Method and system for modeling blood flow with boundary conditions for optimized diagnostic performance

1. A system for modeling blood flow for a patient, the system comprising at least one computer system configured to execute a method, the method comprising:

tuning a boundary condition function parameter value by, for each individual in a tuning population:

retrieving, using at least one processor, an invasively obtained blood flow characteristic value of the individual in the tuning population;

non-invasively computing, using at least one processor, a blood flow characteristic value based at least in part on the boundary condition function parameter value;

comparing the non-invasively computed blood flow characteristic value to the invasively obtained blood flow characteristic value to calculate the value of at least one accuracy metric; and

iteratively: (1) updating the boundary condition function parameter value, and (2) recomputing the computed blood flow characteristic value, until the value of the at least one accuracy metric reaches a threshold or target value;

testing the tuned boundary condition function parameter value by, for each individual in a testing population different from the tuning population;

non-invasively computing a blood flow characteristic value based at least in part on the tuned boundary condition function parameter value;

retrieving an invasively obtained blood flow characteristic value from of the individual in the testing population; and

using at least one processor, comparing the invasively obtained blood flow characteristic value to the non-invasively computed blood flow characteristic value;

generating a patient-specific anatomical model representing at least a portion of anatomy of a patient not in the tuning population or the testing population;

using the tuned, tested, boundary condition function parameter value and the generated patient-specific anatomical model to compute a patient-specific blood flow characteristic value for the patient not in either the tuning population or the testing population; and

outputting the generated patient-specific anatomical model and the computed patient-specific blood flow characteristic value.

2. The system of claim 1 , wherein the system is further configured for:

reducing a difference between the computed blood flow characteristic value and the invasively obtained blood flow characteristic value for each individual in the tuning population.

3. The system of claim 2 , wherein the reducing of the difference between the computed blood flow characteristic value and the invasively obtained blood flow characteristic value is at a plurality of anatomical locations for each individual in the tuning population.

4. The system of claim 1 , wherein the system is further configured for:

for each individual in the tuning population:

retrieving, using the at least one processor, the invasively obtained blood flow characteristic value from the individual in the tuning population at a first anatomical location of the individual in the tuning population; and

retrieving, using at least one processor, a plurality of additional invasively obtained blood flow characteristic values at a plurality of additional anatomical locations of the individual in the tuning population,

wherein the computing the blood flow characteristic value for each individual in the tuning population is based at least in part on a boundary condition function parameter value at at least one anatomical location among the first anatomical location and the plurality of additional anatomical locations.

5. The system of claim 4 , wherein the system is further configured for:

determining unique boundary conditions tuning characteristics for the at least one anatomical location.

6. The system of claim 1 , wherein the system is further configured for:

storing the tuned and tested boundary condition function parameter value in a database.

7. The system of claim 1 , wherein the system is further configured for:

generating a patient-specific boundary conditions model based on the tuned, tested boundary condition function parameter value.

8. The system of claim 7 , where the patient-specific boundary conditions model represents boundaries in at least a portion of an aorta and at least a portion of a plurality of coronary arteries emanating from the portion of the aorta.

9. The system of claim 7 , wherein the patient-specific boundary conditions model is further based on the generated patient-specific anatomical model.

10. The system of claim 1 , wherein the computed and invasively obtained blood flow characteristic values include fractional flow reserve values.

11. A method for modeling blood flow for a patient using at least one computer system, the method comprising:

tuning a boundary condition function parameter value by, for each individual in a tuning population:

retrieving, using at least one processor, an invasively obtained blood flow characteristic value of the individual in the tuning population;

non-invasively computing, using at least one processor, a blood flow characteristic value based at least in part on the boundary condition function parameter value;

comparing the non-invasively computed blood flow characteristic value to the invasively obtained blood flow characteristic value to calculate the value of at least one accuracy metric; and

iteratively: (1) updating the boundary condition function parameter value, and (2) recomputing the computed blood flow characteristic value, until the value of the at least one accuracy metric reaches a desired threshold or target value;

testing the tuned boundary condition function parameter value by, for each individual in a testing population different from the tuning population;

non-invasively computing a blood flow characteristic value based at least in part on the tuned boundary condition function parameter value;

retrieving an invasively obtained blood flow characteristic value of the individual in the testing population; and

using at least one processor, comparing the invasively obtained blood flow characteristic value to the non-invasively computed blood flow characteristic value;

generating a patient-specific anatomical model representing at least a portion of anatomy of a patient not in the tuning population or the testing population;

using the tuned, tested boundary condition function parameter value and the generated patient-specific anatomical model to compute a patient-specific blood flow characteristic value for the patient not in either the tuning population or the testing population; and

outputting the generated patient-specific anatomical model and the computed patient-specific blood flow characteristic value.

12. The method of claim 11 , further comprising:

for each individual in the tuning population, reducing a difference between the computed blood flow characteristic value and the invasively obtained blood flow characteristic value.

13. The method of claim 12 , wherein the reducing of the difference between the computed blood flow characteristic value and the invasively obtained blood flow characteristic value is at a plurality of anatomical locations of the individual in the tuning population.

14. The method of claim 11 , the method further comprising, for each individual in the tuning population:

retrieving the first invasively obtained blood flow characteristic value from a first anatomical location of the individual in the tuning population;

retrieving, using the at least one processor, a plurality of additional invasively obtained blood flow characteristic values at a plurality of additional anatomical locations of the individual in the tuning population,

wherein the computed blood flow characteristic is computed based at least in part on a boundary condition function parameter value at at least one anatomical location among the first anatomical location and the plurality of additional anatomical locations.

15. The method of claim 14 , further comprising:

determining unique boundary conditions tuning characteristics for the at least one anatomical location.

16. The method of claim 11 , further comprising:

storing the tuned boundary condition function parameter value in a database.

17. The method of claim 11 , further comprising:

generating a patient specific boundary conditions model based on the tuned boundary condition function parameter value.

18. The method of claim 17 , wherein the patient specific boundary conditions model represents boundaries in at least a portion of an aorta and at least a portion of a plurality of coronary arteries emanating from the portion of the aorta.

19. The method of claim 17 , wherein the patient specific boundary conditions model is further based on the patient-specific anatomical model.

20. The method of claim 11 , wherein the computed and invasively obtained blood flow characteristic values include fractional flow reserve values.

21. A non-transitory computer readable medium for use on at least one computer system containing computer-executable programming instructions for performing a method for modeling blood flow for a patient, the method comprising:

tuning a boundary condition function parameter value by, for each individual in a tuning population:

retrieving, using at least one processor, an invasively obtained blood flow characteristic value of the individual in the tuning population;

non-invasively computing, using at least one processor, a blood flow characteristic value based at least in part on the boundary condition function parameter value;

comparing the non-invasively computed blood flow characteristic value to the invasively obtained blood flow characteristic value to calculate the value of at least one accuracy metric; and

iteratively: (1) updating the boundary condition function parameter value, and (2) recomputing the computed blood flow characteristic value, until the at least one accuracy metric reaches a desired threshold or target value;

testing the tuned boundary condition function parameter value by, for each individual in a testing population different from the tuning population;

non-invasively computing a blood flow characteristic value based at least in part on the tuned boundary condition function parameter value;

retrieving an invasively obtained blood flow characteristic value of the individual in the testing population; and

using at least one processor, comparing the invasively obtained blood flow characteristic value to the non-invasively computed blood flow characteristic value;

generating a patient-specific anatomical model representing at least a portion of anatomy of a patient not in the tuning population or the testing population;

using the tuned, tested boundary condition function parameter value and the generated patient-specific anatomical model to compute a patient-specific blood flow characteristic value for the patient not in either the tuning population or the testing population; and

outputting the generated patient-specific anatomical model and the computed patient-specific blood flow characteristic value.

22. The non-transitory computer readable medium of claim 21 , the method further comprising:

for each individual in the tuning population, reducing a difference between the computed blood flow characteristic value and the invasively obtained blood flow characteristic value.

23. The non-transitory computer readable medium of claim 22 , wherein the reducing of the difference between the computed blood flow characteristic value and the invasively obtained of blood flow characteristic value is at a plurality of anatomical locations for each individual in the tuning population.

24. The non-transitory computer readable medium of claim 21 , the method further comprising:

for each individual in the tuning population:

retrieving, using the at least one processor, the invasively obtained blood flow characteristic value from the individual in the tuning population at a first anatomical location of the individual in the tuning population; and

retrieving, using at least one processor, a plurality of additional invasively obtained blood flow characteristic values at a plurality of additional anatomical locations of the individual in the tuning population,

wherein the computing the blood flow characteristic value for each individual in the tuning population is based at least in part on a boundary condition function parameter value at at least one anatomical location among the first anatomical location and the plurality of additional anatomical locations.

25. The non-transitory computer readable medium of claim 24 , wherein the method further comprises:

determining unique boundary conditions tuning characteristics for the at least one anatomical location.

26. The non-transitory computer readable medium of claim 21 , wherein the method further comprises:

storing the tuned and tested boundary condition function parameter value in a database.

27. The non-transitory computer readable medium of claim 21 , wherein the method further compromises:

generating a patient-specific boundary conditions model based on the tuned, tested boundary condition function parameter value.

28. The non-transitory computer readable medium of claim 27 , where the patient-specific boundary conditions model represents boundaries in at least a portion of an aorta and at least a portion of a plurality of coronary arteries emanating from the portion of the aorta.

29. The non-transitory computer readable medium of claim 27 , wherein the patient-specific boundary conditions model is further based on the patient-specific anatomical model.