146 results about "Neoplasm diagnosis" patented technology

The present invention relates to a molecular imaging probe for tumor diagnosis, and provides a sugar nucleic acid molecular imaging probe, the probe comprises a DNA aptamer sequence and more than one glycosyl nucleoside module, and is labeled by radionuclide, the DNA aptamer sequence can specifically target tumor cells after functional folding; the glycosyl nucleoside module is a glycosyl modified nucleoside derivative, is accurately modified at the 5'end or / and the 3 'end of the aptamer through DNA solid-phase synthesis, has the imaging characteristics of biological safety, high sensitivity and high resolution, and has an excellent diagnosis effect on part of cancers which are difficult to diagnose by a traditional method. The invention also provides a preparation method and a use method of the sugar nucleic acid molecular imaging probe, so that sugar modification of the aptamer is convenient, rapid, accurate, controllable and modularized, and the sugar nucleic acid molecular imaging probe has huge clinical application potential and transformation value in cancer diagnosis.

The present invention relates to a method and system for predicting the probability of normal tissue damage based on deep learning, belonging to the technical field of medical data processing. The method includes: obtaining the tumor dose data, basic information, and tumor diagnosis information of a patient; the tumor dose data is formulated by a doctor based on the patient's tumor diagnosis information before radiotherapy for the patient; the basic information includes at least the patient's age; based on the tumor dose data, obtaining the dose volume histogram of the patient; based on the dose volume histogram, obtaining the volume parameters and biological equivalent dose of the patient's normal tissue; inputting the volume parameters and biological equivalent dose of the patient's normal tissue, the patient's basic information, and tumor diagnosis information into a normal tissue damage probability prediction model constructed based on deep learning to obtain the damage probability of the patient's normal tissue. Compared with traditional statistical models or empirical formulas, the prediction accuracy of this method is higher, and it can more accurately evaluate the damage probability of normal tissue.

The invention provides a preparation method and application of a CD70 specific nano antibody molecular imaging probe. The probe comprises a tumor targeting group, radionuclide and a bifunctional chelating agent, the tumor targeting group is a CD70 specific nano antibody; the CD70 specific nano antibody is R8B4, and the amino acid sequence of the R8B4 is as shown in SEQ ID No. 1. The probe provided by the invention can realize noninvasive diagnosis of solid tumors such as renal clear cell carcinoma and malignant tumors of a blood system; reabsorption of the compound in the kidney is effectively inhibited through charge adjustment, kidney uptake is remarkably reduced, non-specific signals are reduced, the signal-to-noise ratio during targeted imaging or treatment is increased, and the imaging quality and treatment safety are improved. The probe not only has a wide application prospect in tumor diagnosis, but also provides a new technical support for targeted therapy and individualized precision medical treatment, and has important scientific research and clinical application values.

The present invention relates to the field of molecular imaging, nuclear medicine and single-domain antibody technology for tumor diagnosis and treatment, and in particular to a method for preparing a radionuclide-labeled Trop2-specific single-domain antibody probe and its application. The Trop2-specific single-domain antibody has a CDR1 having an amino acid sequence shown in SEQ ID No.1, a CDR2 having an amino acid sequence shown in SEQ ID No.2, and a CDR3 having an amino acid sequence shown in SEQ ID No.3. The Trop2-specific single-domain antibody prepared by the present invention 18 The F-labeled single-domain antibody probe is used for immuno-PET imaging, which realizes the non-invasive visualization of Trop2 in vivo and further realizes the non-invasive diagnosis of Trop2-positive tumors. The probe has the advantages of simple preparation process, low cost, high specificity, high stability, short imaging cycle, low radiation dose, and easy clinical transformation.

The present invention discloses a CD47-specific molecular imaging probe and its preparation method and application, which relates to the molecular imaging, nuclear medicine and nano-antibody technology fields of tumor diagnosis and treatment, including human CD47-specific monovalent nano-antibody probes and human CD47-specific nano-antibody fusion protein probes; its preparation method comprises: modifying CD47-specific nano-antibody C2 by compounds, synthesizing radionuclide labeling precursors, and preparing the CD47-specific molecular imaging probe by radionuclide labeling; the prepared probe is applied to immune PET imaging and radioimmunotherapy of malignant tumors. The present invention has the advantages of simple preparation process, low cost, high specificity, high stability, and easy clinical transformation. It can realize non-invasive visualization of heterogeneous expression of CD47, screen patients with high expression of CD47, and further carry out CD47-specific radioimmunotherapy, that is, realize integrated diagnosis and treatment.

The invention belongs to the technical field of microbiome clinical diagnosis, and particularly relates to a marker combination, a model and a method for predicting the prognosis risk of a colorectal cancer patient. The method comprises the steps of whole genome sequencing data analysis, human source sequence filtering, microorganism sequence extraction and annotation and machine learning diagnosis model construction. The method has the advantages of being high in accuracy and free of culture, tissue-specific microbiota still exist in low-biomass tumors, and promising diagnostic value is shown. A large amount of clinical patient sequencing data can be subjected to secondary development and utilization, the accuracy of tumor diagnosis is improved, and the method can be widely applied to prognosis survival evaluation of patients.

The invention discloses a colorectal tumor diagnosis auxiliary system based on artificial intelligence, and relates to the technical field of tumor diagnosis, and the colorectal tumor diagnosis auxiliary system comprises a medical image preprocessing module, a feature extraction and optimization module and a deep learning diagnosis model module; wherein the medical image preprocessing module comprises an image acquisition unit and an image processing unit; the image acquisition unit is used for acquiring medical images of all human body parts with tumor diagnosis results; the image processing unit is used for processing the acquired medical image; the feature extraction and optimization module comprises a feature extraction unit and a feature selection and optimization unit; the feature extraction unit uses a deep convolutional neural network to extract depth features of the image; the deep learning diagnosis model module adopts a hybrid model combining a convolutional neural network and a long-short term memory network to carry out auxiliary diagnosis on colorectal tumors; the technical effects that the time for interpreting the medical image is shortened, and meanwhile the accuracy of interpreting the medical image is improved are achieved.

The invention discloses a tumor targeting reagent and application thereof in tumor diagnosis. The targeting reagent has strong affinity to tumors, strong specificity and no biotoxicity, is relatively stable in vivo, and can be used as a molecular probe to be applied to molecular imaging and / or treatment of various integrin alpha6 high-expression tumors; the targeting reagent provided by the invention comprises the tumor targeting peptide RWYDeA, and further comprises a radionuclide chelating agent, other connecting structures and a hydroxyl substitution structure, and the structure is beneficial to improving the tumor targeting property of the targeting reagent, prolonging the tumor binding time and achieving a better tumor diagnosis effect; the method can be used for preparing products for diagnosing / treating diseases related to high expression of integrin alpha6.

The application discloses an exosome small non-coding RNA molecule marker and application thereof, and belongs to the field of tumor liquid biopsy and molecular diagnosis. The exosome small non-coding RNA molecule marker is at least one of tRNA-GlyGCC-5 and sRESE; the nucleotide sequence of the tRNA-GlyGCC-5 is shown as SEQ ID NO:1; and the nucleotide sequence of the sRESE is shown as SEQ ID NO:2. The sRESE in the application is a brand new small non-coding RNA sequence, and is first discovered by the inventor, which is important for the marker of esophageal cancer and the research on disease progression mechanism. The tumor diagnosis kit provided by the application, which comprises the exosome small non-coding RNA molecule marker, is a liquid diagnosis monitoring kit with non-invasiveness, high sensitivity, high specificity and applicability to general survey or screening.

The invention provides an HER2 immunohistochemical pathological image full-automatic quantitative diagnosis method and device and a readable storage medium, the method comprises a foreground tissue segmentation algorithm and an intensity segmentation algorithm, foreground tissue segmentation is based on a Yov8 model, intensity segmentation is based on a PIDNet model, and multi-scale two-stage iteration training is adopted. Through the steps of image screening processing, data labeling, model training and the like, a foreground tissue area can be accurately segmented, the intensity can be subdivided, and meanwhile diagnosis result verification of a pathologist is introduced. According to the method, the defects of a traditional manual film reading and image segmentation method can be overcome, high-precision tissue segmentation and efficient full-automatic quantitative diagnosis are achieved, and the method has wide application prospects in the fields of tumor diagnosis, medicine research and development and the like and has the advantages of being high in automation degree, high in robustness, good in expandability and the like.

The invention provides a benzene azepine derivative, a radioactive probe and application thereof, and belongs to the technical field of biological medicine. According to the present invention, the benzazepine derivative is modified, and the hydrophilic or lipophilic side chain is introduced, such that the prepared benzazepine derivative can be used as the V2R targeting precursor for application, the specific V2R targeting can be achieved, and the new molecular tool is provided for the subsequent V2R positive tumor diagnosis and treatment. The radioactive probe combined with the 68Ga marker shows a good tumor imaging effect, can realize PET imaging of V2R positive tumors, is helpful for improving the accuracy of tumor diagnosis, can also be used for evaluating the treatment effect, has a relatively high target / non-target ratio, can better display the distribution of whole body V2R receptors, and has a good application prospect. The invention has various applications in cancer diagnosis and treatment.

The invention belongs to the field of computational biology calculation, and particularly relates to a colorectal cancer metabolism information generality analysis method based on intrinsic learning. The method comprises the following steps: firstly, training a deep learning model, and identifying an intrinsic metabolite of the colorectal cancer from a high-resolution tumor space metabonomics data set of the colorectal cancer; secondly, introducing a distribution selection mechanism and an intrinsic learning method, and efficiently screening intrinsic metabolites highly related to colorectal cancer diagnosis and staging; then, inputting the intrinsic metabolites into the tumor prediction network to estimate the tumor condition; and finally, evaluating the effectiveness of the screened intrinsic metabolites through multi-task verification, including tumor diagnosis and T / N / M staging prediction of colorectal cancer. Experimental results show that the colorectal cancer screened based on the model is predicted, the AUC in tumor diagnosis and T / N / M staging prediction tasks exceeds 0.9, and the model has high clinical application value.

According to the exosome multi-target detection method based on the nano-frame multi-satellite mode, a high-stability tetrahedron is used as a core skeleton, multiple high-protein-affinity nucleic acid aptamer tongs are assembled and matched according to needs to construct a high-reproducibility biomarker recognition element, a molecular form with multiple satellites wrapping exosome is constructed, and the exosome multi-target detection method based on the nano-frame multi-satellite mode is obtained. According to the method, a'free satellite 'element is formed, and flow cytometry is utilized to detect the particle size and output signals with ultralow background interference, so that multiple detection requirements of different tumors on different expression levels of different markers in different development processes can be met, and an identification-separation-detection integrated high-specificity exosome detection strategy is realized. Clinical examination and diagnosis requirements serve as fundamental guidance, detection potential is excavated on an existing basic flow platform, instrument detection particle size limitation is turned into background killer, a new instrument detection thought is widened, detection performance is improved, exosome encrypted information decoding is accelerated, and the transformation progress of clinical disease prevention and treatment and tumor diagnosis and treatment is promoted and guided.

The invention discloses a manifold confrontation field self-adaption-based tumor diagnosis method, which comprises the following steps of: firstly, pre-training, and using a model pre-trained by source domain data as a model initialization parameter; then, manifold confrontation field self-adaption is carried out, a confrontation learning network framework is designed, a discriminant manifold propagation method is introduced to adjust structural parameters of a manifold module, manifold learning is used for assisting confrontation learning to further minimize the source domain and target domain feature mapping distance, and a target domain feature extractor is trained; and finally, testing, inputting a target domain test tumor image into a feature extractor after adversarial training to extract features, and then classifying data by using a trained classifier to obtain a tumor image classification result. The objective of the invention is to provide a manifold confrontation field-based adaptive tumor diagnosis method, which solves the dependence of existing deep learning on a large amount of labeled data, reduces the sample labeling cost in tumor diagnosis, reduces the labor intensity of doctors and experts, and realizes automatic and high-precision diagnosis classification of non-labeled medical tumor images.

The invention discloses a tumor diagnosis method and system for generating a molecular spatial distribution diagram based on MRI (Magnetic Resonance Imaging), and belongs to the technical field of image data processing. The method comprises the following steps: constructing an MRI-pathological local matching data set; the Transform and the GAN are combined to construct a local MRI (Magnetic Resonance Imaging) to generate a small pathological graph model; and constructing and verifying a molecular spatial distribution diagram. According to the method, the histopathology is taken as a bridge, a two-layer mapping relation is constructed between the MRI and the molecular features, the global molecular features are estimated through local matching data, existing clinical resources are effectively utilized, and three-dimensional space distribution evaluation of the molecular features is indirectly achieved at low cost. And the constructed model can be used for pathological diagnosis in any region on the brain MRI sequence, so that the potential invasion region of the tumor can be explored, and reference is provided for the surgical resection range definition and treatment strategy planning of the glioma.

The invention discloses an intelligent tumor diagnosis large model construction method based on multi-modal medical data fusion. The method comprises the steps of 1, data collection processing and feature extraction, 2, establishment of a dynamic fusion model, 3, arrangement of a training set, 4, model training optimization, 5, establishment of an auxiliary diagnosis model and 6, model deployment. According to the method, a three-level fusion mechanism of a self-adaptive fusion framework is established, medical image data and clinical data of various modes are effectively fused, the model is trained by using a double-domain transfer learning strategy, the small sample learning efficiency and precision are improved, the characteristics of tumors can be reflected more comprehensively and accurately, and the method is suitable for large-scale popularization and application. A powerful auxiliary reference is provided for improving the accuracy and efficiency of tumor diagnosis, and the model can be expanded and deployed in other disease auxiliary diagnosis reference systems and has a wide application prospect.

The invention provides a three-dimensional MRI (Magnetic Resonance Imaging) tumor segmentation method based on boundary perception and tumor diagnosis equipment. The method comprises the following steps: acquiring three-dimensional MRI (Magnetic Resonance Imaging) of multiple tumor patients as a tumor data set, wherein the three-dimensional MRI comprises gadolinium-enhanced T1SC slices; performing tumor segmentation by taking the three-dimensional MRI in the tumor data set as input of a first segmentation model to obtain a category label of a tumor in the three-dimensional MRI; wherein the first segmentation model is a model based on a convolutional neural network CNN, the first segmentation model comprises a first model branch and a second model branch, the first model branch is used for predicting a category label, and the second model branch is used for predicting a surface distance field of a tumor based on boundary perception; the surface distance field is used for describing the nearest distance from each voxel to the tumor surface in the three-dimensional MRI, and training and optimization of the first segmentation model are carried out based on training and optimization of the first model branch and the second model branch.

The invention discloses an ultrasonic tumor examination system for the obstetrics and gynecology department. The ultrasonic tumor examination system comprises a data acquisition module, a data processing module, a data analysis module and a result output module. The data acquisition module synchronously acquires pressure distribution, tumor morphological characteristics and blood flow data; the data processing module maps the pressure field to an ultrasonic image to generate a superposition graph, so that a three-dimensional space model is constructed, and deformation caused by breathing or vascular pulsation is corrected; the data analysis module divides regions according to tumor boundaries determined by pressure, calculates hemodynamic and morphological parameters of each region, and outputs malignancy probability classification through a convolutional neural network; and the result output module generates a space-function thermodynamic diagram and a diagnosis report, and also can form a four-dimensional dynamic report in combination with historical data, thereby improving the tumor diagnosis accuracy, realizing accurate matching of multi-dimensional information, and providing a more comprehensive basis for tumor property judgment.

The invention relates to a radioactive normal tissue damage probability prediction method and system based on deep learning, and belongs to the technical field of medical data processing. The method comprises the following steps: acquiring tumor dose data, basic information and tumor diagnosis information of a patient; the tumor dose data is formulated by a doctor according to tumor diagnosis information of a patient before radiotherapy of the patient; the basic information at least comprises the age of the patient; obtaining a dose volume histogram of the patient based on the tumor dose data; based on the dose volume histogram, acquiring volume parameters and bioequivalent dose of normal tissues of the patient; and inputting the volume parameter and the bioequivalent dose of the normal tissue of the patient, the basic information of the patient and the tumor diagnosis information into a normal tissue damage probability prediction model constructed based on deep learning to obtain the damage probability of the normal tissue of the patient. Compared with a traditional statistical model or empirical formula, the method is higher in prediction precision, and the damage probability of the normal tissue can be evaluated more accurately.

The invention relates to a probe for tumor diagnosis and / or treatment, and discloses a tumor diagnosis and treatment integrated probe and a preparation method thereof. The probe contains a nucleic acid aptamer, tetrahedral framework nucleic acid, a nuclide chelating ligand and nuclide for marking, the nucleic acid aptamer is connected with the tetrahedral framework nucleic acid; the nuclide chelating ligand is coupled with a nucleic acid short single strand, is labeled by the labeling nuclide, and is linked to the tetrahedral framework nucleic acid. The characteristic of controllable programming of DNA nucleic acid is utilized, the size of the tetrahedral framework nucleic acid and the number of the nucleic acid aptamers hybridized on the tetrahedral framework nucleic acid are adjusted in order, the in-vivo specific targeting binding capacity of the nucleic acid aptamers is improved, the tumor uptake effect is enhanced, the retention of normal tissues and organs is reduced, and the tumor treatment effect is improved. The pharmacokinetics of the aptamer can be modulated, the exposure amount of the aptamer at a tumor part is increased, and the aptamer can be effectively used for diagnosis and / or treatment of tumors.

The invention belongs to the technical field of cell sampling and inspection, and particularly relates to an inspection device for oncology department, which comprises a puncture cylinder composed of an upper needle tube and a lower needle tube; the protection assembly is arranged in the puncture cylinder; the trigger assembly is arranged at the upper end of the protection assembly and used for activating a protection mechanism of the protection assembly; the linkage assembly is arranged at the lower end of the lower needle tube; wherein the protection assembly comprises a supporting part, the supporting part is connected into the lower needle tube in a sliding mode, the upper end of the supporting part is connected with a pressing block in a sliding mode, and a capsule is arranged between the supporting part and the pressing block. By introducing a dynamic protection mechanism, a built-in instant freezing system and a modular structural design, the defects of an existing puncture sampling device in the aspects of safety, sample storage, structural flexibility and the like are overcome, and the device has remarkable technical progress and practical value and is suitable for being widely applied to the field of tumor diagnosis.

The invention relates to the technical field of biological medicine and tumor diagnosis, and particularly discloses a human epididymal protein 4 tumor marker and application thereof. The high expression of the human epididymal protein 4 tumor marker gene is closely related to the prognosis of an ovarian cancer patient, and the human epididymal protein 4 can be used as an ovarian cancer tumor marker and has important significance on the diagnosis, treatment and prognosis evaluation of ovarian cancer; the invention provides a detection primer pair of a human epididymal protein 4 tumor marker and application of the detection primer pair as an ovarian cancer diagnosis kit, ovarian cancer diagnosis can be more accurate and rapid, the early diagnosis level of ovarian cancer is improved, and the invention further provides a human epididymal protein 4 tumor marker expression inhibitor siRNA which can be used for detecting the human epididymal protein 4 tumor marker. When being used for inhibiting the expression of the human epididymal protein 4 tumor marker, the human epididymal protein 4 tumor marker has a good interference effect and has clinical application potential.

The invention provides an acoustic-magnetic dual-mode diagnosis and treatment agent as well as a preparation method and application thereof, and belongs to the technical field of preparation of tumor diagnosis and treatment agents. The acoustic-magnetic dual-mode diagnosis and treatment agent is surface-modified magnetic nanoparticles which contain nano balloon genes and are subjected to Escherichia coli induced expression; the nucleotide sequence of the nano-balloon gene is a sequence shown as NCBI: KC601845.1, escherichia coli in the acoustic-magnetic dual-mode diagnosis and treatment agent as a diagnosis and treatment agent carrier has an active targeting property on a tumor hypoxic region, and bacteria contain a nano-balloon and have an acoustic response characteristic; the escherichia coli surface modified magnetic nanoparticles have a magnetic response characteristic. In acoustic-magnetic dual-mode imaging, firstly, on a real-time ultrasonic contrast monitoring image, a nano air bag expressed in bacteria can generate an enhanced tumor ultrasonic echo signal; secondly, under the action of an external changing magnetic field, the magnetic nanoparticles on the surfaces of the bacteria can generate an enhanced tumor magnetic vibration imaging effect, so that more efficient tumor diagnosis and / or treatment can be realized.

The present application relates to the field of tumor markers, in particular to a fascin acetylation modification which can be used as a tumor diagnosis and prognosis analysis marker, a detection reagent and application thereof. The present application is directed to the fact that acetylation modification at K41 site of fascin significantly inhibits the cancer-promoting activity of fascin protein, and in esophageal cancer tissue, the proportion of fascin with acetylation modification at K41 site is significantly lower than that of wild-type fascin in para-cancerous tissue. Based on the acetylation at K41 site of fascin, a specific antibody for acetylation at K41 site of fascin is developed, so as to conduct clinical application research on acetylation at K41 site of fascin, and establish an esophageal cancer prognosis analysis model and targeted treatment.

The invention relates to a mutant calreticulin for diagnosis of myeloid malignant tumors. A method for diagnosing myeloid malignancies comprising determining the presence of a mutant allele of a calreticulin gene is disclosed. In addition, genomic sequences, cDNA sequences, mRNA sequences and protein sequences of the mutant calreticulin are also subject matter of the invention. Furthermore, the invention relates to the medical use of inhibitors of the mutant calreticulin.

Provided is use of an endogenous micropeptide in cancer diagnosis or treatment. Particularly, the present invention relates to use of a micropeptide encoded on a long non-coding RNA as a tumor marker, a tumor treatment drug, and / or a tumor treatment target. Specifically, two micropeptides and variants thereof have been discovered for the first time. Moreover, provided are nucleotide sequences encoding the described micropeptides and recombinant vectors containing these nucleotide sequences, and also provided are use thereof in the preparation of a reagent or a drug for diagnosing, preventing, alleviating, or treating a tumor, and use of a drug or a reagent for an interfering micropeptide or a coding nucleic acid thereof in the preparation of a medicament or a pharmaceutical composition for preventing, alleviating, or treating a disease. The micropeptides not only provide biomarkers for the diagnosis of tumors, but also provide therapeutic drugs or therapeutic targets for the treatment of tumors.

An F-18 labeled chiral pure derivative of hydroxyfuran, a preparation method and use thereof were provided. (4R, 5R)[18F]FAA provided by the present disclosure is a chiral pure radioactive compound, and three other chiral pure [18F]FAA structural formulae are also provided by the present disclosure. The present disclosure provides a chiral pure radioactive probe (4R, 5R)[18F]FAA, which shows unique tumor diagnostic efficiency and similar distribution to AA, and can be used for early diagnosis of tumors, pathological studies, assessment of disease progression, and evaluation for efficacy.

The present disclosure discloses a brand-new skeleton 99mTc-FAPI diagnostic probe and use thereof in the preparation of a drug or a reagent for diagnosing tumors, wherein the structural formula of a dimeric compound targeting FAP is shown by following formula. Compared with conventional FAP inhibitor radiopharmaceuticals, technetium-99m-labeled novel skeleton FAP inhibitor dimeric compound has a very high tumor uptake rate, high contrast between tumor and background and good in vivo biodistribution.

A multimodal hyperspectral vibrational sum-frequency generation (VSFG) platform and a method of tumor diagnosis are provided. The method employs the chemical-specific VSFG microscopy platform as a label-free imaging technique for tumor identification.

The application discloses a cervical cancer circRNA marker and application thereof, and belongs to the technical field of biology. The inventors have found that the expression level of circular RNA hsa_circ_0002828 in the plasma of a cervical cancer patient is significantly lower than that in the plasma of a healthy person, thereby indicating that hsa_circ_0002828 can be used as a diagnostic marker for cervical cancer and for predicting the occurrence of cervical cancer. Meanwhile, after overexpression of hsa_circ_0002828, the proliferation ability and invasion ability of cervical cancer cells can be significantly inhibited, and tumor cell apoptosis can be strongly induced. These results show that hsa_circ_0002828 can be used as a tumor diagnosis marker and a potential target for tumor treatment, and is expected to be applied to the diagnosis and treatment of cervical cancer.