Synthetic data-driven hemodynamic determination in medical imaging
US-2016148371-A1 · May 26, 2016 · US
US11869669B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11869669-B2 |
| Application number | US-202218068604-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 20, 2022 |
| Priority date | Mar 1, 2013 |
| Publication date | Jan 9, 2024 |
| Grant date | Jan 9, 2024 |
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Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.
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What is claimed is: 1. A vascular modeling method, comprising: receiving patient-specific data imaging data of a vasculature of a patient; determining that a vessel of the vasculature of the patient includes a plaque; automatically segmenting the vessel of the patient that includes the plaque; generating a set of possible treatment options for at least a section of the patient's vasculature having energy losses exceeding a predetermined threshold level, wherein the set of possible treatment options includes all feasible treatment options for the at least the section; evaluating the set of possible treatment options; and generating a patient-specific treatment recommendation based on the evaluating the set of possible treatment options. 2. The method of claim 1 , wherein the plaque is automatically segmented based on a contrast of the plaque as compared to a wall of the vessel. 3. The method of claim 1 , wherein the determining that the vessel of the vasculature of the patient includes the plaque includes comparing an intensity value of the patient-specific imaging data to a threshold value. 4. The method of claim 1 , wherein the evaluating the set of possible treatment options includes applying an objective function. 5. The method of claim 4 , wherein the objective function maximizes flow or minimizes pressure changes. 6. The method of claim 5 , wherein the objective function penalizes undesirable characteristics. 7. The method of claim 4 , wherein the objective function identifies a local optimum. 8. The method of claim 1 , wherein the patient-specific treatment recommendation includes a stent or a bypass graft, the method further comprising displaying a type, location, and/or orientation of the stent or the bypass graft. 9. A system for vascular modeling, the system comprising: at least one memory having processor-readable instructions stored therein; and at least one processor configured to access the memory and execute the processor-readable instructions, which when executed by the processor configures the processor to perform a plurality of operations, the operations comprising: receiving patient-specific data imaging data of a vasculature of a patient; determining that a vessel of the vasculature of the patient includes a plaque; automatically segmenting the vessel of the patient that includes the plaque; generating a set of possible treatment options for at least a section of the patient's vasculature having energy losses exceeding a predetermined threshold level, wherein the set of possible treatment options includes all feasible treatment options for the at least the section; evaluating the set of possible treatment options; and generating a patient-specific treatment recommendation based on the evaluating the set of possible treatment options. 10. The system of claim 9 , wherein the plaque is automatically segmented based on a contrast of the plaque as compared to a wall of the vessel. 11. The system of claim 9 , wherein the determining that the vessel of the vasculature of the patient includes the plaque includes comparing an intensity value of the patient-specific imaging data to a threshold value. 12. The system of claim 9 , wherein the evaluating the set of possible treatment options includes applying an objective function. 13. The system of claim 12 , wherein the objective function maximizes flow or minimizes pressure changes. 14. The system of claim 13 , wherein the objective function penalizes undesirable characteristics. 15. A non-transitory computer readable medium storing computer program instructions for planning treatment for vascular modeling, the computer program instructions when executed by a processor causes the processor to perform operations comprising: receiving patient-specific data imaging data of a vasculature of a patient; determining that a vessel of the vasculature of the patient includes a plaque; automatically segmenting the vessel of the patient that includes the plaque; generating a set of possible treatment options for at least a section of the patient's vasculature having energy losses exceeding a predetermined threshold level, wherein the set of possible treatment options includes all feasible treatment options for the at least the section; evaluating the set of possible treatment options; and generating a patient-specific treatment recommendation based on the evaluating the set of possible treatment options. 16. The non-transitory computer readable medium of claim 15 , wherein the plaque is automatically segmented based on a contrast of the plaque as compared to a wall of the vessel. 17. The non-transitory computer readable medium of claim 15 , wherein the determining that the vessel of the vasculature of the patient includes the plaque includes comparing an intensity value of the patient-specific imaging data to a threshold value. 18. The non-transitory computer readable medium of claim 15 , wherein the evaluating the set of possible treatment options includes applying an objective function. 19. The non-transitory computer readable medium of claim 18 , wherein the objective function maximizes flow or minimizes pressure changes. 20. The non-transitory computer readable medium of claim 19 , wherein the objective function penalizes undesirable characteristics.
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