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 for each individual in a tuning population based on comparisons between non-invasively computed and invasively obtained blood flow characteristic values for individuals in the tuning population;

testing the tuned boundary condition function parameter value for each individual in a testing population different from the tuning population based on comparisons between non-invasively computed and invasively obtained blood flow characteristic values for individuals in the testing population;

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:

for each individual in the 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 non-invasively computed blood flow characteristic value, until the value of the at least one accuracy metric reaches a threshold or target value.

3. The system of claim 2 , 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 non-invasively computed 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.

4. The system of claim 3 , wherein the system is further configured for:

determining unique boundary conditions tuning characteristics for the at least one anatomical location among the first anatomical location and the plurality of additional anatomical locations.

5. 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 and the generated patient-specific anatomical model.

6. The system of claim 5 , 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.

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

8. 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 for each individual in a tuning population based on comparisons between non-invasively computed and invasively obtained blood flow characteristic values for individuals in the tuning population;

testing the tuned boundary condition function parameter value for each individual in a testing population different from the tuning population based on comparisons between non-invasively computed and invasively obtained blood flow characteristic values for individuals in the testing population;

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.

9. The method of claim 8 , the method further comprising, for each individual in the 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 non-invasively computed blood flow characteristic value, until the value of the at least one accuracy metric reaches a desired threshold or target value.

10. The method of claim 9 , the method further comprising, for each individual in the tuning population:

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

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 non-invasively 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.

11. The method of claim 10 , further comprising:

determining unique boundary conditions tuning characteristics for the at least one anatomical location among the first anatomical location and the plurality of additional anatomical locations.

12. The method of claim 8 , further comprising:

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

13. The method of claim 12 , 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.

14. The method of claim 8 , wherein the computed and invasively obtained blood flow characteristic values include fractional flow reserve values.

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

tuning a boundary condition function parameter value for each individual in a tuning population based on comparisons between non-invasively computed and invasively obtained blood flow characteristic values for individuals in the tuning population;

testing the tuned boundary condition function parameter value for each individual in a testing population different from the tuning population based on comparisons between non-invasively computed and invasively obtained blood flow characteristic values for individuals in the testing population;

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.

16. The non-transitory computer readable medium of claim 15 , the operations further comprising:

for each individual in the 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 non-invasively computed blood flow characteristic value, until the at least one accuracy metric reaches a desired threshold or target value.

17. The non-transitory computer readable medium of claim 16 , the operations 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 non-invasively computed 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.

18. The non-transitory computer readable medium of claim 17 , the operations further comprising:

determining unique boundary conditions tuning characteristics for the at least one anatomical location among the first anatomical location and the plurality of additional anatomical locations.

19. The non-transitory computer readable medium of claim 15 , the operations further comprising:

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

20. The non-transitory computer readable medium of claim 19 , 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.