42 results about "Left ventricular size" patented technology

The application discloses a heart valve device and relates to the technical field of artificial heart valves, which comprises an outer valve frame and a valve leaflet assembly connected to the inside of the outer valve frame, and the outer valve frame is a ring-shaped grid frame; the outer valve frame comprises an inflow side grid frame and an outflow side grid frame arranged in sequence from an inflow end to an outflow end, and the inflow side grid frame and the outflow side grid frame form an annular recess for clamping a native valve ring on the outer periphery of the outer valve frame; the outflow side grid frame comprises a plurality of groups of grid support units connected in sequence along the circumferential direction and enclosed into a ring, and the grid support unit comprises an outer convex grid support and an inner concave grid support, and the outer surface of the inner concave grid support is arranged in a concave manner relative to the outer surface of the outer convex grid support. In this way, the anterior leaflet of the original mitral valve can be attached to the inner concave grid support, the extrusion of the outer valve frame on the anterior leaflet is reduced, the anterior leaflet is prevented from being extruded to the left ventricular outflow tract by the outer valve frame, and the outflow area of the left ventricular outflow tract is prevented from being reduced to cause obstruction.

A cardiopulmonary management system includes a multi-sensor device and a controller. The multi-sensor device includes an elongated body having a first end and a second end, a first electrode disposed at the first end of the body, a second electrode disposed at the second end of the body, an electrical circuitry disposed near a middle of the body, and a sound sensor. The multi-sensor device is configured to be disposed on a skin of a subject and to measure cardiopulmonary parameters from the subject. The controller is configured to derive a score of sound change, heart rate change, thoracic impedance change, respiratory rate change, QRS wavelength change, QT interval change, electromechanical activation time change, and left ventricular systolic time change based on the measured cardiopulmonary parameters. The controller is further configured to control an operation of the system when the derived score is greater than a threshold.

The application discloses a method for obtaining a left ventricular papillary muscle target section and an ultrasonic evaluation method thereof, which comprises obtaining a standard basic section conforming to a guideline, and then determining a corresponding target section and a two-dimensional ultrasonic probe adjustment mode according to a front-lateral or rear-medial papillary muscle type to be imaged and a current standard basic section. Through taking the probe pose when the standard basic section is obtained as a benchmark, the two-dimensional ultrasonic probe is rotated by a specified angle or is directionally tilted under the premise of maintaining an acoustic window unchanged, so that an image of the target section clearly displaying a specific papillary muscle long axis or short axis shape is obtained; the problem of incomplete papillary muscle imaging and distorted shape caused by the fixed section of the conventional two-dimensional ultrasonic is solved, the target section can be repeatedly and stably obtained, and the integrity and accuracy of the papillary muscle ultrasonic imaging are significantly improved.

Methods and systems are provided for a rate adaptive bi-ventricular fusion pacing. The methods and systems deliver a first pulse at a left ventricular (LV) lead and a second pulse at a right ventricular (RV) lead based on a paced atrio-ventricular (AV) delay. The first pulse timed to be delivered concurrently with an intrinsic ventricular conduction. The methods and systems further repeat the delivery of the first pulse and the second pulse for a predetermined number of cycles. Additionally, the methods and systems measure an intrinsic AV conduction interval, and adjust the paced AV delay based on the intrinsic AV conduction interval and a negative hysteresis delta.

This invention belongs to the field of novel pharmaceutical applications, providing the application of Zhongwu Ning in the preparation of drugs for treating ischemic heart disease. In rat models of myocardial ischemia, Zhongwu Ning significantly increased the left ventricular ejection fraction and left ventricular fractional shortening rate; it also significantly improved the rate of increase and decrease of intracardiac pressure in rats with myocardial ischemia, indicating that Zhongwu Ning can effectively restore left ventricular systolic function and effectively repair myocardial damage caused by myocardial ischemia-reperfusion. Therefore, based on the experimental research results of this application, Zhongwu Ning has certain application prospects in the treatment of ischemic heart disease.

The application belongs to the field of heart disease treatment and natural medicine compound, and provides application of bufalin or a pharmaceutically acceptable salt thereof in preparation of a medicine for treating reperfusion arrhythmia. Experiments in vitro and in vivo prove that bufalin inhibits L-type calcium channels in a concentration-dependent manner, reduces extracellular calcium ion inflow, and further reduces the incidence of ventricular arrhythmia, arrhythmia, reduces ventricular conduction time, increases left ventricular conduction velocity, and reduces ventricular conduction dispersion; and provides a new drug selection for the treatment of reperfusion arrhythmia.

The present application relates to the technical field of image fusion, and discloses a heart failure follow-up data visualization processing method based on multi-modal image fusion, comprising the following steps: constructing a left ventricular fiber direction field and extracting fusion scalar data along the fiber path, establishing an isochronous scalar complex quantification model for describing the change pattern of activation time in the fiber direction, and taking the model as a continuous control variable to participate in subsequent filtering, reconstruction and visualization coding processes. The method completes the structured arrangement of the scalar data along the integral path of the fiber, so that the fusion data is more consistent with the propagation law of the myocardial tissue when outputting the polar coordinate graph and the three-dimensional ventricular coloring graph, and can visually inhibit and prompt the local non-continuous fluctuation.

A kind of Mamba-based lightweight left ventricular echocardiogram segmentation method and system, it is related to medical image analysis technical field, the present application is to solve the problems of insufficient segmentation accuracy, high computational complexity and large parameter quantity of existing medical image segmentation method proposed.The technical points are: to solve the challenge brought by the limitation of computing resources in real medical environment, a U-shaped lightweight segmentation method is constructed based on state space model Mamba, the original image is encoded using image feature encoding module, and residual visual Mamba module is constructed to scan and aggregate multi-angle features in multiple directions of image, adaptive feature enhancement module is also constructed to process echocardiogram data with size and shape differences between individuals, feature aggregation bridge module is used to integrate multi-party features and transfer high-dimensional layer features to low-dimensional layer layer by layer, mask generation module is constructed to output the segmentation result map of the current layer, and segmentation map output module is used to output the segmentation result processed by the whole model.The present application belongs to the field of medical image analysis.

This disclosure relates to an MLPSC-mediated method for treating congenital heart disease. Such methods may be particularly suitable for treating subjects with hypoplastic left ventricular syndrome.

This application provides an ultrasound cardiac dynamic monitoring system and method, relating to the field of ultrasound cardiac function dynamic monitoring technology. The system includes: a patch-type ultrasound probe, a hydrogel patch, a wearable hardware module, and a cardiac function analysis module. The cardiac function analysis module is configured to: receive the ultrasound image; determine a target sampling line in the ultrasound image based on a reinforcement learning model; control the wearable hardware module to acquire M-mode images along the target sampling line; input the M-mode images into a deep learning model to output the key point positions of the left ventricular septum and the left ventricular posterior wall at end-diastole and end-systole based on the deep learning model; calculate the left ventricular ejection fraction (LVEF) based on the LVEF and the key point positions; the LVEF represents the dynamic monitoring and detection results of cardiac function. This system can improve the effectiveness and accuracy of dynamic cardiac monitoring.

Embodiments of the present disclosure provide a left ventricular ejection fraction prediction method, device, equipment, medium and product. The method comprises: acquiring a heart ultrasound sequence of a heart part; inputting the heart ultrasound sequence into a target processing model trained in advance to output a left ventricular graph sequence which has been marked with a left ventricle; determining a plurality of effective image pairs according to area change rates of a plurality of left ventricular segmentation images in the left ventricular graph sequence, and determining left ventricular end-diastolic volumes and left ventricular end-systolic volumes corresponding to each effective image pair; and determining a left ventricular ejection fraction according to the left ventricular end-diastolic volumes and the left ventricular end-systolic volumes associated with the plurality of effective image pairs. The technical solution of the embodiments of the present disclosure processes the heart ultrasound sequence based on the target processing model to determine the left ventricular ejection fraction, which can weaken the influence of factors such as poor single-frame quality, respiratory jitter and arrhythmia, thereby achieving the effect of improving the accuracy of the left ventricular ejection fraction.

The present application relates to the technical field of biology, and discloses a method for rapidly evaluating pneumonia, especially COVID-19, based on artificial intelligence, which comprises the following steps: 1) obtaining lung region ultrasound images and circulatory volume ultrasound images of a subject, wherein the circulatory volume ultrasound images comprise left ventricular outflow tract ultrasound images, left ventricular long-axis section ultrasound images and inferior vena cava long-axis section ultrasound images; 2) inputting the lung region ultrasound images and the circulatory volume ultrasound images of the subject into a trained deep convolutional neural network model, wherein the trained deep convolutional neural network model comprises a trained lung ultrasound image scoring model and a trained circulatory volume ultrasound image scoring model, so as to obtain the evaluation result of pneumonia of the subject. The present application also discloses a trained deep convolutional neural network model suitable for pneumonia, especially COVID-19, a construction method of the trained deep convolutional neural network model, and a remote operation ultrasound robot comprising the trained deep convolutional neural network model.

This application proposes a left ventricular motion estimation method based on shape attention cascades for CMR cine sequences. This method consists of a base module and a sequence module. The base module uses a shape flow layer to extract boundary features, improving estimation accuracy at the left ventricular boundary. The sequence module uses a motion attention layer to ensure temporal coherence of motion estimation through bidirectional encoding of motion features. Furthermore, this application proposes novel data augmentation methods and loss functions, enhancing the accuracy of left ventricular motion estimation through comprehensive improvements to the training method and model structure. Experimental results show that the proposed method outperforms existing methods in both geometric and clinical metrics. This application improves the accuracy of left ventricular motion estimation, contributing to research on motion estimation and the clinical application of automated cardiac function assessment.

Systems and related methods for remotely managing care of a patient having an implanted left ventricular assist device are provided. A system for managing care of a patient having an implanted left ventricular assist device (LVAD) and an implanted pulmonary artery pressure (PAP) sensor includes a patient management server and a clinician portal. The patient management server is configured to receive PAP data and LVAD data for the patient. The PAP data is indicative of a PAP of the patient as measured via the PAP sensor implanted in the patient. The LVAD data is indicative of a measured operating parameter of the LVAD implanted in the patient. The clinician portal is configured to transmit an alert to a clinician in response to at least one of the PAP data and the LVAD data indicating a change in a hemodynamic condition of the patient.

Methods and systems are disclosed for creating and using a neural network model to estimate a cardiac parameter of a patient, and using the estimated parameter in providing blood pump support to improve patient cardiac performance and heart health. Particular adaptations include adjusting blood pump parameters and determining whether and how to increase or decrease support, or wean the patient from the blood pump altogether. The model is created based on neural network processing of data from a first patient set and includes measured hemodynamic and pump parameters compared to a cardiac parameter measured in situ, for example the left ventricular volume measured by millar (in animals) or inca (in human) catheter. After development of a model based on the first set of patients, the model is applied to a patient in a second set to estimate the cardiac parameter without use of an additional catheter or direct measurement.

A mechanism for performing a non-invasive estimate of left ventricular compliance. A temporal variation of left ventricular volume and a temporal variation of left ventricular pressure are determined by processing ultrasound data of a subject. These two temporal variations are then processed to estimate left ventricular compliance.

This application proposes a method and apparatus for controlling the rotation speed of a ventricular assist device (VAD). The method includes: acquiring a first left ventricular pressure and a first right ventricular pressure, wherein the first left ventricular pressure is the left ventricular pressure of the target user at a first moment when the left ventricular assist device is running at a first left rotation speed, and the first right ventricular pressure is the right ventricular pressure of the target user at a first right rotation speed when the right ventricular assist device is running at a first right rotation speed; adjusting the first left rotation speed and / or the first right rotation speed according to the first left ventricular pressure and the first right ventricular pressure to maintain a balance between the fluid output of the left and right ventricles. This application determines whether the fluid output of the user's left and right ventricles is balanced by real-time detection of ventricular pressure, and then adjusts the rotation speed of the left ventricular assist device and / or the right ventricular assist device to regulate the fluid output of the left or right ventricle when there is an imbalance, thereby ensuring a balance between the systemic and pulmonary circulation flow of the user and preventing aspiration and regurgitation problems in the left or right ventricle.

The utility model relates to the technical field of medical instruments, in particular to a ventricular septal defect treatment instrument. The ventricular septal defect treatment instrument comprises a patch, a conveying sheath tube, a push rod and a limiting piece, the patch is arranged in the conveying sheath tube after being compressed, and is positioned at the first end of the conveying sheath tube; the limiting piece is arranged at the second end of the conveying sheath tube, and a through hole allowing the push rod to penetrate through is formed in the limiting piece; the push rod is used for pushing the patch out of the conveying sheath tube. According to the technical scheme, the patch is compressed in the conveying sheath tube, the position of the ventricular septal defect is detected through the head of the conveying sheath tube, the patch can conveniently pass through a small ventricular defect, then the push rod is operated to release the patch, the released patch can be fixed to the left ventricular surface of the ventricular septal through the suture line or the fixing claw, and therefore repairing of the ventricular septal defect is completed.

The invention discloses a left ventricular myocardium deformation quantification method and system. The method comprises the following steps: obtaining a dynamic three-dimensional curved surface sequence of left ventricular myocardium in a complete heartbeat cycle; obtaining a Beltrami coefficient corresponding to each fixed anatomical point in each time frame according to a mapping relation between each frame in the three-dimensional curved surface sequence and a unified parameter domain, and obtaining a local deformation scalar of each frame in the three-dimensional curved surface sequence based on the coefficient; and constructing an intrinsic deformation trajectory curve of each fixed anatomical point on the unified parameter domain in the cardiac cycle, and determining a deformation feature vector according to the curve. According to the method, homeomorphic mapping from a myocardial curved surface at each time point to a unified parameter domain is established, three-dimensional motion is coded into sequential evolution of a Beltrami coefficient on a two-dimensional parameter point, the certainty of mapping is utilized to replace the estimability of frame-by-frame registration in a traditional three-dimensional space, drift and accumulative errors of corresponding points are fundamentally and effectively avoided, and the accuracy of the method is improved. And accurate quantification with high time-space consistency on myocardial deformation can be realized.

This invention belongs to the field of biomedical technology, specifically relating to a composition for treating ischemic heart disease and its application. This invention combines two or more of ginsenoside Rg1, ginsenoside Rb1, ginsenoside Re, and notoginsenoside R1, which can significantly downregulate the levels of myocardial enzymes, aspartate aminotransferase (AST), creatine kinase (CK), and lactate dehydrogenase (LDH) in myocardial coronary effusion, with an inhibitory effect significantly higher than that of a single saponin component and the positive control drug verapamil. Simultaneously, the composition exhibits better recovery capabilities for coronary flow (CF), left ventricular developmental pressure (LVDP), maximum rate of decrease in left ventricular pressure (-dp / dtmax), and heart rate (HR) in myocardial coronary effusion. Therefore, the composition can alleviate and treat myocardial ischemia-reperfusion injury through multiple targets and mechanisms, fundamentally inhibiting the development of ischemic heart disease.

This invention relates to the fields of computer vision and medical image processing technology, and discloses a method for extracting lesion structures from cardiac magnetic resonance imaging (MRI) images based on deep learning. The method first retrieves dynamic cardiac cine sequences and delayed gadolinium-enhanced sequences from the same anatomical location, extracts the centroid trajectory of the left ventricular blood pool, and performs cross-sequence axial alignment and non-rigid deformation correction. Subsequently, a local orthogonal coordinate system based on the myocardial anatomical topology is constructed, and pixel-level motion vector fields with physical constraints are calculated in the dynamic cardiac cine sequences. By projecting the motion vectors onto the local orthogonal coordinate system and performing vector clipping according to the centripetal contraction physical constraint, an effective motion vector field is generated. Finally, dynamic features and image grayscale features are fused, and a logic gating operator is used to extract the lesion structure mask.

A minimally invasive, small percutaneous mechanical circulatory support system delivers a pump transcatheterally to the heart, which actively reduces the burden on the left ventricular system by pumping blood from the left ventricle to the ascending aorta and then to the systemic circulation. The pump may include a tubular housing, a motor, an impeller configured to be rotated by the motor, and a distal tip of the pump. The tip may include a guidewire lumen having a curved and / or extended contour. The system may include an insertion tool having a tubular body and configured to receive the circulatory support device axially movable, and an introducer sheath configured to receive the insertion tool axially movable. A coupling allows for connection and disconnection between the insertion tool and the introducer sheath. The coupling may include a hexagonal portion for self-positioning and further for tactile feedback.

The present invention relates to a device and method for segmenting the membranous septum. The method comprises segmenting the left ventricular outflow tract, LVOT, of the heart in a 3D image data set; determining wall thickness information indicative of the wall thickness of the septum at different locations of a part of the segmented LVOT that is oriented towards the right heart chambers and right atrium; mapping the determined wall thickness information onto the surface of said part of the segmented LVOT; and segmenting the membranous septum in the 3D image data set based on the mapped wall thickness information.

The application discloses a kind of left ventricular ejection fraction calculation method during cardiopulmonary resuscitation based on transesophageal echocardiogram, comprising the following steps: S1, obtain TEE image data and its corresponding segmentation mask, the segmentation mask is at least used to annotate the anatomical structure area of left ventricle;The image and mask data are preprocessed, and shape prior knowledge distillation subspace is constructed based on the mask data processed;S2, the preprocessed TEE data and segmentation mask are input into left ventricular ejection fraction calculation model, and the model is trained under the shape prior knowledge distillation subspace and loss function constraint;S3, the TEE data collected are input into left ventricular ejection fraction calculation model, realize the automatic segmentation of left ventricular region, and output the calculation result of ejection fraction.

This application discloses a method, apparatus, ultrasound device, and storage medium for detecting cardiac ultrasound data. The method includes: acquiring cardiac ultrasound data to be detected; extracting image features from the cardiac ultrasound data and determining the target section type corresponding to the cardiac ultrasound data based on the image features; when the target section type is a parasternal left ventricular long-axis section, determining the target section image for display from the cardiac ultrasound data; determining the diameter data of the left ventricular outflow channel along the parasternal left ventricular long axis from the target section image, and associating the diameter data with the target section image for display. By determining the section type of the cardiac ultrasound data, and when the section type is a parasternal left ventricular long-axis section, directly extracting the target section image for display from the cardiac ultrasound data, this application ensures effective subsequent measurement of the left ventricular outflow channel, obtaining data on the left ventricular outflow channel, and improving measurement accuracy.

The application provides a sepsis cardiomyopathy prognosis risk stratification system and a construction method thereof. The method first classifies SIC patients through multi-modal cardiac ultrasound, and then adopts a machine learning algorithm to screen out key ultrasound variables: left ventricular overall longitudinal strain (GLS) and tricuspid annular plane systolic excursion (TAPSE) which are strongly related to prognosis. Based on these variables, cluster analysis is performed, and SIC risk subphenotypes with significant prognosis difference are successfully constructed, and the mortality of the high-risk subtype is significantly higher. The study found that a single indicator, TAPSE, has extremely high predictive efficiency in identifying high-risk subphenotypes and can achieve rapid bedside assessment. The application first establishes a prognosis risk stratification system for SIC, simplifies the evaluation process, realizes early identification of high-risk patients, and provides key technical support for clinical precise intervention and improvement of prognosis.

We provide herein a method of preventing or limiting the effects of heart failure in a human patient that has sustained myocardial infarction by reducing maladaptive cardiac remodeling in the patient. The method comprises percutaneously inserting a transvalvular blood pump, comprising a rotor and a cannula, into the patient's vasculature and positioning the cannula across the aortic valve of the patient's heart, with a distal end of the cannula located in the left ventricle of the heart and a proximal end of the pump located in the aorta. The method then comprises, prior to reperfusing the heart, operating the positioned pump to unload the left ventricle at a pumping rate of at least 2.5 L / min of blood flow for a support period between at least 30 minutes and less than 60 minutes. Then, after the support period, the method comprises applying coronary reperfusion therapy to the heart.

The application relates to a method and device for determining the thickness of the interventricular septum, a computer device and a storage medium. The method comprises the following steps: acquiring a heart scan image, performing image segmentation on the heart scan image by using an image segmentation model, and determining a segmentation mask of a target detection region in the heart scan image; converting the segmentation mask of the target detection region by using a moving cube algorithm, and determining target three-dimensional point cloud data corresponding to each segmentation mask; determining key point position information of a heart key point according to the target three-dimensional point cloud data and a key point detection model; determining the position information of a three-dimensional section of a left ventricular interventricular septum region according to the key point position information; the three-dimensional section comprises a mitral valve horizontal short-axis section, a left ventricular long-axis section and a four-chamber heart section; and determining the thickness of the interventricular septum of the left ventricular interventricular septum region according to the position information of the three-dimensional section. The above scheme improves the accuracy of the determined thickness of the interventricular septum.