12 results about "Lung tumours" patented technology

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 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.

A tool to create virtual lesions inside a 3D lung tumor image. The image can be an MRI or CT image of a patient's lung to be treated. This virtual pre procedural ablation allows the operator to identify optimal ablation sites and select the optimal ablation parameters for the given anatomy. Also, the actual procedure will be performed with the lung parenchyma surrounding the tumor preventing ultrasound to penetrate beyond the tumor walls. A diagnostic mode will guide the operator to optimize ablation parameters. This virtual pre ablation, the parenchymal ultrasound barrier and the diagnostic catheter operation should enable the operator to conduct the therapeutic procedure safe, fast and effective.

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 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 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 invention relates to an anti-tumor preparation based on respiratory tract symbiotic bacteria as well as a preparation method and application thereof, and provides evidence for the first time aiming at the problem that the respiratory tract flora of a lung cancer patient is not exact in lung cancer progression clinically at present, and the evidence shows that the respiratory tract symbiotic bacteria oral streptococcus has an anti-tumor effect; when the oral streptococcus is delivered back to the respiratory tract, the anti-tumor immune response can be stimulated, and the curative effect of the oral streptococcus can be further enhanced through cobamamide. At present, a non-invasive and non-invasive inhalation type treatment mode for treating lung cancer is lacked clinically, and the anti-tumor preparation can be combined with a novel non-invasive inhalation type bacterium-metabolite immunotherapy to realize a long-term chronic disease management mode, and is a safe and convertible treatment means. On the basis that effective lung tumor control can be realized through independent use, the therapy can synergistically enhance the curative effect of immunotherapy, and tumors are induced to completely subside on 50% of tumor-bearing mice.

The invention relates to the technical field of medical images, in particular to an intelligent visual navigation method for a lung tumor ablation surgical robot based on image fusion. The method comprises the following steps: collecting a multi-source medical image, executing spatial alignment, and outputting a to-be-processed multi-source medical image; identifying a key anatomical structure of the to-be-processed multi-source medical image; generating a segmentation mask according to the key anatomical structure, and determining a target region by using the segmentation mask; obtaining a body surface area and an operable angle of the lung tumor ablation surgical robot; dividing safety candidate points in the body surface area according to the key anatomical structure; taking the tumor center of the target area as a target spot, and searching an obstacle avoidance path from the target spot to the safety candidate point; and planning a puncture path in the obstacle avoidance path by using the operable angle, and outputting puncture path data. Based on the medical image technology, the robot is assisted to complete accurate positioning and navigation control, so that the puncture precision and the operation safety are improved, and the risk in an operation is reduced.

The present invention relates anti-microbial antibody signatures related to lung tumors, including benign tumors and adenocarcinomas. Disclosed herein are antibody panels comprising antigens from bacteria and / or viruses for use in early and accurate diagnosis of lung cancer and for reducing false positive lung carcinoma diagnoses from CT screening.

The invention relates to a CT (Computed Tomography)-guided percutaneous puncture pulmonary nodule targeted tissue positioning method which comprises the following steps: acquiring perfusion images of pulmonary artery and bronchial artery, processing perfusion volume data of the perfusion images, acquiring pulmonary artery blood flow, bronchial artery blood flow and pulmonary artery perfusion indexes, and generating corresponding perfusion pseudo-color images; taking the blood supply area of the bronchial arterial blood flow as lung tumor tissues, and performing lung tumor area targeted localization according to color features in the perfusion pseudo-color graph of the bronchial arterial blood flow to obtain a target spot; the guide sheath needle based on magnetic navigation is used as a puncture positioning needle, and is positioned and punctured to lung tumor tissues according to a target spot for sampling. The accuracy and safety of pulmonary nodule pathological diagnosis are improved, complications are reduced, and a more reliable basis is provided for treatment of patients.

The invention provides a method for enriching tumor specific cells, and particularly relates to a method for obtaining tumor specific cells aiming at specific tumor species by enriching specific markers. The invention also provides application of the tumor specific cell. The separated immune cells have strong release ability to specific cytokines of lung tumors and cervical tumors, have strong specific killing ability to advanced tumors, or have high expression level of tumor specific recognition markers in a corresponding time window after tumor antigen stimulation. The sorting step reduces the amount of cells required for cell therapy or the in vitro culture time required for cell therapy.