10 results about "Plaque rupture" patented technology

The invention relates to a coronary artery plaque rupture risk assessment method based on a non-local physical information neural network, and belongs to the field of artificial intelligence, and the method comprises the following steps: S1, introducing a near-field dynamics theory, reconstructing a mechanical constitutive equation of plaque rupture, and deducing a crack propagation criterion; s2, constructing a non-local physical information neural network, taking geometric structure information and material attributes of the coronary artery plaque as input, and taking a displacement field and a stress field of the plaque as output; taking the plaque mechanics basic equation as a physical constraint condition, and adding a loss function; s3, constructing a data set; s4, training the physical information neural network by using the training set, and adjusting network parameters by using a stochastic gradient descent optimization algorithm to minimize a loss function; optimizing and testing the model; and S5, inputting a coronary artery medical image number to be evaluated into the trained non-local physical information neural network, and outputting a rupture risk evaluation result of the coronary artery plaque.

The invention discloses a system and a method for dynamically identifying vulnerable plaques of an intravascular ultrasonic image. According to the system, plaque evolution information of continuous IVUS image frames is extracted by constructing a feature extraction module based on a space-time convolutional neural network; combining limited OCT annotation data through a transfer learning model; the blood flow wall shear force and the inflammatory marker IL-6 are fused in a plaque rupture risk prediction matrix, and a new mathematical calculation model is provided to predict the plaque risk. The system supports real-time analysis in an interventional operation and automatically marks a high-risk plaque area, and the vulnerable plaque detection sensitivity can reach 94% or above. The hardware architecture comprises an image acquisition unit, a deep learning calculation module and a labeling interaction module; the software architecture comprises a plaque recognition engine, a shear force calculation module, a biological data fusion interface and the like. The system has the advantages of being easy and convenient to operate, high in real-time performance, high in accuracy and the like, and an efficient intraoperative plaque risk assessment tool is provided for interventional therapy.

The invention provides a carotid plaque strain force data acquisition system and method, and the system comprises a region division module which is used for storing a target movie of a carotid plaque, selecting a template frame from the target movie to draw a plaque envelope region of the carotid plaque, and dividing the plaque envelope region into three regions in the x direction; the storage module is used for performing point taking and division on the whole plaque envelope area, determining all recording points of each section of area and data structures and structure information corresponding to the recording points, and storing all the recording points, the data structures corresponding to the recording points and the structure information in a memory to obtain recording point data; the movie playback module is used for calling the image data to perform movie playback, performing patch tracking and determining strain values of all recording points; and the strain force data recording module is used for outputting the strain force value to a file for recording. The plaque rupture risk can be predicted more accurately, and corresponding prevention measures can be taken in advance.

The application discloses application of CCL3-AS1 in regulating stability of carotid artery plaque, overexpression of CCL3-AS1 induces inflammatory activity of macrophages and secretion of MMP9, promotes plaque rupture and thrombosis; on the contrary, knockdown of CCL3-AS1 inhibits inflammatory activity of macrophages and secretion of MMP9, reduces plaque rupture and thrombosis; in addition, the application also discloses that CCL3-AS1 enhances MMP9 mRNA stability by combining with hnRNP-K, thereby increasing MMP9 expression and secretion and degrading fibrous cap collagen. The application discloses important role of CCL3-AS1 in stability of carotid artery plaque and a molecular mechanism, provides a new diagnostic marker and a treatment target, not only provides a new direction for research on atherosclerosis related diseases, but also provides a new tool and a means for clinical diagnosis and treatment.

The invention discloses an application of CCL3-AS1 in regulating and controlling the stability of carotid plaques, which is characterized in that the CCL3-AS1 is overexpressed to induce the inflammatory activity of macrophages and MMP9 secretion and promote plaque rupture and thrombosis; on the contrary, the CCL3-AS1 is knocked down to inhibit the inflammatory activity of macrophages and MMP9 secretion, and plaque rupture and thrombosis are reduced; in addition, the invention also discloses that CCL3-AS1 is combined with hnRNP-K to enhance the mRNA stability of MMP9, so that the expression and secretion of MMP9 are increased, and the fibrocap collagen is degraded. The invention discloses an important function of CCL3-AS1 in carotid plaque stability and a molecular mechanism of CCL3-AS1, provides a novel diagnostic marker and a novel therapeutic target, not only provides a novel direction for research of atherosclerosis related diseases, but also provides a novel tool and means for clinical diagnosis and treatment.

The application provides a CEUS image analysis method based on key frame segmentation and time sequence tracking fusion, a CEUS video risk grading overall framework based on key frame screening, segmentation and time sequence fusion, integrates video preprocessing, key frame extraction, plaque segmentation, time sequence feature fusion and multi-frame risk decision and the like links, forms a complete risk grading process, and can be used for automatic grading of carotid plaque rupture risk. The application has the advantages of significantly improving efficiency, enhancing time sequence sensitivity, stabilizing grading results, being strong in clinical interpretability and being good in universality, and can be popularized to CEUS image analysis of organs such as liver and kidney.

The application discloses a kind of numerical simulation systems of stent intervention smooth particle dynamics based on intravascular image;Including: vascular attribute collection module, stent establishment module, particle and assembly module, stent release setting module and release stent mechanics simulation module, particle and assembly module reads the three-dimensional vascular model of vascular attribute collection module, the three-dimensional stent model of stent establishment module and the specified lesion position of input, and constitutes the complete model to be particle;Particle is generated after particle by the particleization of stent model through the pre-processing of smooth particle method, and the complete model after particle;Stent release setting module sets given geometric constraint to stent;Release stent mechanics simulation module simulates using smooth particle method according to the boundary condition of force.The present application combines patient image data, realizes the stress distribution when stent expansion is predicted before operation, improves compliance and support force balance;Evaluate the risk of plaque rupture, avoid vascular injury.

The invention discloses a numerical simulation system of stent intervention smoothed particle dynamics based on intravascular images. Comprising a blood vessel attribute collection module, a pressing and holding stent establishment module, a pelletization and assembly module, a stent release setting module and a release stent mechanical simulation module, and the pelletization and assembly module reads a three-dimensional blood vessel model of the blood vessel attribute collection module, a three-dimensional stent model of the pressing and holding stent establishment module and an input specified lesion position; forming a complete model to be granulated; performing pretreatment through a smoothed particle method, and performing granulation on the stent model to generate a complete model after granulation; the stent release setting module sets a given geometric constraint to the stent; and the release bracket mechanical simulation module performs simulation by using a smoothed particle method according to the boundary condition of the force. In combination with image data of a patient, stress distribution during stent expansion is predicted before an operation, and flexibility and supporting force balance are improved; the plaque rupture risk is evaluated, and vascular injury is avoided.