379 results about "Breast fluid" patented technology

A device for diagnosis and treatment of tumors and lesions within the body. A cannula adapted to apply suction through the lumen of the catheter to the tumor or lesion is described. The lumen has a self sealing valve through which a cryoprobe is inserted while the suction is being applied. The cryoprobe is then inserted into the lesion, and operated to ablate the lesion.

A device and method of use for securing and coring of tumors within the body during a biopsy of the tumor, specifically breast tumors. An adhesion probe for securing the tumor is described. The probe secures the tumor by piercing the tumor and providing a coolant to the distal tip to cool the tip. The cooled tip adheres to the tumor. A coring instrument adapted for cutting a core sample of the tumor is described. The instrument is provided with a cannula that can cut a core sample of the tumor. The instrument is adapted for use with the probe with the probe fitting within the cannula. The instrument can be used in conjunction with the probe to secure and core a sample of the tumor for biopsy.

A device and method of use for securing and coring of tumors within the body during a biopsy of the tumor, specifically breast tumors. An adhesion probe for securing the tumor is described. The probe secures the tumor by piercing the tumor and providing a coolant to the distal tip to cool the tip. The cooled tip adheres to the tumor. A coring instrument adapted for cutting a core sample of the tumor is described. The instrument is provided with a cannula that can cut a core sample of the tumor. The instrument is adapted for use with the probe with the probe fitting within the cannula. The instrument can be used in conjunction with the probe to secure and core a sample of the tumor for biopsy.

A device and method of use for securing and coring of tumors within the body during a biopsy of the tumor, specifically breast tumors. An adhesion probe for securing the tumor is described. The probe secures the tumor by piercing the tumor and providing a coolant to the distal tip to cool the tip. The cooled tip adheres to the tumor. A coring instrument adapted for cutting a core sample of the tumor is described. The instrument is provided with a cannula that can cut a core sample of the tumor. The instrument is adapted for use with the probe with the probe fitting within the cannula. The instrument can be used in conjunction with the probe to secure and core a sample of the tumor for biopsy.

A method and apparatus for automatically detecting breast tumors and lesions in images, including ultrasound, digital and analog mammograms, and MRI images, is provided. An image of a breast is acquired. The image is filtered and contrast of the image is enhanced. Intensity and texture classifiers are applied to each pixel in the image, the classifiers indicative of the probability of the pixel corresponding to a tumor. A seed point is identified within the image, and a region of interest is grown around the seed point. Directional gradients are calculated for each pixel of the image. Boundary points of the region of interest are identified. The boundary points are passed as inputs to a deformable model. The deformable model processes the boundary points to indicate the presence or absence of a tumor.

Biological samples of mammary fluid or components thereof are obtained using a breast pump device coupled with a solid phase sample collection medium, alternatively facilitated by administering oxytocin to the subject. The breast pump device stimulates expression of mammary fluid and provides for collection of diagnostic samples to evaluate breast disease, including cancer. The biological sample may include whole cells or cellular components, purified or bulk proteins, glycoproteins, peptides, nucleotides or other desired constituents comprising a breast disease marker. Methods, kits and adapter devices relating to the breast pump device are also provided. Yet additional methods, devices, accessories, and materials are provided for laboratory handling and processing of breast fluid samples and for related diagnostic methods.

A method and apparatus for automatically detecting breast tumors and lesions in images, including ultrasound, digital and analog mammograms, and MRI images, is provided. An image of a breast is acquired. The image is filtered and contrast of the image is enhanced. Intensity and texture classifiers are applied to each pixel in the image, the classifiers indicative of the probability of the pixel corresponding to a tumor. A seed point is identified within the image, and a region of interest is grown around the seed point. Directional gradients are calculated for each pixel of the image. Boundary points of the region of interest are identified. The boundary points are passed as inputs to a deformable model. The deformable model processes the boundary points to indicate the presence or absence of a tumor.

The invention discloses a clinical data mining analysis and aided decision-making method based on an Internet integrated medical platform, and relates to the technical field of an Internet medical platform. The clinical data mining analysis and aided decision-making method includes data mining analysis and aided decision-making, wherein data mining analysis includes a multidimensional analysis algorithm module, a data mining algorithm module and a deep learning algorithm module; and aided remote decision-making includes four parts: a prediction module based on index parameters, a prediction module based on inspection report texts, a model training module and a structurized module. The clinical data mining analysis and aided decision-making method based on an Internet integrated medical platform selects several diseases as research objects for data collection and analysis, such as hyperthyroidism, diabetes, thyroid nodules and breast tumors, and collects and integrates clinical medicaldata depended the integrated platform to realize data mining analysis and aided decision-making services for clinical data diseases, such as hyperthyroidism, diabetes, thyroid nodules and breast tumors, so as to provide systematic support for clinical diagnosis of clinicians and disease research by researchers.

The present invention provides gene expression information useful for predicting whether a cancer patient is likely to have a beneficial response to treatment with chemotherapy, comprising measuring, in a biological sample comprising a breast tumor sample obtained from the patient, the expression levels of gene subsets to obtain a risk score associated with a likelihood of a beneficial response to chemotherapy, wherein the score comprises at least one of the following variables: (i) Recurrence Score, (ii) ESRI Group Score; (iii) Invasion Group Score; (iv) Proliferation Group Score; and (v) the expression level of the RNA transcript of at least one of MYBL2 and SCUBE2, or the corresponding expression product. The invention further comprises a molecular assay-based algorithm to calculate the likelihood that the patient will have a beneficial response to chemotherapy based on the risk score.

Methods and compositions for evaluating the prognosis of a breast cancer patient, particularly an early-stage breast cancer patient, are provided. The methods of the invention comprise detecting expression of at least one, more particularly at least two, biomarker(s) in a body sample, wherein overexpression of the biomarker or a combination of biomarkers is indicative of breast cancer prognosis. In some embodiments, the body sample is a breast tissue sample, particularly a primary breast tumor sample. The biomarkers of the invention are proteins and / or genes whose overexpression is indicative of either a good or bad cancer prognosis. Biomarkers of interest include proteins and genes involved in cell cycle regulation, DNA replication, transcription, signal transduction, cell proliferation, invasion, proteolysis, or metastasis. In some aspects of the invention, overexpression of a biomarker of interest is detected at the protein level using biomarker-specific antibodies or at the nucleic acid level using nucleic acid hybridization techniques.

A tissue-sensing adaptive radar method of detecting tumours in breast tissue uses microwave backscattering to detect tumours which have different electrical properties than healthy breast tissue. The method includes steps for reducing skin reflections and for constructing a three-dimensional image using synthetic focusing which shows the presence or absence of microwave reflecting tissues.

The invention provides novel uses for n-glycolylated gangliosides and N-acetylated gangliosides, or derivatives and / or oligosaccharides thereof The invention further provides methods of obtaining such gangliosides, as well as vaccine compositions comprising said gangliosides. The gangliosides may be coupled to carriers and may be accompanied by adjuvants. The vaccine compositions can be used in the treatment of breast cancers, whereby the gangliosides are used to elicit an immune response to corresponding gangliosides on breast tumor cells.

The invention discloses a method for automatically identifying a breast tumor area based on an ultrasound image. The method comprises the following steps of acquiring the ultrasound image of the breast, and preprocessing the ultrasound image; segmenting the ultrasound image subjected to preprocessing through an image segmentation method to obtain a plurality of segmented subareas; extracting a grey level histogram, texture features, gradient features and morphological features of the ultrasound image, and combining the grey level histogram, the texture features, the gradient features and the morphological features of the ultrasound image with two-dimensional position information to obtain high-dimensionality feature vectors; selecting the most effective feature subset of the high-dimensionality feature vectors through feature ordering based on biclustering and a selection method; performing learning classification on the selected most effective feature subset through a classifier, and then automatically identifying the breast tumor area. By means of the method, the breast tumor area can be identified automatically from segment results of the breast tumor ultrasound image, therefore, automation performance of computer-aided diagnosis is improved, manual operation of clinical doctors is reduced, and subjective influence of clinical doctors is reduced.

Compositions and methods for the therapy and diagnosis of cancer, particularly breast cancer, are disclosed. Illustrative compositions comprise one or more breast 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 breast cancer.

The invention belongs to the field of image processing, and particularly relates to an automatic extraction method of regions of interest in three-dimensional breast full-volume images (ABVS). The method comprises the following steps: processing the continuous cross section two-dimensional images in three-dimensional ABVS images by using a maximum direction-based phase information method to obtain the candidate regions of interest on each cross section image; removing the unrelated regions according to the prior knowledge such as the continuity and position characteristic of breast tumor on the two-dimensional cross section images; obtaining the shape and texture features of the residual suspected tumor regions, inputting the shape and texture shapes to a two-valued logistic regression classifier to obtain the probability of each region becoming tumor and selecting the region with the maximum probability as the tumor region; obtaining the minimum ellipsoid comprising the region of interest according to the selected region to serve as the region of interest. The automatic extraction method provided by the invention can be used for realizing the automatic extraction of tumor regions of interest in the three-dimensional ABVS images, obtaining the correct positions of tumor, decreasing the workload of the manual operation and providing important reference to further tumor detection.

X-ray mammography has been the standard for breast cancer screening for three decades, but offers poor statistical reliability; it also requires a radiologist for interpretation, employs ionizing radiation, and is expensive. The combination of multiple independent tests, performed effectively at the same time and co-registered, can produce substantially more reliable detection performance than that of the individual tests. The multi-sensor approach offers greatly improved reliability for detection of early breast tumors, with few false positives, and also can be designed to support machine decision, thus enabling screening by general practitioners and clinicians; it avoids ionizing radiation, and can ultimately be relatively inexpensive.

The invention provides a three-dimensional MRI image-based breast tumor automatic segmentation method. The method comprises the following steps of performing image preprocessing: providing an initial MRI image and performing preprocessing on the initial MRI image by adopting a non local mean filter; performing breast tumor locating: building a multilayer processing model for a training set, performing hierarchical abstraction on characteristics of a training object by adopting a convolutional neural network, automatically extracting segmentation characteristics, and outputting a probability distribution graph of a tumor position; performing breast tumor boundary segmentation: providing a breast three-dimensional MRI image, determining a seed point based on the probability distribution graph of the tumor position, and finishing segmentation initialization to obtain an initial region C0 of a tumor; and performing accurate segmentation on the tumor by using a region growth algorithm.

The invention belongs to the image processing technology field and particularly relates to a breast ultrasound image tumor segmentation method based on the full convolution network. The method comprises steps that the full convolutional neural network based on cavity convolution is constructed and is for rough segmentation of an ultrasound image to obtain a breast tumor; in the constructed DFCN network, cavity convolution is utilized, so the network is made to maintain the relatively deep-level feature map resolution to ensure that the tumor is well segmented in the presence of a large numberof shaded areas; in addition, the batch normalization technology is utilized in the DFCN network, the network is made to have the higher learning rate, and the training process is accelerated; a dynamic contour PBAC model based on the phase information is utilized to optimize the rough segmentation result to obtain the final fine segmentation result. The experimental result shows that the tumor can be precisely segmented, and the good segmentation result is achieved especially for ultrasound images with blurred boundaries and many shadows.

A cancer detection system having a plurality of ultrasonic sensors positioned about a garment worn over at least one breast. The sensors transmit a signal that is received by the other sensors. A processor records the amplitude and time-of-flight of the received signals. The signals include both direct line-of-flight signals and reflected signals. In one embodiment, the processor performs tissue structure analysis. In another embodiment, the recorded data is sent to a remote processor for long term storage, tissue structure analysis, and / or addition to a chronological profile.

The invention discloses a breast prosthesis manufacturing method based on the three-dimensional printing technology. The method comprises the steps that a tumor to be excised is analyzed and positioned according to breast medical image data of a patient before an operation, the shape, size and position of the excision part are determined, a three-dimensional digitalization tumor model is established, the radical treatment of the tumor and the demand for individualization overall beauty of the patient in the breast reestablishing process are comprehensively taken into consideration, a breast prosthesis three-dimensional model is optimized and designed according to the established tumor model and the breast shaping golden method, biologically-compatible materials conforming to the hand touch texture of the breast are selected, and the breast prosthesis is printed and formed through the biological three-dimensional printing technology. According to the breast prosthesis manufacturing method, the relation between the breast tumor and the peripheral tissue can be clearly displayed by analyzing and establishing the three-dimensional digitalization tumor model, and thus a doctor can conveniently determine the tumor excision range before the operation; the individualized accurate breast prosthesis can be provided for the patient quickly through the biological three-dimensional printing technology to improve the tumor radical treatment effect and the plastic surgery treatment effect, the living quality is improved, and the medical cost is lowered.

An ultrasound imaging breast tumor detection and diagnostic system and method is disclosed. The method uses the system to acquire a plurality of 3D breast ultrasound images, and then to cut out multiple regions from the 3D breast ultrasound images using a 3D means shift algorithm, and then to acquire the mean grayscale value (MGV) of each region, and then to classify the regions to groups subject to the mean grayscale value (MGV), and to merge each of the regions of the darkest group with adjacent regions of the similar grayscale into a respective suspicious tumor tissue full region, and then to recognize each suspicious tumor tissue full region to be a tumor tissue region or non-tumor tissue region. Thus, using region as the basic computing unit, tumor tissues are quickly recognized from the 3D breast ultrasound images.

Disclosed are systems biology-based methods for repositioning known pharmaceutical compounds to new indications, through the identification of network-based signatures. In particular, the invention provides new and useful methods for selecting drugs or combinations of drugs (and preferably previously-approved drugs) for use in new therapeutic indications. Also disclosed are methods for identifying anti-breast tumor initiating cell (TIC)-based therapeutics from within populations of target compounds. In illustrative embodiments, the invention provides methods and computer programs for the repositioning of FDA-approved pharmaceutical compounds to new indications using network-based signature analysis coupled with conventional in vitro and in vivo testing of identified drug candidates. The invention also allows identification of drugs or drug combinations for treating unmet medical needs including, for example, “orphan” diseases.

Compositions and methods for the therapy and diagnosis of cancer, such as breast cancer, are disclosed. Compositions may comprise one or more breast tumor proteins, immunogenic portions thereof, or polynucleotides that encode such portions. Alternatively, a therapeutic composition may comprise an antigen presenting cell that expresses a breast tumor protein, or a T cell that is specific for cells expressing such a protein. Such compositions may be used, for example, for the prevention and treatment of diseases such as breast cancer. Diagnostic methods based on detecting a breast tumor protein, or mRNA encoding such a protein, in a sample are also provided.

Compositions and methods for the therapy and diagnosis of cancer, particularly breast cancer, are disclosed. Illustrative compositions comprise one or more breast 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 breast cancer.

The relates to an agglutinin chip used for identifying cancer, in particular to an agglutinin chip for identifying breast cancer based on sialoprotein, a reagent kit and application of the reagent kit, and aims at providing an agglutinin chip for identifying breast cancer in a non-destructive mode through the change of carbohydrate chains in saliva, a reagent kit and application of the reagent kit. The agglutinin chip for identifying breast cancer based on sialoprotein comprises an agglutinin testing probe set. The agglutinin testing probe set at least comprises a combination of PHA-E+L, LTL, BS-I, MAL-I, LCA, BPL, PTL-II, NPA and GSL-I, or at least comprises a combination of LTL, BS-I, MAL-I, LCA, BPL, NPA and GSL-I. By means of the agglutinin chip, differentially-expressed glycoprotein carbohydrate chain structures in a patient saliva sample can be rapidly detected, whether a corresponding person suffers from a breast tumor or not is detected, and whether the breast tumor is breast cancer or not is determined; besides, saliva is adopted as an object to be detected and is easy and convenient to collect, and health risks existing when a serum sample is collected for detection in the prior art are avoided.

The invention provides a breast tumor diagnosis system based on magnetic resonance spectrum imaging, comprising a superconduction MR (Magneto Resistance) scanner and a computer system. Through a computer auxiliary detection measure, the breast tumor diagnosis system realizes the early identification diagnosis of a breast tumor and the further diagnosis of breast cancer. Mammary gland magnetic resonance spectrum data are studied by adopting a distinctive manifold study method and projected to a low dimension embedding space, thus not only a low dimension manifold structure hidden in a high dimension magnetic resonance spectrum space can be revealed, but also the identification information in the mammary gland magnetic resonance spectrum data can be efficiently kept; then optimization clustering is carried out on the low dimension identification characteristic by utilizing a clustering method so that data points without the similar identification characteristic are separated to the maximum; and further a cost sensitive mechanism is introduced to achieve misclassification total cost minimization and realize optimization diagnosis of the breast cancer.