Method and system for patient-specific modeling of blood flow
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 patients 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.
1. A computer-implemented method for assessing cardiac hemodynamic information, comprising:
accessing or acquiring volumetric coronary vascular images depicting a geometry of a location of a patient's blood vessel;
generating, using a computer, an anatomical model of the geometry of the location of the patient's blood vessel from the accessed or acquired volumetric coronary vascular images;
obtaining a solid model by trimming the anatomical model at the geometry of the location of the patient's blood vessel and identifying a location of the solid model corresponding to the location of the patient's blood vessel;
determining a patient-specific boundary condition at the location of the solid model;
acquiring, based on the patient-specific boundary condition, local blood flow information of blood flow through the patient's blood vessel at the location;
estimating, using a computer, a myocardial fractional flow reserve for a selected segment of the coronary vasculature, wherein the estimation is based at least in part on the anatomical model and the acquired local blood flow information; and
determining a visual indicator of the myocardial fractional flow reserve for display, or determining a presence of a blood vessel narrowing or stenosis based on the myocardial fractional flow reserve.
2. The method of claim 1 , comprising:
receiving 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 anatomical model based at least in part on the segmented coronary arteries.
3. The method of claim 1 , comprising:
determining a cardiac phase of interest using a set of reconstructed image data;
segmenting the coronary arteries from one or more reconstructed images at the cardiac phase of interest; and
deriving the anatomical model based at least in part on the segmented coronary arteries.
4. The method of claim 1 , wherein the anatomical model further comprises a location or a topology of a vessel tree.
5. The method of claim 1 , wherein the location of the blood vessel comprises a stenotic lesion.
6. The method of claim 1 , wherein estimating the myocardial fractional flow reserve comprises providing at least the anatomical model and the local blood flow information to a computational fluid dynamics model.
7. The method of claim 6 , wherein the local blood flow information comprises a flow boundary condition used in the computational fluid dynamics model.
8. One or more non-transitory computer-readable media encoding one or more processor-executable routines, wherein the one or more routines cause acts to be performed comprising:
accessing or acquiring volumetric coronary vasculature images depicting a geometry of a location of a patient's blood vessel;
generating an anatomical model of the geometry of the location of the patient's blood vessel from the accessed or acquired volumetric coronary vascular images;
obtaining a solid model by trimming the anatomical model at the geometry of the location of the patient's blood vessel and identifying a location of the solid model corresponding to the location of the patient's blood vessel;
determining a patient-specific boundary condition at the location of the solid model;
acquiring, based on the patient-specific boundary condition, local blood flow information of blood flow through the patient's blood vessel at the location;
estimating a myocardial fractional flow reserve for a selected segment of the coronary vasculature, wherein the estimation is based at least in part on the anatomical model and the blood flow information; and
determining a visual indicator of the myocardial fractional flow reserve for display, or determining a presence of a blood vessel narrowing or stenosis based on the myocardial fractional flow reserve.
9. The one or more non-transitory computer-readable media of claim 8 , wherein the one or more routines cause further acts to be performed comprising:
receiving 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 of the CT image data at the cardiac phase of interest; and
deriving the anatomical model based at least in part on the segmented coronary arteries.
10. The one or more non-transitory computer-readable media of claim 8 , wherein the one or more routines cause further acts to be performed comprising:
determining a cardiac phase of interest using reconstructed image data;
segmenting the coronary arteries from one or more images of the reconstructed image data at the cardiac phase of interest; and
deriving the anatomical model based at least in part on the segmented coronary arteries.
11. The one or more non-transitory computer-readable media of claim 8 , wherein the anatomical model further comprises a location or a topology of a vessel tree.
12. The one or more non-transitory computer-readable media of claim 8 , wherein estimating the myocardial fractional flow reserve comprises providing at least the anatomical model and the local blood flow information to a computational fluid dynamics model.
13. The one or more non-transitory computer-readable media of claim 12 , wherein the local blood flow information comprises a flow boundary condition used in the computational fluid dynamics model.
14. A processor-based system, comprising:
a memory encoding one or more processor-executable routines:
a computer, wherein the computer when executing the one or more processor-executable routines is configured to:
access or acquire volumetric coronary vascular images depicting a geometry of a location of a patient's blood vessel;
generate an anatomical model of the geometry of the location of the patient's blood vessel from the accessed or acquired volumetric coronary vascular images;
obtain a solid model by trimming the anatomical model at the geometry of the location of the patient's blood vessel and identifying a location of the solid model corresponding to the location of the patient's blood vessel;
determine a patient-specific boundary condition at the location of the solid model;
acquire, based on the patient-specific boundary condition, local blood flow information of blood flow through the patient's blood vessel at the location;
estimate a myocardial fractional flow reserve for a selected segment of the coronary vasculature, wherein the estimation is based at least in part on the anatomical model and the local blood flow information; and
determine a visual indicator of the myocardial fractional flow reserve for display, or determining a presence of a blood vessel narrowing or stenosis based on the myocardial fractional flow reserve.
15. The processor-based system of claim 14 , wherein the computer when executing the one or more processor-executable routines is further configured to:
receive a set of computed tomography (CT) image data;
determine a cardiac phase of interest using the CT image data;
segment the coronary arteries from one or more CT images of the CT image data at the cardiac phase of interest; and
derive the anatomical model based at least in part on the segmented coronary arteries.
16. The processor-based system of claim 14 , wherein the computer when executing the one or more processor-executable routines is further configured to:
determine a cardiac phase of interest using reconstructed image data;
segment the coronary arteries from one or more images of the reconstructed image data at the cardiac phase of interest; and
derive the anatomical model based at least in part on the segmented coronary arteries.
17. The processor-based system of claim 14 , wherein the anatomical model further comprises a location or a topology of a vessel tree.
18. The processor-based system of claim 14 , wherein estimating the myocardial fractional flow reserve comprises providing at least the anatomical model and the local blood flow information to a computational fluid dynamics model.
19. The processor-based system of claim 18 , wherein the local blood flow information comprises a flow boundary condition used in the computational fluid dynamics model.
20. The processor-based system of claim 14 , wherein the location of the blood vessel comprises a stenotic lesion.