# US 2021/0241920 A1 · Systems and methods for simulation of occluded arteries and optimization of occlusion-based treatments > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0241920 A1 - Document ID: US20210241920A1 - Status: Published application - Kind: A1 - Application number: 17/237,144 - Filed: 2021-04-22 - Published: 2021-08-05 - Earliest claimed: 2014-11-04 - Assignees: HeartFlow, Inc. - Applicants: HeartFlow, Inc. - Inventors: Sethuraman SANKARAN; Leo J. GRADY; Charles A. TAYLOR; Christopher K. ZARINS - Web page: https://patentgrep.com/patent/US20210241920A1 ## CPC - G16H 50/50: for simulation or modelling of medical disorders - 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)} - G16H 20/40: relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture - G16H 40/67: for remote operation - G16Z 99/00: Subject matter not provided for in other main groups of this subclass - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G16Z: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR ## Abstract Systems and methods are disclosed for simulation of occluded arteries and/or optimization of occlusion-based treatments. One method includes obtaining a patient-specific anatomic model of a patient's vasculature; obtaining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model; obtaining a post-treatment computational model by modifying portions of the initial computational model based on an occlusion-based treatment; generating a pre-treatment blood flow characteristic using the initial computational model or computing a post-treatment blood flow using the post-treatment computational model; and outputting a representation of the pre-treatment blood flow characteristic or the post-treatment blood flow characteristic. ## Claims ### Claim at position 1 1-20. (canceled) ### Claim 21 A computer-implemented method of planning an occlusive procedure, the method comprising: obtaining image data of at least a portion of a patient's vasculature; generating a patient-specific anatomic model of the portion of the patient's vasculature based on the image data by reconstructing at least one centerline and at least one corresponding lumen of at least one blood vessel of the patient's vasculature visible in the image data; determining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model, the initial computational model including a pre-treatment boundary condition; determining a pre-treatment value for a blood flow characteristic by performing a calculation of blood flow using the initial computational model; determining a patient-specific target value for the blood flow characteristic; prior to treatment of the patient, obtaining one or more candidate sites for the occlusive procedure; prior to treatment of the patient, and for each respective candidate site of the one or more candidate sites, performing a candidate site evaluation that includes: determining a post-treatment boundary condition by modifying the patient-specific anatomic model to include one or more cross-sectional outlets, surfaces, or boundaries in modeled vasculature of the patient-specific anatomic model corresponding to an occlusion at the respective candidate site by removing a portion of the patient's vasculature from the patient-specific anatomical model that is downstream of a plane perpendicular to the at least one centerline at the respective candidate site; updating the initial computational model based on the post-treatment boundary condition in the modified patient-specific anatomic model; and noninvasively determining a respective post-treatment value of the blood flow characteristic value by performing a calculation of blood flow using the updated computational model; determining whether the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value; in response to determining that the respective post-treatment value does not meet the patient-specific target value, iteratively identifying a new candidate site and repeating the candidate site evaluation for the new candidate site until the respective post-treatment value of the blood flow characteristics meets or exceeds the target value; and in response to determining that the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value, generating a plan for the occlusive procedure that includes a recommendation for selection of a treatment site corresponding to the respective post-treatment value. ### Claim 22 (depends on 21) The computer-implemented method of claim 21, wherein the calculation of blood flow includes Navier-Stokes equations, reduced order models, or machine learning methods. ### Claim 23 (depends on 21) The computer-implemented method of claim 21, wherein the post-treatment boundary condition is based on circulatory resistance or organ demand at a location of the patient's vasculature associated with the respective candidate site. ### Claim 24 (depends on 21) The computer-implemented method of claim 21, wherein the occlusive procedure includes an amputation, an embolization therapy, or a vascular resection. ### Claim 25 (depends on 21) The computer-implemented method of claim 21, further comprising: determining one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature created by stoppage of blood flow through the patient's vasculature or removal of a portion of the patient's vasculature at each respective candidate site, wherein the post-treatment boundary condition is a boundary condition of at least one of the determined one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature. ### Claim 26 (depends on 21) The computer-implemented method of claim 21, wherein the blood flow characteristic includes organ perfusion or blood pressure. ### Claim 27 (depends on 21) The computer-implemented method of claim 21, wherein identifying the new candidate site includes using a Nelder-Mead algorithm. ### Claim 28 (depends on 21) The computer-implemented method of claim 21, wherein determining whether the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value includes evaluating a cost function. ### Claim 29 (depends on 28) The computer-implemented method of claim 28, wherein: the cost function is defined as a difference in tissue demand and tissue supply; and the target value is determined based on providing tissue supply that exceeds tissue demand for the patient. ### Claim 30 A system for planning an occlusive procedure, comprising: at least one memory storing instructions; and at least one processor operatively connected to the at least one memory, and configured to execute the instruction to perform operations including: obtaining image data of at least a portion of a patient's vasculature; generating a patient-specific anatomic model of the portion of the patient's vasculature based on the image data by reconstructing at least one centerline and at least one corresponding lumen of at least one blood vessel of the patient's vasculature visible in the image data; determining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model, the initial computational model including a pre-treatment boundary condition; determining a pre-treatment value for a blood flow characteristic by performing a calculation of blood flow using the initial computational model; determining a patient-specific target value for the blood flow characteristic; prior to treatment of the patient, obtaining one or more candidate sites for the occlusive procedure; prior to treatment of the patient, and for each respective candidate site of the one or more candidate sites, performing a candidate site evaluation that includes: determining a post-treatment boundary condition by modifying the patient-specific anatomic model to include one or more cross-sectional outlets, surfaces, or boundaries in modeled vasculature of the patient-specific anatomic model corresponding to an occlusion at the respective candidate site by removing a portion of the patient's vasculature from the patient-specific anatomical model that is downstream of a plane perpendicular to the at least one centerline at the respective candidate site; updating the initial computational model based on the post-treatment boundary condition in the modified patient-specific anatomic model; and noninvasively determining a respective post-treatment value of the blood flow characteristic value by performing a calculation of blood flow using the updated computational model; determining whether the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value; in response to determining that the respective post-treatment value does not meet the patient-specific target value, iteratively identifying a new candidate site and repeating the candidate site evaluation for the new candidate site until the respective post-treatment value of the blood flow characteristics meets or exceeds the target value; and in response to determining that the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value, generating a plan for the occlusive procedure that includes a recommendation for selection of a treatment site corresponding to the respective post-treatment value. ### Claim 31 (depends on 30) The system of claim 30, wherein the calculation of blood flow includes Navier-Stokes equations, reduced order models, or machine learning methods. ### Claim 32 (depends on 30) The system of claim 30, wherein the post-treatment boundary condition is based on circulatory resistance or organ demand at a location of the patient's vasculature associated with the respective candidate site. ### Claim 33 (depends on 30) The system of claim 30, wherein the occlusive procedure includes an amputation, an embolization therapy, or a vascular resection. ### Claim 34 (depends on 30) The system of claim 30, wherein: the operations further include determining one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature created by stoppage of blood flow through the patient's vasculature or removal of a portion of the patient's vasculature at each respective candidate site; and the post-treatment boundary condition is a boundary condition of at least one of the determined one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature. ### Claim 35 (depends on 30) The system of claim 30, wherein the blood flow characteristic includes organ perfusion or blood pressure. ### Claim 36 (depends on 30) The system of claim 30, wherein identifying the new candidate site includes using a Nelder-Mead algorithm. ### Claim 37 (depends on 30) The system of claim 30, wherein: determining whether the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value includes evaluating a cost function; the cost function is defined as a difference in tissue demand and tissue supply; and the target value is determined based on providing tissue supply that exceeds tissue demand for the patient. ### Claim 38 A non-transitory computer-readable medium comprising instructions that are executable by a processor to perform operations including: obtaining image data of at least a portion of a patient's vasculature; generating a patient-specific anatomic model of the portion of the patient's vasculature based on the image data by reconstructing at least one centerline and at least one corresponding lumen of at least one blood vessel of the patient's vasculature visible in the image data; determining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model, the initial computational model including a pre-treatment boundary condition; determining a pre-treatment value for a blood flow characteristic by performing a calculation of blood flow using the initial computational model; determining a patient-specific target value for the blood flow characteristic; prior to treatment of the patient, obtaining one or more candidate sites for the occlusive procedure; prior to treatment of the patient, and for each respective candidate site of the one or more candidate sites, performing a candidate site evaluation that includes: determining a post-treatment boundary condition by modifying the patient-specific anatomic model to include one or more cross-sectional outlets, surfaces, or boundaries in modeled vasculature of the patient-specific anatomic model corresponding to an occlusion at the respective candidate site by removing a portion of the patient's vasculature from the patient-specific anatomical model that is downstream of a plane perpendicular to the at least one centerline at the respective candidate site; updating the initial computational model based on the post-treatment boundary condition in the modified patient-specific anatomic model; and noninvasively determining a respective post-treatment value of the blood flow characteristic value by performing a calculation of blood flow using the updated computational model; determining whether the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value; in response to determining that the respective post-treatment value does not meet the patient-specific target value, iteratively identifying a new candidate site and repeating the candidate site evaluation for the new candidate site until the respective post-treatment value of the blood flow characteristics meets or exceeds the target value; and in response to determining that the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value, generating a plan for the occlusive procedure that includes a recommendation for selection of a treatment site corresponding to the respective post-treatment value. ### Claim 39 (depends on 38) The non-transitory computer-readable medium of claim 38, wherein: the operations further include determining one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature created by stoppage of blood flow through the patient's vasculature or removal of a portion of the patient's vasculature at each respective candidate site; and the post-treatment boundary condition is a boundary condition of at least one of the determined one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature. ### Claim 40 (depends on 38) The non-transitory computer-readable medium of claim 38, wherein: determining whether the respective post-treatment value of the blood flow characteristics meets or exceeds the patient-specific target value includes evaluating a cost function; the cost function is defined as a difference in tissue demand and tissue supply; and the target value is determined based on providing tissue supply that exceeds tissue demand for the patient.