277 results about "Lymph nodes size" patented technology

The present disclosure relates generally to medical imaging, and more specifically to techniques for identifying at least one lymph node of a subject using fluorescence images. An exemplary method comprises obtaining a fluorescence image of a field of view including the at least one lymph node of the subject; obtaining a template image; comparing the template image with the fluorescence image to obtain one or more similarity values; and identifying at least one portion of the fluorescence image that corresponds to a location of the at least one lymph node based on the one or more similarity values.

The invention relates to the technical field of biological pharmacy, in particular to a novel vaccine delivery system. According to the vaccine delivery system, lymph node co-delivery of the antigen and the adjuvant can be achieved, the immunity promoting effect of the adjuvant is effectively enhanced, the specific immune response of the antigen is remarkably improved, and the vaccine delivery system is superior to a clinically common oil type composite adjuvant system. Particularly, the vaccine delivery system shows a remarkable anti-tumor effect in tumor prevention and treatment, and a new thought is provided for development and application of a novel vaccine system.

Techniques for segmentation include determining an edge of voxels in a range associated with a target object. A center voxel is determined. Target size is determined based on the center voxel. In some embodiments, edges near the center are suppressed, markers are determined based on the center, and an initial boundary is determined using a watershed transform. Some embodiments include determining multiple rays originating at the center in 3D, and determining adjacent rays for each. In some embodiments, a 2D field of amplitudes is determined on a first dimension for distance along a ray and a second dimension for successive rays in order. An initial boundary is determined based on a path of minimum cost to connect each ray. In some embodiments, active contouring is performed using a novel term to refine the initial boundary. In some embodiments, boundaries of part-solid target objects are refined using Markov models.

The invention belongs to the technical field of biological detection, and particularly relates to a prediction model for predicting prognosis after neoadjuvant immunotherapy of non-small cell lung cancer (NSCLC) through metastatic lymph nodes (mLN) and a construction method of the prediction model. According to the invention, a plurality of spatial high-throughput sequencing bioinformatics technologies are utilized to analyze a key immune cell subset, an immune microenvironment topological feature structure and a three-level lymphosome related functional cell subset of mLN after new adjuvant immunotherapy; the prediction model for predicting prognosis after neoadjuvant immunotherapy aiming at NSCLC through metastatic lymph nodes and the construction method of the prediction model are more in line with post-treatment immune microenvironment spatial histological characteristic changes, and compared with a previous transcriptome sequencing method without spatial information, the prediction model has the advantages that the prediction model is more efficient and efficient; the change of a space tumor immune microenvironment after immunotherapy is more accurately represented, and the prognosis after NSCLC neoadjuvant immunotherapy can be more accurately predicted through cell targets really influencing the immune curative effect.

A contrast agent for imaging lymph nodes or lymphatic vessels with near-infrared light that can selectively image primary lymph nodes relative to secondary or higher lymph nodes. A dose of the composition suitable for imaging lymph nodes or lymphatic vessels.

Immunogenic compositions that include an adjuvant formed from nanoparticles of saponins combined with cholesterol and phospholipids have particular interactions with body tissue and immune cells. These interactions include increased immune response in the draining lymph node, strong activation of T and B cells in the lymph node, and rapid clearance of the saponin fraction while the cholesterol fraction remains in the system.

The invention discloses a lymph node detection method, system and equipment based on anatomical environment perception and a medium, belongs to the technical field of artificial intelligence medicine, and aims to solve the technical problem of low accuracy of lymph node detection. Comprising the steps of acquiring samples and label data, constructing and training a lymph node detection model, and performing real-time lymph node detection. The lymph node detection model comprises a feature extraction network, a cross-slice attention sub-module guided by a central slice, a three-dimensional channel and space significance enhancement sub-module, a hybrid encoder and Transform decoder sub-module and a detection head sub-module; an auxiliary anatomy environment sensing module is adopted to constrain prototype consistency and difficult negative samples; the auxiliary anatomy environment perception module comprises an ROI-level double-view data enhancement sub-module, a prototype consistency constraint sub-module and a difficult negative sample comparison sub-module. The method can enhance the distinguishing ability of the model to the lymph node and the complex anatomical environment where the model is located, and the lymph node detection accuracy is higher.

The invention provides an immunohistochemical method for antibody joint detection and a kit thereof, and particularly relates to the technical field of medical detection.The method comprises the steps that fresh endometrial lymph node tissue is subjected to frozen section, and a continuous section A and a continuous section B are obtained; 10% neutral buffer formalin is used for fixation; blocking by using a peroxidase blocking agent; respectively and independently dropwise adding a CK19 antibody and an MUC1 antibody on the continuous slice A and the continuous slice B; dropwise adding an HRP direct standard signal enhancer; after the DAB develops color, TBS is terminated, hematoxylin is used for redyeing, dehydration is carried out through absolute ethyl alcohol, and sheet sealing is carried out; the immunohistochemical method kit comprises a CK19 antibody, an MUC1 antibody, an HRP direct standard signal enhancer, a peroxidase blocking agent, a DAB developing solution and a TBS cleaning solution. The kit is used for rapid diagnosis of endometrial lymph node micro metastasis, the whole process only needs 15 minutes, and antigen repair is not needed.

The invention relates to a gynecological pelvic and abdominal lymphatic cleaning prediction model training method and a lymph node model.The training method comprises the steps that preoperative image data and intraoperative instrument operation parameters of historical patients are subjected to modeling processing, and a dynamic mechanics-fluid coupling lymph node model based on bionic materials is constructed; mechanical deformation and fluid flow of a lymphatic system in various clinical scenes are simulated; performing data acquisition processing on the used lymph node model, and quantifying the dynamic influence of the surgical operation on the lymphatic system; the relevance between historical operation and injury risk is deeply learned, and the lymphatic vessel rupture probability is output; real-time feedback control processing is carried out based on the lymphatic vessel rupture probability, a training correction instruction and a risk thermodynamic diagram are generated, and medical workers are guided to optimize surgical skills. Through fusion analysis of the high-fidelity bionic model and multi-modal data, dynamic simulation of the mechanical-fluid coupling effect in the operation and real-time quantification of the operation risk are achieved, and the accuracy and clinical transformation value of operation training are improved.

The invention discloses gun-type lymph node forceps with openings perpendicular to opening and closing of forceps handles, and belongs to the technical field of medical instruments. According to the technical scheme, the forceps comprise forceps bodies, forceps handles, forceps heads and a sliding block, the forceps bodies comprise the lower forceps body and the upper forceps body, the forceps handles comprise the movable forceps handle and the fixed forceps handle which are oppositely arranged, the fixed forceps handle is fixed to the lower forceps body, the rear end of the upper forceps body is hinged to the sliding block, and the sliding block is connected with the movable forceps handle; the forceps head comprises a fixed forceps head and a movable forceps head, the fixed forceps head is fixed on the lower forceps body, and the movable forceps head is hinged with the upper forceps body. The gun type lymph node forceps have the beneficial effects that the gun type lymph node forceps are efficient and accurate in clamping capacity, stable in guiding mechanism, high in opening and closing stability, of a pistol loading type structure, flexible in hinge structure, smooth in opening and closing experience, compact in operation design and safe and reliable in performance; and great convenience and guarantee are provided for surgical operation of small tissues such as lymph nodes and the like.

The invention relates to a model for predicting an early gastric cancer lymph node metastasis risk and a construction method and application thereof. The input variables of the model comprise gender, tumor position, tumor maximum diameter, pathological differentiation degree, pT staging condition, submitted lymph node number and lymphatic vessel invasion condition, and the output value of the model is lymph node metastasis prediction probability. A model for predicting the lymph node metastasis risk of the early gastric cancer is designed, the lymph node metastasis risk of a patient with the early gastric cancer can be accurately evaluated through the model, a model for predicting the number of the lymph node metastasis is further obtained, a corrected pN stage (pNM) is provided based on the predicted number of the lymph node metastasis, and the establishment of the pNM stage can be used for predicting the lymph node metastasis risk of the patient with the early gastric cancer. The method can be applied to diagnosis of early gastric cancer patients who cannot perform sufficient lymph node cleaning due to various reasons, is helpful for clinicians to evaluate and calculate early gastric cancer patients who do not reach the sufficient number of detected lymph nodes, and provides a new way for accurate clinical evaluation.

The invention is suitable for the technical field of CT image processing, and provides a diagnosis and segmentation method for a positive lymph node in a CT image based on multi-task learning, and the method comprises the steps: carrying out the preprocessing of a CT image sequence, enhancing the data, constructing a multi-task deep learning model, extracting features through an encoder, and executing a classification task through a classification module. And segmenting the positive lymph node by using a segmentation module in combination with the classification result. According to the method, the classification accuracy (up to 91.1%) and the segmented DICE coefficient (up to 0.602) are both excellent, the method is superior to a single 2D segmentation model, and compared with a 3D segmentation model, the method keeps similar segmentation performance and is shorter in reasoning time. According to the method, classification and segmentation tasks for the positive lymph nodes in the CT image can be completed at the same time, the workload of doctors is relieved, the diagnosis and treatment efficiency of the doctors is improved, and the blank that positive lymph nodes are judged and sketched at the same time in the head and neck CT image of a nasopharyngeal carcinoma patient is filled.

The invention discloses a cell adhesion protein Nectin-4 targeted bicyclic peptide fluorescent probe and a preparation method thereof, the probe provided by the invention can be used for accurate detection of recurrent tumors and metastatic lymph nodes, and the probe is applied to rapid pathology and fluorescent surgical navigation in an operation. The method has the advantages of high signal-to-background ratio, high specificity and long imaging time window.

The present invention belongs to the technical field of pathological testing equipment, and specifically relates to a lymph node retrieval device for pathological testing, which solves the problem that the process of finding lymph nodes in tumor specimens of pathology department is lack of efficient tools and only by manual touch, which is not only time-consuming but also easy to cause inaccurate final results due to subjective factors. The present invention comprises a base and a support rod, a motor is arranged inside the support rod, a cylindrical outer cylinder is fixed on the top of the support rod, a filter barrel arranged concentrically therewith is sleeved inside the outer cylinder, a circular mounting plate is arranged at the bottom of the filter barrel, a pulsator rib is arranged on the upper part of the mounting plate, the motor can drive the filter barrel to rotate, and a plurality of groups of through holes and intercepting thorns are evenly arranged on the cylinder wall of the filter barrel. The present invention has a relatively high degree of automation, reduces the difficulty of completely finding lymph nodes in the current pathological testing process, and eliminates the possibility of differences in test results due to subjective factors of pathologists.

The present invention belongs to the field of biological detection technology, and specifically relates to a prediction model for predicting the prognosis of non-small cell lung cancer (NSCLC) after neoadjuvant immunotherapy through metastatic lymph nodes (mLN) and a construction method thereof. The present invention uses a variety of spatial high-throughput sequencing bioinformatics technologies to analyze the key immune cell subsets, immune microenvironment topological characteristic structures and tertiary lymphoid body-related functional cell subsets of mLN after neoadjuvant immunotherapy. The proposed prediction model for predicting the prognosis of NSCLC after neoadjuvant immunotherapy through metastatic lymph nodes and its construction method are more in line with the changes in spatial histological characteristics of the immune microenvironment after treatment. Compared with the previous transcriptome sequencing method without spatial information, it more accurately characterizes the changes in the spatial tumor immune microenvironment after immunotherapy, and can more accurately predict the prognosis of NSCLC after neoadjuvant immunotherapy through cell targets that truly affect the efficacy of immunity.

This invention discloses an automatic segmentation and scoring method and system for FDG PET-CT lesions in lymphoma, belonging to the field of medical image analysis technology. It aims to improve the segmentation accuracy of lymphoma lesions and the objectivity of the Deauville score. First, standardized uptake values ​​are calculated for FDG PET images, and lymph node morphological features are extracted from CT images based on multi-scale Hessian enhancement filtering to construct a dual-modality PET-CT image pair. Then, a dual-channel depth network is used to extract anatomical structural features and metabolic distribution features respectively. Cross-modal gating fusion is used to suppress physiological uptake interference, outputting preliminary lesion segmentation results. Next, three-dimensional connected component analysis is performed on the segmentation mask, and metabolic heterogeneity index is extracted by combining kurtosis and Haar wavelet multi-scale energy. A graph attention network is used to identify key lesions. Finally, the ratio of key lesions to standardized liver uptake values ​​is combined with the metabolic heterogeneity index to correct the Deauville score, achieving automation from lesion detection to treatment efficacy evaluation.

The invention discloses a thyroid cancer and lymph node accurate positioning system based on three-dimensional imaging, which relates to the technical field of medical image modeling, and comprises the following steps: acquiring two-dimensional images of a cross section and a coronal plane, preprocessing the acquired two-dimensional images, extracting image features of the preprocessed two-dimensional images, and constructing a three-dimensional model based on the image features. Evaluating and adjusting the constructed three-dimensional model, displaying the adjusted three-dimensional model by using a visual tool and providing an interaction tool, generating an electronic diagnosis report based on a three-dimensional model positioning result, storing the generated electronic diagnosis report to a hospital internal database, and performing encryption measures on the access authority of the hospital internal database. According to the thyroid gland and lymph gland positioning method, feature processing is performed based on the preprocessed image, the three-dimensional model is constructed based on the feature processing result, and the adjusted three-dimensional model is displayed by using the visual tool, so that the accuracy of thyroid gland and lymph gland positioning is improved, and the complexity of an operation and the risk of lymph gland omission are reduced.

The invention relates to the technical field of imaging artificial intelligence, and discloses an esophageal cancer lymph node metastasis state prediction method based on a multi-instance learning model, and the method comprises the steps: collecting a CT image of an esophageal cancer patient; marking all visible lymph nodes in the CT image of the esophageal cancer patient; for each marked lymph node, extracting radiomics features and deep learning features of the lymph node; based on a multi-attention mechanism, constructing a multi-instance learning model MILRad through image omics features, and constructing a multi-instance learning model MILDL through deep learning features; and forming lymph node metastasis state prediction in combination with prediction results of the multi-instance learning model MILRad and the multi-instance learning model MILDL through a weighted average mode. The objective of the invention is to introduce an attention mechanism and construct a multi-instance learning model by using radiomics features and deep learning features, so as to predict the esophageal cancer lymph node metastasis probability and improve prediction accuracy and interpretability.

The present invention relates to an "artificial" lymph vessel that allows lymph restoration in order to reach the lymph nodes, in cases where reconstruction is not possible. The invention comprises a tubular body having at least one inlet end with a first diameter and at least one outlet end with a second diameter, with a one-way valve arranged near the at least one outlet end. The one-way valve comprises a sudden reduction in the first diameter in order to create a third diameter, followed by an area in which the third diameter decreases uniformly until it reaches a discharge area with a fourth diameter.

The application discloses a lightweight head and neck lymph node image segmentation method and system, and relates to the technical field of image processing. The application comprises the following steps: receiving a lymph node image for preprocessing, and dividing the image data into a training set and a test set; constructing a segmentation network structure based on a U-Net network, wherein the segmentation network structure comprises an encoder, a volume partial convolution layer, a convolution block and a decoder; adding a lightweight boundary refinement output module at the output end of the segmentation network structure for further refining the edge; training the segmentation network structure by using the training set, taking the minimization of the overall loss function as the network optimization objective function, and optimizing the segmentation network structure. The application adds the volume partial convolution, the convolution block and the lightweight boundary refinement output module between the encoder and the decoder, which can effectively reduce the calculation amount and the parameter amount while enhancing the accuracy of the segmentation result, and improve the calculation efficiency and the model performance.

The utility model discloses a lymph node fetching bag under an endoscope, relates to the technical field of medical instruments, and aims to solve the technical problems that an existing thumbstall is inconvenient to operate when used for fetching lymph nodes from the interior of a human body, unstable in clamping and prone to causing harm to the human body. The device comprises a main rod internally connected with an auxiliary rod in a sliding mode, the auxiliary rod is internally connected with a grabbing device in a sliding and rotating mode, one end of the auxiliary rod is further provided with a collecting device, the collecting device comprises a folding framework, the folding framework is sleeved with a leakage-proof device, one end of the leakage-proof device is open, and the leakage-proof device is further communicated with a collecting bag. The lymph nodes cut from human tissue are collected through the folding framework, the main rod, the auxiliary rod, the collecting bag and the like, operation is easy and convenient, the lymph nodes are not prone to accumulation, and the human body cannot be hurt in the lymph node taking-out process.

The invention discloses a lymph node screening device for tumor examination, and belongs to the technical field of lymph node screening. The lymph node screening device for tumor examination comprises a box body and a containing assembly used for containing cellulite, a separating assembly used for separating fat from lymph nodes is arranged in the box body, the separating assembly separates the fat from the lymph nodes through water pressure, and the containing assembly is installed in the box body through a rotating disc. The turntable rotates in the box body; by arranging the containing assembly, when fat and lymph nodes need to be separated, cellulite is placed on the supporting net, the fat is removed from the surfaces of the lymph nodes through water pressure by the separating assembly, the fat is washed to the surfaces of the trays, the lymph nodes are left on the surface of the supporting net, and the purpose of rapidly screening the lymph nodes is achieved; therefore, the cellulite can be flatly laid on the surface of the supporting net, the thickness of the cellulite is reduced, fat and lymph nodes can be conveniently separated by the separation assembly, and the separation effect is improved.

The invention provides a lymph node identification system and method integrating multi-scale features, and the method comprises the steps: carrying out the grid processing of a pre-obtained original pathological section image, and obtaining a grid data set; based on a preset local feature extraction algorithm and a preset cell detection model, performing local texture information extraction and cell information extraction on each piece of grid data in the grid data set to obtain a plurality of grid data local features; obtaining a candidate organization set based on the plurality of grid data local features; on the basis of a preset global feature analysis algorithm, capturing overall cell distribution features in the candidate tissue set to obtain a target tissue set; obtaining a lymph node distribution diagram based on the candidate tissue set, the target tissue set and an original pathological section image; and recognizing the lymph node of the original pathological section image based on the lymph node distribution diagram. According to the method, comprehensive analysis combining local and global information is realized, and the lymph node identification accuracy is improved.

Provided herein, among other things, is a method for prevention and / or treatment of an autoimmune disease. In some embodiments, the method may comprise administering to a subject a composition, said composition comprising at least one β cell autoantigen, by intralymphatic injection or injection directly into a lymph node.

The present invention relates to methods and compositions for transplanting non-lymphoid tissues into lymphoid organs. It may be used to cultivate organ tissues including for the purpose of supplementing or reconstituting organ function. Tissues that may be propagated in this manner include but are not limited to lung, kidney, thyroid, intestine, and brain.

Disclosed are an artificial lymph node (aLN) comprising an extracellular matrix (ECM) hydrogel conjugated with an antigen presenting complex (Signal 1), a co-stimulatory ligand (Signal 2), and T cell-stimulating cytokine (Signal 3) and methods of their use for stimulating one or more T cells and treating a disease, disorder, or condition selected from a cancer, an infectious disease, and an autoimmune disease.

The invention provides a targeted mRNA delivery system of muscle tissues and / or muscle cells based on aptamer functionalized LNP (Apt-LNP), the delivery system can significantly improve mRNA transfection of the muscle tissues, and meanwhile, mRNA expression in main organs such as liver and spleen is greatly reduced. The expression intensity of muscle tissue in-situ mRNA is improved through modification of the aptamer, meanwhile, mRNA expression in main organs such as the liver and the spleen is greatly reduced, and side effects caused by off-target of mRNA infectious disease vaccines are expected to be avoided. The method is expected to be applied to the field of infectious disease mRNA vaccines The invention also provides a targeting mRNA delivery system of lymph node tissues and / or immune cells based on the aptamer functionalized LNP (Apt-LNP). Compared with an existing lymph node targeting system, the Apt-LNP modified by the aptamer not only can realize lymph node mRNA targeting, but also can further target immune cells, and is expected to be applied to the field of tumor mRNA vaccines to enhance the curative effect of tumor vaccines.

The special pressure bandage comprises an elastic bandage body, the left portion of the bandage body is a short-sleeve pipe opening with shoulders, the right portion of the bandage body is wound and tightened on the armpit on the right side, pressurizing lining pieces are arranged on the inner sides of the neck and shoulder portions of the bandage body, and the pressurizing lining pieces are arranged on the inner sides of the neck and shoulder portions of the bandage body. The compression liner is movable along an inner side of the bandage body. The technical scheme of the utility model has the beneficial effects that the pressurizing lining piece with a variable position is provided, so that the pressurizing stability and the pressure stability are improved, the probability of displacement and even falling is reduced, and a good treatment effect of a local pressurizing bandaging method is ensured; the dressing change can be carried out only by taking down the whole body, the operation is convenient and simple, and medical materials are saved.

The present disclosure relates to compositions comprising a population of immunomodulatory lipid nanoparticles, as well as methods of using thereof to treat and / or prevent cancer (e.g., via local administration to the lymph nodes) and methods of using thereof to treat and / or prevent cancer metastasis in a subject.

The invention discloses a tumor detection marker and application thereof in medicine preparation, and belongs to the technical field of biomedicine. Clinical sample qRT-PCR (quantitative real-time polymerase chain reaction) shows that ENST00000412203.1 is obviously up-regulated in breast cancer tissues, the area (AUC) under the ROC curve reaches 0.9822, and the diagnosis efficiency is excellent. In addition, the invention further finds that the expression of the polypeptide in lymph node metastasis tissues is obviously improved, and metastasis specificity is displayed. Meanwhile, the expression of ENST00000412203.1 is knocked down through siRNA, it is found that proliferation, migration and invasion of breast cancer cells are remarkably inhibited, and therefore the siRNA can be used for preparing targeted therapy drugs for breast cancer and has important clinical application value.