115 results about "Aortic rings" patented technology

The invention discloses a medical image segmentation method and system for an aortic dissection true cavity, an aortic dissection false cavity and an aortic dissection false cavity thrombus. The method comprises the following steps: firstly, acquiring three-dimensional medical image data of the aortic dissection, performing preprocessing operation on the image data to obtain a two-dimensional slice image, and performing local region division on the two-dimensional slice image; secondly, performing feature extraction on the divided image through a hierarchical feature extraction module; then, a dynamic region self-adaption module is used for carrying out region adjustment on the extracted feature map, a region response map is generated through a guide path, and explicit adjustment weights are given to different space regions in the feature map; and finally, uniformly aggregating the multi-scale feature maps after region adjustment, outputting a segmentation mask through a prediction module, and generating a segmentation result with a clear structural boundary and complete semantics. According to the method, while the recognition precision of the complex anatomical structure is improved, the detection capability and boundary sensing performance of a small-size focus are enhanced, and the method has good universality and stability.

The invention discloses an aortic dissection assessment management method based on multi-source information coupling and related equipment. The method comprises the steps that face image information and electrocardio information of a target patient are obtained, wherein the electrocardio information comprises information collected by an ECG recorder; extracting evaluation association features in the face image information and the electrocardio information of the target patient so as to carry out embedding fusion; and performing aortic dissection risk assessment on the target patient based on the fusion features after embedding fusion. The problems that early evaluation and screening of the aortic dissection are difficult, invasive detection is needed, an existing evaluation source data set lacks diversity and is mainly manifested in the fact that covered patient groups are limited, most data sources are single center data, and complex pathological features of the aortic dissection cannot be comprehensively reflected can be solved.

A plain-scan CT image aortic valve calcification segmentation system based on space-time priori comprises a position priori information extraction module, an encoding module and a decoding module, after an aortic image is automatically segmented in an off-line stage to obtain a segmentation mask, attention weights are generated through preprocessing and encoding, and the aortic valve calcification is subjected to image segmentation; and inputting the aorta image serving as a training set into a segmentation model comprising a position prior information extraction module, a coding module and a decoding module, and performing real-time image segmentation through the trained segmentation model in an online stage. According to the method, calcification point features of different sizes and forms are captured through multi-scale prediction; the aorta segmentation prior is introduced, the sensitivity and positioning precision of the model to aortic valve calcification are improved, coronary artery opening sequence time sequence information is introduced, a double-branch structure is adopted to adapt to structural differences, accurate positioning and recognition of aortic valve calcification lesions are achieved, and the false detection rate and the omission ratio are effectively reduced.

An embodiment includes a system comprising: a backbone; a first polyurethane shape memory polymer (SMP) foam on the backbone; a second polyurethane SMP foam on the backbone; a third polyurethane SMP foam on the backbone and between the first and second SMP foams. Other embodiments are described herein.

The application provides an aortic covered stent, an in-situ fenestration instrument and a covered stent manufacturing method, and relates to the technical field of medical instruments.The aortic covered stent comprises a stent body and a covering film covering the stent body, the covering film in the fenestration area is divided into multiple layers and at least comprises an inner layer covering film and an outer layer covering film, and the inner layer covering film and the outer layer covering film are arranged in layers from the inner layer to the outer layer. The inner layer covering film and the outer layer covering film can adopt a lower weaving density, are easy to be punctured to break the film and expand the opening, and a sealing ring can be arranged between the inner layer covering film and the outer layer covering film; the branch stent, the inner layer covering film and the outer layer covering film are attached through surface contact from the inner layer to the outer layer, and the sealing ring is pressed between the inner layer covering film and the outer layer covering film, so that the sealing property is improved and the risk of internal leakage is reduced.

The application discloses medical use of gelated cells loaded with sulfonated chitosan in treatment of atherosclerosis, and belongs to the technical field of biological medicine. The gelated cells loaded with sulfonated chitosan take macrophages as host cells, and intracellular cross-linking forms a photocrosslinking hydrogel network composed of methacrylated hyaluronic acid and sulfonated chitosan. The gelated cells completely retain cell membrane structure and membrane surface protein expression, lose the proliferation ability, and have excellent blood lipid selective adsorption capacity and foam cell lipid metabolism regulation capacity. In-vivo and in-vitro experiments prove that the gelated cells can significantly reduce blood lipid levels of atherosclerosis model animals, reduce aortic plaque area, and have good biological safety, thereby providing a new strategy and candidate drug for prevention and treatment of atherosclerosis, and having a good clinical application prospect.

The present invention discloses a set of diagnostic markers for aortic dissection and their applications. The markers include the genes MMP8, ALOX15, HP, FXYD2, SIGLEC8, and CCL2. The genes MMP8, ALOX15, HP, FXYD2, SIGLEC8, and CCL2 protected by the present invention can be used as biomarkers for AD and as indicators for assessing disease severity in AD patients, enabling efficient diagnosis of patients with aortic dissection.

The invention discloses an application of isoginkgetin or pharmaceutically acceptable salts thereof in preparation of SETD1A small molecule activity inhibitors and drugs for preventing and / or treating vascular injury diseases. According to the invention, the small-molecule inhibitor isoginkgetin taking SETD1A as an intervention target and the pharmaceutical application of the small-molecule inhibitor isoginkgetin are confirmed for the first time. Isoginkgetin can inhibit the modification function of SETD1A under the condition of not influencing the expression quantity of SETD1A, and can improve PDGF-induced phenotype transformation of human aortic smooth muscle cells; intimal neogenesis caused by vascular injury can be obviously relieved; the myocardial fibrosis can be improved.

The invention discloses gamma-aminobutyric acid and application of a pharmaceutical composition thereof in preparation of drugs for preventing or treating aortic dissection and aortic aneurysm. The invention provides the application of gamma-aminobutyric acid in preparation of drugs for preventing or treating aortic dissection for the first time, and verifies the application of gamma-aminobutyric acid in preparation of drugs for preventing and / or treating aortic dissection and aortic aneurysm by inhibiting endothelial cell dysfunction; the application of gamma-aminobutyric acid in preparation of drugs for preventing and / or treating aortic dissection and aortic aneurysm by inhibiting expression of c-FOS to reduce vascular endothelial cell injury is verified; the application of gamma-aminobutyric acid in preparation of drugs for preventing and / or treating aortic dissection and aortic aneurysm by reducing infiltration of macrophages is verified.

The invention relates to a computer-implemented method (100) for generating patient- specific templates of aortic leaflets comprising: - generating (104) a 3D model from digital images (102) of a native aortic root and aortic leaflets of a patient; - generating (106) 3D neo-leaflets models by simulating in silico aortic leaflet neocuspidization from the 3D model with parameters of developable coaptation surfaces and of non-developable load-bearing surfaces of aortic leaflets; - realizing (108) a 2D surface flattening of the coaptation surfaces of the 3D neo- leaflets models; - realizing (110) a 2D surface flattening of the load-bearing surfaces of the 3D neo- leaflets models; - merging (112) a 2D coaptation surface with a 2D load-bearing surface for each neo- leaflet model; and - generating (114) a patient-specific template for each aortic leaflet.

A method of providing support in an aortic region. The method includes wrapping a landing band around an outside of a portion of an aortic vessel in a vicinity of a sinotubular junction (STJ) to form a wrapped portion of the aortic vessel. The method further includes securing the landing band to form a secured landing band. The method also includes endovascularly delivering a stent graft in a radially constricted configuration into the aortic vessel. The method also includes deploying the stent graft to a radially expanded configuration such that the stent graft contacts the wrapped portion of the aortic vessel. The method also includes connecting the stent graft in the radially expanded configuration to the secured landing band.

The invention provides a biomarker composition and an application thereof. The biomarker composition comprises the following proteins: MMP12, UMOD, HbA1c, FGF9, NINJ1 and PRSS8. According to the biomarker composition provided by the invention, through combination of matrix metalloproteinase 12, uromodulin, glycosylated hemoglobin, FGF9, NINJ1 and serine protease 8, the problem of lack of a specific marker for aortic wall structure damage in the prior art is solved.

The invention discloses an application of an NRF2 signal channel activator in preparation of a medicine for preventing or treating hyperuricemia-related atherosclerosis, relates to the technical field of medicines, and particularly relates to an application of the NRF2 signal channel activator in preparation of a medicine for preventing or treating hyperuricemia-related atherosclerosis. The NRF2 signal channel activator is used for up-regulating NRF2 protein expression or enhancing transcriptional activity of the NRF2 protein; the NRF2 signal channel activator is used for up-regulating expression of a downstream target gene SLC7A11 and / or GPX4 so as to inhibit ferroptosis of hyperuricemia aortic macrophages; the level of glutathione (GSH) in serum is increased; the malondialdehyde (MDA) and / or iron ion (Fe < 2 + >) level in serum is reduced; nRF2 signal channel activation and macrophage ferroptosis inhibition are associated, and the NRF2 signal channel is applied to prevention and treatment medicines for hyperuricemia-related atherosclerosis, so that development of specific treatment medicines for patients suffering from hyperuricemia-related atherosclerosis is facilitated.

The invention discloses a method for detecting aortic dissection through peripheral blood BRD4 based on flow cytometry and application. The invention belongs to the technical field of biology, and particularly relates to a method for detecting aortic dissection through peripheral blood BRD4 based on flow cytometry and application. The method for detecting the content or expression level of the bromodomain-containing protein 4 in the sample to be detected comprises the following steps: 1) treating the sample to be detected to obtain mononuclear cells; the method comprises the following steps of (1) determining a mononuclear cell, (2) determining a fluorescein coupling antibody composition of a detection index according to a flow cytometry color matching scheme, (3) uniformly mixing the mononuclear cell in the step (1) and the fluorescein coupling antibody in the step (2), incubating in a dark place and dyeing, (4) loading and testing a sample by a spectrum flow cytometry, and (5) analyzing a data result, and the detection indexes in the step (2) are CD45, CD11B, CD66B, CD14, CC16 and BRD4.

The invention provides application of a detection reagent of an exosome or extracellular envelope derived biomarker in preparation of a composition or a kit for evaluating, diagnosing, screening and / or monitoring an aortic dissection of a subject. The exosome or extracellular envelope derived biomarker provided by the invention is applied to detection, and has high sensitivity and specificity. Compared with the traditional method, the reaction time is greatly shortened. Good clinical application prospects are realized.

The application discloses an aortic dissection identification method and related device, which can be applied to the technical field of deep learning, extracts local features of a to-be-identified heart ultrasound image, and the local features are aortic region features. The local features of the to-be-identified heart ultrasound image are input into a trained dissection classification model to obtain a classification result output by the dissection classification model, and the classification result is used to indicate whether an aortic dissection exists in the to-be-identified heart ultrasound image. A support set at least includes local features of a first type of heart ultrasound image, the first type of heart ultrasound image is a heart ultrasound image with an aortic dissection, and a classification label is a classification result artificially annotated to indicate whether an aortic dissection exists. The classification accuracy of the dissection classification model trained based on the feature similarity between the local features of the to-be-identified heart ultrasound image and the local features of the heart ultrasound image with the aortic dissection is high, and thus, the classification result accuracy is improved.

The invention discloses pharmaceutical application of RNA helicase DHX8, including application of the RNA helicase DHX8 in aortic dissection diagnosis, treatment and drug development. It is found for the first time that DHX8 is significantly down-regulated in aortic dissection patients, animal models and vascular endothelial cells, and overexpression of DHX8 can effectively up-regulate endothelial cell tight connection related genes and repair the endothelial barrier function. The Si DHX8 is used for transfecting human umbilical vein endothelial cells (HUVECs), and the DHX8 is knocked down, so that the tight connection gene OCLN is obviously reduced; when the OE DHX8 plasmid is used for transfecting the HUVECs and overexpressing the DHX8, the tight connection genes OCLN, JAM-A, ZO-1 and VE-cadherin are found to be obviously up-regulated. The DHX8 is used as a new target for aortic dissection diagnosis and treatment, and a detection reagent, a gene therapy vector and an agonist drug of the DHX8 have important clinical transformation values.

The invention relates to the field of diagnostic reagents, in particular to a dual-marker dual-mode quantitative detection probe, a preparation method thereof and application of the dual-marker dual-mode quantitative detection probe in aortic dissection diagnosis. Compared with a traditional probe, the dual-marker dual-mode quantitative detection probe has the advantages that fluorescence-magnetic resonance relaxation dual-mode signals do not interfere with one another, and synchronous quantification can be achieved. The application advantage in aortic dissection diagnosis is that the detection rate of the aortic dissection can be remarkably improved by simultaneous detection of the double markers, and misdiagnosis generated during detection of a single marker is avoided. Meanwhile, double indexes can be obtained through single detection, repeated sampling is avoided, and the detection time is effectively shortened.

The invention discloses an aortic dissection recognition model construction method, an aortic dissection recognition method, aortic dissection recognition equipment and a related device, and relates to the technical field of deep learning, and the model construction method comprises the steps: carrying out the dual-mode matching of a CT plain-scan image and a CTA image of the same period marked with an aortic dissection lesion feature part, and carrying out the recognition of the aortic dissection lesion feature part; determining the same fault with a lesion feature part between the two, and positioning and marking the corresponding lesion feature part on the CT plain-scan image of the same fault; and forming a CT plain-scan image data set by the plurality of CT plain-scan images marked with the diseased regions and the plurality of CT plain-scan images of the normal aortic patients, training a deep learning model by adopting the CT plain-scan image data set, and taking the trained deep learning model as an aortic dissection recognition model. And the aortic dissection recognition model is used for performing aortic dissection recognition on the to-be-recognized CT plain-scan image. The aortic dissection recognition accuracy can be maintained, and meanwhile, the recognition cost can be reduced.

The present application provides an aortic dissection segmentation method and system based on deep reinforcement learning, the method comprising: acquiring aortic dissection slice data, and performing feature extraction using a feature extraction network; splicing each aortic dissection slice data with its corresponding aortic dissection slice feature to obtain a multi-dimensional image data set; constructing an aortic dissection positioning task using a deep reinforcement learning agent and the multi-dimensional image data set; setting an expansion strategy of a field of view window, an action of a positioning window and a reward function, training the aortic dissection positioning task using a DQN algorithm; and finally positioning the aortic dissection of the aortic dissection slice data to be segmented using the optimal deep reinforcement learning agent, and segmenting the aortic dissection according to the positioning result; the present application can reduce the proportion of redundant information of the slice, effectively improve the accuracy of the segmentation result, and improve the accuracy and stability of the positioning window.

The application discloses a method for separating and culturing primary vascular smooth muscle cells from human abdominal aortic wall, and relates to the technical field of human cell culture. The method comprises the following steps: obtaining a collagenase A solution; adding the collagenase A solution to a treated human abdominal aortic aneurysm wall tissue sample and then cutting the sample; transferring the cut human abdominal aortic aneurysm wall tissue sample to a 37-degree cell culture box for culture; centrifuging a cell suspension obtained after termination of digestion; discarding supernatant, resuspending cell precipitate, and repeating centrifugation for three times; resuspending the cell precipitate again, uniformly transferring the cell precipitate to a T25 culture bottle after blowing, and placing the cell precipitate in a 37-degree cell culture box for culture; when a wave peak and wave trough state appears, the cell precipitate is digested and subcultured by using 0.25% trypsin, and then the cell precipitate is transferred to a new T25 culture bottle; and the cell precipitate is subcultured normally to the P3 generation and then stored in liquid nitrogen, so that the cell damage is prevented and the activity and proliferation capacity of the cell are maintained.

The application belongs to the technical field of biological medicine, and particularly relates to application of SFRP1 in treatment of aortic aging drugs. SFRP1 can induce generation of vascular organoids, significantly antagonize vascular smooth muscle cell senescence induced by angiotensin II and bleomycin, enhance vascular smooth muscle cell activity, improve cell oxidative stress ability, reduce cell beta-galactosidase activity, reduce intracellular calcium deposition level, reduce phenotype conversion and reduce extracellular matrix remodeling. Taxifolin can significantly improve accelerated aortic aging in VSMC-specific Sfrp1 knockout mice. SFRP1 and / or Taxifolin both play an anti-aortic aging role, prevent and / or treat aortic aging related diseases. SFRP1 can be used as a screening target to screen drugs against cell senescence damage.

The invention relates to the technical field of medical image segmentation, and discloses a TBAD lesion area automatic segmentation method and device based on an improved UNet network, and the method comprises the following steps: taking a UNet network structure as a basis, introducing a three-dimensional feature encoder on a jump connection channel, introducing a shift window self-attention module on a bottleneck layer, and obtaining a CISUNet network; training a CISUNet network, and taking the trained CISUNet network as an automatic segmentation model of the TBAD lesion area; and inputting the CTA image into the TBAD lesion area automatic segmentation model to obtain a TBAD lesion area segmentation result. The context sensing bottleneck layer captures global context information by using a shift window self-attention mechanism; the three-dimensional feature encoder receives the CTA image and the multi-level feature maps output by the encoder part, performs feature extraction by using multi-scale cavity convolution, and outputs a plurality of feature maps; a three-dimensional channel attention mechanism is introduced into the decoder part, and accurate segmentation of the aortic dissection complex structure is achieved.

The invention relates to the field of medical biological materials, and discloses a degradable aortic dissection repair patch and a preparation method thereof.The preparation method comprises the following steps that a fiber sheet of a double-face structure is prepared in an electrostatic spinning mode, and a polycaprolactone solution is pumped from an injector; carrying out natural air drying treatment on the electrostatic spinning sheet, and cutting the electrostatic spinning sheet into a circular patch unit through a die cutting process; the cut patch is placed on the surface of a prefabricated nickel-titanium alloy conveyor with the orientation face facing downwards; an adhesive is used on the surface of the disordered fiber surface of the patch in a uniform or point coating manner; carrying out sterilization treatment on the patch conveying system; and appearance integrity inspection and patch and support connection strength detection are carried out on the manufactured patch system. The electrostatic spinning technology is controlled to be in a standing rotating deposition mode in a staged mode, a seamless integrated structure of an inner side disordered multidirectional pore layer and an outer side annular directional stress layer is formed on the same fiber sheet, shearing can be effectively buffered through a multidirectional pore network, and the effect that stress distribution is more uniform is achieved.

The invention discloses a B-type aortic dissection whole course intelligent management system based on multi-modal fusion and biomechanics. The system comprises a multi-modal image preprocessing and reconstruction module, a rapid biomechanical simulation and operation planning module, an intraoperative 2D-3D image fusion navigation module and a postoperative outcome prediction and closed loop follow-up visit module. According to the invention, a functional quantitative evaluation system is created for the first time, and the limitation of traditional morphological diagnosis is broken through; the calculation efficiency and clinical real-time performance are extremely high, and the problem that traditional simulation cannot fall to the ground is solved; the stent-derived complications are accurately predicted, and the operation strategy is optimized; an eye perspective function is endowed in the operation, and the operation difficulty and radiation injury are reduced; a whole-course closed-loop learning system is constructed, and continuous evolution of diagnosis and treatment precision is realized; and high-fidelity automatic modeling solves the problem of complex lesion segmentation.

The invention belongs to the technical field of biological medicine and molecular biology, and particularly relates to application of LGR5 in diagnosis and treatment of vascular calcification. Experiments prove that the key effect of the LGR5 in aortic smooth muscle calcification is found for the first time, it is indicated that the LGR5 is a new target spot for regulating and controlling vascular calcification, meanwhile, vascular calcification can be accurately inhibited through knockdown / knockout of the specific Lgr5 gene of vascular smooth muscle, and meanwhile, vascular calcification can be accurately inhibited through knockout / knockout of the specific Lgr5 gene of the vascular smooth muscle. According to the application disclosed by the invention, the mechanism that the Lgr5 regulates and controls the osteogenic differentiation of the vascular smooth muscle cells through the Wnt / beta-catenin signal channel is preliminarily clarified, and a clear action target and a theoretical basis are provided for drug research and development; the invention provides a new strategy for treatment of diseases such as atherosclerosis and the like, and has a wide clinical application prospect.

The invention discloses an intelligent aortic dissection diagnosis method and system based on sublimation AI and physical perception deep learning, and belongs to the technical field of intelligent medical instruments. The method comprises the following steps: a mercuration AI processor controls a DDS module to generate frequency sweep excitation and synchronously collects a response signal of a magnetoelastic sensor; performing adaptive denoising reconstruction on the signal by using a VMD algorithm to obtain an effective signal with a high signal-to-noise ratio; performing spectral analysis on the signal to extract physical characteristics, and performing double-parameter temperature compensation by combining temperature and amplitude; the calibrated features and signals are input into a pre-trained PG-ANet for double-flow fusion reasoning, and a D-dimer concentration predicted value and a risk level are output; and evaluating and predicting the confidence coefficient based on the magnetoelastic quality-frequency linear physical model, and if the confidence coefficient is insufficient, dynamically adjusting the excitation parameter and remeasuring until a high-credibility diagnosis result is output. According to the invention, the problems of difficult signal extraction, large temperature interference, poor generalization of the AI model and physical incredibility of the prediction result under the condition of few samples in the blood high-viscosity environment are solved.

The utility model discloses an aortic dissection model display device which comprises an installation base, a limiting block and a positioning block, a transparent protection cover is arranged at the outer side end of the installation base in a clamped mode, a supporting seat is rotatably installed in the middle end of the installation base, and an installation vertical plate is fixedly installed in the middle of the upper end of the supporting seat; an arc-shaped baffle plate positioned on the outer side of the model is correspondingly arranged at the outer side end of the limiting block; and positioning blocks are fixedly mounted on the outer sides of the ends, close to the mounting vertical plates, of the limiting blocks. The utility model belongs to the technical field of aortic dissection model display, and aims to solve the problems that in the prior art, display is not smooth and coherent enough, and aortic dissection models with different lengths are inconvenient to fix. The technical effects that the aortic dissection model can be effectively driven to rotate smoothly and stably, and meanwhile, the aortic dissection model rotating device is suitable for aortic dissection models of different lengths and sizes.

The invention discloses a CT aorta robustness three-dimensional segmentation method and device based on deep learning, and relates to the technical field of medical image processing, and the method comprises the steps: extracting an aorta slice sequence frame by frame; carrying out linear interpolation and thresholding on the extracted probability graph; setting the initial segmentation mask of the current slice as an initialization prompt of a medical video segmentation model with a memory mechanism; for the initial slice image, calling an initialized memory state function through a medical video segmentation model, generating an initial segmentation result of the initial slice, and encoding the initial segmentation result into an initial memory state; calling a propagation tracking state function to automatically predict an aorta original mask of a current slice through a medical video segmentation model by using memory states established in previous several frames of slices and a current slice image, and obtaining a prediction mask; and carrying out weighted fusion and three-dimensional reconstruction on the prediction mask and the preliminary segmentation mask. According to the method, full-automatic and robust three-dimensional segmentation of the CT aorta is realized.

The invention discloses an electromagnetic direct-driven gas circuit combination device for assisting in counterpulsation of a balloon in an aorta, and relates to the technical field of medical apparatuses and instruments. The device comprises a shell, and a balloon driving device, a helium injection device and a main control circuit are arranged in the shell. The helium filling device is responsible for filling helium into the balloon driving device. And the balloon driving device is responsible for filling helium into the balloon and extracting the helium, so that the balloon is switched between a bulging state and a contraction state. The gas circuit detectors are attached to the two devices, are arranged at key gas circuit nodes to monitor gas circuit states, convert the gas circuit states into electric signals and then transmit the electric signals to the main control circuit so as to judge the operation state of the whole device. The permanent magnet piston has the advantages of being low in power consumption, simple in structure, small in overall size and convenient to carry and use, the driving structure drives the permanent magnet piston through a magnetic field generated by electrifying a conductive coil, the driving mode is direct, speed is high, electric energy conversion efficiency is high, and power consumption is small.