Tumor ultrasonic image sensitivity detection method
By using in vitro tumor spherical model and advanced ultrasound imaging technology, the problem of insufficient sensitivity in early tumor diagnosis is solved, and higher detection sensitivity and accuracy are achieved, providing an important basis for the early diagnosis and treatment of tumors.
Patent Information
- Application Number
- CN202510144080.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-10
- Publication Date
- 2025-05-27
AI Technical Summary
Existing ultrasound imaging techniques are insufficient in the early diagnosis of tumors, especially in the identification and accurate evaluation of small tumors.
The in vitro tumor sphere model was used to prepare 4T1 breast cancer cell tumor spheres of different sizes by suspension culture method, combined with dynamic light scattering technology to detect the contrast agent size, laser confocal microscope for penetration detection, and grayscale value quantification and statistical analysis were performed using ultrasonic imaging technology and quantization software.
It improves the sensitivity and accuracy of ultrasound detection, reduces dependence on experimental animals, shortens the research cycle, enhances the biological relevance of experimental results, and provides a strong basis for the early diagnosis and treatment of tumors.
Smart Images
Figure CN120044128A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of tumor ultrasound imaging, and particularly to a method for detecting the sensitivity of tumor ultrasound images. Background Art
[0002] Ultrasound imaging technology occupies an important position in the field of medical imaging. Its application range is wide, and it plays a crucial role especially in tumor diagnosis. Ultrasonic examination has become the preferred tool for early tumor screening and diagnosis due to its unique advantages, such as non-invasiveness, affordability, and good repeatability. This technology can provide real-time soft tissue images, which are of great value for evaluating the morphology, size, and location of tumors. However, the sensitivity of ultrasound images is not constant. It is affected by various factors, including the size, location, and tissue characteristics of the tumor. The size of the tumor is an important factor affecting the sensitivity of ultrasonic detection. For smaller tumors, due to their weak echo signals, they are easily overlooked, resulting in missed diagnoses. Therefore, the identification and accurate assessment of small tumors show obvious shortcomings, which greatly limit the possibility of early cancer diagnosis. Therefore, developing new simulation experimental models to evaluate the detection performance of different small-sized tumors under ultrasound will provide an important basis for improving the sensitivity and accuracy of ultrasound technology. This is also the core value of our research, in order to provide new ideas and methods for the application of ultrasonic detection in early tumor identification;
[0003] In vitro models (tumor spheres of different sizes) can provide important guidance in studying the relationship between tumor size and different ultrasound detection sensitivities. Multicellular tumor spheres can more realistically simulate the three-dimensional growth environment of tumors, construct a more realistic matrix environment, and reproduce the biological characteristics of in vivo tumor tissues themselves. By using the tumor multicellular sphere model, we can create a controllable environment, excluding many interfering factors faced by in vivo experiments such as individual differences and ethical restrictions, so as to more accurately analyze the influence of tumor size on the sensitivity of ultrasonic detection. Summary of the Invention
[0004] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose a method for detecting the sensitivity of tumor ultrasound images.
[0005] In order to achieve the above purpose, the present invention adopts the following technical scheme:
[0006] A method for detecting the sensitivity of tumor ultrasound images, comprising the following steps:
[0007] S1: Prepare tumor spheres simulating tumors, using the 4T1 breast cancer cell line, formed by suspension culture method in a complete medium containing Matrigel;
[0008] S2: Detect the sizes of nano- and micro-contrast agents, and measure the sizes of the contrast agents in the tumor spheroid samples using a dynamic light scattering instrument.
[0009] S3: Conduct a penetration test on the tumor spheroids, observe whether the contrast material can enter their interiors, and use a laser confocal microscope to evaluate the penetration of the material labeled with Dil dye in the tumor spheroids.
[0010] S4: Perform ultrasonic imaging on tumor spheroids of different sizes, and obtain imaging results in two-dimensional mode and contrast mode using preset ultrasonic imaging conditions.
[0011] S5: Quantify the ultrasonic gray-scale results, transfer the ultrasonic images to ultrasonic quantification software, select the region of interest and calculate the gray-scale values, and conduct statistical analysis.
[0012] Preferably: In step S1, use a 1640 complete medium supplemented with Matrigel at a final concentration of 2.5% and centrifuge with a high-speed refrigerated centrifuge to make the cells converge, accelerating the formation of tumor spheroids by 4T1 breast cancer cells, and observe and measure the sizes of the tumor spheroids every day.
[0013] Furthermore: In step S2, dilute the micro- and nano-contrast materials with the same volume of deionized water, and use a dynamic light scattering device (zetasizer pro) to measure the sizes of the contrast agents. The measurement conditions include a temperature of 25 °C, a measurement angle of 173°, a measurement mode of general mode, and each sample is measured three times.
[0014] Furthermore: In step S3, incubate the tumor spheroids with the contrast material labeled with Dil for 16 hours at 37 °C.
[0015] As a preferred solution of the present invention: In step S3, wash the tumor spheroids with phosphate buffer solution, and observe the penetration of micro- and nano-contrast materials with a confocal microscope.
[0016] As a further solution of the present invention: The ultrasonic imaging conditions in step S4 include a frequency of 18 MHz, a contrast gain of 37 dB, a two-dimensional mode contrast of 19 dB, a scanning depth of 10.55 mm, and a scanning width of 9.25 mm.
[0017] As a still further solution of the present invention: In step S5, use a preset algorithm to automatically identify and outline the boundary of the region of interest, and make manual adjustments to improve the selection accuracy. Then, use the image post-processing function to enhance, filter, and detect edges, calculate the RGB channel values of each pixel within the ROI, and extract the gray-scale values.
[0018] Based on the foregoing solution: In step S5, the gray-scale value calculation formula is I = 0.311×R + 0.591×G + 0.115×B.
[0019] Based on the above-mentioned solution: In step S5, it also includes importing the grayscale quantization data into Graphpad software for statistical analysis. One-way analysis of variance is used, and p < 0.05 is considered to have statistical significance.
[0020] The beneficial effects of the present invention are as follows:
[0021] 1. A method for detecting the sensitivity of tumor ultrasound images. By precisely preparing tumor spheres of 4T1 breast cancer cells with different sizes and using dynamic light scattering technology to detect the sizes of nano- and micro-contrast agents, the accuracy and reliability of the experiment are ensured. The penetration detection by a laser confocal microscope can visually evaluate the penetration of the contrast material in the tumor spheres, and through ultrasound imaging combined with ultrasound quantification software, the gray value of the region of interest can be accurately quantified, providing accurate data for subsequent statistical analysis. And through one-way analysis of variance using Graphpad software, the sensitivity differences of ultrasound images under different conditions can be scientifically evaluated, providing a strong basis for the early diagnosis and treatment of tumors and having broad application prospects.
[0022] 2. A method for detecting the sensitivity of tumor ultrasound images. By using an in vitro tumor sphere model, it helps to reduce the use of mice or other experimental animals, reduce ethical issues and economic costs, and at the same time improve the flexibility of the research. Compared with animal models, the culture time of tumor spheres is usually shorter, enabling researchers to quickly obtain experimental materials.
[0023] 3. A method for detecting the sensitivity of tumor ultrasound images. By using tumor spheres, it can better simulate the three-dimensional growth environment of tumors in vivo, allowing cells to grow in a more physiological state, thereby improving the biological relevance of experimental results.
[0024] 4. A method for detecting the sensitivity of tumor ultrasound images. The preparation and analysis process using the tumor sphere model is relatively simple, reducing experimental steps and complexity. This simplification enables researchers to design and execute experiments faster, shortening the overall research time. Description of the Drawings
[0025] Figure 1 is a schematic diagram of the detection process of a method for detecting the sensitivity of tumor ultrasound images proposed by the present invention;
[0026] Figure 2 is a schematic diagram of tumor spheres with different sizes of a method for detecting the sensitivity of tumor ultrasound images proposed by the present invention;
[0027] Figure 3 is a schematic diagram of the detection of the sizes of micro- and nano-contrast agents of a method for detecting the sensitivity of tumor ultrasound images proposed by the present invention;
[0028] Figure 4It is a schematic diagram of penetration in tumor spheres in a tumor ultrasound image sensitivity detection method proposed by the present invention;
[0029] Figure 5 It is a schematic diagram of the contrast effect of different modes in a tumor ultrasound image sensitivity detection method proposed by the present invention
[0030] Figure 6 It is a schematic diagram of the gray values of tumor spheres of different sizes in a tumor ultrasound image sensitivity detection method proposed by the present invention. Detailed implementation manners
[0031] The technical solutions of this patent will be further described in detail below in conjunction with the specific implementation manners.
[0032] The embodiments of this patent will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below by referring to the drawings are exemplary and are only used to explain this patent and should not be construed as a limitation to this patent.
[0033] Embodiment 1:
[0034] A tumor ultrasound image sensitivity detection method, as Figure 1-6 shown, includes the following steps:
[0035] S1: Preparation of tumor spheres: Use the 4T1 breast cancer cell line to prepare a simulated tumor; first, prepare the culture medium, select the 1640 complete medium and add Matrigel with a final concentration of 2.5% to provide rich growth factors to promote cell growth and aggregation;
[0036] Subsequently, adopt the suspension culture method, inoculate the cells into an ultra-low adhesion culture dish, and let the cells freely suspend in the culture medium to promote self-aggregation to form tumor spheres; alternatively, three-dimensional scaffolds such as collagen or gelatin can be used to support cell growth;
[0037] Then, construct small, medium, and large tumor spheres by inoculating 5000 cells, 8000 cells, and 15000 cells per well respectively, and centrifuge at 1800 rpm for 5 min using a high-speed refrigerated centrifuge to ensure that the tumor cells form clusters;
[0038] After inoculation, culture in an environment of 37°C and 5% CO2, and regularly observe the formation of tumor spheres. Usually, obvious tumor spheres can be formed within 2 to 5 days; after the tumor spheres are formed, observe the morphology, size, and aggregation of the tumor spheres through a microscope;
[0039] Preferably, the vital staining method can be used to evaluate cell viability and apoptosis; and strict prevention of cell contamination should be carried out during the preparation process;
[0040] S2: Detection of the sizes of nano- and micro-contrast agents; Dilute the micro- and nano-contrast agents sufficiently with phosphate buffer to a detectable concentration range, and then gently transfer the sample to a clean cuvette of a dynamic light scattering device (Zetasizer Pro), taking care to avoid generating air bubbles during this process; when measuring with the dynamic light scattering device (Zetasizer Pro), the temperature is 25 °C, the measurement angle is 173°, and the measurement time is 3 minutes. Each sample is measured three times; after the measurement, the dynamic light scattering device (Zetasizer Pro) can calculate the average particle size and particle size distribution map of the sample material;
[0041] S3: Detection of the penetration into tumors; Use a laser confocal microscope to evaluate the penetration of the Dil dye-labeled material into 4T1 spheres;
[0042] Before the evaluation, first incubate the spheres with the Dil-labeled contrast material in 200 μL of culture medium at 37 °C for 16 h, then gently transfer the tumor spheres to a confocal glass dish using a pipette tip, and then wash the tumor spheres with phosphate buffer and observe the penetration of the Dil-labeled material inside the spheres with a confocal microscope. The bottom surface of the tumor sphere is defined as 0 μm;
[0043] S4: Ultrasound imaging of tumor spheres of different sizes; Gently transfer tumor spheres of different sizes to a conical agar mold with an opening diameter of 5 mm using a 1 ml pipette tip or needle, and then perform ultrasound imaging on the tumor sphere model in the conical agar mold. The ultrasound imaging conditions are as follows: frequency: 18 MHz, contrast gain: 37 dB, two-dimensional mode contrast: 19 dB, scan depth: 10.55 mm, scan width: 9.25 mm; the imaging results are presented in two-dimensional mode and contrast mode respectively;
[0044] S5: Quantification of ultrasound gray-scale results; Connect the ultrasound imaging device to the ultrasound quantification software (DFY), transfer the clear ultrasound images to the ultrasound quantification software (DFY), then select the region of interest (ROI) on the ultrasound image. In the region of interest (ROI), use a preset algorithm to automatically identify and outline the boundary of the region of interest (ROI) using the edge, color, and texture features of the tumor region in the image, and then manually adjust the outlined edge area to improve the selection accuracy;
[0045] Subsequently, the image post - processing function of the DFY software was used to enhance, filter, and detect the edges of the selected region of interest (ROI), further improving the clarity and accuracy of the tumor region edge. Subsequently, the RGB channel values of each pixel within the ROI were calculated in the DFY software, and a grayscale quantization formula was applied to extract the grayscale values. The grayscale value formula is: I = 0.311×R + 0.591×G + 0.115×B. Then, the grayscale quantization data was imported into the Graphpad software for statistical analysis. One - way analysis of variance was used, and p < 0.05 was considered to have a significant difference, denoted as *, and p < 0.01 was considered to have a significant difference, denoted as **.
[0046] A method for detecting the sensitivity of tumor ultrasound images. By precisely preparing tumor spheres of 4T1 breast cancer cells with different sizes and using dynamic light scattering technology to detect the sizes of nano - and micro - contrast agents, the accuracy and reliability of the experiment are ensured. At the same time, the in - vitro tumor sphere model helps to reduce the use of mice or other experimental animals, reducing ethical issues and economic costs. It also improves the flexibility of the research. Compared with animal models, the culture time of tumor spheres is usually shorter. Cells can usually form obvious tumor spheres within 2 to 7 days under appropriate culture conditions, enabling researchers to quickly obtain experimental materials. And tumor spheres can better simulate the three - dimensional growth environment of tumors in vivo, allowing cells to grow in a more physiological state, thus improving the biological relevance of experimental results. Moreover, the preparation and analysis process of the tumor sphere model is relatively simple, reducing experimental steps and complexity. This simplification enables researchers to design and execute experiments faster, shortening the overall research time.
[0047] During the detection process, the penetration detection of the laser confocal microscope can visually evaluate the penetration of the contrast material within the tumor spheres, providing strong support for ultrasonic imaging. In addition, this method uses advanced ultrasonic imaging technology and quantization software, which can clearly present the ultrasonic images of tumor spheres and accurately quantify the grayscale values of the region of interest, providing accurate data for subsequent statistical analysis. And through one - way analysis of variance using the Graphpad software, the sensitivity differences of ultrasonic images under different conditions can be scientifically evaluated, providing strong evidence for the early diagnosis and treatment of tumors, and having broad application prospects and important clinical significance.
[0048] As described above, this is a preferred specific embodiment of the present invention. The protection scope of the present invention is not limited thereto. Any person skilled in the art, within the technical scope disclosed by the present invention, in combination with the prior art or common knowledge, any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention should be covered within the protection scope of the present invention.
Claims
1. A method for detecting sensitivity of tumor ultrasound images, characterized in that: The following steps are involved: S1: Preparation of tumor spheres to simulate tumors, using 4T1 breast cancer cell line, formed by suspension culture in complete medium containing Matrigel; S2: Detect the size of nano- and micro-contrast agents, and measure the size of contrast agents in tumor sphere samples using a dynamic light scattering instrument; S3: Perform penetration test on tumor spheres to observe whether the contrast material can enter their interior, and use laser confocal microscopy to evaluate the penetration of Dil dye-labeled materials in tumor spheres; S4: Perform ultrasound imaging on tumor spheres of different sizes and obtain imaging results in two-dimensional mode and contrast mode using preset ultrasound imaging conditions; S5: Quantify the ultrasound grayscale results, transfer the ultrasound images to the ultrasound quantification software, select the region of interest and calculate the grayscale value for statistical analysis.
2. A method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: In step S1, 1640 complete medium supplemented with matrigel at a final concentration of 2.5% was used to centrifuge in a high-speed refrigerated centrifuge to allow cells to converge and accelerate the formation of tumor spheres by 4T1 breast cancer cells. The size of the tumor spheres was measured every day.
3. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: In step S2, the same volume of deionized water was used to dilute the micro- and nano-contrast materials, and the contrast agent size was measured using a dynamic light scattering device (zetasizer pro). The measurement conditions included a temperature of 25°C, a measurement angle of 173°, and a measurement mode of general mode. Each sample was measured three times.
4. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: In step S3, the tumor spheres were incubated with the Dil-labeled contrast material at 37°C for 16 hours.
5. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: In step S3, the tumor spheroids were washed with phosphate buffered saline and the penetration of micro- and nano-contrast materials was observed using confocal microscopy.
6. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: The ultrasound imaging conditions in step S4 include frequency 18 MHz, contrast gain 37 dB, two-dimensional mode contrast 19 dB, scanning depth 10.55 mm, and scanning width 9.25 mm.
7. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: In step S5, a preset algorithm is used to automatically identify and outline the boundaries of the region of interest, and manual adjustments are made to improve the selection accuracy. Then, image post-processing functions are used for enhancement, filtering, and edge detection, and the RGB channel values of each pixel in the ROI are calculated and the grayscale value is extracted.
8. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: The gray value calculation formula in step S5 is I=0.311×R+0.591×G+0.115×B.
9. The method for detecting sensitivity of tumor ultrasound images according to claim 1, characterized in that: Step S5 also included importing the grayscale quantification data into Graphpad software for statistical analysis, using one-way ANOVA, and p < 0.05 was considered statistically significant.