36 results about "Left cardiac chamber" patented technology

The disclosure provides methods and apparatus of left ventricular pacing including automated adjustment of a atrio-ventricular (AV) pacing delay interval and intrinsic AV nodal conduction testing. It includes—upon expiration or reset of a programmable AV Evaluation Interval (AVEI)—performing the following: temporarily increasing a paced AV interval and a sensed AV interval and testing for adequate AV conduction and measuring an intrinsic atrio-ventricular (PR) interval for a right ventricular (RV) chamber. Thus, in the event that the AV conduction test reveals a physiologically acceptable intrinsic PR interval then storing the physiologically acceptable PR interval in a memory structure (e.g., a median P-R from one or more cardiac cycles). In the event that the AV conduction test reveals an AV conduction block condition or if unacceptably long PR intervals are revealed then a pacing mode-switch to a bi-ventricular (Bi-V) pacing mode occurs and the magnitude of the AVEI is increased.

This document discusses, among other things, systems, devices, and methods measure an impedance and, in response, adjust an atrioventricular (AV) delay or other cardiac resynchronization therapy (CRT) parameter that synchronizes left and right ventricular contractions. A first example uses parameterizes a first ventricular volume against a second ventricular volume during a cardiac cycle, using a loop area to create a synchronization fraction (SF). The CRT parameter is adjusted in closed-loop fashion to increase the SF. A second example measures a septal-freewall phase difference (PD), and adjusts a CRT parameter to decrease the PD. A third example measures a peak-to-peak volume or maximum rate of change in ventricular volume, and adjusts a CRT parameter to increase the peak-to-peak volume or maximum rate of change in the ventricular volume.

Methods and apparatus of left ventricular pacing including automated adjustment of a atrio-ventricular (AV) pacing delay interval and intrinsic AV nodal conduction testing. Thus, in the event that the AV conduction test reveals a physiologically acceptable intrinsic PR interval then storing the physiologically acceptable PR interval in a memory structure (e.g., a median P-R from one or more cardiac cycles) and delivering fusion pacing using a decremented value of the intrinsic PR interval.

Systems and methods for enhanced diagnosis of transthyretin-related cardiac amyloidosis in a subject are disclosed. The systems and methods may use both SPECT imaging data as well as an anatomical imaging data, such as computed tomography (CT) data, to produce a combined image. Within the combined image, the radiotracer uptake between two volumes of interests are compared, one of which may represent the left ventricle of the subject and the other may represent the blood pool retention of the subject. Combining the anatomical imaging data with SPECT data enables better anatomical delineation and helps in avoiding areas with coronary or lymph node calcifications and overlying soft tissue and bony pathologies.

The embodiment of the present application discloses an image processing method, electronic equipment and storage medium, wherein the method includes: converting the original image into a target image conforming to the target parameters; inputting the target image into the index prediction module to obtain the target numerical index; The target numerical index performs time-series prediction processing on the target image to obtain a time-series state prediction result, which can realize left ventricular function quantification, improve image processing efficiency, and improve the prediction accuracy of cardiac function indexes.

The present application discloses a method, device, device, and medium for intelligent classification of left ventricular magnetic resonance images. The method includes: acquiring a first word embedding vector corresponding to the first data of a detection object, a second word embedding vector corresponding to the second data, The numerical feature vector formed by splicing the third data; extracting the short-axis video and long-axis video in the heart magnetic resonance image of the detection object, and preprocessing to obtain the target video data; splicing and inputting the above three vectors into the first feature analysis model to obtain the second The first feature analysis result and the target video data are input into the second feature analysis model to obtain the second feature analysis result, and the third feature analysis result is obtained, and input to the third feature analysis model to obtain the classification probability of the left ventricle image of the detection object value. The method uses multi-sequence nuclear magnetic imaging data and clinical data to make classification predictions. The results are more reliable and accurate, and it does not require complicated post-processing procedures, and there is no cumulative error, which improves the robustness.