal can include pigs, hamsters, cows, sheep, etc., and the commercially available organ or tissue can include cloned or in vitro cultured organs or tissues. The organ or tissue can include one or more of 3D organs such as the liver, lung, kidney, spleen, large intestine, small intestine, appendix, lymph node, bladder, pancreas, uterus, ovary, pituitary gland, fetal membrane, heart, and brain, or can also include a tumor cell model, etc. The organ or tissue in the present invention is preferably a non-lesioned organ or tissue (i.e., a biological sample of a factory-standardized organ or tissue). When comparing with the standard index, the data is more accurate and the source is stable. Most of the existing solutions use discarded pathological specimens from patients, and the source is unstable.

[0033] The animal or commercially available organ or tissue is preferably the small intestine of an animal because the small intestine contains various glands with different proliferating cell antigen densities. The animal or commercially available organ or tissue can also preferably be the liver of an animal because the tissue structure of the liver is relatively uniform. Refer to Figure 2 , in a specific embodiment, the small intestine 11 and liver 12 of a pig are used as biological samples to make a quality control wax block 10. Of course, in other feasible embodiments, various other organs or tissues described above can also be used.

[0034] Proliferating cell antigens can be Ki67 antigen, HER2 antigen, EGFR antigen, ER antigen, PD-L1, etc. In the present invention, the detection and evaluation indexes of the common Ki67 antigen in daily pathological clinical work will be elaborated.

[0035] S2: Synchronously perform immunohistochemical staining on the human sample to be tested and the quality control slide 20, and respectively obtain the pathological image of the human sample to be tested after immunohistochemical staining and the quality control image of the quality control slide.

[0036] Reference Figure 3 , which is a quality control product for immunohistochemical staining in a specific embodiment of the present invention, includes a glass slide 30, a quality control slide 20 and an information label 40 provided on the glass slide 30. The glass slide 30 is also provided with a vacancy for setting the human sample to be tested. The human sample to be tested can be a wax block section embedding the human sample to be tested, or any form of sample such as a suspension or a smeared secretion. The quality control slide 20 is the quality control slide mentioned in step S1 and will not be elaborated here. The quality control slide of the present invention adopts factory-standardized animal organs or tissues, which not only has stable quality inspection performance, but also is easy to obtain, has a stable source, low cost, and can be mass-produced.

[0037] The steps of immunohistochemical staining usually include: baking the slide, dewaxing, rehydrating, antigen retrieval, washing with PBS solution, removing H2O2 enzyme, washing with PBS solution, blocking, adding the primary antibody, washing with PBS solution, adding the HRP-labeled secondary antibody, washing with PBS solution, hematoxylin counterstaining, dehydrating and clearing, and mounting the slide, etc. There may be some differences in the antigens, laboratories and operation processes of each immunohistochemical staining. It is advisable to adopt the existing general staining steps, as long as it is ensured that the human sample to be tested and the quality control slide on the same glass slide are subjected to immunohistochemical staining in exactly the same environment.

[0038] In the present invention, it is preferred to use an AR microscope or a WSI (whole slide digital pathology image) instrument to obtain the pathological image and the quality control image, and use computer-aided recognition methods such as deep learning medical image processing to extract the relevant information of the proliferating cell antigen index from the pathological image and the quality control image, so as to improve the efficiency of sample detection. Of course, it is also possible to use an ordinary microscope to observe the number of color dots with the naked eye to obtain the information of the proliferating cell antigen index.

[0039] When using the deep learning medical image processing method to extract information, the machine reads the color dots, which puts forward higher requirements for the depth of staining. The machine can only read the color dots with the chromaticity in a certain range. There is a risk that the color dots are too dark or too light to be recognized by the machine. The quality control method of the present invention can ensure appropriate staining depth and accurate detection results.

[0040] S3: Extract the proliferating cell antigen indexes of at least two parts with different proliferating cell antigen densities from the quality control image.

[0041] ReferenceFigure 4 , which gives the quality control image after the quality control film is stained. The stained image of the small intestine is in the upper right, and the stained image of the liver is in the lower part. It can be seen from the image that the proliferating cell antigen density in different glandular parts of the small intestine is different, and the proliferating cell antigen density in the liver tissue is relatively uniform. From Figure 4 and Figure 5 it can also be seen that: if the proliferating cell antigen density is different, the color depth of the image composed of color dots is also different. If the proliferating cell antigen density is large, the color dots are dense and the color is deep. On the contrary, the color dots are sparse and the color is light.

[0042] Reference Figure 4 and Figure 5 , in a specific embodiment, the parts with at least two different proliferating cell antigen densities at least include the parts with a proliferating cell antigen density of 50% - 100% and the parts with a proliferating cell antigen density of 0 - 30%. Extracting the data of the parts with larger and smaller antigen densities respectively is beneficial to checking whether the staining depth is appropriate.

[0043] The parts with different proliferating cell antigen densities include at least two of the mucosal gland parts of the small intestine (as shown by A in Figure 4 and Figure 5 ), the submucosal lymphoid tissue parts of the small intestine (as shown by B in Figure 4 and Figure 5 ), the muscularis propria tissue parts of the small intestine (as shown by C in Figure 4 and Figure 5 ) and the liver tissue parts (as shown by D in Figure 4 and Figure 5 ). The small intestine contains various glands with different proliferating cell antigen densities, which is a preferred biological sample. The liver has a relatively uniform tissue structure and is also a preferred biological sample. By selecting parts with different proliferating cell antigen densities to extract the proliferating cell antigen index for calibration, when the proliferating cell antigen indexes of the parts with different proliferating cell antigen densities are all close to their corresponding standard indexes, it indicates that the staining depth is appropriate regardless of whether the area has a large or small color dot density.

[0044] Specifically, taking the Ki67 antigen as an example, the Ki67 standard index of the mucosal gland parts of the small intestine is usually between 10% and 30%, the Ki67 standard index of the submucosal lymphoid tissue parts of the small intestine is usually between 50% and 80%, the Ki67 standard index of the muscularis propria tissue parts of the small intestine is usually less than 1%, and the Ki67 standard index of the liver tissue parts is usually between 1% and 10%.

[0045] During the immunohistochemical staining process, different colors are respectively used to label normal antigens (i.e., cell antigens that have not undergone proliferation and division, usually labeled in blue) and proliferating cell antigens (usually labeled in brown), such as Figure 6As shown, the proliferating cell antigen index represents the ratio of the proliferating cell antigen to the total number of antigens, and the total number of antigens is equal to the sum of the normal antigens and the proliferating cell antigens.

[0046] Reference Figure 7 , which is a schematic diagram of a processed image obtained by extracting the proliferating cell antigen index from the quality control image shown in Figure 6 using a medical image processing method based on deep learning. The read proliferating cell antigen (Ki67) index is 88%. The process of extracting the proliferating cell antigen index from the quality control image is the process of identifying the normal antigens and proliferating cell antigens marked with different colors. If the identified proliferating cell antigen index is close to the corresponding proliferating cell antigen standard index of this part (within a certain allowable error range), it is determined that the staining of both the normal antigens and the proliferating cell antigens is qualified, and the process of identifying the quantity (including manual visual identification and computer AI identification) is also qualified.

[0047] Reference Figure 8 , by fusing the Figure 7 and Figure 6 images, it can be seen that the color points of the processed image shown in Figure 7 extracted by deep learning can well match the color points of the quality control image shown in Figure 6 , indicating that the spatial sites of the proliferating cell antigens extracted by deep learning are also reliable and accurate.

[0048] The method of extracting the color point information of pathological images by using the computer-aided interpretation method based on deep learning is a new AI technology in the field of pathology developed in recent years. This technology can efficiently and accurately obtain the color point information of pathological images. The quality control method of the present invention can be compatible with deep learning, extract the information of the pathological image and also extract the information of the quality control image at the same time, without generating redundant quality control work, and the quality control process is simpler.

[0049] S4: Compare the proliferating cell antigen index of each part with its corresponding proliferating cell antigen standard index respectively. If the proliferating cell antigen index of each part is close to its corresponding proliferating cell antigen standard index, it is determined that the quality of immunohistochemical staining is qualified; otherwise, it is determined that the quality of immunohistochemical staining is unqualified.

[0050] In this step, the proliferating cell antigen standard index can be the proliferating cell antigen index of an organ or tissue obtained by using a standard staining method, or a standard numerical range obtained by other analysis means.

[0051] In a preferred embodiment, the small intestine and the liver are selected to make quality control wax blocks. The quality control slides include the small intestine and the liver. The Ki67 indices of the mucosal gland part of the small intestine, the submucosal lymphoid tissue part of the small intestine, the muscularis propria tissue part of the small intestine, and the liver tissue part are respectively extracted from the quality control images, and are respectively compared with the above-mentioned Ki67 standard indices. If each Ki67 index belongs to the range of its corresponding Ki67 standard index, the staining quality is judged to be qualified; if it exceeds the range of the Ki67 standard index, the staining quality is judged to be unqualified, and it is necessary to analyze the out-of-control cause and take timely rectification measures according to the deviation amplitude of the Ki67 index from the Ki67 standard index, etc.

[0052] Specifically, in a specific embodiment, the Ki67 antigen is detected. The mucosal gland part of the small intestine is extracted from the quality control image and its Ki67 index K1 is detected. The range of the Ki67 standard index K1' of the mucosal gland part of the small intestine is 10% - 30%. K1 is compared with K1'. If K1 ∈ [10%, 30%], then K1 is qualified; if then K1 is unqualified.

[0053] The submucosal lymphoid tissue part of the small intestine is extracted from the quality control image and its Ki67 index K2 is detected. The range of the Ki67 standard index K2' of the submucosal lymphoid tissue part of the small intestine is 50% - 80%. K2 is compared with K2'. If K2 ∈ [50%, 80%], then K2 is qualified, if then K2 is unqualified.

[0054] The muscularis propria tissue part of the small intestine is extracted from the quality control image and its Ki67 index K3 is detected. The range of the Ki67 standard index K3' of the muscularis propria tissue part of the small intestine is ≤ 1%. K3 is compared with K3'. If K3 ≤ 1%, then K3 is qualified; if K3 > 1%, then K3 is unqualified.

[0055] The liver tissue part is extracted from the quality control image and its Ki67 index K4 is detected. The range of the Ki67 standard index K4' of the liver tissue part is 1% - 10%. K3 is compared with K3'. If K4 ∈ [1%, 10%], then K4 is qualified, if then K4 is unqualified.

[0056] If K1, K2, K3 and K4 are all qualified, the quality of immunohistochemical staining is judged to be qualified; otherwise, the quality of immunohistochemical staining is judged to be unqualified.

[0057] The density of the proliferating cell antigen determines the density value of the color dots of the proliferating cell antigen. The density of the color dots directly affects the proliferating cell antigen index. If the staining is too deep, the extracted proliferating cell antigen index will be larger than the proliferating cell antigen standard index. For tissues or parts with high density, the obtained proliferating cell antigen index will deviate more from the proliferating cell antigen standard index. If the staining is too light, the extracted proliferating cell antigen index will be smaller than the proliferating cell antigen standard index. For tissues or parts with low density, the obtained proliferating cell antigen index will deviate more from the proliferating cell antigen standard index. By extracting the proliferating cell antigen indexes of at least two parts with different proliferating cell antigen densities and comparing them with their corresponding standard indexes respectively, the present invention can accurately evaluate whether the staining depth is qualified. If the indexes of different proliferating cell antigen densities are all close to the corresponding standard indexes, it is not only judged that the staining depth is qualified, but also judged that the processes of staining and identifying the number of normal antigens and proliferating cell antigens are all qualified.

[0058] In addition, the proliferating cell antigen index is a quantitative value, which can reflect the degree of deviation from the standard index. According to the degree of deviation from the standard index, different levels of quality control evaluations such as excellent, good, and poor can be given, which can quantitatively evaluate the quality control quality. Moreover, according to the degree of deviation from the standard index, the reason for the unqualified staining can also be known, which is convenient for the operator to improve the operation process. The prior art mostly uses positive or negative to evaluate the quality control quality, lacking quantitative evaluation. Not only is the evaluation result inaccurate, but also it cannot judge what causes the improper operation, which is not conducive to improving the operation process.

[0059] In summary, the quality control method of the present invention can evaluate the quality of immunohistochemistry more accurately, objectively, comprehensively, qualitatively and quantitatively, and ensure that the proliferating cell antigen index extracted from the pathological image of the sample to be tested is reliable.

[0060] The quality control method of the present invention further includes the process of judging the quality of indoor / inter-laboratory immunohistochemical staining:

[0061] S5: According to the degree of closeness between the proliferating cell antigen index of each part and its corresponding proliferating cell antigen standard index, score the proliferating cell antigen index of each part respectively; score the quality of immunohistochemical staining, denoted by M, and M is equal to the sum of the scores of the proliferating cell antigen indexes of each part; statistically analyze the M values of the quality control slides of the same batch. If the quality of immunohistochemical staining of each quality control slide is qualified, it is judged that the quality of indoor / inter-laboratory immunohistochemical staining is qualified; otherwise, it is judged that the quality of indoor / inter-laboratory immunohistochemical staining is unqualified.

[0062] Score K1, K2, K3, and K4 respectively according to the proximity of K1, K2, K3, and K4 to their corresponding K1’, K2’, K3’, and K4’. Denote the scores as M1, M2, M3, and M4 respectively. Then M = M1 + M2 + M3 + M4.

[0063] Scoring K1, K2, K3, and K4 can be divided into three grades: qualified, warning, and unqualified. When K1, K2, K3, and K4 are respectively in the middle value range of K1’, K2’, K3’, and K4’, it is judged that K1, K2, K3, and K4 are respectively qualified, relatively satisfactory, and the score is the highest. When K1, K2, K3, and K4 are respectively close to the upper and lower value boundaries of K1’, K2’, K3’, and K4’, it is judged that K1, K2, K3, and K4 are respectively basically qualified, basically satisfactory, and the score is slightly lower, indicating that it is currently at the edge of being qualified and warning should be raised. When some or all of K1, K2, K3, and K4 exceed the range of K1’, K2’, K3’, and K4’, it is judged that K1, K2, K3, and K4 are respectively unqualified, unsatisfactory, and the score is even lower.

[0064] Specifically, in a specific embodiment, if K1 ∈ [15%, 25%], then M1 = 2; if K1 ∈ [10%, 15%) or (25%, 30%], then M1 = 1; if then M1 = -2; if K2 ∈ [60%, 70%], then M2 = 2; if K2 ∈ [50%, 60%) or (70%, 80%], then M2 = 1; if then M2 = -2; if K3 ≤ 1%, then M3 = 2; if K3 > 1%, then M3 = -2; if K4 ∈ [4%, 7%], then M4 = 2; if K4 ∈ [1%, 4%) or (7%, 10%], then M4 = 1; if then M4 = -2.

[0065] When the M value is 8, the dyeing quality can be evaluated as excellent. When the M value is 6 - 7, the dyeing quality is evaluated as good. If the M value is 4 - 5 and K1, K2, K3, and K4 are all qualified, the dyeing quality is evaluated as medium and warning attention should be paid. If the M value is less than 4, the dyeing is evaluated as unqualified, the result is unreliable, and it is recommended to remanufacture or urgently improve relevant measures to avoid a greater misdiagnosis phenomenon.

[0066] The above specific scoring values are only examples, and other values can also be used to evaluate the dyeing quality.

[0067] Statistically analyze the M values of the quality control films of the same batch. Specifically, an M value curve of all quality control films of the same batch can be made, such as Figure 9As shown, if the M values of the curves are all between 6 and 8, which are in the excellent and good grades, it indicates that the quality of indoor / inter-laboratory immunohistochemical staining is excellent, such as Figure 9 in Case 1. If some M values of the curve are between 4 and 5, such as Figure 9 in Case 2, or some M values of the curve are below 4, such as Figure 9 in Case 3, one should be vigilant, find the reasons for the low scores, and take corresponding rectification measures.

[0068] Evaluating the staining quality by scoring is easy for qualitative, quantitative analysis and statistics. There is a quality control image on each pathological image. Therefore, the quality of each pathological image is guaranteed. By statistically analyzing the M values of all quality control slides (including indoor and inter-laboratory) in the same batch, the staining quality of all operators within or between laboratories can be accurately evaluated, which is convenient for timely discovering problems, timely correcting and rectifying, and is more applicable to the consistency evaluation of laboratories in different regions on a large scale.

[0069] The above-described embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of this invention patent shall be subject to the appended claims.

Claims

1. A quality control method for immunohistochemical staining, characterized in that It includes the following processes: Obtain the organs or tissues of an animal, or commercially available organs or tissues, make a quality control wax block with the organs or tissues, section the quality control wax block to obtain a quality control section, and the quality control section includes at least two parts with different proliferating cell antigen densities; Simultaneously perform immunohistochemical staining on the human sample to be tested and the quality control section, and respectively obtain the pathological image of the human sample to be tested and the quality control image of the quality control section after immunohistochemistry; Extract the proliferating cell antigen indices of at least two parts with different proliferating cell antigen densities from the quality control image; Compare the proliferating cell antigen index of each part with its corresponding proliferating cell antigen standard index to judge the quality of the immunohistochemical staining; Among them, the organs or tissues include small intestine and / or liver; The proliferating cell antigen is Ki67 antigen, HER2 antigen, EGFR antigen, ER antigen or PD-L1; The at least two parts with different proliferating cell antigen densities include at least two of the mucosal gland part of the small intestine, the submucosal lymphoid tissue part of the small intestine, the muscularis propria tissue part of the small intestine and the liver tissue part; Obtain the pathological image and the quality control image through an AR microscope or a WSI instrument; Adopt a medical image processing method of deep learning to extract the proliferating cell antigen index from the quality control image.

2. The quality control method for immunohistochemical staining according to claim 1, wherein The at least two parts with different proliferating cell antigen densities at least include a part with a proliferating cell antigen density of 50% - 100% and a part with a proliferating cell antigen density of 0 - 30%.

3. The quality control method for immunohistochemical staining according to claim 2, characterized in that, The process of judging the quality of the immunohistochemical staining includes: If the proliferating cell antigen index of each part is close to its corresponding proliferating cell antigen standard index, it is judged that the quality of the immunohistochemical staining is qualified, otherwise it is judged that the quality of the immunohistochemical staining is unqualified.

4. The quality control method for immunohistochemical staining according to any one of claims 1 to 3, characterized in that, It also includes: Score the proliferating cell antigen index of each part according to the degree of closeness between the proliferating cell antigen index of each part and its corresponding proliferating cell antigen standard index; Score the quality of the immunohistochemical staining, denoted by M, and M is equal to the sum of the scores of the proliferating cell antigen indices of each part; Statistically analyze the M values of the quality control sections of the same batch to judge the quality of in-house / inter-laboratory immunohistochemical staining.

5. The quality control method for immunohistochemical staining according to claim 4, characterized in that, The process of judging the quality of in-house / inter-laboratory immunohistochemical staining includes: If the quality of the immunohistochemical staining of each quality control section is qualified, it is judged that the quality of the in-house / inter-laboratory immunohistochemical staining is qualified; otherwise it is judged that the quality of the in-house / inter-laboratory immunohistochemical staining is unqualified.

6. A quality control product for immunohistochemical staining, characterized in that, It includes a quality control section, which is obtained by making a quality control wax block with the organs or tissues of an animal, or commercially available organs or tissues, and sectioning the quality control wax block, and the quality control section includes at least two parts with different proliferating cell antigen densities; Among them, the organs or tissues include small intestine and / or liver; The proliferating cell antigen is Ki67 antigen, HER2 antigen, EGFR antigen, ER antigen or PD-L1; The sites with at least two different proliferating cell antigen densities include at least two of the mucosal gland sites of the small intestine, the submucosal lymphoid tissue sites of the small intestine, the muscularis propria tissue sites of the small intestine, and the liver tissue sites.

7. The quality control product for immunohistochemical staining according to claim 6, characterized in that, The sites with at least two different proliferating cell antigen densities at least include sites with a proliferating cell antigen density of 50% - 100% and sites with a proliferating cell antigen density of 0 - 30%.

8. The quality control product for immunohistochemical staining according to any one of claims 6 to 7, characterized in that, It further includes a glass slide, the quality control slide is arranged on the glass slide, an information label is also arranged on the glass slide, and the glass slide is also provided with a vacancy for arranging the sample of the person to be tested.

Images