System and methods for estimation of blood flow characteristics using reduced order model and machine learning

A system for determining blood flow characteristics of a patient, the system comprising:

• at least one data storage device storing instructions for determining blood flow characteristics of a patient;
• and
• at least one processor configured to execute the instructions to perform a method comprising:
• receiving, in an electronic storage medium, a patient-specific anatomical model of at least a portion of the patient's vasculature including geometric features at one or more points;
• truncating the patient-specific anatomical model at locations of the patient-specific anatomical model for which blood flow characteristics are to be determined, wherein the truncated patient-specific anatomic model is associated with boundary conditions applied at the inflow of blood flow, outflow of blood flow, and the vessel wall of the truncated patient-specific anatomic model;
• determining values for the blood flow characteristic at the one or more locations of the truncated patient-specific anatomic model;
• generating a patient-specific reduced order model from the received patient-specific anatomical model and the determined values of the blood flow characteristic, the patient-specific reduced order model comprising estimates of values and that simplify geometric features at the one or more points of the vasculature of the patient;
• creating a feature vector comprising the estimates of values that simplify the geometric features for each of the one or more points of the patient-specific reduced order model;
• and
• determining blood flow characteristics at the one or more points of the patient-specific reduced order model using a machine learning algorithm trained to predict blood flow characteristics based on the created feature vectors at the one or more points, using a machine learning regressor based on an error associated with the patient-specific reduced order model.

A non-transitory computer-readable medium storing instructions that, when executed by a computer, causes the computer to perform a method for determining blood flow characteristics of a patient, the method including:

• receiving, in an electronic storage medium, a patient-specific anatomical model of at least a portion of the patient's vasculature including geometric features at one or more points;
• truncating the patient-specific anatomical model at locations of the patient-specific anatomical model for which blood flow characteristics are to be determined, wherein the truncated patient-specific anatomic model is associated with boundary conditions applied at the inflow of blood flow, outflow of blood flow, and the vessel wall of the truncated patient-specific anatomic model;
• determining values for the blood flow characteristic at the one or more locations of the truncated patient-specific anatomic model;
• generating a patient-specific reduced order model from the received patient-specific anatomical model and the determined values of the blood flow characteristic, the patient-specific reduced order model comprising estimates of values and that simplify the geometric features at the one or more points of the vasculature of the patient;
• creating a feature vector comprising the estimates of values that simplify the geometric features for each of the one or more points of the patient-specific reduced order model;
• and
• determining blood flow characteristics at the one or more points of the patient-specific reduced order model using a machine learning algorithm trained to predict blood flow characteristics based on the created feature vectors at the one or more points, using a machine learning regressor based on an error associated with the patient-specific reduced order model.