62 results about "Lung tumor" patented technology

The invention relates to the technical field of medical image processing, in particular to a lung tumor CT image 3D segmentation method and system based on multi-modal image fusion. The method comprises the following steps: acquiring a lung tumor CT image; determining a first texture feature based on the lung tumor CT image; identifying a lung tumor boundary by using the first texture feature; detecting a nodule protrusion area in the boundary of the lung tumor; obtaining tissue infiltration data from the nodule protrusion area; determining a second texture feature according to the tissue infiltration data; determining a tumor heterogeneity feature according to the first texture feature and the second texture feature; evaluating the potential malignancy degree by utilizing tumor heterogeneity characteristics; and dividing a tumor risk area of the lung tumor CT image based on the potential malignancy degree. According to the invention, accurate heterogeneity identification and risk region division of the lung tumor CT image are realized based on a medical image processing technology, and the accuracy of lung tumor 3D segmentation is improved.

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 lung CT tumor image synthesis method based on an artificial intelligence model, and the method comprises the following steps: A1, position selection: applying a pre-trained UNet to CT scanning, segmenting a rough position and a blood vessel region of a lung, and selecting a proper position for a tumor in a region, which is not intersected with a blood vessel, of the lung; a2, texture generation: generating the texture of the tumor from the random Gaussian noise through a neural network; a3 shape generation: a tumor-like shape is generated by using an ellipsoid, and the diversity is enriched by elastic deformation, so that the shape is more similar to a naturally growing tumor in appearance; and A4, performing post-synthesis treatment, and placing the generated tumor shape and texture on the selected points. According to the method, the lung tumor focus is synthesized by using the artificial intelligence network, so that the cost of manual labeling is reduced, and the problems of complex texture, fuzzy edge and noise and artifacts are solved.

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 present invention discloses a spontaneous early lung cancer mouse model, a construction method and an application thereof, and belongs to the technical field of animal model construction. The present invention hybridizes mice that conditionally overexpress GNGT1 with Scgb1a1‑Cre tool mice that specifically target the lungs, and the F1 generation contains the spontaneous early lung cancer mouse model. The early lung cancer mouse model of the present invention that specifically overexpresses GNGT1 in the lungs can successfully construct an early lung cancer model in a relatively short period of time, which can greatly accelerate the research progress of scientific researchers, save time and costs, and expand the range of available models for lung tumor research. The spontaneous early lung cancer mouse model provided by the present invention has high repeatability and good controllability, and is an important bridge to promote the progress of lung cancer research and ultimately its clinical transformation.

The invention discloses a double-end endoscope robot for lung tumor nodule minimally invasive surgery, and relates to the technical field of medical instruments. The system comprises a header pipe, a first endoscope robot and a second endoscope robot are arranged in the header pipe, the first endoscope robot is composed of a first semicircular flexible inner pipe, a first mechanical arm and a first surgical head connector, and the second endoscope robot is composed of a second semicircular flexible inner pipe, a second mechanical arm and a second surgical head connector. And the overall outer diameter of the second endoscope robot is the same as the inner diameter of the first semicircular flexible inner tube. According to the double-headed robot, the two semicircular flexible inner tubes are arranged, the semicircular flexible inner tubes on the double-headed robot can be converted into whole round tubes after separation, the whole round tubes are kept stable in respective bronchus, double headed operation can be conducted at the same time, physical conflicts cannot be generated, the needed space is small, the double-headed robot is suitable for lung minimally invasive surgery, and the surgery time can be greatly shortened.

Two major treatment strategies employed in fighting non-small cell lung cancer (NSCLC) are tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). The choice of strategy is based on heterogeneous biomarkers expressed by the lung tumor tissue. A major challenge for molecular testing of these biomarkers is the insufficiency of biopsy specimens from patients with advanced NSCLC. Disclosed herein is a method for predicting a response to immune-checkpoint blockade immunotherapy. The method generally involves imaging the subject with positron emission tomography with 2-deoxy-2-[fluorine-18] fluoro-D-glucose integrated with computed tomography to produce 18F-FDG PET / CT images of the tumor, analyzing the images using PET, CT, and Kulbek Leibler Divergence statistical (KLD) features or, alternatively using deep leaning such as Neural Networks; generating a radiomic signature from the identified features or Network characteristics; and computing a radiomic score based on the radiomic signature that is predictive of responsiveness to ICIs or TKIs.

Lung cancer remains the leading cause of cancer-related deaths in the world. Despite the fact that introduction of immune checkpoint inhibitors (ICIs) led to a major advancement in lung cancer treatment, disease prognosis continues to remain low and a significant proportion of patients do not respond to such therapies. Cancer vaccines could potentially provide a complementary approach to boost antitumor immunity and act synergistically with ICIs. Novel tumor antigens shared by a large proportion of lung tumor cells are described herein. Several of the tumor antigens described herein derive from aberrantly expressed unmutated genomic sequences, such as intronic and intergenic sequences, which are not expressed in normal tissues. Nucleic acids, compositions, cells and vaccines derived from these tumor antigens are described. The use of the tumor antigens, nucleic acids, compositions, cells and vaccines for the treatment of lung cancer is also described.

The invention discloses application of NCCRP1 as a lung adenocarcinoma immunotherapy biomarker, and belongs to the field of biological medicine. Bioinformatics analysis finds that the NCCRP1 is remarkably and highly expressed in lung adenocarcinoma tissues, and the expression level of the NCCRP1 is in negative correlation with prognosis of a patient. Secondly, the expression level of lung adenocarcinoma cells NCCRP1 is in negative correlation with infiltration of anti-tumor immune cells such as CD8 + T cells. Experiments show that the knockout of the NCCRP1 can significantly inhibit the growth of mouse lung tumors by increasing the infiltration quantity of CD8 + T cells and NK cells in a lung adenocarcinoma microenvironment. The invention provides a new target spot for immunotherapy of lung adenocarcinoma, including NCCRP1 gene editing (knockout / knockdown) and application of an inhibitor in preparation of antitumor drugs.

A method to treat a human patient including: advancing a catheter through a natural airway of the patient and positioning a distal portion of the catheter in the natural airway of a lung of the patient to a target region in the lung, injecting a conductive hypertonic saline solution having a concentration of at least 5% of sodium chloride by weight / volume from the distal portion of the catheter into the target region; delivering energy from the distal portion into the conductive hypertonic saline solution in the target region, wherein the energy heats the liquid in the portion of the airway, and ablating the target region with the heated liquid.

This invention belongs to the field of tumor immunotherapy and provides the application of Hdac3 gene knockout formulations or Ikkα gene knockout formulations in the preparation of drugs that inhibit tumor metastasis. The research results of this invention show that Hdac3 and Ikkα gene mutations significantly inhibit lung tumor metastasis and prolong the survival of mice, and this metastasis inhibition is independent of T, B, and NK cells. Simultaneously, this invention also discovers that Hdac3 and Ikkα mutations inhibit lung tumor metastasis by affecting the sensitivity of tumor cells to tumor necrosis factor, making tumor cells more susceptible to apoptosis, thereby providing a method for sustained in vivo killing of tumor cells. This invention also provides a mutant vector, which exhibits good anti-tumor metastasis effects.

The present invention relates to a treatment of cancer. Here, the inventors discovered that flavin-containing monooxygenase 4 (FM04) expression was increased in lung tumor samples compared with lung healthy tissue. They found that this phenotype was a common feature in lung adenocarcinoma promoted also by translocation of EML4 / ALK as well as by oncogenic KRAS or EGFR using dedicated mouse models. Moreover, FMO4 was strongly increased in human lung tumors compared with healthy lung tissue, and FMO4 expression was inversely correlated with overall survival in patients with lung adenocarcinoma. Importantly, FMO4 protected lung cancer cells against reactive oxidative species-induced apoptosis. Finally, FMO4 loss of function decreased oncogenic KRAS-induced human bronchoalveolar cells transformation in vitro and in vivo. Thus, the present invention relates to an FMO inhibitor for use in the treatment of cancer in a subject in need thereof.

The invention provides an A type 12, 13-epoxy trichothecene compound or a pharmaceutically acceptable salt thereof, and a compound with a chemical formula (I), and the compound has growth inhibition activity on A549, NCI-H1650, NCI-H1944 lung cancer cells and BEAS-2B normal lung cells, and can provide a lead compound for developing lung tumor treatment drugs.

The present disclosure relates to the determination of lung cancer using miRNA ratios. The present invention provides methods of determining the presence of a lung tumor in a subject. Also provided are methods of determining the presence of an invasive lung tumor in a subject. In addition, methods of determining the risk of developing a lung tumor in a subject are provided. Also provided are methods of determining the risk of developing an invasive lung tumor in a subject. Also provided are methods of predicting the risk of developing or having a lung tumor in a subject. Also provided are methods of establishing lung cancer treatment options.

The invention provides a real-time 4D-CBCT imaging method based on a Unet-Transform model, and the method comprises the steps: constructing a comprehensive cascade deep learning network model integrating a Unet network and a Transform network, training the network model, inputting a plurality of CBCT projections containing different respiratory movement amplitudes, which are collected at the same rack angle at the online treatment moment of a patient, into the trained network model, the model outputs three PCA feature tags of a DVF between a predicted phase of breathing motion of a patient at the current moment and a reference phase corresponding to CBCT projection in real time, the PCA feature tags are converted into the DVF through principal component analysis, a reference phase image of an earlier-stage 4D-CT of the patient is deformed under the guidance of the DVF, a corresponding 4D-CBCT image of the breathing phase at the current moment is obtained, and the CBCT image of the breathing motion of the patient at the current moment is obtained. And finally, a 4D-CBCT image sequence capable of covering a complete respiratory cycle is obtained. According to the method, dynamic volume imaging is carried out on the patient during SBRT fractional treatment beam exiting by utilizing a Unt-Transform network model framework, a tool for accurately monitoring movement of tumors in the lung during beam exiting treatment of the patient is provided for clinicians, and technical guarantee is provided for accurate and safe implementation of the lung cancer SBRT.

This invention relates to the field of pharmaceutical technology, specifically proposing the application of ligustilide in the preparation of drugs for inhibiting and / or preventing and / or alleviating and / or treating lung tumors to address the current lack of natural drugs for lung cancer prevention. Lung tumors are nitrosamine-induced carcinogenesis of lung tissue. The invention relates to a pharmaceutical preparation for inhibiting and / or preventing and / or alleviating and / or treating lung tumors, comprising an active ingredient and pharmaceutically acceptable excipients; wherein the active ingredient is ligustilide. Ligustilide directly targets the STING protein, activates the cGAS-STING pathway, promotes STING phosphorylation and cell-mediated immune surveillance, while simultaneously regulating ROS homeostasis and the inflammatory microenvironment, reducing nitrosamine damage to lung epithelial cells, and preventing nitrosamine-induced lung carcinogenesis.

This utility model discloses a voice tremor nursing teaching model in the field of nursing teaching aids. It includes a three-dimensional humanoid model with a left lung model and a right lung model positioned at the chest area. The left lung model is covered with a silicone membrane, forming a pleural cavity model. A catheter is located at the top of the left lung model, with one end extending into the pleural cavity model. Air or liquid is injected into the pleural cavity through the catheter to simulate pneumothorax or pleural effusion. The right lung model includes a detachable and replaceable lung cavity model, lung tumor model, and bronchial obstruction model. A bronchial model is located between the left and right lung models, with a microphone connected to the top of the bronchial model. The two forked ends of the bronchial model at the bottom are connected to the left and right lung models, respectively. This device can replace different models to simulate pathological states, allowing students to intuitively experience the differences in voice tremor under different pathological conditions, improving teaching effectiveness and students' clinical skills training level.

The invention belongs to the technical field of traditional Chinese medicine, and particularly relates to medicinal ink for accelerating lung tumor cell apoptosis and a preparation method and application thereof. Different raw materials are subjected to esterification modification, fermentation or enzymolysis, so that the fat solubility and cell membrane permeability of the composition are promoted, active ingredients can penetrate through a qi and blood barrier more easily to enter lung tissues, the action time is prolonged, the targeting property of the composition is improved, and the conversion of chemical components of traditional Chinese medicines is promoted; a new substance with higher anti-cancer activity is generated or obtained; the bioavailability of each raw material is improved, and a specific enzymolysis product is generated, so that the apoptosis of tumor cells is accelerated. Therefore, different raw materials are specifically prepared, release of active functions of the raw materials is guaranteed from multiple dimensions, and lung tumor cell apoptosis is remarkably accelerated.

The present invention relates to the therapeutic combinations comprising (a) the PARP-1 selective non-trapper inhibitor Compound 1 and (b) an alkylating agent or (c) a topoisomerase inhibitor and the use of said combinations in the treatment of cancer, in particular lung tumors or ovarian and gastric tumors.

The invention discloses an image processing method and device for lung tumor recognition. The method comprises the steps that to-be-recognized lung image information is acquired; preprocessing the to-be-identified lung image information to obtain initial image information; and performing identification processing on the initial image information by using the image identification model to obtain target image identification result information. Therefore, the lung image recognition precision and efficiency can be improved.

The invention relates to the technical field of image segmentation, in particular to a lung tumor CT image automatic segmentation method based on deep learning. The method comprises the following steps: firstly, acquiring three-dimensional CT images of different breathing time phases and a tumor area in the first image; then acquiring a rigid transformation model of lung movement; marking points are determined in a preset range of the tumor area, marking points in each non-first image and deformation vectors of the marking points are determined, stable marking points are screened out, deformation vectors of the unstable marking points are corrected, and then each three-dimensional CT image and correction positions of the marking points in the three-dimensional CT image are input into a trained segmentation model to obtain a segmentation model; and obtaining a lung tumor segmentation result. According to the method, the respiratory movement of the lung tissue is decomposed and analyzed, the movement changes of the mark points in the tumor area in different respiratory time phases are accurately evaluated, then automatic segmentation is carried out based on the segmentation model of deep learning, and the lung tumor CT image segmentation effect based on deep learning is improved.

The present invention relates to the technical field of medicaments for inhibiting lung cancer, and provides an siRNA construct for the targeted silencing of the EFNA2 gene, and an application thereof in the preparation of a drug for inhibiting lung adenocarcinoma cell growth. The present invention comprises four siRNAs for silencing the EFNA2 gene, and the application thereof in the preparation of the drug for inhibiting lung adenocarcinoma cell growth. Specifically, a lipid material is used as a vector for delivering the EFNA2-silencing siRNAs. Among the four siRNA sequences designed for silencing EFNA2, the siRNA-856 sequence exhibits a better silencing effect than siRNA-495, siRNA-547, and siRNA-725, resulting in an apoptosis rate of 28.6% in lung tumor cells. A lipid vector composed of peptide lipids CDO and DOPE efficiently delivers the four EFNA2-siRNA sequences, without cytotoxicity.

The invention relates to the technical field of cryoablation, in particular to a cryoablation device for lung tumors. The device comprises an air supply assembly and a tympanic membrane. Through the design mode of the combined type puncture needle, the cavity formed in the inner end of the outer ring body is used for treating the inner tube body after puncture work is completed, the needle head attached with focus tissue can be hidden to the inner end of the cavity, and therefore the possibility that the needle head makes contact with healthy tissue and organs in the follow-up extraction work is reduced, and the risk of secondary infection is reduced; meanwhile, the outer side of the needle head in the storage process is scraped through the arranged gas supply assembly and the drum membrane, thrust generated in the storage process of the inner tube body acts on the gas supply assembly, gas generated by the gas supply assembly changes the size of the drum membrane, the drum membrane expands to make contact with the outer side of the needle head being stored, and therefore the needle head can be conveniently stored. The adhered focus tissue is scraped by utilizing the contact position of the two, so that the risk that focus cells are in contact with healthy tissues and organs is further reduced.

The invention relates to the technical field of medical clinic, in particular to a deep learning-based lung tumor ablation intelligent evaluation regulation and control method and a deep learning-based lung tumor ablation intelligent evaluation regulation and control system. The method comprises the following steps that a tumor area in a preoperative CT image and an ablation area in an intraoperative CT image are obtained, and a tumor mask and an ablation mask are generated respectively after the preoperative CT image and the intraoperative CT image are subjected to spatial registration; the coverage ratio of the volume of the ablation mask to the volume of the tumor mask is calculated, and the mass center offset distance of the tumor mask and the ablation mask is calculated; dividing the centroid offset distance by the coverage ratio to obtain an offset index; and identifying each risk structure in the ablation mask boundary expansion region, and measuring the nearest distance from each risk structure to the ablation mask boundary. According to the method, a quantitative mechanism between dynamic geometric behaviors and anatomical risks in the ablation process is constructed, an intelligent model capable of predicting complication risks is formed based on the quantitative mechanism, and the accuracy of microwave ablation is improved.

The application discloses a high-power microwave ablation needle for lung tumor, which comprises a bipolar microwave antenna and a matching liquid delivery pipe sleeved on the antenna. The radiation electrode of the antenna is a metal needle tip with high mechanical strength, and the reflection electrode is protected by a hard ceramic sleeve pipe, which is filled with cooling water to improve the matching performance and power tolerance of the microwave antenna. The matching liquid delivery pipe forms a matching liquid delivery channel between the metal needle shaft and the dielectric tube for delivering matching liquid to the central position of the ablation area to adjust the impedance matching of the radiation electrode. The matching liquid can reduce the temperature of the radiation electrode of the antenna, adjust the matching of the antenna radiation electrode, and thus reduce the risk of carbonization of the ablation area due to high temperature. On the other hand, the matching liquid injected into the central area of the ablation can significantly improve the thermal shrinkage of the surrounding lung tissue, and avoid excessive microwave reflection of the shrunk lung tissue.

A traditional Chinese medicine composition for treatment of lung tumor, a preparation method therefor, and a use thereof are provided. The traditional Chinese medicine composition includes the following raw materials by weight: 5-15 parts of Dendranthema morifolium, 2-12 parts of Lonicera japonica, 5-15 parts of Mentha haplocalyx, 5-15 parts of Wolfiporia cocos, 10-20 parts of Atractylodes lancea, 0.5-3 parts of Cinnamomum cassia, 0.5-3 parts of Syzygium aromaticum, 3-12 parts of Astragalus membranaceus, 5-15 parts of Ganoderma lucidum, 10-20 parts of Ligusticum chuanxiong, 5-12 parts of Aucklandia radix, and 2-10 parts of Glycyrrhiza uralensis.

The invention provides a lung tumor early warning protein chip and application thereof. The protein chip comprises an antigen group, the antigen group comprises an antigen; the antibody corresponding to the antigen is p53, NY-ESO-1, CAGE, GBU4-5, SOX2, HuD, MAGE A4, SARS, ZPR1, FAM131A, GGA3, PRKCZ, HDAC1, GOLPH3, NSG1, CD84, EEA1, CEA, CYFRA211 and the like; the protein chip is used for early warning and evaluation of lung tumors, and the early warning and evaluation comprises the following steps: collecting serum of a to-be-detected crowd, detecting the serum by using the protein chip to obtain detection data, and then judging whether the to-be-detected crowd belongs to a low-risk, medium-risk or high-risk crowd according to a risk early warning model; the protein chip systematically detects tumor-related autoantibody risk factor signals by a high-throughput technology, and is used for risk early warning detection of lung tumors.

This invention relates to an antitumor agent based on respiratory tract symbiotic bacteria, its preparation method, and its application. Addressing the current clinical issue of the unclear role of respiratory flora in lung cancer patients' progression, we provide the first evidence that the respiratory tract symbiotic *Streptococcus osticulata* possesses antitumor activity. When *Streptococcus osticulata* is delivered back into the respiratory tract, it can stimulate an antitumor immune response, and its efficacy can be further enhanced by adenosylcobalamin. Currently, there is a lack of non-invasive, non-invasive inhaled treatments for lung cancer. The antitumor agent of this invention can be combined with novel non-invasive inhaled bacterial-metabolite immunotherapy to achieve a long-term chronic disease management model, representing a safe and transferable treatment approach. In addition to achieving effective lung tumor control when used alone, this therapy can synergistically enhance the efficacy of immunotherapy, inducing complete tumor regression in 50% of tumor-bearing mice.

The application discloses a lung CT image synthesis method with a tumor target area, a device and a storage medium. A first CT image block containing a complete tumor target area is extracted from a first lung CT image containing a tumor target area and a first target area sketching mask. A first neural network model is subjected to self-supervised reconstruction training using the first CT image block to obtain a synthesis model. A standard normal distribution is sampled, and the sampling result is used as the input of the synthesis model. The synthesis model is subjected to multiple rounds of sampling to obtain multiple synthesized second CT image blocks. The obtained second CT image blocks are merged to obtain a third CT image block and a second target area sketching mask. The third CT image block is placed in a lung organ region of a second lung CT image without a tumor target area to obtain a lung CT image with a tumor target area. The application realizes the expansion of positive class samples of a lung CT image dataset without data acquisition cost, and effectively solves the problem of imbalance between positive and negative class samples in the training of a deep learning lung tumor target area automatic sketching model.

This invention provides a Kampo (traditional Japanese herbal medicine) composition for treating lung tumors, a method for producing the same, and a method for using the same. [Solution] This is a Kampo medicine composition for treating lung tumors, characterized by being manufactured using the following raw materials: 5% to 15% by weight of Chrysanthemum, 2% to 12% by weight of Honeysuckle, 5% to 15% by weight of Peppermint, 5% to 15% by weight of Poria, 10% to 20% by weight of Atractylodes Rhizome, 0.5% to 3% by weight of Cinnamon, 0.5% to 3% by weight of Lumpsucker's Tears, 3% to 12% by weight of Astragalus, 5% to 15% by weight of Reishi mushroom, 10% to 20% by weight of Ligusticum chuanxiong, 5% to 12% by weight of Saussurea rhizome, and 2% to 10% of Licorice. Adopting the above technical solution has the advantage of significantly preventing tumor growth.