Fractional flow reserve estimation

Patent metadata

Field	Value
Publication number	US-10034614-B2
Application number	US-201213408886-A
Country	US
Kind code	B2
Filing date	Feb 29, 2012
Priority date	Feb 29, 2012
Publication date	Jul 31, 2018
Grant date	Jul 31, 2018

Abstract

Approaches for assessing hemodynamic characteristics for an organ of interest are related. In one implementation, a fluid dynamics model may be provided with data derived from an anatomic imaging modality and blood flow information derived by ultrasound to derive the desired hemodynamic characteristics. In one such implementation, a fractional flow reserve is estimated.

First claim

The invention claimed is:

1. A microprocessor-implemented method for assessing hemodynamic information, consisting essentially of:
acquiring volumetric coronary vasculature images depicting at least a location and topology of a narrowing of a blood vessel;
segmenting the blood vessel from a remainder of the volumetric coronary vasculature images to extract coronary-specific anatomical information representing the geometry of the blood vessel, wherein the coronary-specific anatomical information includes a location of a narrowing of the blood vessel, branch locations of the blood vessel, and a percentage of lumen reduction at the location of the narrowing, such that a localized region based on the location of the narrowing and the branch locations is determined;
non-invasively acquiring local blood flow information in at least one or more vessels proximal to the location of the narrowing;
quantifying a pressure drop across the narrowing based on the reduced section of the blood vessel and the acquired blood flow using a computational fluid dynamics model configured to receive the geometry of the blood vessel and the blood flow information;
calculating a numeric value quantifying a myocardial fractional flow reserve based on the pressure drop; and
generating and outputting for review at least the calculated numeric value quantifying the myocardial fractional flow reserve.

2. The method of claim 1 , wherein the coronary-specific anatomical information further comprises one or more of a location of a vessel tree, a percentage of lumen reduction, or stenosis composition.

3. The method of claim 1 , wherein the location of the narrowing of the blood vessel comprises a stenotic lesion.

4. The method of claim 1 , wherein the local blood flow information comprises a flow boundary condition used in the computational fluid dynamics model.

5. The method of claim 1 , comprising:
employing a computed tomography (CT) system to generate a set of CT image data;
determining a cardiac phase of interest using the set of CT image data;
segmenting the coronary arteries from one or more CT images at the cardiac phase of interest; and
deriving the coronary-specific anatomical information based at least on the segmented coronary arteries.

6. The method of claim 5 , comprising:
employing an ultrasound system to generate a set of ultrasound data;
registering the ultrasound data based on the cardiac phase of interest;
identifying an ultrasound volume of interest based on the volumetric coronary vascular images;
generating a set of velocity data for the ultrasound volume of interest; and
estimating at least the local blood flow information using the set of velocity data.

7. The method of claim 1 , comprising:
employing an interventional X-ray system to generate a set of image data;
determining a cardiac phase of interest using the set of image data;
segmenting the coronary arteries from one or more reconstructed images at the cardiac phase of interest; and
deriving the coronary-specific anatomical information based at least on the segmented coronary arteries.

8. The method of claim 7 , comprising:
employing an ultrasound system to generate a set of ultrasound data;
registering the ultrasound data based on the cardiac phase of interest;
identifying an ultrasound volume of interest based on the volumetric coronary vascular images;
generating a set of velocity data for the ultrasound volume of interest; and
estimating at least the local blood flow information using the set of velocity data.

9. One or more non-transitory computer-readable media encoding one or more processor-executable routines, wherein the one or more routines, when executed by a microprocessor, cause acts to be performed consisting essentially of:
accessing or acquiring volumetric coronary vasculature images depicting at least a location and topology of a narrowing of a blood vessel;
segmenting the blood vessel from a remainder of the volumetric coronary vasculature images to extract coronary-specific anatomical information representing the geometry of the blood vessel, wherein the coronary-specific anatomical information includes a location of a narrowing of the blood vessel, branch locations of the blood vessel, and a percentage of lumen reduction at the location of the narrowing, such that a localized region based on the location of the narrowing and the branch locations is determined;
accessing or acquiring non-invasively acquired local blood flow information for at least one or more vessels proximal to the narrowing;
quantifying a pressure drop across the narrowing based on the reduced section of the blood vessel and the acquired blood flow using a computational fluid dynamics model configured to receive the geometry of the blood vessel and the blood flow information;
calculating a numeric value quantifying a myocardial fractional flow reserve based on the pressure drop; and
generating and outputting for review at least the calculated numeric value quantifying the myocardial fractional flow reserve.

10. The one or more non-transitory computer-readable media of claim 9 , wherein the coronary-specific anatomical information further comprises one or more of a location of a vessel tree, a percentage of lumen reduction, or stenosis composition.

11. The one or more non-transitory computer-readable media of claim 9 , wherein the blood flow information comprises a flow boundary condition used in the computational fluid dynamics model.

12. The one or more non-transitory computer-readable media of claim 9 , wherein the one or more routines, when executed by the microprocessor, cause further acts to be performed comprising:
accessing a set of computed tomography (CT) image data;
determining a cardiac phase of interest using the CT image data;
segmenting the coronary arteries from one or more CT images at the cardiac phase of interest; and
deriving the coronary-specific anatomical information based at least on the segmented coronary arteries.

13. The one or more non-transitory computer-readable media of claim 12 , wherein the one or more routines, when executed by the microprocessor, cause further acts to be performed comprising:
accessing a set of ultrasound data;
registering the ultrasound data based on the cardiac phase of interest;
identifying an ultrasound volume of interest based on the volumetric coronary vasculature images;
generating a set of velocity data for the ultrasound volume of interest; and
estimating at least the blood flow information using the set of velocity data.

14. The one or more non-transitory computer-readable media of claim 9 , wherein the one or more routines, when executed by the microprocessor, cause further acts to be performed comprising:
accessing a set of interventional image data;
determining a cardiac phase of interest using the image data;
segmenting the coronary arteries from one or more images at the cardiac phase of interest; and
deriving the coronary-specific anatomical information based at least on the segmented coronary arteries.

15. The one or more non-transitory computer-readable media of claim 14 , wherein the one or more routines, when executed by the microprocessor, cause further acts to be performed comprising:
accessing a set of ultrasound data;
registering the ultrasound data based on the cardiac phase of interest;
identifying an ultrasound volume of interest based on the volumetric coronary vasculature images;
generating a set of velocity data for the ultrasound volume of interest; and
estimating at least the blood flow information using the set of velocity data.

Assignees

• Edic Peter Michael
• Senzig Robert Franklin
• Thomenius Kai Erik
• Gray Steven James
• Langan David Allen
• Venugopal Prem
• Fowlkes Jeffrey Brian
• Gen Electric

Inventors

• Edic Peter Michael
• Senzig Robert Franklin
• Thomenius Kai Erik
• Gray Steven James
• Langan David Allen
• Venugopal Prem
• Fowlkes Jeffrey Brian

Classifications

• G16H50/30

  for calculating health indices; for individual health risk assessment · CPC title

• G06T7/0012

  Biomedical image inspection · CPC title

• A61B6/4078

  Fan-beams · CPC title

• A61B5/02007

  Evaluating blood vessel condition, e.g. elasticity, compliance · CPC title

• A61B8/5284

  involving retrospective matching to a physiological signal · CPC title