62 results about "Lung tumours" patented technology

The present invention provides molecules that selectively home to various normal organs or tissues, including to lung, pancreas, skin, retina, prostate, ovary, lymph node, adrenal gland, liver or gut; and provides molecules that selectively home to tumor bearing organs or tissues, including to pancreas bearing a pancreatic tumor or to lung bearing a lung tumor. The invention also provides conjugates, comprising an organ or tissue homing molecule linked to a moiety. Such a moiety can be, for example, a therapeutic agent or a detectable agent. In addition, the invention provides methods of using an organ homing molecule of the invention to identify a particular organ or tissue by contacting the organ or tissue with a molecule of the invention. The invention also provides methods to diagnose or treat a pathology of the lung, pancreas, skin, retina, prostate, ovary, lymph node, adrenal gland, liver or gut by administering to a subject having or suspected of having a pathology a molecule that homes to the selected organ or tissue. The invention further provides methods of identifying a target molecule in lung, pancreas, skin, retina, prostate, ovary, lymph node, adrenal gland, liver or gut.

Compositions and methods for the therapy and diagnosis of cancer, particularly lung cancer, are disclosed. Illustrative compositions comprise one or more lung tumor polypeptides, immunogenic portions thereof, polynucleotides that encode such polypeptides, antigen presenting cell that expresses such polypeptides, and T cells that are specific for cells expressing such polypeptides. The disclosed compositions are useful, for example, in the diagnosis, prevention and / or treatment of diseases, particularly lung cancer.

Compositions and methods for the therapy and diagnosis of cancer, particularly lung cancer, are disclosed. Illustrative compositions comprise one or more lung tumor polypeptides, immunogenic portions thereof, polynucleotides that encode such polypeptides, antigen presenting cell that expresses such polypeptides, and T cells that are specific for cells expressing such polypeptides. The disclosed compositions are useful, for example, in the diagnosis, prevention and / or treatment of diseases, particularly lung cancer.

The present invention relates to a method for performing computer-aided detection (CAD) of a disease, e.g. lung tumours, on a medical image data set (20) from a imaging modality, such as MRI or CT. Initially, there is perform a segmentation of the medical image data set (20) using an anatomical model. Secondly, the segmented data is analyzed for characteristics of the disease resulting in a set of analysis data (25), and finally the set of analysis data (25) is evaluating with respect to the disease. At least one of these steps comprises as an input a position dependent probability (P_r) for the disease. The invention is advantageous in that more efficient computations can be performed because the degree of analysis in a certain region of the part of the patient, e.g. the lung, can be adjusted or tailored to the level of probability of the disease in the that region. It is thereby possible to increase computational speed and thereby diseases like cancer, in particular cancer nodules in the lungs, can be more effectively found from medical image analysis.

Provided are methods of treating lung cancer in a patient in need thereof. The method includes administration to the patient a composition comprising a therapeutically effective amount of a compound that reduces the expression level of E3 ubiquitin-protein ligase MDM2. The compound in certain instances is a miR-660 miRNA, or a functional variant thereof. The patient in need of treatment in certain instances expresses miR-660 in a lung tissue sample or biological fluid sample at a level lower as compared to a control level derived from a subject or plurality of subjects that do not have lung cancer, or as compared to a control level derived from a lung cancer patient or plurality thereof, that have been given a favorable prognosis; expresses MDM2 at a higher level in a lung tissue sample or biological fluid sample as compared to a control level derived from a subject or plurality of subjects that do not have lung cancer, or as compared to a control level derived from a lung cancer patient or plurality thereof that have been given a favorable prognosis; and / or expresses p53 in a lung tissue sample or a biological fluid sample below a control level derived from a lung tumor tissue sample, or plurality thereof, or a biological fluid sample, or plurality thereof, obtained from a patient that has a favorable lung cancer prognosis; or a control level derived from a healthy subject.

A lung tumor ablation planning system includes a processor operable to compute a target ablation zone and a set of optimum ablation parameters to create the target lesion with the ablation catheter. Apredictive algorithm is employed to model the ablation zone based on training data. Various ablation plans are displayed to the physician corresponding to various metrics including without limitationmaximizing tumor ablation coverage, shortest travel, obstacle avoidance, and shortest ablation time. Related methods are described.

According to the composite drug-loaded extracellular vesicle inhalation preparation and the preparation method and application thereof, the extracellular vesicle inhalation preparation is used for treating lung tumors in an oral inhalation administration mode, the residence time of treatment drugs in a body can be effectively prolonged, distribution of the drugs in other non-target tissues and organs in the body is reduced. The toxic and side effects of the medicine are reduced while the treatment effect is enhanced, and the medicine shows a good treatment effect of remarkably inhibiting the growth of drug-resistant lung tumors in an animal model.

The present invention relates to a method for performing computer-aided detection (CAD) of a disease, e.g. lung tumours, on a medical image data set (20) from a imaging modality, such as MRI or CT. Initially, there is perform a segmentation of the medical image data set (20) using an anatomical model. Secondly, the segmented data is analyzed for characteristics of the disease resulting in a set of analysis data (25), and finally the set of analysis data (25) is evaluating with respect to the disease. At least one of these steps comprises as an input a position dependent probability (P_r) for the disease. The invention isadvantageous in that more efficient computations can be performed because the degree ofanalysis in a certain region of the part of the patient, e.g. the lung, can be adjusted or tailored to the level of probability of the disease in the that region. It is thereby possible to increase computational speed and thereby diseases like cancer, in particular cancer nodules in the lungs, can be more effectively found from medical image analysis.