Abstract: A device may receive images of a patient, and may perform segmentation of surfaces on the images to create a 3D model. The device may identify normal tissue regions and atrial fibrosis (AF) regions in the 3D model, and may divide the 3D model into the normal tissue regions and the AF regions. The device may assign first cell and tissue properties to the normal tissue regions, and may assign second cell and tissue properties to the AF regions. The device may perform simulations on the normal tissue regions and the AD regions, based on the first and second cell and tissue properties, to generate simulation results, and may extract first features from the simulation results. The device may extract second features from the images, and may process the first and second features, with a model, to select a feature that is predictive of atrial fibrillation recurrence.

Abstract: Provided herein are methods of generating models for prognosing cardiovascular outcomes for monitored subjects infected with an etiologic agent (e.g., severe acute respiratory syndrome coronavirus-2 or another etiologic agent). Related methods, systems, and computer program products are also provided.

Abstract: Methods, system, and media for identifying one or more ablation locations in an atrial tissue region in an atrial fibrillation (AF) patient with atrial fibrosis are disclosed. Three-dimensional imaging data representing the atria of the patient may be received. A patient-specific model of the atria may be generated from the three-dimensional imaging data. Simulation of the AF on the patient-specific model may be conducted to identify AF-perpetrating regions. One or more ablation locations in the atria may be identified from the AF-perpetrating regions.

Abstract: Fully automated computer-implemented deep learning techniques of contrast-enhanced cardiac MRI segmentation are provided. The techniques may include providing cardiac MRI data to a first computer-implemented deep learning network trained in order to identify a left ventricle region of interest to generate left ventricle region-of-interest-identified cardiac MRI data. The techniques may also include providing the left ventricle region-of-interest-identified cardiac MRI data to a second computer-implemented deep learning network trained in order to identify myocardium to generate myocardium-identified cardiac MRI data. The techniques may further include providing the myocardium-identified cardiac MRI data to at least one third computer-implemented deep learning network trained to conform data to geometrical anatomical constraints in order to generate anatomical-conforming myocardium-identified cardiac MRI data.

Abstract: Intraprocedural techniques for identifying a location of an origin of an idiopathic ventricular arrhythmia in a patient are presented.

Abstract: Methods, system, and media for identifying one or more ablation locations in an atrial tissue region in an atrial fibrillation (AF) patient with atrial fibrosis are disclosed. Three-dimensional imaging data representing the atria of the patient may be received. A patient-specific model of the atria may be generated from the three-dimensional imaging data. Simulation of the AF on the patient-specific model may be conducted to identify AF-perpetrating regions. One or more ablation locations in the atria may be identified from the AF-perpetrating regions.

Abstract: A method for guiding ablation of atrial or ventricular arrhythmia in a patient's heart is provided. A digital representation of the electrical functioning of atria or ventricles of the patient's heart is generated based on imaging data of the patient's heart that reveals the presence of adipose tissue. The arrhythmias arising in the presence of the adipose tissue in the digital representation of the patients atria or ventricles are determined. The method further includes identifying, in the digital representation, ablation targets that need to be ablated to terminate determined arrhythmias; executing, in the digital representation, a mock-up of a clinical ablation procedure of the patient to determine the electrical response of the patients heart to ablating the ablation targets, and to determine whether the heart continues to generate new arrhythmias post-procedure; and generating a final set of ablation targets based on the mock-up of the clinical ablation procedure.

Abstract: A system and method are provided for a navigational feedback to a catheter during an arrhythmia ablation procedure. A set of electrocardiogram (ECG) signals of a patient's arrhythmia is recorded that correspond to an unknown target location to be ablated by the catheter. During the ablation procedure, pacing locations and ECG signals corresponding to the pacing locations are collected to derive a mathematical operator that maps a 12-dimensional displacement vector in the ECG space to a 3-dimensional (3D) vector in a physical space. This 3D vector corresponds to a direction and a distance that the catheter needs to be moved in order to reach the target location of the arrhythmia.

Abstract: A device may receive images of a patient, and may perform segmentation of surfaces on the images to create a 3D model. The device may identify normal tissue regions and atrial fibrosis (AF) regions in the 3D model, and may divide the 3D model into the normal tissue regions and the AF regions. The device may assign first cell and tissue properties to the normal tissue regions, and may assign second cell and tissue properties to the AF regions. The device may perform simulations on the normal tissue regions and the AD regions, based on the first and second cell and tissue properties, to generate simulation results, and may extract first features from the simulation results. The device may extract second features from the images, and may process the first and second features, with a model, to select a feature that is predictive of atrial fibrillation recurrence.

Abstract: An embodiment in accordance with the present invention provides a non-invasive solution to risk stratify the risk of in arrhythmia in patients with TOF. Currently, no reliable method for non-invasive risk stratification exists. In the realm of congenital heart disease, cardiac MRI is now used routinely for patients with Tetralogy of Fallot (TOF), the most common form of cyanotic congenital heart disease. An innovative platform for using clinical MRI data to create 3D electromechanical models of the heart enables predictions of whether or not patients with ischemic heart disease have the substrate for arrhythmia and what their relative risk for such an event is. An embodiment of the current invention provides a non-invasive solution to risk stratify the risk of arrhythmia in patients with TOF. Currently, no reliable method for non-invasive risk stratification exists.

Abstract: Methods, system, and media for identifying one or more ablation locations in an atrial tissue region in an atrial fibrillation (AF) patient with atrial fibrosis are disclosed. Three-dimensional imaging data representing the atria of the patient may be received. A patient-specific model of the atria may be generated from the three-dimensional imaging data. Simulation of the AF on the patient-specific model may be conducted to identify AF-perpetrating regions. One or more ablation locations in the atria may be identified from the AF-perpetrating regions.

Abstract: A method of planning a patient-specific cardiac procedure according to an embodiment of the current invention includes receiving three-dimensional imaging data of a patient's heart, simulating at least one of electrophysiological or electromechanical activity of at least a portion of the patient's heart using the three-dimensional imaging data, and planning the patient-specific cardiac procedure based on the simulating. The cardiac procedure is for providing a preselected alteration of at least one of electrophysiological or electromechanical behavior of the patient's heart.

Abstract: A computer-implemented method for non-invasively identifying ablation locations in atrial tissue, can include: receiving three-dimensional imaging data representing atrial tissue of a left atrial flutter (LAFL) subject; generating a subject-specific model of the at least one of the atrial tissue from the three-dimensional imaging data; estimating tissue fiber orientations in the atrial tissue; assigning the estimated tissue fiber orientations to the subject-specific model of the atrial tissue; conducting simulations of LAFL using the subject-specific model to identify regions of slow conduction of a propagating wave within an atrial tissue region of the atrial tissue; a critical isthmus of a rotational wavefront within the atrial tissue region; or a region based on a minimum cut in a flow network; and identifying at least one ablation location in the atrial tissue region based on the identified regions of slow conduction, the critical isthmus, or the minimum cut.

Abstract: A method of determining a likelihood of an occurrence of a cardiac arrhythmia in a patient includes receiving three-dimensional imaging data of said patient's heart, constructing a whole-heart model for simulating at least one of electrophysiological activity or electromechanical activity of the patient's heart using the three-dimensional imaging data, simulating a response of the patient's heart to each of a plurality of stimulations to a corresponding plurality of different locations within the patient's heart using the whole-heart model, classifying each simulation outcome for each stimulation as one of a normal heart rhythm or a cardiac arrhythmia, calculating a likelihood index based on results of the classifying, and determining the likelihood of the occurrence of the cardiac arrhythmia in the patient based on the likelihood index. Software and data processing systems that implement the above methods are also provided.

Abstract: Methods, system, and media for identifying one or more ablation locations in an atrial tissue region in an atrial fibrillation (AF) patient with atrial fibrosis are disclosed. Three-dimensional imaging data representing the atria of the patient may be received. A patient-specific model of the atria may be generated from the three-dimensional imaging data. Simulation of the AF on the patient-specific model may be conducted to identify AF-perpetrating regions. One or more ablation locations in the atria may be identified from the AF-perpetrating regions.

Abstract: A method of planning a patient-specific cardiac procedure according to an embodiment of the current invention includes receiving three-dimensional imaging data of a patient's heart, simulating at least one of electrophysiological or electromechanical activity of at least a portion of the patient's heart using the three-dimensional imaging data, and planning the patient-specific cardiac procedure based on the simulating. The cardiac procedure is for providing a preselected alteration of at least one of electrophysiological or electromechanical behavior of the patient's heart.

Abstract: An embodiment in accordance with the present invention provides a non-invasive solution to risk stratify the risk of in arrhythmia in patients with TOF. Currently, no reliable method for non-invasive risk stratification exists. In the realm of congenital heart disease, cardiac MRI is now used routinely for patients with Tetralogy of Fallot (TOF), the most common form of cyanotic congenital heart disease. An innovative platform for using clinical MRI data to create 3D electromechanical models of the heart enables predictions of whether or not patients with ischemic heart disease have the substrate for arrhythmia and what their relative risk for such an event is. An embodiment of the current invention provides a non-invasive solution to risk stratify the risk of arrhythmia in patients with TOF. Currently, no reliable method for non-invasive risk stratification exists.

Abstract: According to some embodiments of the invention, a method for providing an atrial fibrillation (AF) ablation treatment plan includes receiving imaging data for at least a portion of an atrial region of a subject's heart, and processing the imaging data to characterize tissue as one of fibrotic tissue or non-fibrotic tissue. The method further includes calculating a metric of spatial distribution of at least a portion of the tissue characterized as fibrotic tissue from the processing the imaging data, identifying a cardiac tissue ablation target based on the metric, and providing an AF treatment plan that includes the cardiac tissue ablation target as at least a portion of the AF treatment plan.

Abstract: The present invention includes a method for determining optimal placement sites for internal defibrillators in pediatric and congenital heart defect patients. The method is executed by creating a personalized active heart-torso model. The model is created using imaging scans (e.g., low resolution clinical scans) and advanced image processing techniques. The image processing results in a heart-torso mesh model. The ventricular portion of the mesh incorporates cell membrane dynamics. The combined torso-active ventricular defibrillation model can be used for patient specific modeling of the defibrillation process and optimal defibrillator placement can be determined. This method could also be used to decrease the energy needed for a defibrillation shock, because of the optimized defibrillator placement.

Abstract: A system, computer-readable medium and method can include receiving three-dimensional imaging data of a subject's heart, the subject having an ICD, wherein the ICD causes an imaging artifact in the three-dimensional imaging data that includes regions that are free of the artifact and regions that are affected by the artifact; segmenting the regions that are free of the artifact into a plurality of normal tissue regions and remodeled tissue regions for the subject; extrapolating from the regions that are free of the artifact to provide extrapolated three-dimensional imaging data corresponding to the regions that are affected by the artifact; and simulating at least one of electrophysiological or electromechanical activity of the subject's heart using the segmented and extrapolated three-dimensional imaging data, the simulating including providing a preselected alteration of electrophysiological or electromechanical behavior of the subject's heart for a target of said subject-specific cardiac ablation procedure