45 results about "Benign lesion" patented technology

The invention discloses a tumor malignant risk stratification auxiliary diagnosis system of an artificial intelligence medical image. The system comprises a data acquisition module, a data preprocessing module, a model establishment module, a model verification and optimization module, a stratification diagnosis module and a database platform. The tumor malignant risk stratification auxiliary diagnosis system of the invention is based on artificial intelligence technology, successive stratification of the malignant risk of the tumor can be achieved, the clinical diagnosis thinking is simulated, based on the high-precision ability of detecting benign lesions and malignant tumors of artificial intelligence model, and the space-occupying lesions with definite imaging features are diagnosed automatically. As a result, the system can substantially assist the clinical management decision of space-occupying lesions, improve the existing work flow of clinical diagnosis, increase the confidenceof doctors in diagnosis, reduce the work pressure, reduce the anxiety of patients with low-risk malignant lesions, greatly improve the diagnostic rate of benign lesions and malignant tumors, and hopefully realize the landing implementation of artificial intelligence clinical auxiliary diagnosis.

A system and method for the analysis and visualization of normal and abnormal tissues, objects and structures in digital images generated by medical image sources is provided. The present invention utilizes principles of Iterative Transformational Divergence in which objects in images, when subjected to special transformations, will exhibit radically different responses based on the physical, chemical, or numerical properties of the object or its representation (such as images), combined with machine learning capabilities. Using the system and methods of the present invention, certain objects, such as cancerous growths, that appear indistinguishable from other objects to the eye or computer recognition systems, or are otherwise almost identical, generate radically different and statistically significant differences in the image describers (metrics) that can be easily measured.

A non-invasive tool for skin disease diagnosis would be a useful clinical adjunct. The purpose of this study was to determine whether visible / near-infrared spectroscopy can be used to non-invasively characterize skin diseases. In-vivo visible- and near-infrared spectra (400-2500 nm) of skin neoplasms (actinic keratoses, basal cell carcinomata, banal common acquired melanocytic nevi, dysplastic melanocytic nevi, actinic lentigines and seborrheic keratoses) were collected by placing a fiber optic probe on the skin. Paired t-tests, repeated measures analysis of variance and linear discriminant analysis were used to determine whether significant spectral differences existed and whether spectra could be classified according to lesion type. Paired t-tests showed significant differences (p<0.05) between normal skin and skin lesions in several areas of the visible / near-infrared spectrum. In addition, significant differences were found between the lesion groups by analysis of variance. Linear discriminant analysis classified spectra from benign lesions compared to pre-malignant or malignant lesions with high accuracy. Visible / near-infrared spectroscopy is a promising non-invasive technique for the screening of skin diseases.

The present invention provides a method and a kit for determining whether a head and neck cancer is HPV-related. In one embodiment, an RNAscope® HPV assay was designed to detect the presence of E6 / E7 mRNA of certain high-risk HPV subtypes related to head and neck cancer. The present invention also provides a method and a kit for determining whether a cervical lesion is a benign lesion or a cervical intraepithethial neoplasm lesion. The present invention further provides a method for determining the progression of cervical intraepithethial neoplasm based on the spatial pattern and levels of the E6 / E7 mRNA of certain high-risk HPV subtypes. The present invention also provides a method for determining the risk of developing cervical cancer in a human diagnosed with cervical intraepithethial neoplasm based on presence and absence of the certain subgroups of high-risk HPV subtypes.

A computer-aided diagnosis (CAD) scheme to aid in the detection, characterization, diagnosis, and / or assessment of normal and diseased states (including lesions and / or images). The scheme employs lesion features for characterizing the lesion and includes non-parametric classification, to aid in the development of CAD methods in a limited database scenario to distinguish between malignant and benign lesions. The non-parametric classification is robust to kernel size.

The invention discloses a method and a device for identifying pathological pictures, wherein the method comprises: obtaining sample data including a positive sample that is a pathological picture of malignant lesion and a negative sample that is a picture of normal tissue or a pathological picture of benign lesion, with a lesion area marked on the pathological picture of a malignant lesion; dividing the sample data into a training set and a testing set; training a deep neural network model using the training set; testing a trained deep neural network model using the testing set; adjusting parameters of the trained deep neural network model according to a testing result; identifying the pathological picture using the trained deep neural network model. The invention can improve the efficiency and accuracy of pathological picture identification.

Robust classification methods analyze magnetic resonance spectroscopy (MRS) data (spectra) of fine needle aspirates taken from breast tumors. The resultant data when compared with the histopathology and clinical criteria provide computerized classification-based diagnosis and prognosis with a very high degree of accuracy and reliability. Diagnostic correlation performed between the spectra and standard synoptic pathology findings contain detail regarding the pathology (malignant versus benign), vascular invasion by the primary cancer and lymph node involvement of the excised axillary lymph nodes. The classification strategy consisted of three stages: pre-processing of MR magnitude spectra to identify optimal spectral regions, cross-validated Linear Discriminant Analysis, and classification aggregation via Computerised Consensus Diagnosis. Malignant tissue was distinguished from benign lesions with an overall accuracy of 93%. From the same spectrum, lymph node involvement was predicted with an accuracy of 95% and tumor vascularisation with an overall accuracy of 92%.

A method for selectively heating cancerous conditions of the breast including invasive ductal carcinoma and invasive glandular lobular carcinoma, and pre-cancerous conditions of the breast including ductal carcinoma in-situ, lobular carcinoma in-situ, and intraductal hyperplasia, as well as benign lesions (any localized pathological change in the breast tissue) such as fibroadenomas and cysts by irradiation of the breast tissue with adaptive phased array focused microwave energy is introduced. Microwave energy provides preferential heating of high-water content breast tissues such as carcinomas, fibroadenomas, and cysts compared to the surrounding lower-water content normal breast tissues. To focus the microwave energy in the breast, the patient's breast can be compressed and a single electric-field probe, inserted in the central portion of the breast, or two noninvasive electric-field probes on opposite sides of the breast skin, can be used to measure a feedback signal to adjust the microwave phase delivered to waveguide applicators on opposite sides of the compressed breast tissue. The initial microwave power delivered to the microwave applicators is set to a desired value that is known to produce a desired increase in temperature in breast tumors. Temperature feedback sensors are used to measure skin temperatures during treatment to adjust the microwave power delivered to the waveguide applicators to avoid overheating the skin. The microwave energy delivered to the waveguide applicators is monitored in real time during treatment, and the treatment is completed when a desired total microwave energy dose has been administered. By heating and destroying the breast lesion sufficiently, lesions can be reduced in size and surrounding normal breast tissues are spared so that surgical mastectomy can be replaced with surgical lumpectomy or the lesions can be completely destroyed so that surgical mastectomy or lumpectomy is avoided.

The invention provides a breast ultrasonic image multi-classification system and method based on cross correlation characteristics. The system comprises an ultrasonic image preprocessing unit; an interest area extraction unit used for extracting an image of an interest area; an internal cross correlation density feature extraction unit used for extracting an internal cross correlation density characteristic value of an interest image; a conventional feature extraction unit used for extracting a plurality of conventional characteristic values of the interest area image; and a multi-classification unit used for training classifiers, inputting an internal cross correlation density characteristic value vector and conventional characteristic vectors to three trained classifiers for classification, and regarding the category with the most prediction as a final classification result. According to the classification method, the internal cross correlation density characteristic based on the interest area is additionally provided, the auxiliary diagnosis effect of a breast ultrasonic computer can be effectively improved, the classification category of galactocele which is the benign lesion is added, and the requirement of a breast ultrasonic computer auxiliary system by doctors is further met.

The invention relates to a novel photosensitizer monomer completely soluble in water. Chlorophyll a is taken as a raw material for preparing pheophorbide a, 3-devinyl-3-(1'- hexahydro)ethyl-methyl pheophorbide-a is directly synthesized from pheophorbide a, and a water-soluble salt shown as the structural formula is obtained by processing with an alkali metal hydroxide. In the structural formula, R1, R2 and R3 are H or M, R1, R2 and R3 are not H simultaneously, and M is selected from Na, K or NH4<+>. The above water-soluble salts do not change the large ring structure with photosensitivity, are convenient to apply because of good water solubility, are applicable to prepare medicines for treating or diagnosing malignant tumor (especially superficial malignant tumor in all lumens), precancerous lesions and benign lesion during photodynamic therapy.

A panel of biomarkers for the diagnosis and treatment of breast cancer was examined in the saliva of a cohort of 1) healthy women, 2) women with benign lesions of the breast and 3) women with diagnosed breast cancer. Recognized tumor markers c-erbB-2 (erb), cancer antigen 15-3 (CA 15-3), and tumor suppresser oncogene protein 53 (p53) were found in the saliva of all three groups of women. The levels of erb and CA 15-3 in the cancer patients evaluated, however, were significantly higher than the salivary levels of healthy controls and benign tumor patients. Conversely, pantropic p53 levels were higher in controls as compared to those women with breast cancer and those with benign tumors.

The invention discloses applications of metabolic markers in diagnosing and identifying benign or malignant lesions of thyroid gland. The malignant lesions of thyroid gland are used for referring thyroid cancer, and the benign lesions of thyroid gland are used for referring thyroid benign node; and the metabolic markers are 1-oleoyl-sn-glycerol-3-phosphatidylcholine and / or 1-stearoyl-sn-glycerol-3-phosphatidylcholine. It is confirmed that when 1-oleoyl-sn- glycerol-3-phosphatidylcholine and 1-stearoyl-sn-glycerol-3-phosphatidylcholine are used for diagnosing and identifying thyroid cancer and thyroid benign node separately, certain accuracy is achieved; and when 1-oleoyl-sn- glycerol-3-phosphatidylcholine and 1-stearoyl-sn-glycerol-3-phosphatidylcholine are used for diagnosing and identifying thyroid cancer and thyroid benign node together, higher accuracy is achieved; so that 1-oleoyl-sn- glycerol-3-phosphatidylcholine and 1-stearoyl-sn-glycerol-3-phosphatidylcholine, and a composition of 1-oleoyl-sn- glycerol-3-phosphatidylcholine and 1-stearoyl-sn-glycerol-3-phosphatidylcholine can be taken as the metabolic markers in diagnosing and identifying thyroid cancer and thyroid benign node.

The invention discloses a use of a Kin17 gene or protein in preparation of cervical cancer diagnosis and treatment medicaments. The inventor discoveries that an expression level of the Kin17 protein in normal cervical epithelial tissue and cervical benign lesion tissue cells is low but the expression level is high in cervical cancer tissue and thus the Kin17 protein keeps rapid proliferation activity of cervical cancer cells, is closely related to pathological parameters, chemotherapeutic effects and disease progress and has an important effect in cervical cancer generation and development. Through silencing of Kin17 expression in cervical cancer cells, cancer cell proliferation activity is inhibited and cervical cancer cell sensitivity to chemotherapeutic drugs is improved. The Kin17 gene or protein can be used as a novel cervical cancer diagnosis marker and medicament target. The Kin17 gene or protein can be used for cervical cancer early-identification diagnosis, patient prognosis evaluation and clinical treatment.

The invention belongs to the technical field of medical treatment, and discloses a machine learning-based bimodal image omics ground glass nodule classification method, which comprises the following steps of: step 1, case data collection: collecting patients who receive 18F-FDG PET / CT examination due to suspicious ground glass nodules (GGN); step 2, image acquisition and reconstruction: performing image acquisition by adopting a PET / CT (positron emission tomography / computed tomography) imaging instrument; step 3, image feature extraction; and step 4, data processing and analysis. According to the method, the image omics model based on the combination of the PET image and the HRCT image is constructed by applying a machine learning method, the GGN is classified, including pre-infiltration lesion, micro-infiltration adenocarcinoma, infiltration adenocarcinoma and benign lesion, verification and testing, the method is good in robustness, high in accuracy, simple and feasible. According to the method, the functional metabolism information and the physical anatomical information of the molecular level of the focus are integrated, the prediction efficiency of traditional CT parameters and single CT radiomics is effectively improved, and clinical management of the GGN is facilitated.

The invention relates to a 2-(1-n-hexyloxy)ethylchlorin f salt, and a pharmaceutical composition and an application thereof. Specifically, the invention relates to the 2-(1-n-hexyloxy)ethylchlorin f salt used in photo-dynamic therapy and / or sono-dynamic therapy. The salt is soluble in water, and has stable properties. The salt can be used as a photosensitizer and / or a sound-sensitizer. The salt is suitable to be used for treating and diagnosing relatively large malignant, precancerous lesions or benign lesions. The invention also relates to a pharmaceutical composition comprising the novel compound, and the application and a preparation method of the novel compound.

A method for selectively heating cancerous conditions of the breast including invasive ductal carcinoma and invasive glandular lobular carcinoma, and pre-cancerous conditions of the breast including ductal carcinoma in-situ, lobular carcinoma in-situ, and intraductal hyperplasia, as well as benign lesions (any localized pathological change in the breast tissue) such as fibroadenomas and cysts by irradiation of the breast tissue with adaptive phased array focused microwave energy is introduced. Microwave energy provides preferential heating of high-water content breast tissues such as carcinomas, fibroadenomas, and cysts compared to the surrounding lower-water content normal breast tissues. To focus the microwave energy in the breast, the patient's breast can be compressed and a single electric-field probe, inserted in the central portion of the breast, or two noninvasive electric-field probes on opposite sides of the breast skin, can be used to measure a feedback signal to adjust the microwave phase delivered to waveguide applicators on opposite sides of the compressed breast tissue. The initial microwave power delivered to the microwave applicators is set to a desired value that is known to produce a desired increase in temperature in breast tumors. Temperature feedback sensors are used to measure skin temperatures during treatment to adjust the microwave power delivered to the waveguide applicators to avoid overheating the skin. The microwave energy delivered to the waveguide applicators is monitored in real time during treatment, and the treatment is completed when a desired total microwave energy dose has been administered. By heating and destroying the breast lesion sufficiently, lesions can be reduced in size and surrounding normal breast tissues are spared so that surgical mastectomy can be replaced with surgical lumpectomy or the lesions can be completely destroyed so that surgical mastectomy or lumpectomy is avoided.

Compositions and methods are disclosed for evaluating a subject's vasculature integrity, for differentiating between a malignant lesion and a benign lesion, for evaluating the accessibility of a tumor to nano-sized therapeutics, for treating tumors, and for live or real time monitoring of a nano-probe's biodistribution.

The invention provides a kit for benign lesion identification and malignant lesion detection of the oral mucosa and a detection method thereof. The detection method comprises the following steps that 1, oral cavity examination is performed, and detailed information of lesions is recorded; 2, the mouth is rinsed with clean water to remove food debris; 3, a preexamination reagent is taken for gargling for 1-5 minutes; 4, a first examination reagent is taken in a dipping mode with a cotton swab to be embrocated on the partial lesions, and dyeing is performed for 2-10 minutes; 5, a second examination reagent is taken for gargling for 1-5 minutes; 6, semi-quantitative or quantitative evaluation is performed on the dyeing results by comparing the dyeing results with a color plate or a self-excitated fluorescence detecting instrument. The kit can be used for auxiliary differential diagnosis of the benign lesion and the malignant lesion of the oral mucosa and can assist a clinician to early diagnose an oral cavity cancer and monitor the malignant process of the oral precancerous lesions.

The invention provides a kit for benign lesion identification and malignant lesion detection of the oral mucosa and a detection method thereof. The detection method comprises the following steps that 1, oral cavity examination is performed, and detailed information of lesions is recorded; 2, the mouth is rinsed with clean water to remove food debris; 3, a preexamination reagent is taken for gargling for 1-5 minutes; 4, a first examination reagent is taken in a dipping mode with a cotton swab to be embrocated on the partial lesions, and dyeing is performed for 2-10 minutes; 5, a second examination reagent is taken for gargling for 1-5 minutes; 6, semi-quantitative or quantitative evaluation is performed on the dyeing results by comparing the dyeing results with a color plate or a self-excitated fluorescence detecting instrument. The kit can be used for auxiliary differential diagnosis of the benign lesion and the malignant lesion of the oral mucosa and can assist a clinician to early diagnose an oral cavity cancer and monitor the malignant process of the oral precancerous lesions.

The invention discloses a fluorescence quantitative PCR (polymerase chain reaction) detection method for MK (midkine) mRNA (messenger ribose nucleic acid) in peripheral blood. According to the method, expression levels of MK mRNA in peripheral blood of a patient suffering from NSCLC (non-small cell lung cancer), a patient suffering from LEL (lung benign lesion) and a healthy examined person are compared, correlation between the expression levels and NSCLC clinical and pathological characteristics is analyzed, feasibility of taking expression of MK mRNA in peripheral blood as an NSCLC differential and diagnostic marker is discussed, a result indicates that the expression levels of MK mRNA in peripheral blood of the patient suffering from NSCLC, the patient suffering from LEL and the healthy examined person are remarkably different, and high expression levels are remarkably associated with clinical staging, lymphatic metastasis and cell differentiation degree of NSCLC. Therefore, detection of MK mRNA in peripheral blood can be applied to effective detection of differential diagnosis of NSCLC.

A method for treating cancerous or benign conditions of a body or organ employs selective irradiation of the body tissue with energy. The method includes the steps of monitoring temperatures of the skin surface adjacent the body, positioining at least one energy applicator around the body, delivering energy to the at least one energy applicator to selectively irradiate the body tissue with energy and treat at least one of cancerous and benign conditions of the body, adjusting the level of power to be delivered to the at least one energy applicator during treatment based on the monitored skin temperatures, monitoring the energy delivered to the at least one energy applicator, determining total energy delivered to the at least one energy applicator, and completing the treatment when the desired total energy dose has been delivered by the at least one energy applicator to the body.

The invention provides a system and method for multiple classification of breast ultrasound images based on cross-correlation features, including an ultrasound image preprocessing unit; a region of interest extraction unit for extracting images of the region of interest; an internal cross-correlation density feature extraction unit for extracting sense The internal cross-correlation density eigenvalue of the image of interest; the traditional feature extraction unit is used to extract a variety of traditional eigenvalues ​​of the image of the region of interest; the multi-class classification unit is used to train the classifier and convert the internal cross-correlation density eigenvalue vector The traditional feature vectors are input to the three trained classifiers for classification, and the most predicted category is taken as the final classification result. The classification method of the present invention increases the feature based on the internal cross-correlation density of the region of interest, can effectively improve the effect of breast ultrasound computer-aided diagnosis, and increases the classification category of breast cysts, a benign lesion, and further satisfies doctors' requirements for breast ultrasound computer-aided systems. demand.

The invention discloses a use of a Kin17 gene or protein in preparation of cervical cancer diagnosis and treatment medicaments. The inventor discoveries that an expression level of the Kin17 protein in normal cervical epithelial tissue and cervical benign lesion tissue cells is low but the expression level is high in cervical cancer tissue and thus the Kin17 protein keeps rapid proliferation activity of cervical cancer cells, is closely related to pathological parameters, chemotherapeutic effects and disease progress and has an important effect in cervical cancer generation and development. Through silencing of Kin17 expression in cervical cancer cells, cancer cell proliferation activity is inhibited and cervical cancer cell sensitivity to chemotherapeutic drugs is improved. The Kin17 gene or protein can be used as a novel cervical cancer diagnosis marker and medicament target. The Kin17 gene or protein can be used for cervical cancer early-identification diagnosis, patient prognosis evaluation and clinical treatment.

The invention discloses an artificial intelligence medical imaging system for auxiliary diagnosis of tumor malignant risk stratification, comprising: a data acquisition module, a data preprocessing module, a model establishment module, a model verification and optimization module, a hierarchical diagnosis module and a database platform. The auxiliary diagnosis system for tumor malignant risk stratification of the present invention is based on artificial intelligence technology, which can realize successive stratification of malignant risk of tumors, simulate clinical diagnosis ideas, and detect benign lesions and malignant tumors with high precision using artificial intelligence models The ability to automatically diagnose space-occupying lesions with clear imaging features can substantially assist clinical management decision-making of space-occupying lesions, improve the existing workflow of clinical diagnosis, increase physicians' confidence in diagnosis, reduce work pressure, and reduce the risk of low malignancy The anxiety of patients with lesions has greatly improved the diagnosis rate of benign lesions and malignant tumors, and it is expected to realize the implementation of artificial intelligence clinical auxiliary diagnosis.

The invention discloses a serum miRNA combination for thyroid tumor diagnosis and 131 iodine treatment and prognosis. The application of the substance for detecting miRNA in preparation of a product with any one of the following functions: diagnosing thyroid cancer, screening thyroid cancer, distinguishing thyroid cancer from thyroid benign lesion, distinguishing thyroid cancer from healthy people, evaluating prognosis conditions of thyroid cancer patients after 131 iodine treatment, and predicting survival conditions of the thyroid cancer patients after 131 iodine treatment. The miRNA is Has-miR-378d, Has-miR-130b-5p, and / or Has-miR-548j-3p, and the miRNA is characterized in that: Has-miR-378d, Has-miR-130b According to the serum miRNA marker explored by the invention, rapid early diagnosis of thyroid cancer and prejudgment of 131I treatment effect and survival prognosis condition can be realized, so that clinical doctors are guided to provide prevention and treatment schemes for patients.

The invention discloses a ground glass nodule benign and malignant classification method based on a two-way three-dimensional convolutional neural network. The method comprises the steps of 1, collecting participants; 2, acquiring an image; 3, preprocessing the image; and 4, training a deep learning model. According to the ground glass nodule benign and malignant classification method based on the two-way three-dimensional convolutional neural network, data obtained from a PET image and a CT image is developed and fused through deep learning to serve as the two-way 3D-CNN of an input stream so as to be used for classifying benign lesions and malignant lesions in the GGN. According to the network, an end-to-end working process can be realized in a classification process without professional image analysis software and too much human intervention; in addition, the classification accuracy of the network is higher than that of the qualified nuclear medicine practitioners; and then the CNN may contribute to benign and malignant classification and clinical management of the GGN in the absence of well-trained and experienced film readers.

The invention provides an application of specific lectin in preparation of a test tool for identifying lung cancer and a device. For a sample taken from bronchoalveolar lavage fluid, the specific lectin is any one or any combination of the following lectins: MAL-II, RCA120, ECA, HHL, GSL-I, DBA, DSA and AAL. When a sugar chain structure identified by the lectins MAL-II, RCA 120, ECA, and HHL is significantly increased and a sugar chain structure identified by the lectins GSL-I, DBA, DSA, and AAL is significantly reduced, the sample comes from a patient with benign pulmonary disease (BPD), otherwise the sample comes from a lung cancer patient as determined. According to the invention, the bronchoalveolar lavage fluid is used as a test sample. Since the sample is directly obtained from a primary lesion adjacent to tumor cells, it has high organ specificity and can directly reflect true condition of the patient. The test tool of the invention is safe and minimally invasive.

The invention relates to a protein chip for lung cancer diagnosis and a kit. The protein chip for the lung cancer diagnosis comprises a solid phase supporting matter and an antigen which is wrapped with the surface of the solid phase supporting matter, wherein the antigen comprises the following twelve antigen fragments: a Paxi11in antigen fragment, a CTAG1B antigen fragment, an SOX2 antigen fragment, an HSPA9 antigen fragment, a UBQLN1 antigen fragment, a C14orf104 antigen fragment, an ENO-1 antigen fragment, a RPS3 antigen fragment, a CHK antigen fragment, an HNRPA1 antigen fragment, a PCNAantigen fragment and an Eif4g3 antigen fragment. According to the protein chip and the kit, the antigens which are obviously expressed in the early lung cancer and are capable of enabling related antibody growing in the immune system are creatively selected, and the antigens are not expressed or expressed a little in non-cancer benign lesion; the screened antigen fragments are combined to use; theprotein chip technology is carried out to detect the own antibody, related to tumor, in human serum and identify benign nodule of early lung cancer and the lung; and the sensitivity and the specificity are high.