CN107941765B - Evaluation method of gastric serosa surface collagen tissue of gastric cancer resection specimen - Google Patents
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Abstract
The invention provides a gastric serosa surface collagen tissue evaluation method of a gastric cancer resection specimen, and relates to the technical field of pathological identification. The invention has reasonable design, mature technology, simplicity, convenience and feasibility, and has wide clinical application prospect and good scientific research and popularization value.
Description
Technical Field
The invention relates to the technical field of pathological identification, in particular to a method for evaluating a collagen tissue on the surface of a gastric serosa of a gastric cancer resection specimen.
Background
The latest cancer statistical data in China show that the gastric cancer is a malignant tumor with the second morbidity and the second tumor mortality in China and is one of the main cancers threatening the health of residents in China. In the process of gastric cancer development, tumor cells break through from a mucosa layer to a submucosa layer and a muscular layer by layer, finally infiltrate a serosa layer and fall off to an abdominal cavity to form planting metastasis. The serosal layer is the last barrier for tumor cells to enter the abdominal cavity, so that the knowledge of the change of the gastric serosal surface in gastric cancer is of great significance for the research of the gastric cancer abdominal cavity implantation metastasis.
Extracellular matrix (ECM) is a major component in the tumor microenvironment and plays an important role in the development of tumors. On one hand, the tumor cells secrete a large amount of cytokines to act on EMC, so that the components and the conformation of the EMC are changed, and conditions are created for escape of the tumor cells. On the other hand, ECM changes with the progress of the tumor disease process in the whole process of occurrence and development of the tumor, and influences the adhesion and migration of cells by stimulating the production of biochemical signals and biophysical signals, and the two interact to influence the infiltration and metastasis process of the tumor.
Collagen is a main component in ECM and is also a main player of ECM function. In the research of breast cancer collagen, the collagen fiber is directly involved in the migration process of tumor cells, the collagen density is increased, the proliferation and differentiation of mammary epithelial cells can be directly promoted, and the risk of breast cancer lung metastasis is obviously increased; in the research of gastric cancer collagen, the collagen on the surface of a gastric serosa infiltrated by tumor has a remarkable difference with the collagen on the surface of a normal gastric serosa, and the change of the collagen on the surface of the gastric serosa is closely related to the prognosis of gastric cancer.
Therefore, the collagen is an important index for researching the occurrence and development of the gastric cancer and helping to clinically judge the prognosis of the gastric cancer, and the observation and analysis of the macroscopic and microscopic structures of the collagen have important significance for scientific research and clinical application. However, at present, there is no method for visually evaluating collagen on the surface of the gastric serosa, and a commonly used collagen analysis method, namely collagen (hydroxyproline) content analysis, is complex and time-consuming in operation and limited in accuracy degree, is not convenient for analysis and is insufficient for providing sufficient collagen information.
Therefore, the research and development of the evaluation method of the gastric serosa surface collagen tissue of the gastric cancer resection specimen further intuitively, accurately and abundantly obtains the information of the gastric serosa surface collagen, helps clinical workers to know the change of the gastric serosa surface collagen, and has very important significance in the aspects of evaluating the malignancy degree, the metastasis, the recurrence possibility and the like of the tumor of a gastric cancer patient.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
The first purpose of the invention is to provide a gastric serosa surface collagen tissue evaluation method of a gastric cancer resection specimen, which is used for carrying out tissue evaluation on the gastric serosa surface collagen of the gastric cancer resection specimen through Masson dyeing combined with multi-photon imaging analysis, and is helpful for clinical workers to visually, accurately and abundantly obtain the information of the gastric serosa surface collagen, and further know the change condition of the gastric serosa surface collagen.
The invention provides a method for evaluating a collagen tissue on the surface of a gastric serosa of a gastric cancer resection specimen, which comprises the following steps:
(a) sample preparation: separating gastric serosa tissues from a gastric cancer resection specimen to prepare a gastric serosa surface tissue wax block, and then horizontally cutting a tissue slice along the gastric serosa surface of the wax block to prepare a multiphoton imaging slice to be detected;
(b) multiphoton collagen imaging: performing second harmonic imaging on the multiphoton imaging slice to be detected in the step (a) to obtain a multiphoton collagen imaging graph;
(c) and (3) staining the section: masson staining is carried out on the sections imaged by the multiphoton collagen in the step (b), and then a section scanner is used for scanning the Masson stained sections to obtain a Masson stained image;
(d) imaging analysis: comparing the multiphoton imaging graph obtained in the step (b) with the Masson staining graph obtained in the step (c), marking a collagen part in the multiphoton image, and then performing visual image analysis on the collagen part of the multiphoton imaging graph and/or introducing the collagen part into an image analysis system for performing collagen layer analysis.
Further, when preparing the serosa surface tissue wax block in the step (a), embedding the serosa lower layer downwards.
Further, the thickness of the tissue slice in the step (a) is 3-8 μm.
Further, a small amount of non-fluorescing oil is dropped on the multiphoton imaging section before the second harmonic imaging in step (b).
Further, the second harmonic imaging of step (b) is imaging with a single channel detector.
Furthermore, the output power of the single-channel detector in the step (b) is 1.5W-1.8W.
Furthermore, the imaging wavelength of the imaging carried out by the single-channel detector in the step (b) is 800-820 nm, and the receiving wavelength is 390-410 nm.
Further, the imaging multiple of the second harmonic imaging of the step (b) is 10 times.
Further, the Masson stained section in the step (c) was imaged at a magnification of 20 times and a resolution of 0.50 μm/image.
Further, the collagen layer analysis of step (d) is to introduce the multiphoton image into an analysis system to obtain the collagen alignment direction, the collagen area, and the collagen network index.
Compared with the prior art, the invention has the beneficial effects that:
the method for evaluating the collagen tissue on the surface of the gastric serosa of the gastric cancer resection specimen provided by the invention is used for evaluating the collagen tissue on the surface of the gastric serosa of the gastric cancer resection specimen by combining Masson staining and multi-photon imaging analysis, wherein the Masson pathological staining can be used for carrying out macroscopic analysis on the general structure and the general proportion of the collagen on the surface of the gastric serosa; the method combines two collagen analysis modes together, can quickly, simply, conveniently and accurately analyze the collagen on the surface of the gastric serosa, is beneficial to clinical workers to know the condition of the collagen on the surface of the gastric serosa of a patient, and has important reference value in the aspects of evaluating the malignancy degree, metastasis and recurrence possibility of the tumor of the gastric cancer patient. The invention has reasonable design, mature technology, simplicity, convenience and feasibility, and has wide clinical application prospect and good scientific research and popularization value.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flowchart of a method for evaluating a serosal surface collagen tissue of a gastric cancer resection specimen according to example 1 of the present invention;
FIG. 2 is a multiphoton collagen imaging diagram of a specimen with a high collagen content measured by a conventional method according to effect example 1 of the present invention;
fig. 3 is a multiphoton collagen image of a specimen with a small collagen content measured by a conventional method according to effect example 1 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
According to an aspect of the present invention, a method for evaluating a serosal surface collagen tissue of a gastric cancer resection specimen, the method comprising the steps of:
(a) sample preparation: separating gastric serosa tissues from a gastric cancer resection specimen to prepare a gastric serosa surface tissue wax block, and then horizontally cutting a tissue slice along the gastric serosa surface of the wax block to prepare a multiphoton imaging slice to be detected;
(b) multiphoton collagen imaging: performing second harmonic imaging on the multiphoton imaging slice to be detected in the step (a) to obtain a multiphoton collagen imaging graph;
(c) and (3) staining the section: masson staining is carried out on the sections imaged by the multiphoton collagen in the step (b), and then a section scanner is used for scanning the Masson stained sections to obtain a Masson stained image;
(d) imaging analysis: comparing the multiphoton imaging graph obtained in the step (b) with the Masson staining graph obtained in the step (c), marking a collagen part in the multiphoton image, and then performing visual image analysis on the collagen part of the multiphoton imaging graph and/or introducing the collagen part into an image analysis system for performing collagen layer analysis.
The method for evaluating the collagen tissue on the surface of the gastric serosa of the gastric cancer resection specimen provided by the invention is used for evaluating the collagen tissue on the surface of the gastric serosa of the gastric cancer resection specimen by combining Masson staining and multi-photon imaging analysis, wherein the Masson pathological staining can be used for carrying out macroscopic analysis on the general structure and the general proportion of the collagen on the surface of the gastric serosa; the invention combines two collagen analysis modes together, and can quickly, simply and accurately analyze the collagen on the surface of the gastric serosa. The multi-photon imaging is a multi-photon microscopic imaging technology based on nonlinear optics and femtosecond laser, auto-fluorescence generated by cells in living tissues and second harmonic generated by non-centrosymmetric tissues (such as collagen) are utilized for imaging, the method does not need the steps of tissue cutting, fixing, embedding, slicing, dyeing and the like of the traditional pathological biopsy, can quickly observe the tissue structure and the cell morphology of a specimen in real time, and has the advantages of strong penetrating power, small light damage, high resolution and the like, and can clearly image paraffin sections, fresh isolated tissues and living tissues. Therefore, the method has wide application prospect and scientific research and popularization value when the multi-photon imaging technology is applied to the evaluation of the collagen tissues on the surface of the gastric cancer serosa.
The evaluation method of the collagen tissue on the gastric serosal surface of the gastric cancer resection specimen is helpful for clinical workers to know the condition of the collagen on the gastric cancer serosal surface of the patient, and has important reference value in the aspects of evaluating the malignancy degree, metastasis and recurrence possibility of the gastric cancer patient. The invention has reasonable design, mature technology, simplicity, convenience and feasibility, and has wide clinical application prospect and good scientific research and popularization value.
In a preferred embodiment of the present invention, the step (a) of preparing the serosal surface tissue wax block comprises embedding the serosal layer in a downward orientation.
In a preferred embodiment of the present invention, the thickness of the tissue slice in the step (a) is 3 to 8 μm.
As a preferred embodiment, the thickness of the tissue slice in step (a) is 3-8 μm, which is more favorable for observation of optical electron microscope and multiphoton imaging.
In a preferred embodiment of the present invention, a small amount of non-fluoroscopic oil is dropped on the multiphoton imaging section before the second harmonic imaging is performed in the step (b).
As a preferred embodiment, the dripping of a small amount of non-fluoroscopic oil on the multiphoton imaging section can avoid the effect of auto-fluorescence of the specimen tissue on the second harmonic imaging.
In a preferred embodiment of the present invention, the step (b) second harmonic imaging is imaging with a single channel detector.
In the above preferred embodiment, the output power of the single-channel detector in step (b) is 1.5W to 1.8W.
In the above preferred embodiment, the imaging wavelength of the imaging performed by the single-channel detector in the step (b) is 800-820 nm, and the receiving wavelength is 390-410 nm.
According to the characteristics of the section to be measured prepared from the collagen on the surface of the gastric serosa of the gastric cancer resection specimen, the specific excitation wavelength and the specific receiving wavelength are adopted to image the multi-photon imaging section, so that a clearer and more accurate second harmonic image can be obtained.
In a preferred embodiment of the present invention, the second harmonic imaging of step (b) is performed at a magnification of 10.
In a preferred embodiment of the present invention, the Masson stained section in step (c) is imaged at a magnification of 20 times and a resolution of 0.50 μm/image.
In a preferred embodiment, the scanning image of the Masson stained section in the step (b) is 20 times, and the resolution is 0.50 μm/image, so that the scanning image of the Masson stained section can be more clear.
In a preferred embodiment of the present invention, the collagen layer analysis in step (d) is performed by introducing a multiphoton image into an analysis system to obtain the collagen alignment direction, the collagen area, and the collagen network index.
As a preferred embodiment, the Collagen alignment direction (Collagen orientation) analysis method is to enhance the edges of Collagen fibers in the SHG image using an image analysis technique based on a curve Transform (Curvelet Transform) in order to accurately quantify the Collagen alignment direction in the Second Harmonic (SHG) image. First, a coefficient C in a curve space is obtained by fast discrete curve transformDIs defined as the inner product of the SHG image pixel intensity and each curve basis function. The above calculations are then implemented using a rapid curve transformation toolkit based on MATLAB language. Then, the SHG image is reconstructed by using the inverse transformation of the fast curve transformation, so that the influence of noise is minimized, and the edge of the collagen fiber is greatly enhanced to obtain a clear and complete collagen contour so as to calculate the direction of the collagen.
The Collagen area (Collagen area) analysis method is a method of image segmentation based on a gaussian mixture model to extract pixel points belonging to Collagen fibers in an SHG image so as to calculate the Collagen area in the image. The intensity values of all pixels in the SHG image can be modeled as a mixture of two gaussian distributions, one representing collagen pixels with strong SHG signal and the other representing background pixels in the image. And (3) adopting an Expectation Maximization algorithm (Expectation Maximization) and dividing the image, wherein the collagen area is the ratio of the number of the pixels belonging to the collagen in the image to the total number of all the pixels in the image.
The mesh Index (differentiation Index) is a ratio of the number of fiber branch points in the collagen fiber network to the total fiber length, and the higher the ratio, the more crosslinked collagen fibers in the image are represented, and the greater the density and hardness are. Firstly, a skeletonization method is used for extracting a central axis of collagen fibers from a segmented binary collagen template. Then, dividing all the pixel points on the collagen fiber skeleton into three types: if only one adjacent point exists, the point belongs to the end point; if two adjacent points exist, the two adjacent points belong to curve points on the skeleton; if there are more than two adjacent points, they belong to a branch point, representing more than one collagen fiber meeting there. And finally, calculating the number of branch points and further obtaining the mesh index.
Through the analysis of the collagen arrangement direction, the collagen area and the reticular index, and then the calculation is carried out by commercial software, the collagen quantitative data of the collagen tissue on the gastric serosa surface of the gastric cancer resection specimen can be obtained.
Example 1
As shown in fig. 1, a method for evaluating a serosal surface collagen tissue of a gastric cancer resection specimen, the method comprising the steps of:
(a) sample preparation: separating gastric serosa tissues from a gastric cancer resection specimen to prepare a gastric serosa surface tissue wax block, horizontally cutting a tissue slice with the thickness of 3 mu m along the gastric serosa surface of the wax block, and embedding the lower layer of the gastric serosa downwards to prepare a multi-photon imaging slice to be detected;
(b) multiphoton collagen imaging: performing second harmonic imaging on the multiphoton imaging slice to be detected in the step (a) to obtain a multiphoton collagen imaging graph; the output power of the single-channel detector is 1.5W, the imaging wavelength is 800nm, the receiving wavelength is 390nm, and the imaging multiple is 10 times;
(c) and (3) staining the section: performing Masson staining on the sections imaged by the multiphoton collagen in the step (b), and scanning the Masson stained sections by using a section scanner, wherein the scanning imaging multiple is 20 times, and the resolution is 0.50 mu m/image, so as to obtain a Masson stained image;
(d) imaging analysis: comparing the multiphoton imaging graph obtained in the step (b) with the Masson stain graph obtained in the step (c), marking a collagen part in the multiphoton image, and then performing visual image analysis on the collagen part in the multiphoton imaging graph.
Example 2
A gastric serosa surface collagen tissue evaluation method of a gastric cancer resection specimen comprises the following steps:
(a) sample preparation: separating gastric serosa tissues from a gastric cancer resection specimen to prepare a gastric serosa surface tissue wax block, horizontally cutting a tissue slice with the thickness of 8 mu m along the gastric serosa surface of the wax block, and embedding the lower layer of the gastric serosa downwards to prepare a multi-photon imaging slice to be detected;
(b) multiphoton collagen imaging: performing second harmonic imaging on the multiphoton imaging slice to be detected in the step (a) to obtain a multiphoton collagen imaging graph; the output power of the single-channel detector is 1.8W, the imaging wavelength is 820nm, the receiving wavelength is 410nm, and the imaging multiple is 10 times;
(c) and (3) staining the section: performing Masson staining on the sections imaged by the multiphoton collagen in the step (b), and scanning the Masson stained sections by using a section scanner, wherein the scanning imaging multiple is 20 times, and the resolution is 0.50 mu m/image, so as to obtain a Masson stained image;
(d) imaging analysis: comparing the multiphoton imaging graph obtained in the step (b) with the Masson staining graph obtained in the step (c), marking a collagen region in the multiphoton image, and then introducing the collagen region in the multiphoton imaging graph into an image analysis system for collagen layer analysis.
Example 3
A gastric serosa surface collagen tissue evaluation method of a gastric cancer resection specimen comprises the following steps:
(a) sample preparation: separating gastric serosa tissues from a gastric cancer resection specimen to prepare a gastric serosa surface tissue wax block, horizontally cutting a tissue slice with the thickness of 5 mu m along the gastric serosa surface of the wax block, and embedding the lower layer of the gastric serosa downwards to prepare a multi-photon imaging slice to be detected;
(b) multiphoton collagen imaging: performing second harmonic imaging on the multiphoton imaging slice to be detected in the step (a) to obtain a multiphoton collagen imaging graph; the output power of the single-channel detector is 1.6W, the imaging wavelength is 810nm, the receiving wavelength is 400nm, and the imaging multiple is 10 times;
(c) and (3) staining the section: performing Masson staining on the sections imaged by the multiphoton collagen in the step (b), and scanning the Masson stained sections by using a section scanner, wherein the scanning imaging multiple is 20 times, and the resolution is 0.50 mu m/image, so as to obtain a Masson stained image;
(d) imaging analysis: comparing the multiphoton imaging graph obtained in the step (b) with the Masson stain graph obtained in the step (c), marking a collagen part in the multiphoton image, and then performing visual image analysis on the collagen part in the multiphoton imaging graph.
Effect example 1
The method for evaluating the collagen tissue on the surface of the gastric serosa of the gastric cancer resection specimen can intuitively and accurately evaluate the collagen tissue on the surface of the gastric serosa, and has the characteristics of simplicity, convenience and practicability. The measurement of collagen on the surface of the gastric serosa of a gastric cancer resection specimen is carried out particularly by using the existing collagen (hydroxyproline) content analysis method, wherein: the specimen 1 was a specimen whose collagen content was high, and the specimen 2 was a specimen whose collagen content was low.
The existing collagen (hydroxyproline) content analysis method mainly comprises the following operation processes: drying the tissue slices at 100 ℃ to constant weight, and hydrolyzing the tissue slices in a 6mol/L HCl solution at 110 ℃ for 18 hours; washing the residue with deionized water for three times after the acidolysis solution is evaporated, wherein the residue is completely evaporated between each washing step to remove residual acid; after a sample is dissolved and treated by ethyl acetate citrate buffer solution (pH 6), the hydroxyproline value is analyzed by colorimetric analysis, and the analysis result multiplied by a fixed coefficient of 7.46 is the collagen content with the unit of ug/mg. The method is complicated and time-consuming in operation process, and the microstructure of the collagen cannot be analyzed.
The above-described specimens 1 and 2 were evaluated by the method for evaluating a collagen tissue on a gastric serosal surface of a gastric cancer resection specimen according to example 3 of the present invention, wherein:
as shown in FIG. 2, the multiphoton collagen imaging graph of specimen 1 shows that the content of collagen in the serosal surface of the stomach is low, the arrangement is orderly, the damage of the collagen structure is not seen, the evaluation patient is earlier in stage, the probability of the occurrence of abdominal cavity implantation transfer after the operation is lower, and the prognosis is better.
As shown in FIG. 3, the multiphoton collagen image of specimen 2 shows that the arrangement of collagen on the serosal surface of the stomach is disordered and the collagen structure is damaged, which indicates that the stage of the patient is later, the possibility of abdominal cavity implantation metastasis after the operation is higher and the prognosis is poorer. The abdominal cavity thermal perfusion treatment can be considered, the life quality of the patient is improved, and the prognosis is improved.
Therefore, the evaluation method of the collagen tissue on the surface of the gastric serosa of the gastric cancer resection specimen has the same result as that obtained by the existing collagen (hydroxyproline) content analysis method, is more visual, accurate, simple and feasible compared with the existing collagen (hydroxyproline) content analysis method, can analyze the microstructure of collagen, and simultaneously avoids the influence of the complex experimental operation flow of the existing collagen (hydroxyproline) content analysis method on the experimental result.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (1)
1. A method for evaluating a collagen tissue on a gastric serosal surface of a gastric cancer resection specimen is characterized by comprising the following steps:
(a) sample preparation: separating gastric serosa tissues from a gastric cancer resection specimen to prepare a gastric serosa surface tissue wax block, horizontally cutting a tissue slice with the thickness of 5 mu m along the gastric serosa surface of the wax block, and embedding the lower layer of the gastric serosa downwards to prepare a multi-photon imaging slice to be detected;
(b) multiphoton collagen imaging: performing second harmonic imaging on the multiphoton imaging slice to be detected in the step (a) to obtain a multiphoton collagen imaging graph; the output power of the single-channel detector is 1.6W, the imaging wavelength is 810nm, the receiving wavelength is 400nm, and the imaging multiple is 10 times;
(c) and (3) staining the section: performing Masson staining on the sections imaged by the multiphoton collagen in the step (b), and scanning the Masson stained sections by using a section scanner, wherein the scanning imaging multiple is 20 times, and the resolution is 0.50 mu m/image, so as to obtain a Masson stained image;
(d) imaging analysis: comparing the multiphoton imaging graph obtained in the step (b) with the Masson stain graph obtained in the step (c), marking a collagen part in the multiphoton image, and then performing visual image analysis on the collagen part in the multiphoton imaging graph.
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