12 results about "Aortic dissection" patented technology

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 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 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.

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.

This invention belongs to, but is not limited to, the field of medical device technology, and particularly relates to a clamping forceps for clamping different tissues in complex aortic dissections. It comprises a handle assembly, a transmission assembly, and a jaw assembly, with each component connected in a modular, detachable manner. The handle assembly serves as the power input and control terminal, with its internal control module and power output fixedly connected to one end of the transmission assembly to transmit power and clamping force adjustment signals. The other end of the transmission assembly is detachably and fixedly connected to the jaw assembly, accurately transmitting the power and adjustment signals input from the handle assembly to each clamping unit of the jaw assembly. The jaw assembly serves as the clamping execution terminal, with each clamping unit correspondingly connected to a micro-drive mechanism of the transmission assembly, forming an integrated connection architecture of handle control, transmission, and jaw execution.

A system for treating aortic dissection including an aortic dissection implant comprising an expandable anchoring structure and an elongate tubular structure. The expandable anchoring structure can be configured to apply radial force to the sinuses of the aortic root and / or the sinotubular junction when expanded. The elongate tubular structure can comprise an expandable support frame and one or more layers. The expandable support frame can be configured to extend from the descending aorta to the ascending aorta and curve along with a curvature of the aortic arch when expanded within the aorta. The one or more layers can comprise a first porous layer comprising an atraumatic outer surface positioned over the expandable support frame and a second non-porous layer positioned over a portion of the first porous layer. The second non-porous layer may be configured to be positioned on opposite sides of the aortic dissection and to be inflatable via blood flow to seal against the dissection.

The application belongs to the technical field of medicine research, and particularly relates to a hydrogen sulfide donor compound, a medicine composition containing the hydrogen sulfide donor compound, and a synthesis method and application thereof. The hydrogen sulfide donor compound has a structure as shown in general formula (I). The hydrogen sulfide donor compound can release H2S responsively under physiological conditions, especially in the presence of endogenous mercaptan, and can realize bifunctional release by introducing a drug active fragment. Experimental results show that the H2S release behavior of the compound is stable and has excellent biocompatibility. In animal experiments, the compound can reduce the incidence of aortic dissection and improve Alzheimer's disease and Parkinson's disease, has potential application value for prevention and treatment of cardiovascular diseases and neurodegenerative diseases, and also has expansion potential for other diseases related to oxidative stress.

An explainable artificial intelligence system for early prediction of missed severe diagnoses in intensive care unit patients is provided. The system comprises a data processing module configured to receive and process electronic health record data including patient demographics, vital signs, laboratory results, and diagnostic codes. A machine learning module with ensemble, deep learning, and large language models analyzes processed data to predict likelihood of severe diagnoses including acute myocardial infarction, acute pulmonary embolism, bacterial pneumonia, aortic dissection, meningitis, spinal abscess, bacterial endocarditis, and arterial thromboembolism. An explainability module generates feature importance rankings and provides interpretable explanations for predictions.