66 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 invention discloses a preparation method of a nuclear magnetic resonance imaging contrast agent based on surface hepatocyte targeting molecule modification ferroferric oxide nanoparticles, which comprises the following steps: synthesizing ferroferric oxide nanoparticles (Fe3O4 NPs) by a thermal decomposition method, and connecting the Fe3O4 NPs with a ligand dopamine-PEG2000-EOB carrying hepatocyte targeting molecules by a ligand exchange method to obtain the nuclear magnetic resonance imaging contrast agent. The nanoparticles Fe3O4-EOB-PEG capable of carrying out selective T2 nuclear magnetic resonance imaging on the hepatocytes are formed. The method is simple and easy to operate, the controllability of the preparation process is high, the biocompatibility of the obtained product is good, T2 signals of hepatocytes can be remarkably improved, the good early diagnosis effect on liver tumors is achieved, and wide application prospects are achieved.

The invention discloses an enhanced Swinin-Unet liver tumor segmentation method fusing blood vessel guidance and adaptive deformation attention. Through combination of elastic B-spline registration and affine transformation, nonlinear deformation is compensated, a multi-modal image space alignment error is reduced, and tumor boundary blur and feature dislocation are reduced. Topological features are extracted in combination with a blood vessel reconstruction module, and model attention is effectively guided. The encoder adopts a convolution pool and a deformable attention SADR down-sampling, and a lightweight deformable attention module is integrated through jump connection, so that effective multi-scale feature fusion and space alignment are realized, and the model perceptibility is enhanced. The graph theory model is embedded into liver lobe partition and blood vessel curvature constraint, and it is ensured that the segmentation result is strictly matched with blood vessel blood supply topology. In order to solve the class imbalance problem, an FA loss function is provided and combined with a structure correction algorithm (SGDR), so that incomplete segmentation and false positive artifacts are effectively reduced. Experimental verification on a LiTS data set shows that the method is superior to an existing method in liver and tumor segmentation, and Dice coefficients reach 93.38% and 91.39% respectively.

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 invention discloses a contrast-agent-free CT liver tumor recognition method based on a teacher-student network, relates to the technical field of image recognition, and solves the problem that an existing contrast-agent-free liver tumor recognition technology is difficult to adapt to a contrast-agent-free CT image. Therefore, the technical problem of low identification accuracy of the contrast-agent-free CT image is solved. Constructing a teacher network model and a student network model, wherein the teacher network is used for preprocessing original images and text data to obtain visual feature maps and text knowledge features; performing knowledge extraction on the visual feature map to obtain extracted features; performing knowledge fusion on the extracted features and the text knowledge features to obtain fusion features; the fusion features are transmitted to a student network through knowledge distillation; a student network: optimizing feature distribution of the student network according to a plurality of features of the teacher network; acquiring a contrast-agent-free CT image; inputting the contrast-agent-free CT image into a student network to obtain an identification result; and the efficiency and accuracy of tumor recognition are improved.

The invention discloses a curative effect evaluation system for treating liver cancer by combining HDRBT with thermal ablation in multi-modal radiomics, and relates to the field of liver cancer treatment, and the system comprises a multi-modal image data acquisition module which is used for collecting multi-modal image data; the three-dimensional visual model construction module is used for reconstructing a three-dimensional structure of liver tumors, peripheral blood vessels and bile ducts through an image segmentation algorithm, and generating a visual model by fusing radiomics characteristics; the combined treatment plan generation module is used for integrating the dosimetry parameters of the HDRBT and the process parameters of the thermal ablation, optimizing a catheter implanting path, the position of a thermal ablation electrode and a treatment sequence, and generating a combined treatment scheme; and the curative effect evaluation module is used for quantitatively analyzing tumor volume change, ablation boundary integrity and residual tumor activity through accurate registration of multi-modal images before and after treatment. According to the scheme, the problems of incomplete thermal ablation and high recurrence rate of hepatocellular carcinoma can be solved, and full-chain technical support is provided for clinical precise application.

The invention discloses a Vismodegib and BMS-1 co-loaded bionic nano delivery system as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. According to the preparation method disclosed by the invention, Vismodegib and BMS-1 are prepared into a nano-micelle core, and then red blood cell vesicles are utilized to prepare the bionic nano delivery system co-loaded with Vismodegib and BMS-1. Experiments prove that the bionic nano delivery system prepared by the invention inhibits the growth of mouse in-situ tumors and the formation of lung / liver tumor metastasis lesions, and the effect is obviously superior to that of Vismodegib or BMS-1 used alone, Vismodegib and BMS-1 combined use and Vismodegib or BMS-1 loaded nano delivery carriers. The invention provides a new idea for clinical treatment of triple negative breast cancer.

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 a liver tumor interventional therapy path optimization method based on reinforcement learning, and the method comprises the steps: S1, carrying out the imaging of a liver and a tumor region, and generating the positioning data of the liver tumor region; s2, selecting a preliminary drug delivery path according to the defined initial state space; s3, performing path optimization on the preliminary drug delivery path by using an SARSA algorithm, and optimizing the drug delivery path according to the drug concentration and the treatment progress which are fed back in real time; s4, simulating the optimized drug delivery path process through a water drop algorithm, and correcting the drug delivery path in real time according to the treatment target; and S5, according to the treatment feedback information and the dynamic change of the tumor area, completing the path planning of the final treatment scheme, and implementing drug delivery to maximize the treatment effect. According to the invention, the dynamic optimization and accurate adjustment of the drug delivery path in the liver cancer treatment process are realized, the problem of insufficient drug delivery accuracy and effect in the prior art is solved, and the clinical treatment effect is improved through the design of a personalized treatment scheme.

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.

Several embodiments of the methods and compositions disclosed herein relate to immune cells engineered to express cytotoxic chimeric receptors and various dosing regimens for administering such cells. In several embodiments, the immune cell expresses a chimeric receptor that targets a ligand of NKG2D on a tumor cell. In several embodiments, the cancer is a leukemia, e.g., acute myelogenous leukemia (e.g., recurrent / refractory acute myelogenous leukemia) or myelodysplastic syndrome. In several embodiments, the tumor is a solid tumor, such as breast cancer, cervical cancer, colorectal cancer, gastric cancer, head and neck cancer, hepatocellular cancer, lung cancer, melanoma, intrahepatic cholangiocarcinoma, or other liver tumor, such as a secondary metastatic tumor from colorectal cancer. In several embodiments, the immune cells are administered in combination with a therapeutic agent, such as an additional anti-cancer agent.

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.

The use of AST-3424 in the preparation of a drug for treating a patient with hepatocellular carcinoma. A pathological paraffin block or pathological section of ex-vivo liver tumor tissue from the patient with hepatocellular carcinoma is subjected to immunohistochemical staining to detect the protein expression level of an AKR1C3 enzyme, with the detection result showing an H-score greater than or equal to 200; or the pathological paraffin block or pathological section of ex-vivo liver tumor tissue from the patient with hepatocellular carcinoma is subjected to immunohistochemical staining to detect the protein expression level of an AKR1C3 enzyme, with the detection result showing that the sum of percentages of moderate-intensity staining and high-intensity staining is greater than or equal to 70%. The dosing regimen for AST-3424 is as follows: in each 21-day cycle, administration is performed on day 1 and day 8; the initial dose is 6.0 mg / m2 per administration; and the patient will be permitted to receive treatment for a maximum of 34 cycles.

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.

Provided is a method and apparatus of intelligent analysis for liver tumors, including an analysis module for receiving YOLOR-based training to acquire sufficient intelligence to detect and locate liver tumor automatically and attain a mAP score as high as 0.56 required to distinguish lesions of benignant and malignant liver tumors in medical images from each other, attaining a mAP score of 0.628 for tumors at least 5 cm in size or a mAP score of 0.33 for tumors less than 5 cm in size. Thus, the area under the liver tumor differentiation curve of the analysis module and the mAP score reach 0.9 and 0.56 respectively. The values equal those of the effect of the diagnosis rate of liver tumors with CT and MRI in practice. The method is advantageous in terms of higher speed and thus can diagnose liver tumors earlier, preclude delays and radiation, but incur low cost.

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.

This invention discloses a minimally invasive surgical planning method and system based on image navigation, belonging to the field of medical information technology. Specifically, it includes: acquiring a three-dimensional model of the patient through CT scanning; performing structural analysis on the three-dimensional model and dividing the organ region into meshes; calculating the grayscale differences between meshes; identifying lesion meshes; calculating the shortest distance from any in vitro candidate point to the geometric center of the lesion region based on the three-dimensional coordinates of the skin region and the lesion mesh; calculating the optimal score of any in vitro candidate point based on the three-dimensional Euclidean distance; selecting the optimal puncture point; and generating an in vivo and in vitro candidate point set through orthogonal projection and vertical extension. This process is repeated until any puncture point reaches the lesion region. Finally, all puncture points are connected to obtain the final puncture path. This invention automatically obtains the optimal ablation path through iterative optimization, improving the efficiency of liver tumor ablation.

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.