89 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 relates to a gadolinium-doped carbon dot complex based on liver cancer cell membrane coating and a preparation method of the gadolinium-doped carbon dot complex. The gadolinium-doped carbon dot complex is prepared on the basis of gadolinium-doped carbon dots Gd-CDs which are prepared from indocyanine green, citric acid, polyethylene glycol and gadolinic acid through a one-step microwave thermal method and have fluorescence-magnetic resonance bimodal imaging capacity. The Gd-CDs complex Gd-CDs coated HCM is placed in a cell membrane suspension extracted from human hepatoma carcinoma cells HepG2, and the Gd-CDs complex Gd-CDs coated HCM which is uniform in particle size and has the capacity of photothermal and immunotherapy of hepatocellular carcinoma is obtained through extrusion construction of a liposome extruder. The Gd-CDs (at) HCM complex constructed by the invention not only has good bimodal imaging ability, but also has a specific inhibition effect on liver tumor cells, can be applied to preparation of drugs for inhibiting the growth of the liver tumor cells, and realizes a good treatment effect on liver cancer at a nanometer level.

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 pharmaceutical 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 pharmaceutical combination in the present application shows good anti-lung tumor and anti-liver tumor activities.

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 provides a DNA methylation marker gene combination for detecting liver tumor related diseases, a reagent and application, and belongs to the technical field of biology. Gene subregions of liver tumor related diseases are further optimized, a subregion combination with a better effect is provided, and when the genome provided by the invention cooperates as a biomarker for plasma separation DNA methylation detection, better sensitivity and specificity are achieved; the accuracy of early screening or re-screening of liver tumor related diseases can be remarkably improved, and the screening efficiency can be 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 present invention provides a generation method for a surgical resection-type sufficient radiation therapy dose plan for a large hepatocellular carcinoma. Assuming the principles of liver segmentectomy or hemihepatectomy principles when surgical liver resection is used to resect a liver tumor, a radiation therapy plan is generated using a liver region volume remaining after the assumed surgical resection as a target. The method specifically comprises: step 1, obtaining an original medical image; step 2, identifying a target region, a maximal dose region, and a remaining liver region from the original medical image, and obtaining a region identification result; step 3, obtaining a remaining liver region volume, and determining whether the remaining liver region volume is within a preset range; if the remaining liver region volume is not within the preset range, ending; otherwise, executing step 4; step 4, performing radiation therapy plan design on the basis of the region identification result and the original medical image, and obtaining a radiation therapy plan result. The maximum value of the preset range is 700 ml, and the minimum value is 300 ml. The present method can automatically implement radiation therapy plan generation.

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 novel liver tumor ablation protection device comprises an ultrasonic probe, a circulating water cooling assembly is arranged at the bottom end of the ultrasonic probe, and one end of the circulating water cooling assembly is connected with external cooling equipment; wherein an air blowing assembly is further arranged on the outer surface wall of the ultrasonic probe, one end of the air blowing assembly is connected with an external air pump mechanism, the circulating water cooling assembly and the air blowing assembly are started, and in the moving detection process of the ultrasonic probe, the circulating water cooling assembly is driven to dynamically cool surrounding organs. The circulating water cooling assembly is connected with external cooling equipment, visceral organs around an operation can be effectively cooled through flowing of cooling water in the circulating water cooling assembly, and due to the fact that the ultrasonic probe can drive the circulating water cooling assembly to move when moving, cooling can be achieved while the visceral organs are detected; the timeliness and comprehensiveness of visceral organ protection are improved, and damage to surrounding visceral organs caused by high temperature generated by the ablation needle is effectively prevented.

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 invention relates to a small interfering nucleic acid for inhibiting FGFR1 (Fibroblast Growth Factor Receptor 1) gene expression and pharmaceutical application thereof. The small interfering nucleic acid comprises a positive-sense strand and an antisense strand, all nucleotides in the positive-sense strand and the antisense strand are modified nucleotides, and the positive-sense strand and the antisense strand are reversely complementary to form a double-strand region. The small interfering nucleic acid can be used for preparing medicines for preventing and treating diseases related to FGFR1 gene expression, and the diseases are selected from bladder cancer, liver tumor, colon cancer, lung cancer, cervical cancer and the like.

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.

The invention discloses a preparation method and application of a rutin-coated manganese carbonate nanoparticle compound. The preparation method comprises the following steps: chelating Mn < 2 + > and polyphenol on rutin, and adding a sodium carbonate solution to obtain the rutin-coated manganese carbonate nanoparticle compound. The rutin-coated manganese carbonate nanoparticles are used as an MRI contrast agent, and are especially suitable for contrast of metastatic liver tumor focuses.

The present invention provides a method and system for evaluating the response after liver tumor intervention based on a generative adversarial network. A method for evaluating the response after liver tumor intervention based on a generative adversarial network includes the following steps: S1. Training a deep learning model to obtain an evaluation model capable of giving a prognosis evaluation result; S2. The evaluation model takes the plain CT scan after liver surgery and the postoperative serological test information as inputs and outputs a prognosis evaluation result. The present invention does not require liver puncture, which can reduce the trauma risk and medical resources for patient prognosis estimation; after the operation, the patient of the present invention does not need to take enhanced CT, and there will be no radiation risk and medical resource consumption caused by taking enhanced CT. At the same time, it can give a prognosis evaluation result based on enhanced CT, ensuring that the CT image used as the evaluation basis can clearly show the lesion, having the effect of enhanced CT, and being able to give a more accurate evaluation result.

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.

The present invention relates to a liver tumor segmentation method based on feature selection and residual fusion. The present invention first optimizes the bottleneck features and jump links of UNet through the attention mechanism, and proposes a bottleneck feature selection module based on the global feature compression operation, namely, a global feature selection module and a neighboring feature selection module. Then, the feature of the spatial attention module is recalibrated using jump links, and finally, the semantic mismatch problem of the front and back spatial features is solved by the spatial feature residual fusion module, so that the features can be expressed efficiently while maintaining low complexity. The present invention makes the result of 2D liver tumor segmentation more accurate, performs component ablation tests on the LiTS public dataset and compares them with the current method, and achieves average Dice scores of 96.2% and 68.4% in the liver and liver tumor segmentation tasks, respectively, which is 0.8% higher than the average Dice score of the current best 2D liver tumor segmentation model.

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.