SYSTEMS AND METHODS FOR EMBOLISM PREDICTION USING EMBOLUS SOURCE AND DESTINATION PROBABILITIES

• US 20200135338A1
• Filed: 12/26/2019
• Published: 04/30/2020
• Est. Priority Date: 01/14/2015
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: GRADY, Leo, CHOI, Gilwoo, TAYLOR, Charles A., ZARINS, Christopher K.
• Granted Patent: US 11,646,118 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

Systems and methods are disclosed for determining a patient risk assessment or treatment plan based on emboli dislodgement and destination. One method includes receiving a patient-specific anatomic model generated from patient-specific imaging of at least a portion of a patient'"'"'s vasculature; determining or receiving a location of interest in the patient-specific anatomic model of the patient'"'"'s vasculature; using a computing processor for calculating blood flow through the patient-specific anatomic model to determine blood flow characteristics through at least the portion of the patient'"'"'s vasculature of the patient-specific anatomic model downstream from the location of interest; and using a computing processor for particle tracking through the simulated blood flow to determine a destination probability of an embolus originating from the location of interest in the patient-specific anatomic model, based on the determined blood flow characteristics.

Claims

1-20. -20. (canceled)

21. A computer-implemented method of determining a patient risk assessment or treatment plan based on emboli dislodgement and destination, the method comprising:

receiving a patient-specific anatomic model generated from patient-specific imaging of at least a portion of a patient'"'"'s vasculature;

determining or receiving a location of interest in the patient-specific anatomic model of the patient'"'"'s vasculature;

computing, using a computing processor, a blood flow characteristic of blood flow through at least the portion of the patient-specific anatomic model downstream from the location of interest;

determining, using the computing processor, a velocity field of the computed blood flow; and

computing, using the computing processor, a destination probability of an embolus originating from the location of interest in the patient-specific anatomic model, based on the computed blood flow and the determined velocity field; and

computing, using the computing processor, a likelihood of the location of interest being an embolic source, based on the determined destination probability.

22. The computer-implemented method of claim 21, further comprising:

determining, in the patient'"'"'s vasculature, a location of a plaque, a location meeting a predetermined criteria of pathology, or a location of possible vascular shedding; and

determining or receiving the location of interest in the patient-specific anatomic model based on the determined location of plaque, determined location meeting the predetermined criteria of pathology, or the location of possible vascular shedding.

23. The computer-implemented method of claim 21, further comprising:

determining a target location in the patient'"'"'s vasculature, wherein the destination probability is a probability that the embolus traveling through the patient'"'"'s circulatory system reaches the target location, based on the computed blood flow characteristic.

24. The computer-implemented method of claim 21, further comprising:

determining a vulnerable location of embolism based on the determined destination probability.

25. The computer-implemented method of claim 21, further comprising:

determining an association between a target location in the patient-specific anatomic model, the destination probability, and the location of interest; and

outputting a patient risk assessment or treatment plan based on the determined association.

26. The computer-implemented method of claim 25, further comprising:

determining, for a second location of interest, a second destination probability of an embolus associated with the second location of interest;

determining an association between the target location in the patient-specific anatomic model, the destination probability, and the second location of interest;

comparing the association between the target location in the patient-specific anatomic model, the destination probability, and the location of interest, and the association between the target location in the patient-specific anatomic model, the destination probability, and the second location of interest; and

determining or generating a display or a treatment recommendation based on the comparison.

27. The computer-implemented method of claim 21, further comprising:

determining patient risk of a disease, based on the computed destination probability of the embolus, wherein the patient risk of the disease includes patient risk of a disease associated with a location in the patient'"'"'s vasculature.

28. The computer-implemented method of claim 27, wherein the risk of disease includes a risk of embolism, cognitive impairment, stroke, transient ischemic attack, pulmonary embolism, renal embolism, or a combination thereof.

29. A computer-implemented method of determining a patient risk assessment or treatment plan based on emboli dislodgement and destination, the method comprising:

receiving a patient-specific anatomic model generated from patient-specific imaging of at least a portion of a patient'"'"'s vasculature;

determining or receiving a location of interest in the patient-specific anatomic model of the patient'"'"'s vasculature;

computing, using a computing processor, a blood flow characteristic of blood flow through at least the portion of the patient-specific anatomic model downstream from the location of interest;

determining, using the computing processor, a velocity field of the computed blood flow; and

computing, using the computing processor, a destination probability of an embolus originating from the location of interest in the patient-specific anatomic model, based on the computed blood flow and the determined velocity field; and

computing, using the computing processor, a likelihood of the location of interest being an embolic source, based on the determined destination probability.

30. The system of claim 29, wherein the system is further configured for:

determining, in the patient'"'"'s vasculature, a location of a plaque, a location meeting a predetermined criteria of pathology, or a location of possible vascular shedding; and

determining or receiving the location of interest in the patient-specific anatomic model based on the determined location of plaque, determined location meeting the predetermined criteria of pathology, or the location of possible vascular shedding.

31. The system of claim 29, wherein the system is further configured for:

determining a target location in the patient'"'"'s vasculature, wherein the destination probability is a probability that the embolus traveling through the patient'"'"'s circulatory system reaches the target location, based on the computed blood flow characteristic.

32. The system of claim 29, wherein the system is further configured for:

determining a vulnerable location of embolism based on the determined destination probability.

33. The system of claim 29, wherein the system is further configured for:

determining an association between a target location in the patient-specific anatomic model, the destination probability, and the location of interest; and

outputting a patient risk assessment or treatment plan based on the determined association.

34. The system of claim 33, wherein the system is further configured for:

determining, for a second location of interest, a second destination probability of an embolus associated with the second location of interest;

determining an association between the target location in the patient-specific anatomic model, the destination probability, and the second location of interest;

comparing the association between the target location in the patient-specific anatomic model, the destination probability, and the location of interest, and the association between the target location in the patient-specific anatomic model, the destination probability, and the second location of interest; and

determining or generating a display or a treatment recommendation based on the comparison.

35. The system of claim 29, wherein the system is further configured for:

determining patient risk of a disease, based on the destination probability of the embolus, wherein the patient risk of the disease includes patient risk of a disease associated with a location in the patient'"'"'s vasculature.

36. The system of claim 35, wherein the risk of disease includes a risk of embolism, cognitive impairment, stroke, transient ischemic attack, pulmonary embolism, renal embolism, or a combination thereof.

37. A non-transitory computer readable medium for use on a computer system containing computer-executable programming instructions for performing a method of determining a patient risk assessment or treatment plan based on emboli dislodgement and destination, the method comprising:

receiving a patient-specific anatomic model generated from patient-specific imaging of at least a portion of a patient'"'"'s vasculature;

determining or receiving a location of interest in the patient-specific anatomic model of the patient'"'"'s vasculature;

computing, using a computing processor, a blood flow characteristic of blood flow through at least the portion of the patient-specific anatomic model downstream from the location of interest;

determining, using the computing processor, a velocity field of the computed blood flow; and

computing, using the computing processor, a destination probability of an embolus originating from the location of interest in the patient-specific anatomic model, based on the computed blood flow and the determined velocity field; and

computing, using the computing processor, a likelihood of the location of interest being an embolic source, based on the determined destination probability.

38. The non-transitory computer readable medium of claim 37, the method further comprising:

determining, in the patient'"'"'s vasculature, a location of a plaque, a location meeting a predetermined criteria of pathology, or a location of possible vascular shedding; and

determining or receiving the location of interest in the patient-specific anatomic model based on the determined location of plaque, determined location meeting the predetermined criteria of pathology, or the location of possible vascular shedding.

39. The non-transitory computer readable medium of claim 37, the method further comprising:

determining a target location in the patient'"'"'s vasculature, wherein the destination probability is a probability that the embolus traveling through the patient'"'"'s circulatory system reaches the target location, based on the computed blood flow characteristic.

40. The non-transitory computer readable medium of claim 39, the method further comprising:

determining a vulnerable location of embolism based on the determined destination probability.