Colorectal polyp scanning system based on SHG image
Through the colorectal polyp scanning system based on SHG images, the density and distribution of collagen in polyp samples was detected, and the problem of limited accuracy of traditional evaluation methods was solved, and efficient and accurate assessment of the risk of colorectal polyp cancer was achieved.
Patent Information
- Application Number
- CN202411762929.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-03
- Publication Date
- 2025-03-11
AI Technical Summary
The traditional method of cancer risk assessment of colorectal polyps has limited accuracy and the detection process is complex, making it difficult to achieve rapid and non-invasive detection.
Using a colorectal polyp scanning system based on SHG images, the density and distribution of collagen in the mucosal lamina propria and submucosal layer in polyp samples was quantified using two-photon microscopy system and the CT-FIRE and CurveAlign model in MATLAB, thereby predicting the risk of carcinogenesis of polyps.
It realizes efficient and accurate assessment of the risk of colorectal polyps cancer, provides a fast and non-invasive detection method, and improves the accuracy and convenience of the prior art.
Smart Images
Figure CN119595631A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to a colorectal polyp scanning system based on SHG images, belonging to the technical field of tumor detection and image analysis. Background Art
[0002] Colorectal polyps are common benign lesions in the digestive system, and some polyps may develop into malignant tumors. Early and accurate assessment of the risk of polyp canceration is of great significance for the prevention and treatment of cancer. However, traditional histopathology and imaging examinations have limited accuracy in predicting the risk of polyp canceration, and usually require complex fixation and staining processes, and rely on cancer indicators to make judgments, making it difficult to achieve rapid and non-invasive detection.
[0003] Studies have shown that the extracellular matrix (ECM) components in colorectal polyps, especially the structure and density of collagen, have a significant impact on the risk of polyp canceration. Although the role of collagen in histopathology has been widely studied, the risk of polyp canceration has not been predicted by changes in collagen distribution and density in rectal polyps. In this regard, based on the established correlation between collagen distribution characteristics at different tissue levels (such as submucosal layer and lamina propria) in the colorectal region and adenoma grade, low-grade adenomatous polyps are accompanied by collagen thickening in the submucosal layer, and the thickening of collagen in high-grade adenomas and polyps with cancer further extends to the lamina propria and upper mucosal layer, showing significant densification and fiber disorder. The significant correlation between the risk of canceration of colorectal polyps and the distribution and density of collagen can be used, and second harmonic generation (SHG) imaging, which can specifically detect the non-centrosymmetric molecular structure of collagen, can be used as an imaging method to accurately predict the risk of polyp canceration.
[0004] SHG technology can be used to accurately capture microstructural changes related to carcinogenesis in polyp samples (such as collagen densification and fiber disorder) with high resolution and without labeling, providing an efficient and convenient technical means for early screening of colorectal cancer. Summary of the invention
[0005] The purpose of the present invention is to provide a colorectal polyp scanning system based on SHG images, which can predict the risk of canceration by detecting the extracellular matrix (ECM) components in colorectal polyps.
[0006] The technical solution adopted by the present invention is:
[0007] A colorectal polyp scanning system based on SHG images, comprising a scanning system and a data processing system;
[0008] The scanning system uses a fluorescence microscope to scan the polyp slice sample using a second harmonic generation shooting mode and generates a collagen-related image;
[0009] The data processing system analyzes the SHG-based collagen imaging results and extracts collagen-related information displayed in the image.
[0010] Preferably, the data processing system extracts the characteristics of collagen fibers in the image, including length, angle and curvature, as well as key information such as the directional distribution and alignment degree of the overall collagen fibers, and compares the characteristic data of collagen in the polyp sample with clinical polyp tissue sections for pathological analysis, which can be used to assist in determining the risk of canceration of the polyp.
[0011] Preferably, the scanning system is a two-photon microscopy imaging system, and the shooting mode is second harmonic.
[0012] Preferably, the data processing system also extracts the spatial distribution of collagen density and fiber arrangement direction in the mucosal lamina propria and submucosal layer of the polyp in the image, and quantifies the density and distribution of collagen through the CT-FIRE and CurveAlign models in MATLAB, so that its correlation with the degree of canceration of the polyp sample can be established based on this.
[0013] Preferably, the imaging settings of the two-photon excitation fluorescence microscope are: laser wavelength 890-920nm, signal collection wavelength 445-460nm, and step 5nm.
[0014] The SHG image-based colorectal polyp scanning system of the present invention can effectively evaluate the risk of polyp canceration by detecting the density and distribution level of collagen in the mucosal lamina propria and submucosa in polyp samples, provide a scientific basis for early cancer screening, and improve the accuracy and convenience of existing detection methods. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Figure 1 The two-photon microscopy results. A. Two-photon microscopy results of paraffin sections of clinical samples. Blue represents the cell nucleus and gold represents collagen; B. A magnified image of two-photon microscopy (second harmonic) results of paraffin sections of clinical samples, focusing on the changes in collagen content and density in the mucosal lamina propria. Specific implementation methods
[0017] The present invention is further described below in conjunction with embodiments, but the description of the embodiments does not impose any limitation on the protection scope of the present invention.
[0018] Unless otherwise defined, all technical terms and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the present invention, and the terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In addition, although demonstrations of parameters including specific values may be provided herein, it should be understood that the parameters do not need to be exactly equal to the corresponding values, but may be approximated to the corresponding values within an acceptable error tolerance or design constraint.
[0019] Unless otherwise specified, the materials and instruments used in the following examples can be obtained from conventional commercial channels.
[0020] Example 1: Two-photon microscopy (second harmonic generation) analysis of colorectal polyp samples
[0021] 1. Collect patient polyp samples: store in pre-cooled saline buffer, spread flat on a slide, and cover with a cover glass to prevent drying;
[0022] 2. Second harmonic generation imaging using a two-photon microscopy system
[0023] The SHG mode of the two-photon imaging microscope system was used, with the two-photon wavelength set at 890-920 nm and the receiving wavelength set at 445-460 nm with a step of 5 nm, while bright-field tissue photographs were taken simultaneously.
[0024] 3. Collagen information extraction
[0025] The MATLAB-based collagen fiber analysis tools CT-FIRE and CurveAlign were obtained from the uw-loci / curvelets page on GitHub, and the characteristics of single fibers and the entire fiber group were analyzed, respectively, to process and analyze SHG imaging data. Among them, CT-FIRE focuses on the extraction and quantification of single fiber features, such as length, direction, and curvature. Its operation process includes installing and configuring the toolkit, acquiring high-quality SHG images, setting ROI (region of interest) and parameters after importing data, and then automatically extracting fiber characteristics through analysis and exporting results to visualize the spatial distribution and characteristics of each fiber. CurveAlign is used to analyze the overall fiber directionality and alignment. By loading the output or original SHG image of CT-FIRE, setting the analysis window and parameters, and running the analysis, quantitative indicators including angle distribution and alignment index are generated, and the accuracy of the results is verified by superimposing images. CT-FIRE provides fiber characteristic analysis at the microscopic level, while CurveAlign focuses on macroscopic directionality. The combination of the two can reveal the multi-level structural characteristics of tissues. In addition, Image J is used to calculate the SHG signal intensity to evaluate the collagen content and area occupied.
[0026] 4. Determine the risk of colorectal polyp samples and compare them with other clinical pathological analysis results
[0027] Based on the characteristic that "low-grade adenoma polyps are accompanied by thickening of collagen in the submucosal layer, and the thickening of collagen in high-grade adenomas and co-malignant polyps further extends to the mucosal lamina propria and the upper mucosal layer, showing significant densification and disordered fiber arrangement", the risk of canceration of polyp samples is judged to provide early warning for patients with precancerous lesions. At the same time, comparison with conventional hematoxylin-eosin staining (H&E), immunohistochemical staining (Ki-67, p53 or β-catenin), and microsatellite instability (MSI) detection in clinical practice is used to verify the accuracy of this method. Example 2: Two-photon microscopy system (second harmonic generation) analysis of colorectal polyp slice samples
[0028] 1. Collect patient polyp samples and prepare them into paraffin sections: After polyp samples are obtained through colonoscopy biopsy, they should be immediately placed in pre-cooled saline or PBS buffer to maintain tissue activity and prevent contamination. Subsequently, the samples are fixed with 2.5% paraformaldehyde solution for 12-24 hours to ensure the spatial structural integrity of the extracellular matrix (ECM) and collagen fibers. The samples must be completely immersed in the fixative during the fixation process and the fixative must be replaced in time. The fixed samples are gradually dehydrated using gradient ethanol (70% to 100%), each step lasting 1 hour, and finally transparentized with xylene. After dehydration, the samples are placed in liquid paraffin at 0°C and immersed in two steps (initial penetration for 30 minutes and complete penetration for more than 1 hour), and then cooled into solidified paraffin blocks. The samples are cut into 5μm slices using a rotary slicer. The slices need to be laid flat on a positively charged slide, stretched flat in a water bath, and dried for use. All slices are stored in a drying room and labeled with patient information to provide standardized, high-quality sample support for subsequent microscopic imaging analysis.
[0029] 2. Use the two-photon microscopy system for second harmonic generation photography: Use the SHG imaging mode of the two-photon microscope to photograph the slice sample, the two-photon excitation wavelength is set to 890-920nm, the wavelength of the received signal is 445-460nm, and the step is 5nm. This imaging setting can generate high-resolution SHG images, and at the same time cooperate with bright field imaging to obtain overall tissue morphology information ( Figure 1 ).
[0030] 3. Collagen information extraction: Download CT-FIRE and CurveAlign toolkits from the uw-loci / curvelets page on GitHub, and perform in-depth analysis of SHG images using MATLAB software:
[0031] (1) CT-FIRE analysis: Focuses on the extraction of single fiber features, including microscopic properties such as fiber length, direction, and curvature. The specific steps include loading images, setting regions of interest (ROIs) and parameters, and generating fiber quantitative results through automatic analysis.
[0032] (2) CurveAlign analysis: used to evaluate the overall fiber directionality and alignment. By loading CT-FIRE output or original images, setting the analysis area and parameters, the angle distribution and alignment index are generated and their accuracy is verified.
[0033] (3) ImageJ analysis: ImageJ software was used to calculate the total intensity of the SHG signal, evaluate the relative content and coverage area of collagen fibers, and further supplement the overall information of fiber analysis.
[0034] 4. Determine the risk of colorectal polyp samples and compare them with other clinical pathological analysis results
[0035] Combined with the characteristics of collagen thickening and distribution: (1) Low-grade adenoma polyps: mainly manifested by thickening of collagen in the submucosal layer. (2) High-grade adenoma or polyps with malignant changes: collagen densification extends to the mucosal lamina propria and the upper mucosal layer, accompanied by disordered fiber arrangement. The above characteristics are used to assess the risk of canceration of polyps and compare them with the results of traditional pathological detection methods (such as H&E staining, immunohistochemical markers Ki-67, p53, etc.) and molecular detection (such as MSI) to verify the accuracy and applicability of the new technology and provide timely warning and guidance for patients with precancerous lesions.
[0036] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with this technology to understand the contents of the present invention and implement them accordingly. They cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.
Claims
1. A colorectal polyp scanning system based on SHG images, characterized in that: Including scanning system and data processing system; The scanning system uses a fluorescence microscope to scan the polyp slice sample using a second harmonic generation shooting mode and generates a collagen-related image; The data processing system analyzes the SHG-based collagen imaging results and extracts collagen-related information displayed in the image.
2. The colorectal polyp scanning system according to claim 1, characterized in that: The data processing system extracts the characteristics of collagen fibers in the image, including length, angle and curvature, as well as key information such as the directional distribution and alignment degree of the overall collagen fibers.
3. The colorectal polyp scanning system according to claim 1 or 2, characterized in that: The scanning system is a two-photon microscopic imaging system, and the shooting mode is second harmonic.
4. The colorectal polyp scanning system according to claim 3, characterized in that: The data processing system also extracts the collagen density and spatial distribution of the fiber arrangement direction of the mucosal lamina propria and submucosa of the polyp in the image, and quantifies the density and distribution of collagen through the CT-FIRE and CurveAlign models in MATLAB.
5. The colorectal polyp scanning system according to claim 4, characterized in that: The two-photon microscopic imaging system is set as follows: two-photon wavelength 890-920nm, signal collection wavelength 445-460nm, step 5nm; and the optimal wavelength is determined according to the strongest signal of the sample.