48 results about "Lymph node metastasis" patented technology

The invention relates to the field of medical image analysis, in particular to a deep learning prediction system and method based on multi-modal thyroid cancer lymph node metastasis, and the system comprises a data collection module, a preprocessing module, a nodule segmentation module, a feature extraction module, a feature fusion module, a metastasis prediction module, an interpretability analysis module and a result display module. An ultrasonic image, an elastic imaging image, an ultra-micro blood flow image and clinical index data of a patient are integrated, an improved U-Net algorithm is used for precise segmentation of a thyroid nodule region, a multi-branch deep network is used for extracting multi-modal features, a dynamic weight fusion algorithm is used for integrating the features, and the accuracy of the thyroid nodule region is improved. According to the method, the thyroid cancer lymph node metastasis state (non-metastasis, central region metastasis or lateral neck metastasis) is predicted, meanwhile, a two-dimensional interpretability framework of Grad-CAM activation diagram and SHAP value contribution degree analysis is introduced, an intuitive prediction basis is provided for doctors, and the thyroid cancer lymph node metastasis prediction accuracy is remarkably improved.

The invention discloses a breast cancer lymph node metastasis prediction system based on a gene spectrum, and relates to the technical field of breast cancer prediction systems. Comprising a data acquisition module which collects gene spectrum data of a breast cancer patient and collects detailed clinical information of the patient; the preprocessing module is used for carrying out data cleaning and data normalization processing on the collected data; and the feature extraction module is used for extracting principal component features by applying principal component analysis on the basis of the gene expression data. According to the method, gene expression data are considered, various gene spectrum data such as gene mutation and copy number variation and detailed clinical information are integrated, the biological characteristics of the breast cancer can be reflected more comprehensively, and the prediction accuracy is improved.

The invention belongs to the technical field of medicines, and particularly relates to application of circRNA (Ribonucleic Acid) coded protein as a gastric cancer marker. The circRNA disclosed by the invention is provided with an ORF (Open Reading Frame) capable of coding a microprotein circUBE2G1-99aa of 99 amino acids, and the amino acid sequence of the protein is shown as SEQ ID NO: 1. According to the present invention, the designed circUBE2G1-99aa targeting antibody is adopted to detect the expression level of circUBE2G1-99aa in the collected clinical sample, and the expression level of circUBE2G1-99aa in the stomach cancer patient tissue is down-regulated, and is negatively correlated with the large tumor, the lymph node metastasis and the advanced pathological stage of the stomach cancer patient.

The invention provides a papillary thyroid carcinoma lymph node metastasis prediction method, system and equipment. The method comprises the following steps: acquiring a staining collagen image of a first papillary thyroid carcinoma section stained by a hematoxylin eosin staining method; obtaining a multi-photon collagen image of the second papillary thyroid carcinoma slice through a multi-photon imaging method; setting an observation area on the multi-photon collagen image according to the dyed collagen image; extracting collagen characteristics in the observation area; constructing a collagen feature scoring model according to an LASSO algorithm and the collagen features; obtaining a collagen feature score according to the collagen feature scoring model; acquiring clinical risk factors; the papillary thyroid carcinoma metastasis risk information is output according to the clinical risk factors and the collagen feature scores, the collagen features in the papillary thyroid carcinoma microenvironment can be accurately and quantitatively extracted by combining the multi-photon imaging technology and collagen feature analysis, accurate prediction of the papillary thyroid carcinoma metastasis risk is achieved, and the accuracy of the papillary thyroid carcinoma metastasis risk is improved. And the prediction accuracy can be further improved in combination with clinical risk factors.

The invention relates to the field of image analysis, in particular to a colon cancer lymph node metastasis risk prediction method and system based on image analysis. The method comprises the following steps: acquiring a pathological section scanning image, carrying out layer-by-layer downsampling and feature reconstruction, and generating pathological section topological features; carrying out adaptive clustering analysis and multi-parameter fusion evaluation on the basis of the pathological section topological features to obtain independent migration evaluation values of individual tumor cells; performing tumor metastasis branch analysis according to the independent migration evaluation value, and constructing a metastasis branch path distribution diagram; extracting an immunohistochemical staining image of a patient to obtain immune cell space distribution data; and performing multi-region lymphatic metastasis simulation and metastasis risk situation prediction based on the immune cell spatial distribution data and the metastasis branch path distribution diagram to obtain a final metastasis risk assessment result. According to the method, the lymph node metastasis risk is accurately and efficiently analyzed, and the credibility of a pathological analysis result is improved.

The invention relates to application of plasma exosomes A1BG and TF in diagnosis of cervical cancer lymph node metastasis. Detection of lymph node metastasis is achieved through the plasma exosome A1BG and the plasma exosome TF, the ratio of the abundance of the plasma exosome A1BG to the mass of the total exosome is limited to be smaller than or equal to 14.2690 ng / mg, the ratio of the abundance of the exosome TF to the mass of the total exosome is limited to be smaller than or equal to 96.2011 ng / mg, and combined detection is conducted through the plasma exosome A1BG and the plasma exosome TF, so that the sensitivity is 44%, the specificity is 100%, and the detection time is shortened. The preoperative joint detection of the A1BG and the TF can be prompted to detect nearly half of the patient without lymph node metastasis, and unnecessary pelvic lymph node cleaning operation is avoided.

The invention relates to the field of molecular diagnosis and tumor risk assessment, in particular to a marker combination and a kit for assessing the lymphatic metastasis risk of cervical cancer and application of the marker combination and the kit. The marker comprises a group of gene markers and a group of microbial markers, the gene markers comprise CARD9, MNX1AS2, MRAS, OLFML2A and RPS28, preferably, the gene markers further comprise at least one of CFL1P1 and GRASLND, and the microbial markers comprise microorganisms of the genus Dialister, the genus Catonella and the genus Campylobacter. The marker provided by the invention can be used for constructing an accurate risk assessment model, and can be used for developing a corresponding PCR (Polymerase Chain Reaction) kit, a mass spectrum or a chromatographic analysis system to realize metastasis risk prediction, curative effect assessment and new drug screening of cervical cancer patients.

The invention provides a papillary thyroid carcinoma neck lymph node metastasis risk prediction method and system based on blood indexes and TI-RADS grading, and relates to the technical field of medical data analysis. According to the method, an original data set is constructed by obtaining TI-RADS classification, the maximum diameter of nodules, the number of nodules, gender, age and conventional hematology indexes including apolipoprotein B and carcino-embryonic antigen of a patient, characteristic variables are screened by adopting LASSO regression, and an independent prediction risk factor model is established in combination with multi-factor Logistic regression. And further constructing a column graph model, carrying out performance verification through multiple statistical indexes, and deploying the model to a webpage calculator based on a shiyapp to realize convenient output of the individualized risk probability. According to the method, efficient and accurate prediction of the preoperative lymph node metastasis risk is realized, and reliable decision support can be provided for clinic.

The invention discloses an application of an LAMP1 inhibitor in preparation of a medicine for preventing and / or treating esophageal cancer. Specifically, the application value of the LAMP1 inhibitor Parishin C in esophageal cancer treatment is found and verified for the first time, invasion and metastasis of esophageal squamous carcinoma cells and in-vivo lymph node metastasis can be remarkably inhibited by targeting LAMP1 protein and downstream signal channels of the LAMP1 protein and Parishin C, and a new drug choice is provided for metastatic esophageal cancer lacking effective treatment means clinically.

The invention discloses application of LncRNA GSEC in preparation of a medicine for treating oral squamous cell carcinoma, and relates to the technical field of biological medicine. The nucleotide sequence of the LncRNA GSEC is shown as SEQ ID NO: 1, the medicine contains an active component capable of inhibiting expression or functions of the LncRNA GSEC, the active component is one or more of siRNA, shRNA or a small-molecule inhibitor, and the medicine is used for inhibiting proliferation, migration and / or invasion of OSCC cells and / or inducing cell apoptosis. The specific high expression of the LncRNA GSEC in oral squamous cell carcinoma tissues and cells is disclosed for the first time, and the expression level of the LncRNA GSEC is remarkably and positively correlated with adverse clinical parameters such as tumor T staging and lymph node metastasis, so that the LncRNA GSEC is proved to serve as a novel molecular target with clinical application potential.

The present invention provides a method and application for predicting breast cancer metastasis. The present invention uses body fluid exosomes as samples, utilizes liquid chromatography tandem mass spectrometry, obtains the protein phenotype of patients with breast cancer metastasis, establishes a metastasis diagnosis model based on proteomics, and provides a kit or chip for detecting breast cancer lymph node metastasis, and the application of breast cancer lymph node metastasis protein markers in the preparation of kits and / or chips. Compared with traditional diagnostic methods such as axillary lymph node dissection and tissue biopsy, the present invention has the characteristics of non-invasive and convenient detection, and can accurately determine whether the sample to be tested is a breast cancer metastasis sample.

The invention relates to application of a combination of STM2457 and gefitinib in preparation of a medicine for preventing and treating lung cancer, and belongs to the technical field of biological medicines. The invention provides an application of an METTL3 inhibitor and gefitinib in preparation of a medicine for preventing and treating lung cancer. In a cell experiment, the expression of METTL3 is inhibited and then Gefitinib is used, so that the killing effect of the Gefitinib on lung cancer cells is promoted, and the drug resistance of the lung cancer cells on the Gefitinib is reduced. The small molecule inhibitor STM2457 of the METTL3 and the Gefitinib are combined for medication, so that the killing effect on cancer cells can be synergistically improved. In a mouse experiment, compared with a single drug, the drug combination has the advantages that the growth of tumors is more effectively inhibited, the lymph node metastasis of lung cancer cells can be effectively prevented, no obvious side effect exists, and a good treatment effect is shown. Therefore, the drug combination of the METTL3 inhibitor and the Gefitinib has a remarkable treatment effect on the NSCLC.

The invention provides an application of a dendrimer modified perovskite nanocrystal probe in prediction of mammary gland lymph node metastasis. The probe is formed by coupling a biological material of a targeted EPN3 gene and a water-soluble perovskite nanocrystal through electrostatic interaction, the water-soluble perovskite nanocrystal is formed by packaging perovskite quantum dots and a dendritic macromolecular packaging material through the coordination bonding effect of chemical bonds. The EPN3 modified water-soluble perovskite nanocrystalline probe provided by the invention can be used for high-sensitivity rapid detection of tumor tissues or cells with breast cancer lymph node metastasis.

The invention belongs to the field of disease detection reagents, and particularly relates to application of a reagent for detecting a marker in preparation of an ovarian cancer diagnosis product or a prognosis evaluation product, the marker is piRNA as shown in SEQ ID NO: 1, an ovarian cancer diagnosis model established on the basis of the piRNA has an ROC curve lower area of 0.902, sensitivity of 0.844, specificity of 0.767 and accuracy of 0.804, and the marker is piRNA as shown in SEQ ID NO: 2. Ovarian malignant tumor patients, benign tumors and healthy individuals can be effectively distinguished, and the ovarian malignant tumor marker is remarkably superior to existing clinical common tumor markers CA-125, CEA, CA19-9, HE4, ROMA and the like. Meanwhile, the early diagnosis efficiency of the marker for ovarian tumor patients is remarkable (the area under the ROC curve is 0.854), and is superior to that of the existing clinical common tumor marker CA-125 (the area under the ROC curve is 0.815). And the expression level of the marker in ovarian cancer serum is related to the treatment state, lymph node metastasis state, clinical staging and survival prognosis time of an ovarian cancer patient, so that a reagent for detecting the marker can be used for preparing an ovarian cancer diagnosis product or a prognosis evaluation product.

The invention provides a multi-scale cross-regional lymph node metastasis pathological image recognition method, which comprises the following steps of: cutting a region of interest from a full-slice pathological image, dividing standard image blocks under an amplification factor, and extracting a feature sequence by utilizing a pre-training model; the multi-scale module performs intra-scale and inter-scale self-attention calculation and fusion on each amplification factor feature to construct unified multi-scale feature representation; the cross-region module recombines the features into a two-dimensional grid and divides regions, and local feature optimization and global semantic association are realized through multi-head self-attention in the regions and among the regions; and outputting the diagnosis result and probability of lymph node metastasis through the classifier, and generating a multi-scale attention heat map to integrate into a visual diagnosis report. According to the method, the accuracy and the interpretability of lymph node metastasis detection can be remarkably improved through collaborative modeling of the multi-scale information and the cross-regional dependency relationship of the pathological image.

The invention belongs to the field of medical contrast agents, and relates to an albumin-based near-infrared two-region fluorescence / magnetic resonance bimodal probe as well as a preparation method and application thereof. The bimodal probe disclosed by the invention is a protein compound formed by self-assembling a near-infrared two-region fluorescent dye (IR820), a nuclear magnetic contrast agent (GdL) and albumin. The near-infrared two-region fluorescent dye (IR820) and the nuclear magnetic contrast agent (GdL) respectively show the characteristics of near-infrared two-region fluorescence enhancement and relaxation rate increase in a serum albumin solution. The near-infrared two-region fluorescent dye and the nuclear magnetic contrast agent have the advantages of simple preparation process, high relaxation rate, good stability, good biocompatibility and the like. The near-infrared two-region fluorescence / magnetic resonance bimodal probe disclosed by the invention can be used for diagnosis, real-time monitoring and surgical navigation of tumor lymph node metastasis.

The invention discloses a histopathologic recognition method and device for prostate cancer lymph node metastasis, and the method comprises the steps: carrying out the pathology recognition according to a pathology image of a prostate lymph node, and obtaining a first confidence coefficient corresponding to an original pathology recognition result; performing mask processing on the pathological image to obtain an original pathological mask image; correcting the first confidence coefficient according to a plurality of pathological example images in a preset pathological image library to obtain a target confidence coefficient; and when the original pathological mask image comprises the target tissue mask part, performing pixel correction on the target tissue mask part according to the target confidence, and outputting a target pathological mask image. The first confidence coefficient is corrected through the plurality of pathological example images in the preset pathological image library, so that confidence coefficient errors caused by insufficient generalization performance of pathological recognition can be reduced, and the accuracy of the output target pathological mask image can be improved.

The invention discloses a tongue squamous cell carcinoma in-situ PDX model construction method based on SERINC3 high expression and application of SERINC3, and belongs to the technical field of tumor biology and animal model construction. The method comprises the following steps: segmenting small tissues from cancer tissues of a patient suffering from tongue squamous cell carcinoma, implanting the small tissues into the armpit of an NCG mouse to culture tumor tissues, and then subculturing the tumor tissues; the subcultured tumor tissue is taken and implanted into the lingual margin of an NCG mouse, and after the tumor is cultured, lentivirus carrying sh-NC / sh1-SERINC3 / sh2-SERINC3 plasmids is injected into the tumor at multiple points to obtain the tongue squamous cell carcinoma in-situ PDX model. The model constructed by the invention can better simulate the natural occurrence and development process of TSCC, reconstructs a tumor microenvironment closer to clinical practice, and particularly has remarkable advantages in the aspect of simulating head and neck lymph node metastasis of tongue squamous cell carcinoma.

The invention discloses a protein marker combination for predicting papillary thyroid carcinoma lateral cervical lymph node metastasis and a screening method and application thereof, and belongs to the technical field of biological medicine. The marker combination comprises 31 proteins, namely VWA8, PDHX, DENR, ATP5MG, SFTPB, MAOA, PHB1, CHI3L1, ACAA2, PTPN9, AFM, ACADVL, HSPE1, PPP2R2A, REEP5, FABP5, NME3, AUH, TMEM214, NDUFAF2, PHB2, FUCA2, PAXX, APOO, TMEM109, CHID1, MAGT1, ARL8B, BCAP29, AFG3L2 and MTCH2, in total. According to the method, multiple independent proteomics queues are integrated, direction consistency and performance screening are combined, a high-stability candidate marker library is constructed, a prediction model is constructed based on machine learning, and excellent prediction performance is shown in multiple verification sets. The method can be used for evaluating the preoperative lateral cervical lymph node metastasis risk of papillary thyroid carcinoma, and has an important clinical transformation value.

The invention provides a biomarker for diagnosing lymphatic metastasis of cervical cancer and application of the biomarker, and belongs to the field of medical diagnosis. According to the invention, three biomarkers of resting sulfydryl oxidase 1, paraoxonase 1 and keratin 6A for diagnosing lymphatic metastasis of cervical cancer are obtained through multivariate statistical analysis, difference screening, random forest, ROC analysis and other biosignal analysis methods. Based on the biomarker provided by the invention, a kit and the like for diagnosing lymphatic metastasis of cervical cancer are constructed, and the kit and the like are used for accurately judging whether lymphatic metastasis occurs in cervical cancer patients or not.

This invention relates to an animal model of mediastinal lymph node metastasis in lung cancer and its construction method. The core of this invention lies in the precise intrapulmonary in situ microinjection technique to directly implant human lung cancer cells into the lung parenchyma of immunodeficient mice. Utilizing the natural lymphatic drainage pathway of the lung tissue, tumor cells are induced to migrate to the mediastinal lymph nodes, thus successfully constructing a complete metastasis chain model from the primary tumor to regional lymph nodes. This model can more realistically simulate the microenvironment and process of lung cancer lymph node metastasis, and is suitable for metastasis mechanism research, drug evaluation, and the development of personalized treatment strategies, possessing high translational medicine value.

The invention relates to application of a medicine for inhibiting ZIP1 gene expression in inhibiting pancreatic cancer lymph node metastasis. Pancreatic cancer cells can secrete S100A4, act on lymphatic endothelial cells (LEC) and up-regulate expression of ZIP1 molecules, glycolysis on the LEC is further up-regulated, lactic acid is generated, the lactic acid destroys expression of tight junction protein Claudin5 between the LEC, pancreatic cancer cells are promoted to enter lymphatic vessels and generate lymphatic metastasis, ZIP1 is used as a target spot, siRNA is constructed, or CRISPR / Cas9 technology is used, and the pancreatic cancer cells can be used for treating lymphatic metastasis. The expression of the lymphatic vessel ZIP1 gene is reduced, and the lymphatic metastasis of pancreatic cancer is blocked.

The invention discloses a thyroid cancer lymph node minimal metastatic focus detection model and a system thereof, the detection model takes a dual-scale Transform fusion model based on a meta-learning algorithm as a network architecture, cross-task generalization is realized, and the classification performance under the condition of few samples is remarkably improved; in addition, the detection model utilizes a Transform-based concentric dual-scale image block extraction and fusion mechanism to extract two Patches of 10 * high magnification (cellular morphology) and 4 * low magnification (tissue structure) from the same space coordinate, the features of the two scales are integrated through a Patch-Embedding high-dimensional feature fusion module, and finally the classification task of the thyroid cancer lymph node metastasis is completed. And obtaining a classification result and outputting an interpretable attention map. The accuracy and robustness of thyroid cancer lymph node micro-metastasis detection are improved, and more reliable decision support is provided for pathologists.

The invention provides an intraoperative fluorescence multi-mode image processing method for evaluating colorectal cancer lymph node metastasis state, which can be applied to the technical field of medical imaging. The method comprises the following steps: acquiring a multi-modal image of an intraoperative lymph node through imaging equipment, and performing data enhancement on the multi-modal image through an image denoising algorithm to obtain an enhanced multi-modal image; performing local feature extraction and global feature extraction on each mode in the enhanced multi-mode image, and splicing the local feature and the global feature of each mode to obtain a spliced feature of each mode; carrying out weighted fusion on splicing features of all modals in the enhanced multi-modal image, and carrying out feature sharing and same-dimension vector operation on a weighted fusion result to obtain multi-modal fusion features; and preprocessing the multi-modal fusion features, and carrying out feature mapping and classification processing on the preprocessed multi-modal fusion features to obtain metastatic state information of the lymph nodes in the operation.

The invention provides a renal cell carcinoma prognosis lifetime prediction method based on internal and external verification of a data set, and relates to the field of clinical medical diagnostics. The clinical factors related to the prognosis lifetime of the renal cell carcinoma, such as complications, tumor size, lymph node metastasis, tumor remote metastasis, tumor grading, tissue types, immunotherapy and targeted therapy, can efficiently predict the prognosis survival probability of a renal cell carcinoma patient, and can improve the identification accuracy of a prediction model; therefore, reference is provided for treatment of renal cell carcinoma patients.

The invention discloses a biliary duct cancer lymph node calcification point detection method based on multiple modes and difference enhancement. According to the characteristics of bile duct cancer lymph node metastasis calcification points under ultrasonic images, an image text fusion module in a YOLO-World network is improved, a difference enhancement algorithm is added in the module, and the accuracy of calcification point detection is improved on the premise that the detection speed is not affected. The method is used for detecting the calcification point target of the bile duct cancer lymph node metastasis ultrasound image, and has the advantages of earlier detection, higher detection accuracy, more accurate positioning and the like.

The invention provides a gynecological tumor lymph node metastasis detection method based on edge feature extraction and fusion, and belongs to the technical field of medical image detection technologies. And preprocessing the pelvic cavity enhanced CT image, and inputting the processed image into a pre-trained gynecological tumor pelvic lymph node metastasis accurate detection model. According to the accurate detection model for the pelvic lymph node metastasis of the gynecological tumor, multi-scale features and edge features of lymph nodes are extracted by using a multi-scale feature and edge information extraction convolution technology by virtue of a newly designed backbone network, and multi-scale feature fusion is carried out through a feature channel selection aggregation module. The features of the neck network fusion are transmitted to a detection head for analysis, the detection head deeply analyzes the features, and finally the detection result of the gynecological tumor lymph node metastasis is obtained. According to the pelvic lymph node detection method, the edge details and the spatial position of the pelvic lymph node can be accurately captured, and the detection precision is greatly improved through accurate analysis of the lymph node form and the edge features when an enhanced CT image of a patient is processed.

The invention discloses a marker, a kit and a method for thyroid papillary carcinoma lymphatic metastasis assessment, and belongs to the technical field of carbohydrate chemistry. The marker comprises a miRNA (micro Ribonucleic Acid) biomarker and an IgG (Immunoglobulin G) N-glycan, wherein the miRNA biomarkers are miR-616-3p and miR-1285-5p, and the miRNA biomarkers are miR-616-3p and miR-1285- And the IgG N-glycans are GP4, GP10, GP13 and GP24. A biomarker model is constructed by jointly detecting six key indexes of miR-616-3p, miR-1285-5p, GP4, GP10, GP13 and GP24, the problem of multicollinearity is effectively solved, the AUC value reaches 0.930, the general efficiency level of a clinical conventional diagnosis method is remarkably exceeded, and a high-precision judgment tool is provided for PTC LNM clinical decision. The numerical value shows extremely high discrimination capability; and the constructed model is based on internal correlation analysis of miRNA and initial glycan which are remarkably related to PTC LNM, and has good specificity and reliability.

The invention relates to the field of tumor molecular diagnosis, in particular to a breast cancer lymph node metastasis prediction method and application thereof. Specifically, the invention provides a construction method of a breast cancer lymph node metastasis prediction model by taking the signal intensity of an LTR repetitive sequence region as one of extracted cfDNA features, and provides an application of the model in prediction of the breast cancer lymph node metastasis condition, so that non-invasive detection of breast cancer lymph node metastasis is realized, and the prediction accuracy of breast cancer lymph node metastasis is improved. The method is especially suitable for patient groups needing dynamic monitoring or difficult to obtain tumor tissues.

The invention relates to the field of medical diagnosis, in particular to a method and a model which are constructed based on transcriptome sequencing and are used for diagnosing lymph node metastasis of early-stage cervical cancer. The invention provides a method for constructing a cervical cancer lymph node metastasis diagnosis model, which comprises the following steps of: screening to obtain seven preferable cervical cancer lymph node metastasis biomarkers on the basis of gene expression differences of cervical tissue samples of cervical cancer lymph node metastasis patients and cervical cancer lymph node non-metastasis patients, and establishing a diagnosis model and a diagnosis line diagram. Corresponding scores are obtained according to the numerical value of the optimized cervical cancer lymph node metastasis biomarker, then the scores are added to obtain a total score, and the risk probability of cervical cancer lymph node metastasis is calculated according to the total score. According to the invention, a diagnosis and detection model is constructed for a plurality of genes, molecular detection is carried out on a plurality of genes of cervical cancer tissues, and valuable diagnosis is carried out on whether cervical cancer lymph node metastasis happens to cervical cancer patients whose lymph nodes are not swollen or not through image examination.