3233 results about "Rat heart" patented technology

In one embodiment, a medical system includes a catheter configured to be inserted into a chamber of a heart of a living subject, and including multiple electrodes configured to capture electrical activity from electrical activation signals propagating in tissue of the chamber, a display, and processing circuitry configured to automatically select bipolar signals to be captured into an electro-anatomical map from respective electrode pairs of the multiple electrodes responsively to an alignment of the respective electrode pairs with a direction of propagation of the electrical activation signals, and render the electro-anatomical map to the display.

The present disclosure provides a method and system for analyzing unipolar electrophysiological (EP) signals acquired by a multi-electrode catheter placed in a ventricle of a patient's heart. The method includes receiving unipolar EP signals, extracting unipolar far-field signals from the unipolar EP signals, and analyzing the extracted unipolar far-field signals to estimate the distribution of scar regions across a thickness of wall tissue of the ventricle. Using the estimated distribution, a unipolar far-field EP map showing the scar regions is generated. The method further includes displaying the unipolar far-field EP map including the scar regions to a user. The system comprises a display device and a processor configured to perform the steps of the method.

Systems and Methods are disclosed for detecting acute coronary syndrome (ACS) events, arrythmias, heart rate abnormalities, medication problems such as non-compliance or ineffective amount or type of medication, and demand / supply related cardiac ischemia. The system may have both implanted and external components that communicate with a Physicians's programmer, and smart-devices for monitoring and alerting to detected medically relevant events or states. At least one processor provides event detection using statistical threshold criteria calculated upon at least a portion of a patient's data / distributions and set for a patient or based upon what a doctor determines as abnormal for a patient. Cardiovascular condition is tracked using histogram, trend, and summary information related to heart rate and / or cardiac features such as S-T segment measures of heartbeats. Heartbeats with elevated rates, and below a “high” range, provide medically relevant detections including medication non-compliance. Novel methods of power management and patient monitoring are disclosed.

The invention relates to the technical field of image segmentation, in particular to an automatic segmentation method and system for an echocardiogram of the department of cardiology, and the method comprises the following steps: based on image data of the echocardiogram, extracting gray level distribution, edge feature and texture feature information, analyzing gray level change amplitude, screening gray level change abnormal regions, and recognizing connectivity features. According to the method, the segmentation accuracy is effectively improved by extracting image gray, edge and texture features and identifying abnormal regions, noise and artifact interference are reduced by optimizing low connectivity regions, and the segmentation accuracy is improved. A problem area is analyzed and positioned in combination with multi-frame gray level change, a segmentation result is adjusted, the processing stability and consistency are enhanced, meanwhile, an optimized alarm node is output based on a frequency trend, more accurate and stable heart image analysis is supported, and the clinical application practicability is improved.

The invention provides a four-dimensional cardiac function imaging method and device based on a biological magnetic signal. The method comprises the following steps: acquiring a magnetocardiogram signal of a to-be-detected object and dynamic structure information of a target trunk part in a full cardiac cycle; wherein the target trunk part at least comprises double lungs, a trunk, a heart cavity of the trunk and a pericardium structure, and the dynamic structure information comprises a contour structure and a multi-frame dynamic image; performing spatial registration on the dynamic structure information and the sensor for acquiring the magnetocardiogram signal to obtain coordinates of the sensor in a coordinate system of the dynamic structure information; according to the dynamic structure information, the coordinate of the sensor and the magnetocardiogram signal, calculating and reconstructing cardiac electrical excitation activity to obtain a calculation and reconstruction result; and converting the calculation reconstruction result into a four-dimensional visual image. According to the method, heart magnetic imaging and heart movement are combined, on the basis of obtained dynamic structure information and heart magnetic signals, the characteristics of biological magnetic signals are fully utilized, and the signal processing technology is integrated through space registration, so that accurate reconstruction of four-dimensional representation of the heart and visual display of functional activities are realized; therefore, the obtained four-dimensional visual image can completely represent the dynamic electrophysiological activities of the whole heart (including epicardium, endocardium and intrawall tissues) in a cardiac cycle, and a technical scheme with different concepts is provided for non-invasive imaging of cardiac electrical excitation activities.

A prosthetic heart valves including an annular frame and one or more detachable outer skirts and methods associated therewith are disclosed. The frame includes a plurality of interconnected struts and one or more outer skirts releasably attached to an exterior surface of the frame. In some examples, an outer skirt is attached to the frame via at least one retaining suture formed by a plurality of stitches looped around a pull suture. Removal of the pull suture from the suture line enables the outer skirt and frame to separate as the stitches are pulled through openings in the outer skirt and remain attached to the frame. Removability of the outer skirt can facilitate improvements in implant and explant procedures of the prosthetic valves, such as, for example, valve-in-valve procedures.

The invention discloses a thoracoscope minimally invasive cardiac surgery navigation system based on multi-modal image fusion, and the system comprises the steps: constructing a 5D heart digital twin containing an anatomical structure, a soft tissue boundary, metabolic activity and electrophysiological information through fusing preoperative CT, MRI, PET and intraoperative ultrasonic images; real-time dynamic registration is realized by using an electrocardio gating driven biomechanical model; superposing the multi-color coding navigation information to the visual field of the thoracoscope through a wavelength selection type spectroscope; a dynamic risk scoring model is constructed based on the distance, the speed and the tissue vulnerability, and three-level grading intervention is triggered; a miniature force feedback actuator is integrated to realize closed-loop control; and pre-operation virtual drilling and post-operation federal learning optimization are supported. The system remarkably improves the surgical precision and safety, and is suitable for high-difficulty heart minimally invasive surgeries such as mitral valve repair and atrial fibrillation ablation.

The invention provides a benzofuranone compound as well as a pharmaceutical composition and application thereof, and relates to the technical field of medicines. The benzofuranone compound is a compound as shown in a formula I, a stereoisomer thereof, a tautomer thereof, a crystalline hydrate thereof, a solvate thereof, a prodrug thereof or a pharmaceutically acceptable salt thereof. The benzofuranone compound and the pharmaceutical composition and the pharmaceutical preparation prepared from the benzofuranone compound can prevent or treat organ injury diseases, and have good treatment effects in kidney injury, liver injury, lung injury, brain injury and heart injury.

The invention provides a left heart data analysis method and system based on image segmentation, and relates to the technical field of medical image processing. Comprising the following steps: acquiring cardiac ultrasound image data and preprocessing; performing image segmentation on the preprocessed image data to obtain a segmentation result including a left ventricle, a left ventricular wall and a left atrium; searching a boundary line of the left ventricle and the left atrium, selecting two boundary points corresponding to the minimum and maximum abscissas in the boundary line as left and right mitral valve ring points respectively, and establishing a long axis based on the mitral valve ring midpoint and the cardiac apex point; modeling the ventricle into a structure formed by superposing a plurality of discs along the long axis direction, and obtaining the diameter of the corresponding disc; based on the obtained diameters of the corresponding discs, the left ventricular volumes in the diastolic period and the systolic period are calculated respectively, and the left ventricular ejection fraction is calculated. According to the method, image segmentation and geometric modeling are fused to achieve accurate calculation of the cardiac ejection fraction, meanwhile, the accuracy of cardiac structure image segmentation is improved, and an interpretable ejection fraction estimation process is achieved.

The invention relates to a myocardial resection area determination method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a heart scanning image, and determining a heart three-dimensional model according to the heart scanning image; determining a heart short-axis section and a heart long-axis section according to the heart three-dimensional model; the clock direction angle of the scalpel is determined on the short axis section of the heart; based on the clock direction angle, the excision depth of the scalpel is determined on the long-axis section of the heart; and performing myocardial resection on the heart three-dimensional model according to the clock direction angle and the resection depth through a scalpel model, determining an updated three-dimensional model after myocardial resection, and marking a resection area on the updated three-dimensional model. According to the scheme, accurate preoperative planning guidance and comprehensive heart structure information presentation are provided for the myocardial rotary cutting operation, and therefore the accuracy and safety of the myocardial rotary cutting operation are improved.

The invention discloses a postoperative sub-delirium syndrome risk prediction system for a cardiac surgery patient, and relates to the technical field of medical treatment, and the system comprises a clinical data collection module which is used for collecting multi-dimensional clinical data of the cardiac surgery patient in a perioperative period under extracorporeal circulation, the data comprises patient baseline information, preoperative neurocognitive function evaluation indexes, intraoperative physiological parameters and postoperative early-stage vital signs; and the risk identification module is used for utilizing a single-factor statistical analysis mechanism. According to the postoperative sub-delirium syndrome risk prediction system for the cardiac surgery patient, accurate prediction of the sub-delirium syndrome risk is achieved by collecting multi-dimensional clinical data of the patient in the perioperative period, such as baseline information, preoperative neurocognitive function, intraoperative physiological parameters and postoperative early-stage vital signs; the independent risk factors are scientifically screened and quantified by using single factor analysis and a multivariate Logistic regression model, and the problem of incomplete data dimensions in traditional evaluation is effectively solved.

A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

Disclosed are valve replacement devices, systems, and methods. Valve replacement devices may comprise one- or two-piece systems comprising a receiver body (also called an adapter) and a valve assembly with replacement leaflets attached to and located within the receiver body. In two-piece systems, the valve assembly may be removable from the receiver body such that both can be delivered together or separately, and the receiver body may remain implanted while the valve assembly may be removed and replaced. Also described are devices, systems, and methods related to delivering, removing, and replacing a valve replacement. Such delivery methods may include transseptal insertion of a new minimum leaflet structure, and securement of the valve replacement using several securement type (e.g., supra-annular, sub-annular, radial, leaflet securement, etc.). Also described is a braided helical design that mimics the heart's natural movement, and a flange structure for assisting the functioning of the valve replacement.

A method for predicting a cardiac index (CI) for a patient includes receiving a set of a measurements from the patient that characterizes an anatomical condition, a physical condition, a physiological condition, or a combination thereof. The method also includes receiving a non-invasive physiological measurement from the patient. The method also includes performing feature extraction on the non-invasive physiological measurement to produce one or more extracted features. The method also includes combining the set of measurements and the extracted features to produce a dataframe. The method also includes predicting the CI for the patient. The CI is predicted using a prediction model based upon the dataframe.

The invention discloses a macrophage-targeting inhalable nano material, a preparation method thereof and application of the inhalable nano material in treatment of sepsis myocarditis, and belongs to the technical field of medicines. The nano-material is a nano-liposome, the nano-liposome comprises a mannose modified nano-liposome microsphere, and the mannose modified nano-liposome microsphere comprises a liposome skeleton shell layer, a drug and a targeting layer; the liposome skeleton shell layer comprises soybean lecithin and cholesterol; the medicine comprises quercetin and TPPU (Thermoplastic Polyurethane); and the targeting layer is formed by connecting mannose modified DSPE-PEG2000 to the outer surface of the liposome skeleton shell layer. The nano material can accurately target macrophages at a cardiac inflammation part, has a multi-target-point synergistic effect, is more convenient and faster in administration, remarkably improves the safety and comprehensively improves the treatment effect.

The invention provides a method for constructing a CT-MRI (Computed Tomography-Magnetic Resonance Imaging) personalized three-dimensional heart model based on multi-modal imaging, which comprises the following steps of: firstly, carrying out myocardial and infarction region segmentation on a CMR-LGE image, and carrying out myocardial and intramyocardial adipose tissue segmentation on a CE-CT image to generate a corresponding Label image; then, a high-precision three-dimensional volume mesh model of the corresponding ventricle is constructed based on the segmentation results of the two types of images; and then, mapping the corresponding Label image with the tissue type to a corresponding finite element model according to the coordinates of the grid, and obtaining a corresponding personalized ventricular model with the tissue type. An interpolation method based on a general ventricular coordinate system is adopted, data of an MR ventricular model with infarct tissue attributes is transferred to a CT ventricular model, and therefore a mixed CT-MRI ventricular model is constructed. And finally, storing the constructed CT-MRI ventricular model data with the integrated tissue attributes as a standard geometric and topological file format.

The invention relates to the technical field of active peptides, in particular to a myocardial active peptide capable of relieving heart failure and protecting heart and a preparation method thereof. The method takes pig hearts as raw materials, and sequentially comprises the following steps: pretreating the pig hearts, adding water, and homogenizing; adding alkaline protease to carry out first constant-temperature enzymolysis; adding neutral protease and flavourzyme to carry out second constant-temperature enzymolysis; then lipase is added for third-time constant-temperature enzymolysis, and enzyme deactivation and cooling are carried out; and finally, adding activated carbon into the enzymatic hydrolysate, filtering with diatomite, and spray-drying to obtain the myocardial active peptide. According to the method, the yield and the purity of the active peptide are remarkably improved through a synergistic process of three-step enzymolysis and activated carbon purification, the obtained product is rich in small molecule peptide with a definite heart protection function, and a new way is provided for high-value utilization of pig heart resources and development of functional products for preventing and treating heart failure.

The invention discloses a heart sound, electrocardio and echocardiogram multi-modal data phase synchronization method, which belongs to the technical field of medical image processing, and comprises the following steps: A1, obtaining an original echocardiogram video and independently recorded heart sound audio data information; a2, preprocessing the acquired data and performing sample automatic construction; a3, a double-path neural network architecture is constructed, electrocardiogram waveform extraction is carried out, and a digital electrocardiogram signal sequence is obtained; a4, periodic feature points of the heart sound and the electrocardio are recognized based on the digital electrocardio signals; and A5, aligning the asynchronous data based on linear phase resampling. According to the method, the video frames, the electric signals and the heart sound signals under different sampling rates are forcibly mapped into the unified phase coordinate system through a linear interpolation algorithm, absolute synchronization of the video frames, the electric signals and the heart sound signals in cardiac pulsation physiological logic is finally achieved, and the influence of individual heart rate differences on data alignment is eliminated.

The invention relates to a simulation-based target removal area determination method and device. The method comprises the following steps: acquiring a heart simulation model and corresponding blood flow field information; according to the left heart lumen model and the blood flow field information, determining a first target area in the ventricular septum model; stress calculation is carried out according to the ventricular septum model, and a second target area in the ventricular septum model is determined; determining an initial target area according to the first target area and the second target area; according to the ventricular septum model, determining the thickness range of the initial target area at the end of contraction; determining a target cutting thickness according to a preset basic thickness and a thickness range; according to the heart simulation model, the initial target area, the target resection thickness and the blood flow field information, a first target resection area is determined. By adopting the method, the cardiac muscle tissue area needing to be cut off can be accurately determined.

Systems and methods for fully automated anatomical analysis of an anatomical structure are provided to facilitate pre-operative planning. The computerized method may include obtaining a plurality of images, e.g., MSCT images, of patient-specific cardiovascular anatomy, and analyzing the MSCT images with a trained artificial intelligence module to identify one or more anatomical landmarks and to construct a virtual three-dimensional model of the anatomical structure. For example, the trained artificial intelligence module may execute segmentation, point detection, curve detection, or plane detection deep learning modules, independently or in combination, to identify the anatomical landmarks. The method further may include deriving anatomical measurements of the one or more identified anatomical landmarks, and displaying the virtual three-dimensional model alongside the anatomical measurements of the one or more identified anatomical landmarks.

The invention discloses a cardiac function rehabilitation state monitoring method for coronary heart disease postoperative population. The method comprises the following steps: constructing a third-order dynamic baseline adaptive to postoperative pathological evolution; carrying out stress-physiological coupling modeling on the basis of a double-AI (Artificial Intelligence) collaborative architecture; and carrying out trend early warning of equal-condition longitudinal pairing. The heart function rehabilitation state monitoring system comprises an electrocardiosignal preprocessing unit, the electrocardiosignal preprocessing unit is connected with a multi-dimensional electrocardiosignal feature extraction unit, and the multi-dimensional electrocardiosignal feature extraction unit is connected with a third-order individualized baseline management unit and a front stress recognition AI unit. And the third-order individualized baseline management unit and the front stress identification AI unit are respectively connected with the core correlation deduction AI unit. According to the method and system for monitoring the cardiac function rehabilitation state of the crowd after the coronary heart disease operation, dynamic baseline construction and the pathological evolution rule after the coronary heart disease operation are deeply bound, and the problem of high false alarm of a traditional fixed baseline in the early stage of the operation is thoroughly solved through triple-stage design and a dual calibration mechanism.

The invention discloses a heart CT continuous slice-oriented image sequence segmentation method and system, and relates to the technical field of medical image processing, and the method comprises the steps: carrying out the frame-by-frame feature extraction of an obtained heart CT continuous slice image sequence based on a CSWin Transform backbone network, and extracting a direction perception feature through a cross stripe window self-attention mechanism; splicing all single-frame features of the image sequence along a height dimension to construct a sequence feature map, inputting the sequence feature map to a sequence biaxial attention module, performing feature enhancement through a vertical direction branch, an original branch and a global branch, and integrating outputs of the three branches to obtain a final enhanced feature; and inputting the enhanced features into an enhanced segmentation head, and generating a heart region segmentation mask of the image sequence after progressive up-sampling, boundary perception enhancement and multi-scale feature fusion processing. According to the invention, accurate, efficient and consistent three-dimensional segmentation of the heart region of the image sequence can be realized.

A delivery device for percutaneously delivering a stented prosthetic heart includes a sheath, a handle, and adjustment device including a fine adjustment mechanism, and an outer stability shaft. The sheath defines a lumen and is configured to compressively constrain the stented prosthetic heart valve. The handle is coupled to the proximal portion of the sheath and includes an actuator mechanism coupled to a proximal portion of the sheath that is configured to selectively move the sheath relative to the housing to release the stented prosthetic heat valve. The adjustment device is coupled to the handle and includes an adjustment lumen through which the sheath and the handle slidably extend. The outer stability shaft is coupled to the adjustment device. The fine adjustment mechanism is configured to selectively move the handle and the sheath relative to the adjustment device and the outer stability shaft.

Provided are a measurement method and system and a related apparatus. The method is applied to a first electronic device and comprises: acquiring user information; acquiring first physiological data of a user in a resting state, the first physiological data comprising a first blood pressure value and a first heart rate; outputting a first prompt, the first prompt being used for prompting the user to start exercising; measuring second physiological data after the user finishes exercising, the second physiological data comprising a second blood pressure value and a second heart rate; acquiring an exercise load of the user; determining, on the basis of the user information, the first physiological data, the second physiological data, and the exercise load, a first evaluation result, the first evaluation result comprising cardiac reserve function evaluation; and outputting the first evaluation result. In this way, not only can the blood pressure status of a user be evaluated, but also the cardiac reserve function of the user can be judged, such that the user knows his / her own health status in time.

The invention discloses an electrophysiological signal fusion method and device, relates to the technical field of biomedicine, and mainly aims to solve the problem of low cardiac imaging evaluation accuracy caused by poor effectiveness of existing electrophysiological signal fusion. The method includes the steps that electrophysiological signals obtained after cardiac organs are collected and subjected to active magnetic field compensation and passive magnetic field compensation are obtained, and active magnetic field compensation signals of active magnetic field compensation are completed by controlling a main control magnetic field source based on a deep neural network model; a passive magnetic field compensation signal of the passive magnetic field compensation is completed based on residual magnetic field data modeling; screening effective signals from the electrophysiological signals, and performing inversion reconstruction on the effective signals to obtain current density distribution; cross-modal fusion is conducted on the electrophysiological signals, the current density distribution and the electrocardiosignals through a deep learning model after model training is completed, a signal fusion result is obtained, and the deep learning model is trained based on Maxwell constraints.

A clip may be configured to close the portion of the heart, to reduce blood flow therethrough as well as passage of clots or other undesired materials. The clip may be configured to close the left atrial appendage (LAA). The closure of the LAA may reduce the possibility of stroke or other maladies stemming from fluid flow with the LAA. Delivery systems may comprise expansion apparatuses for a left atrial appendage clip. The expansion apparatuses may include retention mechanisms for retaining the clip.

A method is provided that includes inserting an inflow cannula of a left ventricular assist device (LVAD) of a LVAD system into a left chamber of a heart of a patient transeptally via a right atrium and a superior vena cava (SVC). An outflow cannula of the LVAD is coupled to a left subclavian artery or a left axillary artery. Other embodiments are also described.

The present application relates to a motion image processing method and apparatus, and a cardiac image reconstruction processing method. The motion image processing method comprises: respectively acquiring a multi-temporal motion template image of a motion-controlled model in a target motion mode and an actual motion image of a motion-uncontrolled entity; and on the basis of a registration parameter obtained by means of the multi-temporal motion template image and the actual motion image, performing augmentation on the actual motion image, so as to obtain a multi-temporal motion image of the motion-uncontrolled entity in the target motion mode. The cardiac image reconstruction processing method comprises: acquiring target scanning data of a target heart; on the basis of a preset mode, determining a plurality of reconstruction center moments within an exposure duration; on the basis of the plurality of reconstruction center moments, reconstructing the target scanning data, so as to obtain cardiac images at the plurality of reconstruction center moments; and on the basis of the cardiac images at the plurality of reconstruction center moments, determining a cardiac image at a target reconstruction center moment.

This disclosure relates to electro-anatomical mappings of cardiac tissue at different depths using a multi-electrode catheter. A multi-electrode catheter within a heart of a patient has a first plurality of electrodes on a first side and a second plurality of electrodes on a second side, wherein the first side is proximate to cardiac tissue at a first location and the second side is facing away from the cardiac tissue. Electrical activity is received from at least one electrode on the first side and the at least one electrode on the second side, and a signal analysis is performed thereon based at least in part on distances between electrodes on different sides of the multi-electrode catheter. The process is repeated for further locations of cardiac tissue in the heart, and an electro-anatomical map of the heart depicting electrical activity or scar tissue is generated based on the signal analysis.