Method and system for enhancing medical image-based blood flow computations using physiological measurements

Patent metadata

Field	Value
Publication number	US-10872698-B2
Application number	US-201615221180-A
Country	US
Kind code	B2
Filing date	Jul 27, 2016
Priority date	Jul 27, 2015
Publication date	Dec 22, 2020
Grant date	Dec 22, 2020

Abstract

A method and system for simulating blood flow in a vessel of a patient to estimate hemodynamic quantities of interest using enhanced blood flow computations based on invasive physiological measurements of the patient is disclosed. Non-invasive patient data including medical image data is received and a patient-specific anatomical model the patient's vessels is generated. Invasive physiological measurements of the patient are received and a computational blood flow model is personalized using the invasive physiological measurements. Blood flow is simulated in the patient-specific anatomical model and one or more hemodynamic quantities of interest are computed using the personalized computational blood flow model.

First claim

The invention claimed is:

1. A method for simulating blood flow in a vessel of a patient to estimate one or more hemodynamic quantities of interest, comprising:
receiving non-invasive patient data including medical image data and non-invasive clinical measurements of a patient;
generating a patient-specific anatomical model of at least one vessel of the patient from the medical image data;
receiving an invasive physiological measurement of the patient acquired using a sensor inserted into a particular vessel of the patient at a first patient state;
personalizing a computational blood flow model for simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient by reconstructing the patient-specific anatomical model based on the invasive physiological measurement of the patient and personalizing one or more parameters or boundary conditions of the computational blood flow model based on the reconstructed patient-specific anatomical model; and
simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient at a second patient state and computing one or more hemodynamic quantities of interest using the personalized computational blood flow model.

2. The method of claim 1 , wherein the invasive physiological measurement is a different quantity than the one or more hemodynamic quantities of interest computed using the personalized computational blood flow model.

3. The method of claim 1 , wherein the particular vessel from which the invasive physiological measurement of the patient is acquired is different that the at least one vessel of the patient for which the blood flow is simulated using the personalized computational blood flow model.

4. The method of claim 1 , wherein:
receiving an invasive physiological measurement of the patient acquired using a sensor inserted into a particular vessel of the patient at a first patient state comprises receiving invasive measurements of an aortic pressure and a distal pressure for a stenosis in the at least one vessel;
personalizing a computational blood flow model comprises:
calculating an invasively measured pressure drop for the stenosis from the invasive aortic and distal pressure measurements, and
adjusting a flow rate through the stenosis in the computational blood flow model to determine a flow rate for which a simulated pressure drop for the stenosis computed using the computational blood flow model matches the invasively measured pressure drop for the stenosis; and

simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient at a second patient state and computing one or more hemodynamic quantities of interest using the personalized computational blood flow model comprises:
computing a transit time based on the determined flow rate and computing an index of microvascular resistance (IMR) based on the transit time and the distal pressure measurement.

5. The method of claim 4 , wherein simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient at a second patient state and computing one or more hemodynamic quantities of interest using the personalized computational blood flow model further comprises:
computing a microvascular resistance based on the determined flow rate and the distal pressure measurement.

6. The method of claim 1 , wherein:
receiving an invasive physiological measurement of the patient acquired using a sensor inserted into a particular vessel of the patient at a first patient state comprises receiving an invasive blood velocity measurement for the at least one vessel of the patient;
personalizing a computational blood flow model comprises calculating a flow rate for the computational blood flow model based on the invasive flow velocity measurement and a cross-sectional area in the patient-specific anatomical model of the at least one vessel; and
simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient at a second patient state and computing one or more hemodynamic quantities of interest using the personalized computational blood flow model comprises:
simulating blood flow in the patient-specific anatomical model of the at least one vessel with the calculated flow rate imposed in the computational blood flow model,
computing a pressure drop over a stenosis in the at least one vessel based on the simulated blood flow,
determining a distal pressure to the stenosis based on the computed pressure drop and an average aortic pressure estimated from non-invasive pressure measurements of the patient,
computing a microvascular resistance based on the distal pressure and the simulated blood flow through the stenosis, and
computing a transit time based on the simulated flow rate and computing an index of microvascular resistance (IMR) based on the transit time and the distal pressure.

7. The method of claim 1 , wherein:
receiving an invasive physiological measurement of the patient acquired using a sensor inserted into a particular vessel of the patient at a first patient state comprises receiving an invasive measurement of a transit time required for blood to pass a stenosis region in the at least one vessel of the patient;
personalizing a computational blood flow model comprises calculating a flow rate through the stenosis region for the computational blood flow model based on the invasive measurement of the transit time and a volume of the stenosis region in the patient-specific anatomical model of the at least one vessel; and
simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient at a second patient state and computing one or more hemodynamic quantities of interest using the personalized computational blood flow model comprises:
simulating blood flow in the patient-specific anatomical model of the at least one vessel with the calculated flow rate through the stenosis region imposed in the computational blood flow model,
computing a pressure drop over the stenosis region in the at least one vessel based on the simulated blood flow,
determining a distal pressure to the stenosis region based on the computed pressure drop and an average aortic pressure estimated from non-invasive pressure measurements of the patient,
computing a microvascular resistance based on the distal pressure and the calculated flow rate through the stenosis region, and
computing an index of microvascular resistance (IMR) based on the transit time and the distal pressure.

8. The method of claim 1 , wherein:
receiving an invasive physiological measurement of the patient acquired using a sensor inserted into a particular vessle of the patient at a first patient state comprises receiving invasive pressure measurements of an aortic pressure and a distal pressure for a stenosis in the at least one vessel;
personalizing a computational blood flow model comprises:
calculating an invasively measured pressure drop for the stenosis from the invasive aortic and distal pressure measurements, and
adjusting a flow rate through the stenosis in the computational blood flow model to determine a flow rate for which a simulated pressure drop for the stenosis computed using the computational blood flow model matches the invasively measured pressure drop for the stenosis; and

simulating blood flow in the patient-specific anatomical model of the at least one vessel of the patient at a second patient state and computing one or more hemodynamic quantities of interest using the personalized computational blood flow model comprises:
simulating blood flow through the stenosis in the patient-specific anatomical model and computing a fractional flow reserve

Assignees

• Siemens Healthcare Gmbh

Inventors

• Itu Lucian Mihai
• Passerini Tiziano
• Sharma Puneet
• Redel Thomas

Classifications

• G16H50/50 Primary

  for simulation or modelling of medical disorders · CPC title