Method and system for image processing and patient-specific modeling of blood flow

• US 10,441,361 B2
• Filed: 08/25/2016
• Issued: 10/15/2019
• Est. Priority Date: 08/12/2010
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: Taylor, Charles A.
• Primary Examiner(s): Rahmjoo, Manuchehr
• Application Number:
  US15/246,766
• Publication Number:
  US 20160364859A1
• Time in Patent Office: 1,146 Days
• Field of Search: 382103
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Abstract

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient'"'"'s heart, and create a three-dimensional model representing at least a portion of the patient'"'"'s heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient'"'"'s heart and determine a fractional flow reserve within the patient'"'"'s heart based on the three-dimensional model and the physics-based model.

Claims

1. A method processing images for planning treatment for arterial stenoses, comprising:

receiving medical image data of at least a patient'"'"'s coronary arteries, wherein the medical image data is non-invasively produced from a computerized tomography scanner;

identifying, using an image processor, a set of stenoses in the patient'"'"'s coronary arteries from the received non-invasively produced medical image data;

generating a plurality of treatment options for the identified set of stenoses, wherein each of the plurality of treatment options corresponds to a simulated stenting configuration in which stenting of one or more of the identified stenoses is simulated; and

calculating, for each of the generated plurality of treatment options, predicted hemodynamic metrics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that treatment option.

2. The method of claim 1, further comprising:

evaluating the generated plurality of treatment options based on the predicted blood flow characteristics calculated for each of the generated plurality of treatment options for the identified set of stenoses.

3. The method of claim 2, further comprising:

displaying a plurality of results of calculating the predicted blood flow characteristics resulting from the simulated stenting configuration corresponding to each of the generated plurality of treatment options for the identified set of stenoses.

4. The method of claim 2, wherein evaluating the plurality of treatment options comprises ranking the plurality of treatment options.

5. The method of claim 1, wherein calculating, for each of the generated plurality of treatment options, predicted blood flow characteristics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option comprises:

calculating, for each of the generated plurality of treatment options, predicted fractional flow reserve (FFR) values for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option.

6. The method of claim 5, wherein calculating, for each of the generated plurality of treatment options, predicted fractional flow reserve (FFR) values for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option comprises:

determining a pressure loss model for the one or more of the identified stenoses that are stented in the corresponding stenting configuration;

simulating blood flow and pressure in the coronary arteries of the patient with the determined pressure loss model for the one or more of the identified stenoses that are stented; and

calculating FFR values for each of the identified set of stenoses based on the simulated blood flow and pressure in the coronary arteries of the patient.

7. The method of claim 1, further comprising:

generating a patient-specific anatomic model for blood flow through the patient'"'"'s coronary arteries and the identified set of stenoses, from the medical image data of the patient;

modifying the patient-specific anatomic model for blood flow, for each of the generated plurality of treatment options; and

calculating the predicted blood flow characteristics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option, based on a simulation of blood flow through the modified patient-specific anatomic model for blood flow.

8. The method of claim 1, wherein identifying a set of stenoses in a patient'"'"'s coronary arteries from the received non-invasively produced medical image data comprises:

extracting a patient-specific anatomical model of the coronary arteries from the medical image data;

detecting a plurality of stenoses in the coronary arteries using the patient-specific anatomical model of the coronary arteries;

estimating a blood flow characteristic for each of the detected plurality of stenoses; and

identifying a set of hemodynamically relevant stenoses from the detected plurality of stenoses based on the blood flow characteristic estimated for each of the detected plurality of stenoses.

9. The method of claim 8, wherein estimating a blood flow characteristic for each of the detected plurality of stenoses comprises:

simulating blood flow and pressure in the coronary arteries using a computational model of coronary circulation; and

estimating the blood flow characteristic for each of the detected plurality of stenoses based on a simulated pressure change across each of the detected plurality of stenoses.

10. The method of claim 8, wherein estimating a blood flow characteristic for each of the detected plurality of stenoses comprises:

estimating a fractional flow reserve (FFR) value for each of the detected plurality of stenoses.

11. A system for processing images for planning treatment for arterial stenotic lesions, the system comprising:

a data storage device storing instructions for processing images for planning treatment for arterial stenoses; and

a processor configured to execute the instructions to perform a method including the steps of;

receiving medical image data of at least a patient'"'"'s coronary arteries, wherein the medical image data is non-invasively produced from a computerized tomography scanner;

identifying, using an image processor, a set of stenoses in the patient'"'"'s coronary arteries from the received non-invasively produced medical image data;

generating a plurality of treatment options for the identified set of stenoses, wherein each of the plurality of treatment options corresponds to a simulated stenting configuration in which stenting of one or more of the identified stenoses is simulated; and

calculating, for each of the generated plurality of treatment options, predicted hemodynamic metrics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option.

12. The system of claim 11, further comprising:

evaluating the generated plurality of treatment options based on the predicted blood flow characteristics calculated for each of the generated plurality of treatment options for the identified set of stenoses.

13. The system of claim 12, further comprising:

displaying a plurality of results of calculating the predicted blood flow characteristics resulting from the simulated stenting configuration corresponding to each of the generated plurality of treatment options for the identified set of stenoses.

14. The system of claim 11, wherein calculating, for each of the generated plurality of treatment options, predicted blood flow characteristics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option comprises:

calculating, for each of the generated plurality of treatment options, predicted fractional flow reserve (FFR) values for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option.

15. The system of claim 14, wherein calculating, for each of the generated plurality of treatment options, predicted fractional flow reserve (FFR) values for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option comprises:

determining a pressure loss model for the one or more of the identified stenoses that are stented in the corresponding stenting configuration;

simulating blood flow and pressure in the coronary arteries of the patient with the determined pressure loss model for the one or more of the identified stenoses that are stented; and

calculating FFR values for each of the identified set of stenoses based on the simulated blood flow and pressure in the coronary arteries of the patient.

16. The system of claim 11, wherein the generated plurality of treatment options comprises a respective treatment option corresponding to each possible stenting configuration of one or more of the identified set of stenoses.

17. The system of claim 11, further comprising:

generating a patient-specific anatomic model for blood flow through the patient'"'"'s coronary arteries and the identified set of stenoses, from the medical image data of the patient;

modifying the patient-specific anatomic model for blood flow, for each of the generated plurality of treatment options; and

calculating the predicted blood flow characteristics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option, based on a simulation of blood flow through the modified patient-specific anatomic model for blood flow.

18. The system of claim 11, wherein identifying a set of stenoses in a patient'"'"'s coronary arteries from the received non-invasively produced medical image data comprises:

extracting a patient-specific anatomical model of the coronary arteries from the medical image data;

detecting a plurality of stenoses in the coronary arteries using the patient-specific anatomical model of the coronary arteries;

estimating a blood flow characteristic for each of the detected plurality of stenoses; and

identifying a set of hemodynamically relevant stenoses from the detected plurality of stenoses based on the blood flow characteristic estimated for each of the detected plurality of stenoses.

19. The system of claim 11, wherein evaluating the plurality of treatment options comprises ranking the plurality of treatment options.

20. A non-transitory computer readable medium storing computer program instructions for processing images for planning treatment for arterial stenoses, the computer program instructions when executed by a processor causes the processor to perform operations comprising:

receiving medical image data of at least a patient'"'"'s coronary arteries, wherein the medical image data is non-invasively produced from a computerized tomography scanner;

identifying, using an image processor, a set of stenoses in the patient'"'"'s coronary arteries from the received non-invasively produced medical image data;

generating a plurality of treatment options for the identified set of stenoses, wherein each of the plurality of treatment options corresponds to a simulated stenting configuration in which stenting of one or more of the identified stenoses is simulated; and

calculating, for each of the generated plurality of treatment options, predicted hemodynamic metrics for the identified set of stenoses resulting from the simulated stenting configuration corresponding to that generated treatment option.