Patent ID: 11922630
Assignee: THE JOHNS HOPKINS UNIVERSITY
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC G

Claim 0:
1. A method, comprising:
receiving, by a device, clinical late gadolinium enhanced cardiac magnetic resonance imaging (LGE-MRI) images of a patient;
performing, by the device, segmentation of epicardial and endocardial surfaces on the LGE-MRI images to create a patient-specific three-dimensional (3D) model for the patient;
identifying, by the device, normal tissue regions and atrial fibrosis regions in the 3D model based on intensity;
dividing, by the device, the 3D model into the normal tissue regions and the atrial fibrosis regions;
assigning, by the device, first cell and tissue properties to the normal tissue regions according to a model of human cardiac myocyte and based on transverse and longitudinal conduction velocities;
assigning, by the device, second cell and tissue properties to the atrial fibrosis regions according to a model of diffuse fibrosis with complete fibrotic remodeling;
performing, by the device, simulations on the normal tissue regions and the atrial fibrosis regions, based on the first cell and tissue properties and the second cell and tissue properties, to generate simulation results;
extracting, by the device, first features from the simulation results based on the 3D model and based on a simulation protocol;
extracting, by the device, second features from the LGE-MRI images;
processing, by the device, the first features and the second features, with a machine learning model, to select a feature, from at least one of the first features or the second features, that is predictive of atrial fibrillation recurrence; and
utilizing, by the device, the feature to augment the simulation protocol for a future patient.