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BR-112021013537-B1 - METHOD FOR PATIENT-SPECIFIC MODELING OF HEMODYNAMIC PARAMETERS IN CORONARY ARTERIES

BR112021013537B1BR 112021013537 B1BR112021013537 B1BR 112021013537B1BR-112021013537-B1

Abstract

METHOD FOR PATIENT-SPECIFIC MODELING OF HEMODYNAMIC PARAMETERS IN CORONARY ARTERIES. This refers to computer-readable systems, methods, and means for patient-specific modeling of hemodynamic parameters in coronary arteries. Exemplary methods may include performing computational fluid dynamics simulations using a patient-specific anatomical coronary artery model derived from medical imaging data and patient-specific boundary conditions derived from a continuously recorded blood pressure waveform to determine patient-specific hemodynamic parameters in a patient's coronary arteries.

Inventors

  • Andrzej Kosior
  • Kryspin Mirota
  • Wojciech Tarnawski

Assignees

  • Hemolens Diagnostics Sp. z o.o

Dates

Publication Date
20260310
Application Date
20190111

Claims (20)

  1. 1. METHOD (100, 200, 400), comprising: receiving patient-specific anatomical structure data (102, 202, 302, 402, 502) and patient-specific physiological data (104, 210, 322, 406, 522), wherein the anatomical structure data comprise structural information about a patient's coronary arteries, and wherein the patient-specific physiological data comprise a continuously recorded blood pressure waveform; generating, based at least in part on the anatomical structure data, an anatomical model of at least one portion of the patient's coronary arteries (106, 204, 306, 308, 310, 312, 314, 316, 318, 320, 404, 506, 508, 510, 512, 514, 516, 518, 520); determine, based at least in part on the continuously recorded blood pressure waveform, boundary conditions for a computational fluid dynamics (CFD) simulation of blood flow in the anatomical model (108, 212, 334, 336, 338, 340, 408, 524, 526, 528, 530); simulate blood flow in the anatomical model using CFD and boundary conditions (110, 208, 214, 326, 328, 330, 342, 412, 536, 538, 540); and determine, based at least in part on the simulation, one or more hemodynamic parameters associated with the patient's coronary arteries (112, 214, 344, 414, 542), characterized by: the continuously recorded blood pressure waveform being from a non-invasive measurement, and in which determining the boundary conditions (108, 212, 334, 336, 338, 340, 408, 524, 526, 528, 530) comprises: determining, based at least in part on a blood circulation system model and the continuously recorded blood pressure waveform, volumetric blood flow rate data; determining, based at least in part on a cardiac chamber pressure-volume model and volumetric blood flow rate data, ventricular pressure data; determining, based at least in part on a coronary blood flow model, the continuously recorded blood pressure waveform and ventricular pressure data, coronary artery inflow data, and determining, based at least in part on a law of Allometric scale and coronary artery inflow data, coronary artery outflow data.
  2. 2. METHOD, according to claim 1, characterized in that the anatomical structure data are from a non-invasive measurement.
  3. 3. METHOD, according to claim 1, characterized in that the anatomical structure data are from a computed tomography angiogram.
  4. 4. METHOD, according to claim 1, characterized by the generation of the anatomical model (106) not including segmenting an aorta.
  5. 5. METHOD, according to claim 1, characterized in that the anatomical model is a model only of the patient's coronary arteries.
  6. 6. METHOD, according to claim 1, characterized in that the boundary conditions comprise inflow boundary conditions for the patient's coronary arteries and outflow boundary conditions for the patient's coronary arteries.
  7. 7. METHOD, according to claim 1, characterized by the blood circulation system model comprising at least one lumped parameter functional block selected from a lumped parameter functional block of (a) CR, (b) CRL and (c) RCRL shown below:
  8. 8. METHOD, according to claim 1, characterized by the pressure-volume model of cardiac chambers being a time-varying elastance model.
  9. 9. METHOD, according to claim 1, characterized by the coronary blood flow model comprising at least one lumped parameter functional block selected from lumped parameter functional blocks of (a) CRp, (b) CpR, (c) RCRp, (d) CpRp and (e) RCpRp, shown below:
  10. 10. METHOD, according to claim 1, characterized by the coronary blood flow model comprising a plurality of (e) functional blocks of concentrated RCpRp parameters shown below:
  11. 11. METHOD, according to claim 1, characterized in that a coronary flow state at the inlet is determined based at least in part on the lumped parameter block model of blood circulation system and coronary blood flow coupling, shown below:
  12. 12. METHOD, according to claim 1, characterized by the effects of cardiac wall heterogeneity flow being described by a multi-layered, multi-compartment model with a variable tissue pressure coefficient.
  13. 13. METHOD, according to claim 12, characterized in that one or more hemodynamic parameters comprise one or more hemodynamic parameters related to the chronotropism, inotropism or lusitropism of the heart obtained with a cooperative purinergic receptor stimulation model of agonism.
  14. 14. METHOD, according to claim 1, characterized in that blood flow simulations are performed using a transient solver or a steady-state solver.
  15. 15. METHOD, according to claim 1, characterized in that the pressure drop and vessel flow characteristics are determined by a steady-state approach.
  16. 16. METHOD, according to claim 1, characterized in that one or more hemodynamic parameters are selected from blood pressure, blood flow, blood flow rate, wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), fractional flow reserve (FFR), instantaneous wave free ratio (iFR) and coronary flow reserve (CFR).
  17. 17. METHOD, according to claim 1, characterized by further comprising emitting one or more determined hemodynamic parameters.
  18. 18. METHOD, according to claim 17, characterized by the transmission (214, 344, 414, 542) comprising sending one or more determined hemodynamic parameters to a display device.
  19. 19. METHOD, according to claim 17, characterized by the transmission (214, 344, 414, 542) comprising sending one or more determined hemodynamic parameters to a remote computer.
  20. 20. METHOD, according to claim 17, characterized by further comprising determining a patient-specific treatment plan (116, 216, 416) based, at least in part, on one or more determined hemodynamic parameters.

Description

BACKGROUND [001] Cardiovascular disease is the leading cause of death for men and women in the United States and is responsible for no less than 30% of deaths worldwide. Although medical advances in recent years have provided important progress in the diagnosis and treatment of heart disease, the incidence of premature morbidity and mortality is still high. One reason for this is the lack of precise estimates of patient-specific parameters that accurately characterize the anatomy, physiology, and hemodynamics of coronary arteries, all of which play an important role in the progression of cardiovascular disease. [002] Medical imaging-based techniques (e.g., computed tomography angiography) are typically used in clinical practice to characterize the severity of stenosis in the coronary arteries. However, such techniques provide only an anatomical assessment, which is often inadequate for clinical decision-making. In particular, anatomical assessment of coronary artery stenosis severity frequently leads to overestimation or underestimation, both of which are undesirable. Overestimation of stenosis severity can lead to unnecessary intervention and the subsequent risk of restenosis, while underestimation would likely lead to non-treatment. An accurate functional assessment may require pressure and/or flow measurements, which are determined non-invasively. [003] Several computational fluid dynamics (CFD) techniques have been developed for the functional assessment of coronary artery disease. However, they are typically based on simplified geometries of the coronary arteries, with generic boundary conditions derived from general population data. This makes such techniques unsuitable for a comprehensive patient-specific assessment of coronary artery disease, such as assessing the severity of stenosis in the case of coronary artery stenosis. [004] Examples of such a method were revealed in Chung JH, Lee KE, Nam CW, Doh JH, Kim HI, Kwon SS, Shim EB, Shin ES (2017) Diagnostic Performance of a Novel Method for Fractional Flow Reserve Computed from Noninvasive Computed Tomography Angiography (NOVEL-FLOW Study) The American Journal of Cardiology, 120(3):362-368. This study aimed to reduce the complexity of the computational method, resulting in a shortening of the average time to provide results to 185 minutes. In said document, the boundary conditions were calculated using estimated blood pressure waveforms derived from fitting a function obtained from simulation studies to experimental data, such as systolic blood pressure, diastolic blood pressure, and heart rate. The document does not unequivocally reveal whether the systolic blood pressure, diastolic blood pressure, and heart rate parameters were obtained non-invasively. The 3D model of the coronary arteries was obtained non-invasively using coronary computed tomography angiography (CCTA). The method offers good accuracy compared to known methods. [005] An example of a method implementing CFD calculation and invasive studies was revealed in Kousera CA, Nijjer S, Torii R, Petraco R, Sen S, Foin N, Hughes AD, Francis DP, Xu XY, Davies JE (2014) Patient-specific coronary stenoses can be modeled using a combination of OCT and flow velocities to accurately predict hyperemic pressure gradients IEEE Transactions on Bio-medical Engineering, 61(6):1902-1913. This study aimed to provide a patient-specific numerical study that combines the results of the high-precision reconstruction method, optical coherence tomography (OCT), with angiography and patient-specific pressure with velocity waveforms. Angiography, OCT, and pressure measurements were performed using catheters and thus in an invasive manner. The authors of this study acknowledged the limitations of this method, stemming from invasive measurements, and the need for manual data manipulation; that is, the method is not automated. However, this document does not suggest the use of non-invasive measurement methods. The simulations obtained show a good correlation with the experimental data. BRIEF DESCRIPTION OF THE DRAWINGS [006] The detailed description is presented with reference to the accompanying drawings. The drawings are provided for illustrative purposes only and merely depict exemplary embodiments of the disclosure. The drawings are provided to facilitate understanding of the disclosure and should not be considered as limiting the scope, reach, or applicability of the disclosure. In the drawings, the leftmost digit (or digits) of a numerical reference may identify the drawing in which the numerical reference first appears. The use of the same numerical references indicates similar components, but not necessarily the same or identical components. However, different numerical references may also be used to identify similar components. Several embodiments may utilize elements or components beyond those illustrated in the drawings, and some elements and/or components may not be present in several embodiments. The us