Heartflow, Inc.

Nan Xiao

Charles Anthony Taylor, Jr

Sethuraman Sankaran

Hyun Jin Kim

David Spain

Leo John Grady

Gilwoo Choi

Sophie Khem

Jin Kim

Rhea Tombropoulos

Travis Michael Sanders

Souma Sengupta

David Lesage

Michiel Schaap

Sophia Khem

Buzzy Spain

Systems and methods are disclosed for to determining a blood supply and blood demand. One method includes receiving a patient-specific model of vessel geometry of at least a portion of a coronary artery, wherein the model is based on patient-specific image data of at least a portion of a patient's heart having myocardium; determining a coronary blood supply based on the patient-specific model; determining at least a portion of the myocardium corresponding to the coronary artery; determining a myocardial blood demand based on either a mass or a volume of the portion of the myocardium, or based on perfusion imaging of the portion of the myocardium; and determining a relationship between the coronary blood supply and the myocardial blood demand.

Systems and methods for processing electronic images to assess end-organ demand

Systems and methods are disclosed for determining blood flow characteristics of a patient. One method includes: receiving, in an electronic storage medium, patient-specific image data of at least a portion of vasculature of the patient having geometric features at one or more points; generating a patient-specific reduced order model from the received image data, the patient-specific reduced order model comprising estimates of impedance values and a simplification of the geometric features at the one or more points of the vasculature of the patient; creating a feature vector comprising the estimates of impedance values and 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.

Systems and methods for estimation of blood flow characteristics using reduced order model and/or machine learning

Systems and methods are disclosed for blood flow simulation. For example, a method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow in a vasculature of a patient or a geometry based on the vasculature of the patient; based on results of the plurality of blood flow simulations, generating a response surface mapping one or more first parameters of the first model to one or more second parameters of a reduced order model of vascular blood; determining values for the one or more parameters of the reduced order model mapped, by the response surface, from parameter values representing a modified state of the vasculature; and performing simulation using the reduced order model parameterized by the determined values, to determine a blood flow characteristic of the modified state of the vasculature.

Systems and methods for estimation of blood flow using response surface and reduced order modeling

Systems and methods are disclosed for assessing the severity of plaque and/or stenotic lesions using contrast distribution predictions and measurements. One method includes: receiving patient-specific images of a patient's vasculature and a measured distribution of a contrast agent delivered through the patient's vasculature; associating the measured distribution of the contrast agent with a patient-specific anatomic model of the patient's vasculature; defining physiological and boundary conditions of a blood flow model of the patient's blood flow and pressure; simulating the distribution of the contrast agent through the patient-specific anatomic model; comparing the measured distribution of the contrast agent and the simulated distribution of the contrast agent through the patient-specific anatomic model to determine whether a similarity condition is satisfied; and updating the defined physiological and boundary conditions and re-simulating distribution of the contrast agent through the one or more points of the patient-specific anatomic model until the similarity condition is satisfied.

Systems and methods for assessing the severity of plaque and/or stenotic lesions using contrast distribution predictions and measurements

Systems and methods are disclosed for identifying and modeling unresolved vessels, and the effects thereof, in image-based patient-specific hemodynamic models. One method includes: receiving, in an electronic storage medium, one or more patient-specific anatomical models representing at least a vessel of a patient; determining, using a processor, the values and characteristics of one or more patient-specific morphometric features in the one or more patient-specific anatomical models; modifying the patient-specific anatomical model using the determined patient-specific morphometric features; and outputting, one or more of, a modified patient-specific anatomical model or a patient-specific morphometric feature to an electronic storage medium or display.

Systems and methods for identifying and modeling unresolved vessels in image-based patient-specific hemodynamic models

System and methods for estimation of blood flow using response surface and reduced order modeling

Systems and methods for diagnosis and assessment of cardiovascular disease by comparing arterial supply capacity to end-organ demand

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

Systems and methods are disclosed for assessing the severity of plaque and/or stenotic lesions using contrast distribution predictions and measurements. One method includes: receiving patient-specific images of a patient's vasculature and a measured distribution of a contrast agent delivered through the patient's vasculature; associating the measured distribution of the contrast agent with a patient-specific anatomic model of the patients vasculature; defining physiological and boundary conditions of a blood flow model of the patient's blood flow and pressure; simulating the distribution of the contrast agent through the patient-specific anatomic model; comparing the measured distribution of the contrast agent and the simulated distribution of the contrast agent through the patient-specific anatomic model to determine whether a similarity condition is satisfied; and updating the defined physiological and boundary conditions and re-simulating distribution of the contrast agent through the one or more points of the patient-specific anatomic model until the similarity condition is satisfied.

System and method for diagnosis and assessment of cardiovascular disease by comparing arterial supply capacity to end-organ demand

Growing community of inventors

Redwood City, CA, United States of America

Nan Xiao