Circulating tumor cell detection and analysis device

Abstract

The invention discloses a circulating tumor cell detection and analysis device, and belongs to the field of cell detection. A circulating tumor cell detection and analysis device comprises a box body, a sample tube, a mixing device and a glass slide area, an operation panel and a PLC are arranged on the front face of the box body, the sample tube, the mixing device and the glass slide area are arranged in the box body, a circulating tumor cell detection system A is further arranged in the box body, and a dyeing quality monitoring system B is arranged on the mixing device. The problem that the detection result is not accurate and stable enough due to limitation in the prior art is solved, various characteristics of the circulating tumor cells can be accurately recognized by collecting the images and performing a series of operations in cooperation with the deep learning target detection network, a reliable basis is provided for diagnosis, and the detection efficiency is improved. By monitoring the fluorescence signal, the temperature, the pH value and the like in real time, the dyeing quality can be strictly controlled, the reliability of the detection result is ensured, and misdiagnosis caused by the dyeing problem is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of cell detection, and in particular to a circulating tumor cell detection and analysis device. Background Art

[0002] Circulating tumor cells (CTCs) are tumor cells that shed from solid tumors and enter the bloodstream. Their detection is crucial for early diagnosis, disease monitoring, efficacy assessment, and prognosis. Traditional CTC detection methods rely primarily on techniques such as immunocytochemistry and flow cytometry, which are susceptible to human interference, resulting in inaccurate and unstable test results. Therefore, they do not meet current needs. To address this, we have proposed a CTC detection and analysis device. Summary of the Invention

[0003] The purpose of the present invention is to provide a circulating tumor cell detection and analysis device, which captures images of biological samples that have been fluorescently stained in the slide area, and enhances the accuracy of cell analysis by improving image acquisition quality, processing effect and feature recognition accuracy. A staining quality monitoring system is set up to monitor the staining status of biological samples in real time, and timely warn of staining abnormalities to ensure that samples entering the detection link meet the requirements, thereby solving the problems raised in the above-mentioned background technology.

[0004] To achieve the above objectives, the present invention provides the following technical solutions: a circulating tumor cell detection and analysis device, comprising a housing, sample tubes, a mixing device, and a glass slide area. The front of the housing is provided with an operation panel and a PLC controller, respectively. The interior of the housing is provided with sample tubes, a mixing device, and a glass slide area. The interior of the housing is also provided with a circulating tumor cell detection system A for collecting data from biological samples in the glass slide area. The mixing device is provided with a staining quality monitoring system B for monitoring the quality of fluorescent staining of the biological samples. The circulating tumor cell detection system A comprises an image acquisition module, an image processing module, a feature recognition module and a cell analysis module, and is configured to acquire images of biological samples that have been fluorescently stained in the glass slide area (4), process the acquired images, analyze the processed images and output analysis results; The cell analysis module integrates a circulating tumor cell activity assessment submodule, which comprehensively assesses the activity status of cells by combining cell morphology, fluorescence intensity, and mitochondrial activity. It can quickly identify highly invasive tumor cells based on the cell activity index. The staining quality monitoring system B is configured to monitor whether the fluorescent staining quality of the biological sample meets the requirements of circulating tumor cell detection and analysis by building a staining effectiveness monitoring module into the hybrid mechanism.

[0005] Furthermore, the circulating tumor cell detection system A comprises: An image acquisition module is configured to use a high-resolution camera to capture minute details of biological sample cells on the slide area, and the high-resolution camera supports multi-angle shooting to obtain cell images from different directions; an image processing module configured to use a denoising algorithm to remove background noise and interference signals from the image, use a color space conversion algorithm to analyze the color information of the image, automatically adjust the hue, saturation and brightness of the image based on the analysis results, and use a histogram-based contrast enhancement algorithm to adaptively adjust the brightness and contrast of the image; A feature recognition module is configured to build a deep learning-based object detection network that is trained on a large dataset of labeled circulating tumor cell images. The network identifies the location and boundaries of cells in the image and extracts multiple features from the identified cell regions, including cell morphology, fluorescence intensity, and texture. The cell analysis module is configured to establish a cell analysis model, input the features identified by the feature recognition module into the cell analysis model for analysis, and make a comprehensive judgment on whether the patient has circulating tumor cells and the possible type and stage of the tumor through the cell analysis model.

[0006] Furthermore, the image acquisition module includes: According to the fluorescence intensity and background signal of the cells, the exposure time is intelligently adjusted, specifically: For areas with weak fluorescence signals, extend the exposure time to obtain images with sufficient brightness; For areas with strong fluorescent signals, the exposure time is automatically reduced to avoid overexposure; At the same time, frame synthesis technology is used to fuse multiple frames of images with different exposure times to generate high-quality wide dynamic range images.

[0007] Furthermore, the circulating tumor cell detection system A further comprises: A report generation module is configured to automatically generate a detailed analysis report based on the analysis results output by the cell analysis module. The report uses both pictures and texts and includes the number of circulating tumor cells detected, their distribution, cell characteristics, diagnostic conclusions, and recommended follow-up treatment plans; The quality monitoring module is configured to monitor the working status of each module in real time during the entire detection and analysis process. Once a quality problem or abnormality is found, an alarm will be immediately issued and abnormal data and fault information will be recorded; For example, the camera imaging quality, focus accuracy, exposure parameters, etc. of the image acquisition module; the denoising effect, color correction accuracy, etc. of the image processing module; the recognition accuracy, false alarm rate and missed alarm rate of the feature recognition module.

[0008] Furthermore, the dyeing quality monitoring system B comprises: a staining effectiveness monitoring module configured to detect the intensity of the fluorescent signal in each area of ​​the biological sample after fluorescent staining, and simultaneously detect changes in the temperature and pH value of the biological sample in the mixing mechanism; The abnormality warning module is configured to compare the data obtained by the staining effectiveness monitoring module with the threshold range required for the detection of circulating tumor cells. If any data exceeds the threshold range, it is determined that the biological sample has a staining abnormality; The early warning release module is configured to immediately generate corresponding early warning information once a staining abnormality is identified. The early warning information includes the type of abnormality, the time of occurrence, and the cause of the abnormality. The early warning information is sent to the terminal devices of operators and laboratory managers through various communication methods.

[0009] Furthermore, the dyeing effectiveness monitoring module is specifically: Fluorescence detection: A highly sensitive fluorescence detection probe is installed inside the hybrid mechanism to detect the fluorescence signal intensity of each area of ​​the biological sample after fluorescence staining; Temperature monitoring: A high-precision temperature sensor is integrated into the mixing mechanism to monitor the temperature changes of biological samples during the staining process in real time; pH monitoring: A pH sensor is installed inside the mixing mechanism to detect changes in the pH value of biological samples during the staining process.

[0010] Furthermore, a liquid storage tank is provided on the box body, and the liquid storage tank, sample tube, mixing mechanism and glass slide area are interconnected through a connecting pipe. A first suction pump is provided on the connecting pipe at the sample tube, a second suction pump is provided on the connecting pipe at the liquid storage tank, and a third suction pump is provided on the connecting pipe at the mixing mechanism. The first suction pump, the second suction pump and the third suction pump are all connected to the PLC controller signal.

[0011] Furthermore, the mixing mechanism includes a mixing chamber, a bracket and a shaking device. The bracket is installed inside the box, the mixing chamber is placed on the bracket, and the staining quality monitoring system B is located in the mixing chamber. The mixing chamber mixes the biological sample through the shaking generated by the shaking device arranged on the side.

[0012] Furthermore, the cell analysis module is integrated with a circulating tumor cell activity assessment submodule, which is configured as follows: Receive cell morphological features, fluorescence intensity features, and mitochondrial activity probe signal intensity extracted by the feature recognition module; cell morphological features include: cell perimeter, cell area, and cell circularity; fluorescence intensity features include: the average fluorescence intensity of the marker and the standard deviation of the fluorescence intensity fluctuation over time; According to the cell morphology characteristics, fluorescence intensity characteristics and mitochondrial activity probe signal intensity, the cell activity index was calculated using the following formula: in, is the cell activity index, 、 and is the weighting coefficient, , , is the cell circularity, is the cell area, is the cell perimeter, is the reference value of the circularity of healthy cells, is the mean fluorescence intensity of the marker, is the standard deviation of the fluorescence intensity of the marker over time, is the fluorescence intensity stability coefficient calibrated by experiment, is the signal intensity of the mitochondrial activity probe, is the healthy threshold of mitochondrial activity; Based on the cell activity index, the activity classification results are determined: When the cell activity index is greater than or equal to the first threshold, it is determined to be a highly invasive circulating tumor cell; When the cell activity index is greater than or equal to the second threshold and less than the first threshold, it is determined to be a medium-activity circulating tumor cell; When the cell activity index is less than the second threshold, it is judged as a low activity / apoptosis prone cell. The activity classification results are transferred to the report generation module.

[0013] Furthermore, a three-axis accelerometer is installed on the surface of the driving shaft of the shaking device of the hybrid mechanism to collect three-dimensional vibration data in real time; The main vibration frequency in the three-dimensional vibration data is identified through spectrum analysis. When the main vibration frequency offset exceeds the positive and negative preset range or the effective value of the vibration acceleration is greater than the preset multiple of gravity acceleration, a mechanical bearing wear warning signal is sent to the PLC controller.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention uses high-resolution camera multi-angle shooting and image processing denoising, color correction, contrast enhancement and other operations, combined with a deep learning target detection network, to accurately identify the various characteristics of circulating tumor cells, providing a reliable basis for diagnosis. By real-time monitoring of fluorescence signals, temperature, pH values, etc., the staining quality can be strictly controlled. Once an abnormality is found, an early warning will be issued and recorded immediately to ensure the reliability of the test results and avoid misdiagnosis due to staining problems.

[0015] Combining cell morphology, fluorescence intensity, and mitochondrial activity allows for a comprehensive assessment of cell viability. Compared to single features, this multi-dimensional information provides a more accurate assessment of cell viability. The cell viability index can help quickly identify highly invasive tumor cells, providing support for early diagnosis and treatment strategies.

[0016] It can promptly detect mechanical equipment failures, avoid equipment damage or unexpected downtime, and reduce maintenance costs. It can monitor equipment operating status in real time and provide timely feedback on fault information, providing equipment maintenance and operating personnel with sufficient time to intervene and prevent the failure from affecting production. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Schematic diagram of the appearance of the circulating tumor cell detection and analysis device of the present invention; Figure 2 Schematic diagram of the interior of the circulating tumor cell detection and analysis device of the present invention; Figure 3 It is a structural schematic diagram of the mixing mechanism of the present invention; Figure 4 Schematic diagram of the modules of the circulating tumor cell detection and analysis device of the present invention; Figure 5 Flowchart of dyeing quality monitoring system B of the present invention.

[0018] In the figure: 1. Box body; 11. Operation panel; 12. PLC controller; 13. Liquid storage tank; 14. First suction pump; 15. Second suction pump; 16. Third suction pump; 2. Sample tube; 3. Mixing mechanism; 31. Mixing chamber; 32. Bracket; 33. Shaking device; 4. Glass loading area. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] In order to solve the technical problem that the existing circulating tumor cell detection methods mainly rely on immunocytochemistry and flow cytometry and are easily interfered by human factors, resulting in inaccurate and unstable detection results, please refer to Figure 1-Figure 5 , this embodiment provides the following technical solutions: A circulating tumor cell detection and analysis device includes a housing 1, sample tubes 2, a mixing device 3, and a glass slide 4. An operation panel 11 and a PLC controller 12 are provided on the front of the housing 1. The operation panel 11 is used to issue instructions, and the PLC controller 12 is used to control the coordination of various mechanisms within the housing 1 according to the issued instructions to complete circulating tumor cell detection and analysis. The housing 1 is provided with a sample tube 2, a mixing device 3, and a glass slide 4. The sample tube 2 is used to store a biological sample. The mixing device 3 is used to mix a fluorescent dye with the biological sample. A circulating tumor cell detection system A is also provided within the housing 1 for collecting data from biological samples in the glass slide 4. The mixing device 3 is provided with a staining quality monitoring system B for monitoring the quality of fluorescent staining of the biological sample. The circulating tumor cell detection system A comprises an image acquisition module, an image processing module, a feature recognition module and a cell analysis module, and is configured to acquire images of biological samples that have been fluorescently stained in the glass slide area (4), process the acquired images, analyze the processed images and output analysis results; The cell analysis module integrates a circulating tumor cell activity assessment submodule, which comprehensively assesses the activity status of cells by combining cell morphology, fluorescence intensity, and mitochondrial activity. It can quickly identify highly invasive tumor cells based on the cell activity index. The staining quality monitoring system B is configured to monitor whether the fluorescent staining quality of the biological sample meets the requirements of circulating tumor cell detection and analysis by building a staining effectiveness monitoring module into the mixing mechanism 3.

[0021] The technical effects of the above technical solution are as follows: the circulating tumor cell detection system A can collect, process and analyze images of biological samples after fluorescent staining in the slide area 4, thereby comprehensively judging whether the patient has circulating tumor cells and the possible type and stage of the tumor, providing a reliable basis for clinical diagnosis, while the staining quality monitoring system B has a built-in staining effectiveness monitoring module, which can monitor the fluorescent staining quality of the biological sample in the mixing device 3 in real time, including indicators such as fluorescence signal intensity, temperature and pH value changes, to avoid detection errors caused by staining problems, improve the accuracy and reliability of the test results, reduce sample waste and repeated testing costs, and ensure the efficiency and stability of the entire detection and analysis process.

[0022] Circulating tumor cell detection system A, including: An image acquisition module is configured to use a high-resolution camera to capture minute details of the biological sample cells on the slide area 4, and the high-resolution camera supports multi-angle shooting to obtain cell images from different directions; an image processing module configured to use a denoising algorithm to remove background noise and interference signals from the image, use a color space conversion algorithm to analyze the color information of the image, automatically adjust the hue, saturation and brightness of the image based on the analysis results, and use a histogram-based contrast enhancement algorithm to adaptively adjust the brightness and contrast of the image; A feature recognition module is configured to build a deep learning-based object detection network that is trained on a large dataset of labeled circulating tumor cell images. The network identifies the location and boundaries of cells in the image and extracts multiple features from the identified cell regions, including cell morphology, fluorescence intensity, and texture. The cell analysis module is configured to establish a cell analysis model, input the features identified by the feature recognition module into the cell analysis model for analysis, and make a comprehensive judgment on whether the patient has circulating tumor cells and the possible type and stage of the tumor through the cell analysis model.

[0023] The technical effects of the above technical solution are as follows: the image acquisition module uses a high-resolution camera and supports multi-angle shooting, providing rich and comprehensive image information for subsequent accurate cell feature extraction, ensuring that the key features of the cells are not missed. The image processing module uses denoising, color space conversion and histogram contrast enhancement algorithms to optimize the image to make the cell image clearer. The feature recognition module accurately identifies the cell position and boundaries through the target detection network, extracts morphology, fluorescence intensity, texture and other features, and can fully capture the key information of the cell, providing strong support for the subsequent accurate judgment of the nature of the cell. The cell analysis module is based on the established cell analysis model and can make a comprehensive judgment on whether the patient has circulating tumor cells and the possible type and stage of the tumor, providing comprehensive diagnostic information, assisting doctors to make clinical decisions more accurately, and improving the accuracy and timeliness of tumor diagnosis. It is of great significance for the early detection of tumors, formulation of treatment plans and prognosis evaluation.

[0024] Image acquisition module, including: According to the fluorescence intensity and background signal of the cells, the exposure time is intelligently adjusted, specifically: For areas with weak fluorescence signals, extend the exposure time to obtain images with sufficient brightness; For areas with strong fluorescent signals, the exposure time is automatically reduced to avoid overexposure; At the same time, frame synthesis technology is used to fuse multiple frames of images with different exposure times to generate high-quality wide dynamic range images.

[0025] The technical effect of the above technical solution is: through intelligent exposure adjustment, it ensures that areas of different fluorescence intensities in the image can be properly presented. At the same time, frame synthesis technology is used to fuse multiple frames of images with different exposure times to generate wide dynamic range images, which further improves the image quality and enables the image to more accurately reflect the actual situation of the cells. Through the above design, a reliable image foundation is provided for subsequent cell analysis, thereby improving the accuracy and reliability of the detection results.

[0026] Circulating tumor cell detection system A, further comprising: A report generation module is configured to automatically generate a detailed analysis report based on the analysis results output by the cell analysis module. The report uses both pictures and texts and includes the number of circulating tumor cells detected, their distribution, cell characteristics, diagnostic conclusions, and recommended follow-up treatment plans; The quality monitoring module is configured to monitor the working status of each module in real time during the entire detection and analysis process. Once a quality problem or abnormality is found, an alarm will be immediately issued and abnormal data and fault information will be recorded; For example, the camera imaging quality, focus accuracy, exposure parameters, etc. of the image acquisition module; the denoising effect, color correction accuracy, etc. of the image processing module; the recognition accuracy, false alarm rate and missed alarm rate of the feature recognition module.

[0027] The technical effects of the above technical solution are: the report generation module automatically generates detailed analysis reports, so that doctors can quickly obtain key information and provide strong support for clinical decision-making; while the quality monitoring module's real-time monitoring of the detection and analysis process can promptly detect and resolve possible quality problems or abnormal situations, helping to avoid detection errors caused by equipment failure, reagent problems or operational errors, and ensuring the authenticity and accuracy of the test results.

[0028] Staining quality monitoring system B, including: The staining effectiveness monitoring module is configured to detect the fluorescence signal intensity of each area of ​​the biological sample after fluorescent staining, and to detect the temperature and pH value changes of the biological sample in the mixing mechanism 3, specifically: Fluorescence detection: A highly sensitive fluorescence detection probe is installed inside the mixing mechanism 3 to detect the fluorescence signal intensity of each area of ​​the biological sample after fluorescence staining; Temperature monitoring: A high-precision temperature sensor is integrated into the mixing mechanism 3 to monitor the temperature changes of the biological sample during the staining process in real time; pH monitoring: A pH sensor is installed inside the mixing mechanism 3 to detect changes in the pH value of the biological sample during the staining process; The abnormality warning module is configured to compare the data obtained by the staining effectiveness monitoring module with the threshold range required for the detection of circulating tumor cells. If any data exceeds the threshold range, it is determined that the biological sample has a staining abnormality; The early warning release module is configured to immediately generate corresponding early warning information once a staining abnormality is identified. The early warning information includes the type of abnormality, the time of occurrence, and the cause of the abnormality. The early warning information is sent to the terminal devices (such as computers, mobile phones, etc.) of operators and laboratory managers through various communication methods (such as local area network, wireless communication, etc.).

[0029] The technical effect of the above technical solution is: the staining effectiveness monitoring module can accurately grasp the key parameters in the staining process by real-time detection of the fluorescence signal intensity of each area of ​​the biological sample after fluorescent staining, as well as the temperature and pH value changes of the sample in the mixing mechanism 3, which helps to ensure that the staining quality meets the requirements of circulating tumor cell detection and analysis, and avoids problems such as inaccurate or undetectable test results due to poor staining quality. The abnormal warning module can promptly detect problems that may occur during the staining process, such as excessively strong or weak fluorescence signals, abnormal temperature or pH values, etc., which affect the staining quality. After identifying the abnormal staining situation, the warning release module immediately generates detailed warning information, so that relevant personnel can take measures quickly, adjust the staining process or re-stain in time, and avoid continuing to conduct subsequent tests on samples with poor staining quality, thereby improving detection efficiency and reducing waste of time and resources.

[0030] The housing 1 is provided with a liquid storage tank 13. The liquid storage tank 13, the sample tube 2, the mixing mechanism 3, and the glass slide area 4 are interconnected via connecting pipes. A first suction pump 14 is provided on the connecting pipe at the sample tube 2, a second suction pump 15 is provided on the connecting pipe at the liquid storage tank 13, and a third suction pump 16 is provided on the connecting pipe at the mixing mechanism 3. The first suction pump 14, the second suction pump 15, and the third suction pump 16 are all connected to the PLC controller 12 for signal transmission. The mixing mechanism 3 includes a mixing chamber 31, a bracket 32, and a shaking device 33. The bracket 32 ​​is installed inside the box 1, and the mixing chamber 31 is placed on the bracket 32. The staining quality monitoring system B is located in the mixing chamber 31. The mixing chamber 31 mixes the biological sample by shaking generated by the shaking device 33 installed on the side. In actual use, the sample tube 2 is placed in the box 1, and instructions are issued through the operation panel 11 and unified signal control is performed by the PLC controller 12. The biological sample in the sample tube 2 is extracted into the mixing chamber 31 through the first suction pump 14, and then the fluorescent dye in the liquid storage tank 13 is extracted through the second suction pump 15. The shaking device 33 is started to mix the biological sample in the mixing chamber 31 with the fluorescent dye. Then, the mixed biological sample is extracted into the glass slide area 4 through the third suction pump 16, so that the circulating tumor cell detection system A can perform the detection and analysis of circulating tumor cells.

[0031] The technical effects of the above technical scheme are: the operation of each suction pump is precisely controlled by the PLC controller 12 to ensure the precise delivery and proportional adjustment of biological samples and fluorescent dyes, improve the accuracy and repeatability of the test, and avoid inaccurate test results caused by delivery errors. The liquid storage tank 13, the sample tube 2, the mixing mechanism 3, and the glass slide area 4 are interconnected through the connecting tube and are uniformly controlled by the PLC controller 12, thereby realizing high integration and automated operation of the entire detection system, reducing manual intervention, reducing the risk of operational errors, and improving detection efficiency and system stability. The mixing mechanism 3 uses the shaking generated by the shaking device 33 to fully mix the biological sample and the staining reagent in the mixing chamber 31, ensuring the uniformity and consistency of staining, avoiding uneven staining caused by insufficient mixing, and improving the staining quality. The staining quality monitoring system B is located in the mixing chamber 31 and can monitor key parameters such as the fluorescence signal intensity, temperature and pH value of the biological sample during the staining process in real time to ensure that the staining process meets the requirements, promptly discover and resolve staining abnormalities, and improve the reliability of the test results.

[0032] Working principle: The liquid storage tank 13, sample tube 2, mixing mechanism 3, and glass slide area 4 are interconnected through connecting tubes and are uniformly controlled by the PLC controller 12, realizing a high degree of integration and automated operation of the entire detection system. Through multi-angle shooting with a high-resolution camera and image processing denoising, color correction, contrast enhancement and other operations, combined with a deep learning target detection network, it can accurately identify the various characteristics of circulating tumor cells and provide a reliable basis for diagnosis. By real-time monitoring of fluorescence signals, temperature, pH value, etc., it can strictly control the staining quality. Once an abnormality is found, it will immediately issue an early warning and record it to ensure the reliability of the test results and avoid misdiagnosis due to staining problems.

[0033] The cell analysis module is integrated with a circulating tumor cell activity assessment submodule, which is configured as follows: Receive cell morphological features, fluorescence intensity features, and mitochondrial activity probe signal intensity extracted by the feature recognition module; cell morphological features include: cell perimeter, cell area, and cell circularity; fluorescence intensity features include: the average fluorescence intensity of the marker and the standard deviation of the fluorescence intensity fluctuation over time; According to the cell morphology characteristics, fluorescence intensity characteristics and mitochondrial activity probe signal intensity, the cell activity index was calculated using the following formula: in, is the cell activity index, 、 and is the weighting coefficient, , , is the cell circularity, is the cell area, is the cell perimeter, is the reference value of the circularity of healthy cells, is the mean fluorescence intensity of the marker, is the standard deviation of the fluorescence intensity of the marker over time, is the fluorescence intensity stability coefficient calibrated by experiment, is the signal intensity of the mitochondrial activity probe, is the healthy threshold of mitochondrial activity; Based on the cell activity index, the activity classification results are determined: When the cell activity index is greater than or equal to the first threshold, it is determined to be a highly invasive circulating tumor cell; When the cell activity index is greater than or equal to the second threshold and less than the first threshold, it is determined to be a medium-activity circulating tumor cell; When the cell activity index is less than the second threshold, it is judged as a low activity / apoptosis prone cell. The activity classification results are transferred to the report generation module.

[0034] The working principle and beneficial effects of the above technical solution are: Cell area, cell perimeter, and cell circularity are three key geometric characteristics that reflect the shape and size of a cell. Cell morphology is often closely related to its activity state. Normal cells exhibit a relatively regular, nearly circular appearance, while apoptotic or inactive cells may exhibit distorted shapes and reduced circularity. Circularity is a measure of cell health and morphological characteristics. Healthy cells typically have a circularity value close to 1, while diseased or cells with decreased activity exhibit lower circularity. The mean fluorescence intensity and standard deviation of a marker can reflect changes in the cell's internal metabolic state or specific biomarkers. Cellular biomarkers are typically detected using fluorescent labeling, and the level of fluorescence intensity is closely related to the cell's physiological activity and function. Fluorescence fluctuation is associated with the dynamics of intracellular biological processes. For example, when a cell is active, the fluorescence intensity of a marker may exhibit large fluctuations, while in a quiescent or apoptotic state, the fluctuations are smaller. Mitochondrial activity probes measure mitochondrial activity to reflect the cell's energy state. Mitochondria are the cell's energy production plants, and active mitochondria generally indicate a high metabolic level. Healthy cells typically have high mitochondrial activity, while degenerated or apoptotic cells have low mitochondrial activity.

[0035] The embodiments of the present invention combine cell morphology, fluorescence intensity, and mitochondrial activity to comprehensively assess the activity status of cells. Compared with a single feature, the integration of multi-dimensional information can provide a more accurate assessment of cell activity. The level of cell activity index can help quickly identify highly invasive tumor cells, thereby providing support for early diagnosis and treatment strategies for tumors.

[0036] A three-axis accelerometer is installed on the surface of the driving shaft of the shaking device 33 of the mixing mechanism 3 to collect three-dimensional vibration data in real time; The main vibration frequency in the three-dimensional vibration data is identified through spectrum analysis. When the main vibration frequency offset exceeds the positive and negative preset range or the effective value of the vibration acceleration is greater than the preset multiple of gravity acceleration, a mechanical bearing wear warning signal is sent to the PLC controller 12.

[0037] The working principle and beneficial effects of the above technical solution are: A triaxial accelerometer, mounted on the rotating shaft of mechanical equipment, can capture vibrations in all directions. Spectral analysis is performed on the collected vibration data. Fourier transform is used to convert time-domain data into frequency-domain data, identifying the dominant frequency component in the vibration signal. Normal operation of mechanical equipment typically exhibits specific frequency characteristics. When a system failure (such as wear or imbalance) occurs, the dominant frequency often changes. Preset thresholds are set based on the offset of the dominant vibration frequency and the effective value of the acceleration. When the offset of the dominant vibration frequency exceeds the normal range, or the vibration acceleration exceeds a preset multiple (relative to gravity), the system identifies a possible mechanical failure and promptly sends a warning signal to the PLC controller. Upon receiving the warning signal, the PLC controller can take appropriate measures, such as slowing down or stopping the machine for inspection, to prevent further escalation of the fault.

[0038] The embodiments of the present invention can promptly detect mechanical equipment failures, avoid equipment damage or unexpected downtime, and reduce maintenance costs. They can monitor equipment operating status in real time and provide timely feedback on failures, providing sufficient time for equipment maintenance and operators to intervene and prevent failures from impacting production.

[0039] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0040] While the embodiments of the present invention have been shown and described, it will be apparent to those skilled in the art that various changes, modifications, substitutions, and alterations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A circulating tumor cell detection and analysis device, comprising a housing (1), a sample tube (2), a mixing device (3) and a glass slide area (4), characterized in that: The front of the box (1) is provided with an operation panel (11) and a PLC controller (12), and the interior of the box (1) is provided with a sample tube (2), a mixing device (3) and a glass slide area (4). The interior of the box (1) is also provided with a circulating tumor cell detection system A for collecting data of biological samples in the glass slide area (4), and the mixing device (3) is provided with a staining quality monitoring system B for monitoring the fluorescent staining quality of the biological sample; The circulating tumor cell detection system A comprises an image acquisition module, an image processing module, a feature recognition module and a cell analysis module, and is configured to acquire images of biological samples that have been fluorescently stained in the glass slide area (4), process the acquired images, analyze the processed images and output analysis results; The cell analysis module integrates a circulating tumor cell activity assessment submodule, which comprehensively assesses the activity status of cells by combining cell morphology, fluorescence intensity, and mitochondrial activity. It can quickly identify highly invasive tumor cells based on the cell activity index. The staining quality monitoring system B is configured to monitor whether the fluorescent staining quality of the biological sample meets the requirements of circulating tumor cell detection and analysis by building a staining effectiveness monitoring module into the mixing mechanism (3).

2. A circulating tumor cell detection and analysis device according to claim 1, characterized in that: The circulating tumor cell detection system A comprises: An image acquisition module is configured to use a high-resolution camera to capture minute details of biological sample cells on the glass slide area (4), and the high-resolution camera supports multi-angle shooting to obtain cell images from different directions; an image processing module configured to use a denoising algorithm to remove background noise and interference signals from the image, use a color space conversion algorithm to analyze the color information of the image, automatically adjust the hue, saturation and brightness of the image based on the analysis results, and use a histogram-based contrast enhancement algorithm to adaptively adjust the brightness and contrast of the image; A feature recognition module is configured to build a deep learning-based object detection network that is trained on a large dataset of labeled circulating tumor cell images. The network identifies the location and boundaries of cells in the image and extracts multiple features from the identified cell regions, including cell morphology, fluorescence intensity, and texture. The cell analysis module is configured to establish a cell analysis model, input the features identified by the feature recognition module into the cell analysis model for analysis, and make a comprehensive judgment on whether the patient has circulating tumor cells and the possible type and stage of the tumor through the cell analysis model.

3. A circulating tumor cell detection and analysis device according to claim 2, characterized in that: The image acquisition module includes: According to the fluorescence intensity and background signal of the cells, the exposure time is intelligently adjusted, specifically: For areas with weak fluorescence signals, extend the exposure time to obtain images with sufficient brightness; For areas with strong fluorescence signals, the exposure time is automatically reduced; At the same time, frame synthesis technology is used to fuse multiple frames of images with different exposure times to generate high-quality wide dynamic range images.

4. A circulating tumor cell detection and analysis device according to claim 2, characterized in that: The circulating tumor cell detection system A further comprises: A report generation module is configured to automatically generate a detailed analysis report based on the analysis results output by the cell analysis module. The report uses both pictures and texts and includes the number of circulating tumor cells detected, their distribution, cell characteristics, diagnostic conclusions, and recommended follow-up treatment plans; The quality monitoring module is configured to monitor the working status of each module in real time during the entire detection and analysis process. If quality problems or abnormal conditions are found, an alarm will be issued immediately and abnormal data and fault information will be recorded.

5. The circulating tumor cell detection and analysis device according to claim 1, characterized in that: The staining quality monitoring system B comprises a staining effectiveness monitoring module configured to detect the intensity of the fluorescence signal of each region of the biological sample after fluorescent staining, and simultaneously detect changes in the temperature and pH value of the biological sample in the mixing mechanism (3); The abnormality warning module is configured to compare the data obtained by the staining effectiveness monitoring module with the threshold range required for the detection of circulating tumor cells. If any data exceeds the threshold range, it is determined that the biological sample has a staining abnormality; The early warning release module identifies abnormal dyeing conditions and immediately generates corresponding early warning information, which includes the type of abnormality, time of occurrence, and cause of the abnormality. The early warning information is sent to the terminal devices of operators and laboratory managers through various communication methods.

6. A circulating tumor cell detection and analysis device according to claim 5, characterized in that: The dyeing effectiveness monitoring module is specifically: Fluorescence detection: A highly sensitive fluorescence detection probe is used and installed inside the mixing mechanism (3) to detect the fluorescence signal intensity of each area of ​​the biological sample after fluorescence staining; Temperature monitoring: A high-precision temperature sensor is integrated into the mixing mechanism (3) to monitor the temperature changes of the biological sample during the staining process in real time; pH monitoring: A pH sensor is installed inside the mixing mechanism (3) to detect changes in the pH value of the biological sample during the staining process.

7. A circulating tumor cell detection and analysis device according to claim 1, characterized in that: The box body (1) is provided with a liquid storage tank (13). The liquid storage tank (13), the sample tube (2), the mixing mechanism (3) and the glass slide area (4) are interconnected through connecting pipes. A first suction pump (14) is provided on the connecting pipe at the sample tube (2), a second suction pump (15) is provided on the connecting pipe at the liquid storage tank (13), and a third suction pump (16) is provided on the connecting pipe at the mixing mechanism (3). The first suction pump (14), the second suction pump (15) and the third suction pump (16) are all connected to the PLC controller (12) for signal transmission.

8. The circulating tumor cell detection and analysis device according to claim 1, characterized in that: The mixing mechanism (3) includes a mixing chamber (31), a bracket (32) and a shaking device (33), wherein the bracket (32) is installed inside the box (1), the mixing chamber (31) is placed on the bracket (32), and the staining quality monitoring system B is located in the mixing chamber (31). The mixing chamber (31) mixes the biological sample by shaking generated by the shaking device (33) arranged on the side.

9. A circulating tumor cell detection and analysis device according to claim 2, characterized in that: The cell analysis module is integrated with a circulating tumor cell activity assessment submodule, which is configured as follows: Receive cell morphological features, fluorescence intensity features, and mitochondrial activity probe signal intensity extracted by the feature recognition module; cell morphological features include: cell perimeter, cell area, and cell circularity; fluorescence intensity features include: mean fluorescence intensity of the marker and standard deviation of fluorescence intensity fluctuation over time; According to the cell morphology characteristics, fluorescence intensity characteristics and mitochondrial activity probe signal intensity, the cell activity index was calculated using the following formula: in, is the cell activity index, 、 and is the weighting coefficient, , , is the cell circularity, is the cell area, is the cell perimeter, is the reference value of the circularity of healthy cells, is the mean fluorescence intensity of the marker, is the standard deviation of the fluorescence intensity of the marker over time, is the fluorescence intensity stability coefficient calibrated by experiment, is the signal intensity of the mitochondrial activity probe, is the healthy threshold of mitochondrial activity; Based on the cell activity index, the activity classification results are determined: When the cell activity index is greater than or equal to the first threshold, it is determined to be a highly invasive circulating tumor cell; When the cell activity index is greater than or equal to the second threshold and less than the first threshold, it is determined to be a medium-activity circulating tumor cell; When the cell activity index is less than the second threshold, it is judged as a low activity / apoptosis prone cell. The activity classification results are transferred to the report generation module.

10. The circulating tumor cell detection and analysis device according to claim 8, characterized in that: A three-axis accelerometer is installed on the surface of the driving shaft of the shaking device (33) of the mixing mechanism (3) to collect three-dimensional vibration data in real time; The main vibration frequency in the three-dimensional vibration data is identified by spectrum analysis. When the main vibration frequency offset exceeds a preset positive or negative range or the effective value of the vibration acceleration is greater than a preset multiple of gravity acceleration, a mechanical bearing wear warning signal is sent to the PLC controller (12).

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