38 results about "Liver tumor" patented technology

The invention relates to the technical field of minimally invasive ablation, in particular to a liver tumor microwave ablation postoperative contraction deformation prediction method, which comprises the following steps: performing unified standardization processing on different periods of liver MRI images; accurately marking a preoperative liver tumor area, a postoperative ablation area and a postoperative liver tumor ghost area of the liver MRI image to obtain masks of the corresponding areas; designing a distance perception function as an attention parameter of different areas of the liver MRI image; constructing a multi-sequence distance guide complementary network model; selecting a loss function; selecting an elastic registration method to perform pre-operation and post-operation registration; and calculating an ablation safety boundary through the ablation area mask and the adjusted tumor mask. The liver tumor microwave ablation postoperative curative effect evaluation accuracy can be effectively improved, and a foundation is laid for formulating a subsequent treatment plan of a patient.

The invention provides a liver tumor early diagnosis method and system based on artificial intelligence, and relates to the technical field of biomedical engineering, and the method comprises the steps: obtaining original information metadata related to the liver, the original information metadata comprises image data original information metadata and biomarker original information metadata, the image data comprises liver CT (computed tomography) and MRI (magnetic resonance imaging) image data, the biomarkers comprise serum tumor marker levels, and the physiological and environmental factors of the patients comprise age, gender, dietary habits and genetic backgrounds of the patients. According to the method, the problems that a tumor in a small and complex area is easily missed or misdiagnosed in the prior art are solved, the path density is predicted through denoising, segmentation and feature extraction of image data preprocessing in combination with a path simulation model based on a graph theory and a Monte Carlo simulation method, and a potential tumor area can be accurately judged.

The present application provides a therapeutic combination of a quinoline derivative and an antibody, which comprises an immune checkpoint inhibitor and a tyrosine kinase inhibitor, wherein the tyrosine kinase inhibitor is a compound of formula I or a pharmaceutically acceptable salt thereof. The therapeutic combination in the present application shows good activity against lung tumor and liver tumor.

The application belongs to the technical field of biotechnology, and particularly relates to a colorectal cancer high liver metastasis cell line and a preparation method and application thereof. The cell line was preserved in the China Center for Type Culture Collection on January 14, 2026, and the preservation number is CCTCC NO: C202618. The cell line is derived from a mouse colorectal cancer cell line MC38, and is constructed by lentivirus transfection to express luciferase stably, and is obtained by continuously performing at least five rounds of liver metastasis tumor orthotopic iteration screening in C57BL / 6 mice through rectal submucosal injection. The MC38-P06 cell line provided by the application has a significantly enhanced liver metastasis ability, a shorter MC38-P01 model time, a higher liver tumor load, and a shorter mouse survival period, and can be used for screening and evaluating anti-liver metastasis drugs, researching liver microenvironment regulation mechanisms, and identifying liver metastasis related diagnostic markers.

The invention discloses an image segmentation method for accurate recognition of liver tumor boundaries. The method comprises the following steps: acquiring pathological images at different time periods; segmenting through a deep learning network to obtain a target area containing main blood vessels and tumor boundaries; performing differential fitting on the pathological image, and predicting a safety boundary; judging whether the distance between the safety boundary and the tumor boundary is smaller than a first safety distance or not, and if yes, calculating to obtain an undercut margin rate; if the under-cut edge rate is greater than a first threshold value, performing weighted expansion on the security boundary, calculating the under-cut edge rate again, if the under-cut edge rate is greater than the first threshold value, performing weight reduction iteration, and stopping iteration until the first threshold value is met or the number of iterations is reached; calculating a blood vessel distance between the safety boundary after iteration and the main blood vessel, and if the blood vessel distance is smaller than a second safety distance, marking as a blood vessel risk point; and outputting a target area containing the tumor boundary, the vascular risk point and the safety boundary. According to the invention, the residual risk can be reduced, and the dual requirements of complete resection and function retention are considered.

The present invention relates to systems and methods of processing CT scan images comprising a liver of a subject to detect and / or predict hepatocellular carcinoma (HCC) in the subject.

The invention provides a full-autonomous ultrasonic robot real-time liver tumor tracking system, and relates to the technical field of medical images and robots. According to the invention, through deep fusion of a multi-mode force touch sensing closed loop and an image segmentation visual closed loop, full-autonomous ultrasonic tracking of liver tumors is realized. Mechanical sensing ensures that the probe is always in stable contact with a patient in a proper posture and force, and visual segmentation feedback ensures that the probe is continuously aligned with and focuses on a tumor target. Under the synergistic effect of the two paths of feedback, the robot can automatically complete the whole process from probe placement, stable attachment, target recognition to real-time tracking, the uncertainty of manual operation is greatly relieved, and the safe, efficient and intelligent liver tumor real-time ultrasonic monitoring robot system is achieved.

The invention discloses a liver-targeted therapeutic drug based on I-type photodynamic COF as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. The preparation method comprises the following steps: firstly, synthesizing a novel I-type photosensitizer, modifying imine type COF with the photosensitizer to obtain a series of COF-E with I-type photodynamic capability, then loading a chemotherapeutic drug, and modifying a targeting molecule on the surface of a material through a pi-pi accumulation effect. The biocompatibility and cytotoxicity of the obtained liver tumor targeted nano therapeutic drug are evaluated through the cellular level. The liver tumor targeted therapeutic drug has good stability, can be triggered to release by a tumor microenvironment, and can play a synergistic therapeutic role of type I photodynamic therapy and chemotherapy; in addition, the compound has a good treatment effect in a subcutaneous hypoxia solid tumor model, and is expected to be applied to clinical research.

This invention discloses a microalgal exosome nanoparticle targeting liver cancer tissue and its preparation method, belonging to the field of biomedical materials technology. The method includes: (1) preparing microalgal cell exosomes by combining ultracentrifugation, ultrafiltration, and size exclusion method. The microalgal cells are Chlorella cells or Synechocystis cells, and the particle size of the microalgal cell exosomes is 30-150 nm; (2) loading immune checkpoint inhibitors into microalgal cell exosomes by electroporation to obtain drug-loaded microalgal exosomes, and causing membrane fusion between the liver tumor cell membrane and the drug-loaded microalgal exosomes to prepare the microalgal exosome nanoparticles targeting liver cancer tissue. The microalgal exosome nanoparticles prepared by this invention have the advantages of good targeting of liver cancer tissue, good biosafety, and accurate and precise drug efficacy, and have broad application prospects in tumor treatment.

This invention discloses Lactobacillus plantarum ( Lactobacillus plants The application of Lactobacillus plantarum AY01 in the preparation of products inhibiting colorectal cancer liver metastasis is described. The Lactobacillus plantarum AY01 is deposited at the China Center for Type Culture Collection (CCTCC) with accession number CCTCC M 20221517. The advantages of this invention are: Lactobacillus plantarum AY01 has the characteristics of inhibiting CT26.WT cell viability, suppressing CT26.WT cell clone formation, inhibiting CT26.WT cell scratch repair, reducing its migration ability, and thus reducing tumor metastatic potential. Mouse experiments with colorectal cancer liver metastasis show that the bacterial suspension of this strain can significantly reduce the number of tumors at metastatic sites in the liver, inhibit liver tumor colonization and proliferation, reduce inflammatory cell infiltration, reduce the proportion of Ki-67 and PCNA positive cells in the liver, alleviate liver tissue damage caused by colorectal cancer liver metastasis, promote the restoration of normal liver structure, protect the liver, and exert an anti-colorectal cancer liver metastasis effect, providing theoretical support for probiotic adjuvant therapy for colorectal cancer liver metastasis.

The invention belongs to the technical field of medicines, and particularly relates to an experimental method for treating liver cancer by using oleanolic acid. Comprising an in-vitro experiment method and an in-vivo experiment method. The in-vitro experiment method comprises the following steps: S1, cell culture; s2, cell proliferation and migration; s3, detecting cell apoptosis and a cell cycle; s4, performing immunoblotting; s5, carrying out real-time quantitative PCR; the in-vivo experiment method comprises the following steps: step 1, performing chick embryo chorioallantoic model experiment; and 2, carrying out tumor-bearing experiment, treatment and tissue sampling on the mouse. The application of the oleanolic acid in liver cancer treatment is systematically researched for the first time, it is found that the oleanolic acid has the remarkable effects of inhibiting proliferation, inducing apoptosis, resisting angiogenesis and the like on liver tumors through the synergistic effect of multiple mechanisms, the remarkable curative effect on cancer mice is achieved, and a new medicine choice is provided for liver cancer treatment.

This application provides the use of plasma-free DNA methylation markers in liver tumor detection. Specifically, the kit includes a reagent for detecting the methylation level of a combination of DNA methylation markers, the combination of DNA methylation markers being selected from one or more of IKZF1, Septin9, IRF4, DAB2IP, TSPYL5, CHFR, BEND4, GRASP, GPAM, and BDH1, to provide a liver tumor detection kit. The model constructed from the detection results of the methylation of the above marker combinations is used for early screening and recurrence monitoring of HCC.

The invention belongs to the technical field of image processing, and particularly discloses a multi-modal medical image segmentation method based on a sparse hypergraph diffusion network, and the method comprises the steps: inputting a registered multi-modal medical image into a hierarchical encoder, and extracting multi-scale features to construct a context feature pyramid; under the condition of the pyramid, a sparse hypergraph diffusion network drives a reverse stochastic differential equation to perform iterative denoising to generate a target segmentation mask, and each stage of a decoder executes prediction, quantization, gating, correction, dynamic identification and fine processing of difficult pixels; and finally, solving an equation by adopting a predictor and a corrector, converting a denoising result into a segmentation probability graph, and carrying out post-processing to obtain a final segmentation label. The multi-modal information fusion effect and segmentation precision are improved, the method is suitable for segmentation of multi-modal medical images of brain tumors, liver tumors and the like, and reliable support is provided for clinical diagnosis.

The invention discloses a method for creating a tumor personalized treatment simulation model based on overlapped microwave ablation in the technical field of biomedical engineering and computer simulation, and the method comprises the steps: constructing a three-dimensional geometric model containing a liver and a tumor based on medical image data of a patient; and establishing an overlapping microwave ablation finite element model coupling electromagnetic wave propagation and biological tissue heat transfer according to the three-dimensional geometric model. According to the method, the overlapping ablation process is dispersed into a plurality of continuous'ablation-cooling-re-ablation 'stages, the thermal field of the previous stage is inherited as the initial condition of the next stage, and the tissue characteristics changed due to temperature change are dynamically updated, so that accurate simulation of the overlapping thermal field cumulative effect is realized, and the accuracy of the thermal field cumulative effect is improved. Therefore, the prediction precision of the form of the final solidification area of overlapping ablation of the liver tumor is improved, and a doctor can clearly know the possible effect of ablation treatment according to the predicted visual solidification area and the quantitative evaluation index.

The invention provides application of detection of enterococcus faecalis in liver cancer tissue in treatment of liver cancer. The invention finds that enterococcus faecalis is highly abundant in liver tumor tissues and is positively correlated with the pathogenesis of HCC (Hepatocellular Carcinoma). Enterococcus faecalis or an enterococcus faecalis conditioned medium promotes liver cancer cell proliferation, protein translation, cell migration and tumorigenesis. Animal experiments prove that colonization of enterococcus faecalis can promote in-vivo growth of liver cancer, and everolimus (an mTOR pathway inhibitor) administration can significantly inhibit the promotion effect. The colonization amount of the enterococcus faecalis can be used as a marker of a liver cancer clinical treatment strategy of colonization of the enterococcus faecalis.

1. The name of the design product: microwave ablation instrument handle (2). 2. The use of the design product: for treating liver tumors and benign thyroid nodules. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

This invention provides a liver-targeting glycoligand molecule modified with dual-antenna GalNAc and its drug delivery system. This liver-targeting glycoligand molecule and its drug delivery system, through ASGPR recognition, can maximize the concentration of therapeutic drugs in liver tumor parenchymal cells, thereby improving the targeting of drug distribution, increasing the therapeutic index, reducing systemic toxicity, and improving patient survival time and quality of life. The liver-targeting glycoligand molecule of this invention is synthesized using an enzymatic synthesis method, which involves fewer synthesis steps, mild enzymatic reaction conditions, high regioselectivity, high reaction efficiency, is environmentally friendly, and has low production costs, making it highly promising for industrialization.

This invention discloses a medical waste liquid recycling container for nurses in the liver tumor department, specifically relating to the field of medical equipment technology. Most existing medical waste liquid recycling containers use a single stirring shaft for mixing, resulting in low mixing efficiency between the waste liquid and the neutralizing agent, thus reducing reaction efficiency. Furthermore, most recycling containers directly discharge the waste gas generated during the reaction, leading to odor diffusion. In addition, the recycling tank in most waste liquid recycling containers has a fixed structure and cannot be rotated or adjusted, making it inconvenient to export the waste liquid after neutralization. The present invention includes a vehicle body with a rotating mechanism. The inner side of the rotating mechanism has a recycling tank, and the inner cavity of the recycling tank has a mixing mechanism that can drive the mixing blades to rotate and can also drive the recycling tank to rotate in the opposite direction. This allows the recycling tank and the mixing blades to rotate coaxially and in opposite directions, thereby accelerating the mixing efficiency of the waste liquid and the neutralizing agent, and thus improving reaction efficiency.

The present application relates to the technical field of image reconstruction, in particular to a liver tumor interventional preoperative blood vessel three-dimensional model reconstruction system, which can realize the following steps through the mutual cooperation between multiple modules: obtaining a liver CTA three-dimensional matrix of a target patient before liver tumor intervention; determining the blood vessel confidence corresponding to each voxel in the tumor peripheral region and the normal liver region; determining the gradient distortion degree corresponding to each voxel in the tumor peripheral region; determining the effective blood vessel proportion in the tumor peripheral region; performing adaptive blood vessel fracture completion screening processing according to the gradient distortion degree and the blood vessel confidence to obtain the tumor peripheral blood vessel region; and performing blood vessel reconstruction based on the effective blood vessel proportion in the tumor peripheral region and the gray value corresponding to the voxel in the tumor peripheral blood vessel region. The present application realizes the identification of the tumor peripheral blood vessel region and improves the accuracy of identification, thereby improving the rationality of liver tumor interventional preoperative blood vessel three-dimensional model reconstruction.

The application discloses an intelligent liver image sign analysis and LI-RADS classification system based on a multi-task model, which inputs two-dimensional liver tumor images of multiple phases into a multi-task convolutional neural network model, automatically extracts potential features required by a classification task based on an LI-RADS standard in a main task, and extracts potential features required by main sign classification defined by the LI-RADS standard in a subtask, so that higher LI-RADS grading accuracy can be realized, and classification basis can be provided for doctors in actual applications such as clinical diagnosis. The application uses a multi-task convolutional neural network, an image-based tumor size automatic analysis method, and an end-to-end and supervised contrast learning combined mode to train a model, so that the liver tumor LI-RADS classification system which can provide judgment basis for doctors is realized.

1. The name of the design product: microwave ablation instrument equipment. 2. The use of the design product: for treating liver tumors and benign thyroid nodules. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses a method for obtaining and separating primary hepatic tumor cells and application thereof, and relates to the technical field of cytobiology, tumor research and antitumor drug development, the method is characterized in that MYC and AKT double genes are adopted in a mouse body to drive and induce liver cancer, and the primary hepatic tumor cells are obtained and separated from obtained liver cancer tissues. And the stable mouse liver tumor cell line (MLAML-1001D) is established and obtained. The liver cancer model constructed by double-gene driving has a complete tumor microenvironment, and highly simulates and restores the physiological microenvironment of liver cancer of clinical patients in the aspects of interaction of tumor cells and stromal cells, interaction of cells and extracellular matrix, interaction of tumor cells and immune cells and the like; therefore, a more accurate and efficient model is provided for researching growth, invasion and metastasis mechanisms of liver cancer and screening and evaluating liver cancer related drugs.

This invention relates to the field of pharmaceutical adjuvant technology, and discloses a composite nanoparticle formulation with enhanced microwave ablation effect on liver tumors, its preparation method, and its application, comprising the following steps: Step S1, reacting silica nanospheres, ammonia, and zirconium propofol (IV) in a mixed solvent composed of anhydrous ethanol and acetonitrile to obtain ZrO2@SiO2 nanospheres; Step S2, using NaOH solution to etch and remove the SiO2 template inside the ZrO2@SiO2 nanospheres to obtain hollow ZrO2 nanospheres; Step S3, loading copper nitrate into the hollow ZrO2 nanospheres to obtain a ZrO2@Cu(NO3)2 intermediate; Step S4, dispersing the intermediate with PVP and H2BDC in DMF, and reacting under sealed and constant temperature to obtain ZrO2@CuO / Cu-MOF composite nanoparticles. The composite nanoparticles obtained by this scheme can be used as microwave ablation enhancers. The mesoporous structure of ZrO2 and the microwave absorption characteristics of Cu-based components work synergistically to effectively enhance the microwave ablation effect on tumors. At the same time, Cu-MOF can load drugs to achieve synergistic treatment of "ablation + chemotherapy".

A cancer tumor treatment effect evaluation method combining a T1 weighted image and an arterial phase image comprises the steps that firstly, two independent U-Net segmentation networks are used for accurately segmenting liver tumor areas in the T1 weighted magnetic resonance image and the arterial phase CT (or MR) image before and after treatment respectively; then, highlighting the segmented tumor areas in each image through an image processing algorithm, and automatically selecting a representative slice with the maximum tumor cross section area; then, calculating the ratio of the average pixel intensity to the area of the tumor area of each slice, and taking the average value as a characteristic value; and finally, based on the feature values of the T1 weighted image and the arterial phase image before and after treatment, constructing a comprehensive curative effect evaluation change rate (R value) quantitative index. According to the invention, through combination of deep learning and image processing, rapid, automatic and quantitative evaluation of the cancer curative effect is realized, and accurate and reliable decision support is provided for clinicians.

The invention relates to the technical field of biological medicines, in particular to application of an IFI27 gene as a liver cancer treatment target. It is found for the first time that IFI27 is remarkably up-regulated in liver cancer tissue, the expression level of IFI27 in paracancerous normal tissue is low, good tumor specificity is shown, and it is indicated that IFI27 plays an important role in liver cancer progression. Furthermore, an in-vitro cell experiment proves that the proliferation activity, the clone forming ability and the migration invasion ability of a liver cancer cell line can be remarkably inhibited by knocking down IFI27 expression through shRNA, and powerful evidence is provided for taking the IFI27 gene as a liver cancer treatment target. It is further verified that the growth of liver tumors can be effectively inhibited by knocking down IFI27 expression in an animal body. In conclusion, the IFI27 can be used as a potential new target for targeted therapy of the liver cancer, and a small-molecule inhibitor or a biological preparation aiming at the IFI27 has research value and clinical transformation potential for being developed into an innovative medicine for the liver cancer. The invention provides a new theoretical basis and an intervention strategy for precise treatment of liver cancer.

Several embodiments disclosed herein relate to the treatment of a tumor using immunotherapy. Several embodiments relate to the treatment of a liver tumor, such as hepatocellular carcinoma or a metastasis from another tumor location. Additional embodiments relate to combination therapies that employ Natural Killer (NK) cells engineered to express cytotoxic receptor complexes and additional anti-cancer agents to treat tumors.

The application belongs to the field of medicine, and particularly relates to a medicine composition for improving the treatment effect of liver tumor and the use thereof. The medicine composition comprises chrysin and hydroxycamptothecine or vincristine, and the weight ratio of the chrysin and the hydroxycamptothecine or vincristine is 1:(1.5-5). The main components of the medicine composition, i.e. the chrysin, the hydroxycamptothecine or the vincristine, are all natural and non-toxic, can be prepared into oral preparations together with common pharmaceutically acceptable carriers, and it is proved through pharmacodynamics experiments that the two components have a synergistic effect, and can greatly improve the treatment effect of liver tumor.

The application provides a preparation method and application of a liver tumor tissue single-cell suspension, and the preparation method comprises the following steps: step 1, pretreating liver tumor tissue; step 2, step-by-step enzymolysis; the pretreated liver tumor tissue in step 1 is subjected to step-by-step enzymolysis by using an enzyme solution, and the enzyme solution in each step is collected after filtration to obtain a cell suspension; step 3, gradient centrifugation; the cell suspension is subjected to gradient centrifugation by using a cell separation solution to separate immune cells and liver parenchymal cells; step 4, red blood cell lysis; the immune cells obtained in step 3 are subjected to red blood cell lysis by using a red blood cell lysis solution, and centrifugal washing is carried out to obtain an immune cell precipitate; step 5, collecting the liver parenchymal cells in step 3 and the immune cell precipitate in step 4, washing the liver parenchymal cells and the immune cell precipitate by using a cell washing solution, centrifuging to obtain a cell precipitate, resuspending the cell precipitate by using a cell resuspension solution, and filtering to obtain the liver tumor tissue single-cell suspension.

The application discloses a bamboo polypeptide-based GPC3-targeted anti-liver tumor nano drug and a preparation process and application thereof. The application constructs a three-layer core-shell nano delivery system with ROS response in the core, pH response in the middle layer and GPC3 targeting in the outer layer. The system takes narrow fractionated bamboo polypeptide and low-substituted hydroxypropyl bamboo beta polysaccharide as a carrier skeleton, and is compounded with bovine gall extract, saffron monomer, plant-derived slow-release nitric oxide donor, hybrid glycoligosaccharide, modified glycyrrhetinic acid and fat-soluble antioxidant components. The in-situ disulfide bond of the bamboo polypeptide realizes ROS response disintegration, the reversible covalent bond of the middle layer polysaccharide realizes pH response dissociation, and the outer layer is grafted with GPC3-specific targeting heptapeptide. All the technical parameters of the application are selected from the optimal interval of the published literature. The system is structurally stable in a physiological environment and can controllably release drugs in a liver tumor microenvironment. The preparation process is standardized and can be industrialized. The product can be used for preparing GPC3-positive liver tumor combined CAR-T immunotherapy drugs, chronic liver fibrosis liver protection drugs and anti-tumor liver protection health food raw materials.

The application belongs to the technical field of image processing, and specifically discloses a multi-modal medical image segmentation method based on a sparse hypergraph diffusion network, which comprises the following steps: inputting a registered multi-modal medical image into a hierarchical encoder to extract multi-scale features and construct a context feature pyramid; taking the pyramid as a condition, driving an inverse stochastic differential equation to iteratively denoise and generate a target segmentation mask through a sparse hypergraph diffusion network, wherein each stage of the decoder performs prediction, quantization, gating, correction, dynamic identification and fine processing of difficult pixels; finally, a predictor and a corrector are used to solve an equation, the denoising result is converted into a segmentation probability map, and the final segmentation label is obtained through post-processing. The application improves the multi-modal information fusion effect and segmentation precision, is suitable for multi-modal medical image segmentation of brain tumors, liver tumors and the like, and provides reliable support for clinical diagnosis.