46 results about "Aortic dissection" patented technology

The application discloses an aortic dissection risk reverse evaluation method and system, relates to the technical field of cardiovascular disease risk evaluation, and discloses an aortic dissection risk reverse evaluation method and system, which calculates a contradiction coefficient of blood vessel stability and behavior load by integrating medical image data and daily behavior dynamic data, generates early warning information based on the difference, effectively solves the technical problems that a traditional evaluation method cannot dynamically capture mechanical changes of a blood vessel wall and identify potential risk conflicts, can dynamically monitor the contradictory relationship between the geometric stability of a blood vessel and daily behavior load in real time, generates high-risk early warning information in time, avoids the early warning loss caused by too long an examination interval in the traditional evaluation method, and improves the accuracy and timeliness of risk evaluation.

The invention belongs to the field of biological medicine, and particularly relates to application of a compound in preparation of a medicine for preventing and treating aortic dissection, the compound is nobiletin, the chemical name of the compound is 3 ', 4', 5, 6, 7, 8-hexamethoxyflavone, and the CAS number is 478-01-3. The invention also correspondingly provides a pharmaceutical composition. The death rate of aortic dissection is high, treatment depends on surgical treatment, and the death rate is extremely high. At present, an effective medicine for preventing and treating the aortic dissection is lacked clinically, the nobiletin is screened and determined to be used as the medicine for preventing and treating the aortic dissection, the molecular mechanism of the nobiletin is clear that the nobiletin targets ferroptosis related protein SLC7A11 to improve ferroptosis of vascular smooth muscle cells, namely VSMC, and a new target spot is provided for treatment of the aortic dissection.

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 technical field of molecular biology and medicine, and particularly discloses application of WWP1 in preparation of a medicine for preventing and / or treating aortic dissection, and relates to application of WWP1 in prevention and treatment of aortic dissection. Molecular biology experiment detection of the expression level of the WWP1 in aortic dissection aortic tissue and the expression level of smooth muscle cell contraction and secretion phenotype marker genes proves that the expression level of the WWP1 in an aortic dissection aortic tissue sample is obviously higher than that of a control aortic tissue; and overexpression of the WWP1 in an animal model significantly reduces the morbidity of the aortic dissection and improves the contraction phenotype of the aortic smooth muscle, i.e., the protectiveness of the WWP1 in the morbidity process of the aortic dissection is improved. Based on the research result, the WWP1 can be used as a drug target for screening, preventing and treating the aortic dissection.

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 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 invention belongs to but is not limited to the technical field of medical instruments, and particularly relates to aortic dissection blocking forceps capable of being adjusted in multiple degrees of freedom, comprising a multi-joint linkage adjusting module, which has a core of a forceps arm composed of at least three lockable rotary joints, realizes multi-dimensional posture adjustment of a forceps body, and adapts to different blood vessel trends; the forceps head self-adaptive rotating module is connected to the joint at the farthest end, 360-degree continuous rotation of the forceps head is achieved, and it is ensured that the clamping face of a jaw is perpendicular to the longitudinal axis of the blood vessel; the accurate control and positioning module is integrated with an angle fine adjustment knob and an ergonomic handle, and real-time and accurate posture fine adjustment and stable holding in an operation are achieved; and the safe locking and quick release module is linked with a joint locking mechanism and a handle quick release button to realize joint locking and unlocking and quick clamp loosening under emergency conditions.

The invention discloses a biomarker for aortic dissection detection and an application of the biomarker. The biomarker is one or more of MDK, NTN1, CCL21, LIPC, DNASE1L3, TFPI2, CTSG, HAMP, CXCL14, PLA2G2A, SCUBE1, GZMK, HP1BP3, SRP14 and TOP1. The biomarker is obtained by screening plasma of a patient with aortic dissection through plasma proteomics, and shows relatively high sensitivity and specificity. ELISA verification proves that the biomarker can be used as an early diagnostic biomarker of the aortic dissection, and can also be used as one of indexes for evaluating the disease severity of AD patients, so that a new direction is provided for clinical early diagnosis and long-term prognosis evaluation of the aortic dissection.

The embodiment of the invention provides an aortic dissection risk prediction method, and belongs to the technical field of medical care informatics, and the method specifically comprises the steps: obtaining the Fourier transform infrared spectrum, Raman spectrum and clinical data of a serum sample of a to-be-detected object; preprocessing the Fourier transform infrared spectrum and the Raman spectrum, and standardizing clinical data; respectively extracting multi-scale features of the infrared spectrum and the Raman spectrum through a multi-scale feature extraction module; inputting the infrared and Raman spectrum features of the same scale into a cross-modal fusion module to obtain enhanced cross-modal features; performing information interaction through a multi-scale interaction module to obtain unified feature representation; and outputting a disease risk prediction result or a prognosis risk prediction result by using a classification and discrimination module based on the unified feature representation and the clinical data. According to the scheme, the stability and accuracy of disease risk prediction and prognosis risk prediction are improved.

The invention discloses an application of a gene for coding LRP1-beta chain oligopeptide as a target in screening / preparing a medicine for treating aortic dissection, an application of a reagent for inducing overexpression of the LRP1-beta chain oligopeptide in preparing the medicine for treating the aortic dissection, and an application of the LRP1-beta chain oligopeptide as a biomarker in preparing an aortic dissection diagnostic reagent. Experiments prove for the first time that the LRP1-beta chain oligopeptide can inhibit phenotypic transformation of vascular smooth muscle cells and inflammatory infiltration of macrophages by down-regulating expression of OPN, alleviate inflammatory response and relieve or inhibit occurrence and development of aortic dissection, provides a new direction and thought for treatment of aortic dissection, and has broad application prospects in treatment of aortic dissection. The compound is expected to be applied to research and development of new drugs for treating aortic dissection

The invention discloses a biomarker related to aortic dissection, a kit, a system and application thereof, and relates to the technical field of biological medicine. The biological marker related to the aortic dissection comprises a second biological marker; the second biomarker is used for predicting the clinical death risk of aortic dissection patients, and the second biomarker comprises SYTL1 protein, B2M protein, LYVE1 protein, TTR protein, PRSS2 protein, CSTF1 protein and H2BC5 protein. The plasma-based protein biomarker capable of predicting the mortality risk of the aortic dissection patient is successfully screened out, the pathogenesis of the disease can be explored easily, and the method has important significance on efficient, accurate and low-cost diagnosis of the aortic dissection patient.

The application belongs to the technical field of medical devices, and discloses a multi-parameter linkage measuring and shearing equipment for artificial blood vessel suitable for aortic dissection repair, which adopts a modular integrated connection mode, and is composed of a rack, a guiding and positioning module, an integrated measuring and shearing module, a driving module, a control module and a power supply module. The modules are connected through detachable mechanical connection, electrical connection and signal connection to realize linkage and cooperation. The guiding and positioning module is fixedly connected to the front end of the rack, the integrated measuring and shearing module is slidably connected to the rack through a sliding guide mechanism and is accurately positioned with the guiding and positioning module, the driving module is embedded in the rack and is power-connected to the integrated measuring and shearing module through a transmission assembly, the control module is installed in the middle of the rack through a fixed support and is electrically connected to the integrated measuring and shearing module, the driving module and the power supply module, and the power supply module is detachably connected to the rear end of the rack to provide stable power supply for the whole equipment.

The utility model belongs to the technical field of medical teaching appliances, and particularly relates to an aortic dissection inflation model for teaching, which comprises a base, a transparent plate is arranged on the base, and a simulation inner membrane is arranged on one side of the transparent plate. A first air bag, a second air bag and a third air bag which are sequentially connected and mutually spaced are arranged on the surface of the simulation inner film, the simulation inner film, the first air bag, the second air bag and the third air bag are all of a half-section structure, and an air supply device is arranged in the base; the first air bag, the second air bag and the third air bag can be selectively inflated through the air supply device arranged in the base, so that various lesion types of the aortic dissection are simulated. The method enables the teaching process to be more vivid, and helps students to form deeper memory. Meanwhile, the simulated inner membrane and each air bag adopt a half-section structure design and are matched with a transparent plate, so that students can intuitively observe the internal structure of the inner membrane, and the teaching activity is more vivid and vivid.

The application discloses application of securinine in preparation of a drug for preventing and / or treating aortic dissection, and securinine can significantly reduce the incidence of aortic dissection caused by BAPN, and securinine can significantly reduce the expression levels of XAF1, Cleved-caspase3 and Cleved-caspase7 proteins, and can effectively inhibit the apoptosis of mouse aortic endothelial cells.

The present application belongs to the technical field of medical informatization and medical image artificial intelligence, and relates to a multi-modal strong reminding closed-loop intelligent early warning system and method for chest pain triple syndrome. The present application solves the problem that the existing system cannot identify the disposal conflict when aortic dissection and acute coronary syndrome coexist. The scheme includes: through the two-stage analysis of the CT or CTA image of the chest pain patient by the AI identification module of the multi-task learning architecture, the cardiovascular region of interest features are extracted and the risk probability and feature map of three types of diseases are output; the risk fusion module calculates the weighted risk value, identifies the conflict risk of high-risk events and lesion spatial overlap; the early warning pop-up window module generates a horizontal three-column layout pop-up window, asynchronously loads typical image slices and highlights the conflict prompt; the strong reminding module forces the pop-up window to the top and drives the physical warning light to high-frequency flicker and the buzzer to urgent alarm; the closed-loop confirmation module receives the unique confirmation instruction, updates the event state and generates the audit log containing the high-precision timestamp.

The invention relates to an aortic dissection embolism system based on a shape memory polymer, and the system comprises an embolism part which is made of shape memory polymer foam and has a compressed loading state and a preset state after expansion, and the embolism part is provided with a through central cavity and an edge cavity surrounding the periphery of the central cavity; an interventional catheter for accommodating the embolic member in a loaded state to perform interventional delivery; the delivery shaft is arranged in the intervention catheter in a sliding mode and used for carrying the embolism part to be released from the far end side of the intervention catheter to the aortic dissection, the embolism part in the loading state is integrally wound around the periphery of the delivery shaft, or the delivery shaft is arranged in the central cavity in a penetrating mode. Through the structural improvement of the embolism parts and the control of the expansion starting time, the released and expanded embolism parts are arranged in order, the space filling rate is high, and the surgical treatment effect can be further improved.

The present invention belongs to the field of biological detection, and specifically relates to a protein antigen combination for aortic dissection detection and the use thereof. The specific technical solution comprises an antigen composition comprising an FBN2 protein fragment and an SPEG protein, wherein the FBN2 protein fragment has an amino acid sequence as shown in SEQ ID NO: 1, and the SPEG protein has an amino acid sequence as shown in SEQ ID NO: 5. Provided are a protein antigen and a specific combination of antigens, which, by means of detecting autoantibodies corresponding thereto, can be used for the detection or diagnosis of aortic dissection, are particularly suitable for risk assessment and prediction prior to the onset of aortic dissection, and can be further prepared into a related reagent or kit on the basis of requirements.

The invention discloses an application of valerian triester in preparation of products for preventing and treating aortic dissection, which can reduce the occurrence rate of aortic events, relieve the reduction of survival rate caused by aortic dissection, inhibit aortic dilatation caused by aortic dissection, reduce the number of elastic fiber fractures caused by aortic dissection and improve the survival rate of aortic dissection. The hematoma and the false cavity between aortic walls caused by the aortic dissection are improved, and the structural damage of the aortic walls caused by the aortic dissection is improved. According to the technical scheme provided by the invention, a brand new compound option is provided for the drug treatment of the aortic dissection.

The invention discloses application of ellagic acid in preparation of a medicine for preventing and / or relieving aortic dissection, and particularly discusses the protective effect and mechanism of ellagic acid on angiotensin II induced mouse aortic dissection. The ellagic acid has a protective effect on AngII-induced mouse AD, and the action mechanism of the ellagic acid may be related to inhibition of phosphorylation of MAPK JNK / p38, reduction of phenotypic transformation of vascular smooth muscle cells, oxidative stress and apoptosis.

The invention discloses an aortic dissection AI auxiliary diagnosis method based on multi-modal information fusion, and the method comprises the steps: building a dual-branch feature extraction network, obtaining a multi-scale fusion feature finally outputted by an image branch according to an enhanced image and an image feature extraction branch, and carrying out the multi-scale fusion feature extraction. According to the clinical index set aligned to the image acquisition time and the clinical index feature extraction branches, obtaining a fused global clinical feature sequence; obtaining a final multi-modal feature after fusion according to a multi-scale fusion feature finally output by the image branch, the fused global clinical feature sequence and a cross-modal fusion module so as to obtain a probability of a predicted disease type based on clinical data of a user; after the loss function is adopted to train the double-branch feature extraction network, the probability of the predicted disease type can be obtained based on the clinical data of the to-be-diagnosed user, and a clinician is assisted to judge the disease type of the to-be-diagnosed user.

The application discloses a method for detecting aortic dissection based on peripheral blood BRD4 by using flow cytometry and application thereof. The application belongs to the technical field of biology and particularly relates to a method for detecting aortic dissection based on peripheral blood BRD4 by using flow cytometry and application thereof. The method for detecting the content or expression level of bromodomain-containing protein 4 in a to-be-detected sample established by the application comprises the following steps: 1) processing a to-be-detected sample to obtain single nucleus cells; 2) determining a fluorescein-coupled antibody composition of a detection index according to a flow cytometry color matching scheme; 3) mixing the single nucleus cells in step 1) and the fluorescein-coupled antibody in step 2) uniformly, and performing staining by incubation in the dark; 4) performing sample testing on a spectrum flow cytometer; and 5) performing data result analysis. The detection index in step 2) is CD45, CD11B, CD66B, CD14, CC16 and BRD4.

The application discloses a training method of an aortic dissection stress field prediction model and related products. First, a plurality of CT images of aortic dissection patients are obtained, and cross sections of the maximum diameter of the dissection are identified to obtain a plurality of target cross sections. Based on the cross sections, initial samples and corresponding geometric mechanics information thereof are constructed, and augmented samples and geometric mechanics information thereof are generated. Then, the initial samples and the augmented samples are determined as training samples, and a three-value label set is constructed for each training sample. Subsequently, the initial stress field of the training sample is physically boundary cleaned according to the three-value label set to obtain a target stress field. Finally, the training sample and a regular coordinate set thereof are taken as input, the target stress field is taken as a label, and a Fourier operator network is trained to generate a prediction model. The application can construct a stress field prediction model with strong generalization ability and high stability under small sample conditions, and realize rapid and accurate mechanical evaluation of individualized anatomical structures of different patients.

The application provides an aortic dissection postoperative cardiopulmonary function rehabilitation device, and belongs to the technical field of cardiopulmonary rehabilitation. The aortic dissection postoperative cardiopulmonary function rehabilitation device comprises a fixing structure and a clamping structure, the fixing structure comprises a first gasket, a second gasket, a U-shaped frame, a fixing assembly, a rectangular shell, an adjusting assembly, an arc-shaped clamping plate and two connecting belts, the first gasket is rotationally connected with the second gasket, the U-shaped frame is slidingly connected with the first gasket, the fixing assembly is connected with the U-shaped frame, and the rectangular shell is connected with the fixing assembly. In the application, the aortic dissection postoperative cardiopulmonary function rehabilitation device can conveniently avoid foot deviation during rehabilitation training, improve the training effect, and conveniently adjust the position of the U-shaped frame according to the height of a user, thereby improving the practicability of the device.

The present application relates to the technical field of postoperative risk grading identification, in particular to a system for grading the adverse risk of distal remodeling after aortic dissection surgery. The system first determines a thrombus permeation resistance coefficient according to the gray level difference of CT images of the patient at different times, and extracts the thrombus isolation thickness; based on the thrombus permeation resistance coefficient, solves the anisotropic potential function equation to determine the cumulative leakage cost; performs structure tensor analysis on the gradient in the cumulative loss field formed by the cumulative leakage cost to determine the jet channel consistency factor; combines the cumulative leakage cost, the jet channel consistency factor and the thrombus isolation thickness to calculate the fluid impact load borne by the outer wall of the blood vessel; and based on the fluid impact load and the jet channel consistency factor, determines the risk level of different connected domains in the CT image. The present application improves the accuracy of jet impact risk identification.

The invention relates to the technical field of image data processing, in particular to an intelligent aortic dissection rupture risk identification method and system based on semantic segmentation, and the method comprises the steps: collecting CT images of a same patient at different time points; acquiring a plurality of connected domains of an aorta region in the CT image; obtaining the cavity wall morphological irregularity of the cavity wall connected domain; determining a noise cavity region based on cavity wall morphological irregularity; obtaining a non-fracture prediction coefficient by using the true and false connected domains of the noise cavity region; determining a risk trend index according to the non-fracture prediction coefficient; according to the risk trend index, determining a noise cavity area with a fracture risk; based on the risk trend index of the noise cavity region with the fracture risk and the cavity wall morphological irregularity, obtaining a risk prediction coefficient of the noise cavity region with the fracture risk; and obtaining a risk level evaluation result according to the risk prediction coefficient. The risk identification accuracy can be improved.

This invention provides a method and system for predicting the risk of aortic remodeling after aortic dissection, comprising the following steps: receiving CTA images of the patient's chest and abdomen at multiple time points, such as preoperative and short or mid-operative postoperatively, and obtaining aortic segmentation results based on the CTA images; obtaining the displacement field of each voxel point between the two time points based on the aortic segmentation results, and obtaining vascular deformation mapping results based on the displacement field; extracting multi-dimensional features from the three-dimensional aortic segmentation model and the vascular deformation mapping results respectively; and predicting the risk of adverse aortic remodeling after surgery based on the multi-dimensional features. The beneficial effects of this invention are: by comprehensively utilizing multi-dimensional, dynamic, and static features, the prediction model constructed by this invention theoretically has higher discrimination and calibration than existing single-index models. Therefore, this invention can detect early, local abnormal deformations that cannot be detected by traditional diameter measurement, significantly advancing the risk identification time point.

The invention discloses a valved endovascular graft for Endo-Bentall, which relates to the technical field of medical instruments and comprises an ascending aorta graft and two coronary artery covered stents. The ascending main section is a straight tube type covered stent, the far end of the ascending main section is anchored to the ascending aorta, and the near end of the ascending main section is provided with an embedded branch opening in the sinus tube section; the sinus canal section is in a concave shape and is provided with a metal bare stent and an embedded branch opening for bridging the coronary artery; a biological valve is sewn in the sinus valve section, and the far end of the sinus valve section is anchored to the left ventricular outflow tract. The anchoring area sequentially comprises a left ventricular outflow tract, a sinus tube junction and an ascending aorta. The coronary artery branch covered stent is conical and small-caliber, the near end is connected with the embedded branch, and the far end extends into the coronary artery. The graft can be used for repairing dissection lesions and reconstructing coronary artery and aortic valves in the whole cavity.

The invention belongs to the technical field of medical teaching models, and provides an aortic dissection model display device, which comprises a support table mechanism, an aortic blood vessel model is arranged in the support table mechanism, a dissection cavity is formed in the outer wall of the aortic blood vessel model, two groups of through holes are formed in the side wall of the aortic blood vessel model from top to bottom, and the two through holes are communicated with the dissection cavity; the liquid supply assembly comprises a liquid storage tank and a water pump, the liquid outlet end of the water pump is communicated with the liquid inlet of the aorta blood vessel model, and the liquid outlet end of the water pump is communicated with the liquid outlet of the aorta blood vessel model; and the intimal rupture simulation assembly comprises a cover plate detachably connected to the through hole, a via hole is formed in the cover plate, an opening control mechanism is arranged between the via hole and the cover plate, and the opening control mechanism is used for communicating the aorta blood vessel model with the interlayer cavity. The device can dynamically and intuitively simulate the process that the blood flow breaks through the inner membrane crevasse to enter the interlayer cavity, and is beneficial to understanding of learners.

The invention belongs to the technical field of medicine research, and particularly relates to a sequence-controllable macromolecular hydrogen sulfide donor, a pharmaceutical composition, a synthetic method and application. The high-molecular hydrogen sulfide donor has a structure as shown in a general formula (I). The high-molecular hydrogen sulfide donor compound can responsively and slowly release HS in a long-acting manner under physiological conditions, especially in the presence of endogenous mercaptan, and bifunctional release can be realized by introducing a drug active fragment. Experimental results show that the compound is stable in HS release behavior and has good biocompatibility, the occurrence rate of aortic dissection can be remarkably reduced, and meanwhile the compound has the expansion potential for other diseases related to oxidative stress; .