Non-invasive identification of resting state diastolic hemodynamic information

Abstract

To determine instantaneous wave-free ratio (IWFR) as a diastole-based hemodynamic index.SOLUTION: A diastole-based hemodynamic index may be calculated noninvasively for a patient by receiving image data respective of an anatomical region of the patient, creating an electronic model of the anatomical region, creating one or more boundary conditions model value sets representative of flow conditions during diastole, calculating one or more pressure drops at a location in the anatomical region, and determining, based on the calculated pressure drop (possibly drops) and based on a reference pressure, a hemodynamic index value, such as IWFR, for the location.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] This disclosure generally relates to a method for detecting and analyzing patient hemodynamic information based on non-invasive imaging and computational fluid dynamics. Regarding identification and display, the identification and display may include resting state diastolic-based hemodynamic information, e.g. This includes identifying and displaying the instantaneous wave-free ratio (IWFR). nothing.

[0002] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application is a continuation of U.S. Provisional Patent Application No. 62 / 788,914, filed January 6, 2019. The benefit of and priority to this U.S. provisional patent application, the entire contents of which are hereby incorporated by reference, are hereby claimed. The disclosure is hereby incorporated by reference. [Background technology]

[0003] Coronary heart disease (CHD) is the most common cause of death in the United States. CHD is a leading cause of death, with direct and indirect annual costs estimated at hundreds of billions of dollars. It is caused by atherosclerosis, which progresses This may lead to ischemia, angina, myocardial infarction and death. Depending on the severity and complexity of the condition, medical treatment, endovascular stents, and coronary artery bypass grafting may be used. We offer patients a variety of treatment options, including coronary artery bypass graft (CABG) surgery. A typical diagnosis and treatment plan may include clinical evaluation, non-invasive stress testing, and for suitable patients, invasive coronary angiography and subsequent medical treatment and / or coronary angiography. This includes coronary revascularization. Typically, patients undergoing medical treatment If symptoms persist or a significant defect in myocardial perfusion is detected, the medical professional would perform an invasive coronary angiogram on the patient. The decision to revascularize using coronary stents or CABG surgery is based on angiography. Based on anatomical findings by [1] and more recently, invasively measured fractional flow reserve (F The catheter is also used to measure hemodynamic information such as fractional flow reserve (FR). Measuring FFR in the laboratory requires inserting pressure wires into the patient's coronary arteries. FFR values ​​below 0.8 are generally considered to indicate clinically significant obstructive lesions. , revascularization will be permitted in appropriate clinical circumstances.

[0004] Instantaneous fractional flow reserve (IWFR) is superior to FFR in identifying obstructive coronary artery lesions. It is a hemodynamic index that has been proven to have the same diagnostic accuracy as FFR. IWFR is measured invasively using a pressure wire. Like FFR, IWFR is the intravascular pressure distal to the lesion(s) relative to the pressure in the aorta (Pa) IWFR is defined as the ratio of force (Pd) to force (Pd). IWFR differs from FFR in several ways. First, FFR requires the induction of hyperemia when measuring the pressure ratio, while IWFR As a result, FFR is measured under resting conditions, just as IWFR is measured under resting conditions. Second, FFR uses pressure averaged over the cardiac cycle. IWFR is used to measure the flow rate during diastole, when resistance to flow is approximately constant at a minimum. Pressure measurements averaged during the so-called wave-free period are used.

[0005] IWFR is not the only hemodynamic parameter measured under resting conditions during diastole. Other pressure ratio indices measured under resting conditions during diastole are The diastolic pressure ratio (dPR), which is the average of the standing ratios, and the diastolic pressure ratio (dPR) Pressure ratio (dPR) measured at the midpoint mid ), both of which are equivalent to IWFR. It has been proven to have diagnostic accuracy of 100% or higher. Summary of the Invention

[0006] Disclosed herein is a non-invasive determination of resting state diastolic hemodynamic information of a patient. A first exemplary method for providing respective hemodynamic information includes imaging three-dimensional electrocardiograms of the patient's coronary arteries. obtaining a child model representing a diastolic period of a cardiac cycle of the patient when the patient is in a resting state; and obtaining a set of boundary condition model values. Three-dimensional computational fluid dynamics (CFD) simulation of the coronary artery model based on the model value set performing a first coronary artery stenting procedure according to the CFD simulation; and calculating a pressure drop between the location and a second location in the coronary artery. The method may include: determining the pressure drop based on the calculated pressure drop and based on a reference pressure; and determining a hemodynamic index value indicative of the presence of a lesion at the location.

[0007] In one embodiment of the first exemplary method, the set of boundary condition model values ​​is represents the entire diastolic period of the cardiac cycle.

[0008] In one embodiment of the first exemplary method, the set of boundary condition model values ​​is represents the waveless period of the diastolic phase of the cardiac cycle.

[0009] In one embodiment of the first exemplary method, the set of boundary condition model values ​​is represents the mid-diastolic point of the cardiac cycle.

[0010] In one embodiment of the first exemplary method, the method comprises: Further comprising creating a model.

[0011] In one embodiment of the first exemplary method, the method comprises: receiving image data of each of the plurality of pixels; and and creating a child model.

[0012] In one embodiment of the first exemplary method, the set of boundary condition model values ​​is an inlet flow rate at the inlet of the coronary artery, representing a resting state of the coronary artery; and and two or more outlet flow rates calculated according to the model.

[0013] In one embodiment of the first exemplary method, the method comprises: specifying the flow split model according to the shape of the model; and and calculating the two or more outlet flow rates according to a division model.

[0014] An exemplary embodiment of a system for providing patient-specific hemodynamic information includes: a non-transitory computer readable memory for storing a coronary artery pressure signal; and a processor for detecting a coronary artery pressure signal of the patient. obtaining a three-dimensional electronic model of the patient's cardiac cycle during the diastolic phase when the patient is in a resting state; and obtaining a set of boundary condition model values ​​representative of the interval. The processor may further include a processor for detecting the boundary condition model value set. Based on the results of the experiment, a three-dimensional computational fluid dynamics (CFD) simulation of the coronary artery model was performed. performing a first location of the coronary artery according to the CFD simulation; calculating a pressure drop between the coronary artery and a second location; and and a hemodynamic index value indicative of the presence of a lesion at said location based on said reference pressure. The device may be configured to execute instructions to:

[0015] In one embodiment of the exemplary system, the set of boundary condition model values ​​is Represents the entire diastolic period of the cardiac cycle.

[0016] In one embodiment of the exemplary system, the set of boundary condition model values ​​is Represents the waveless period of the diastolic phase of the cardiac cycle.

[0017] In one embodiment of the exemplary system, the set of boundary condition model values ​​is Represents the mid-diastolic point of the cardiac cycle.

[0018] In one embodiment of the exemplary system, the memory is causing the processor to create the electronic model of the anatomical region. The instruction to execute the command is further stored.

[0019] In one embodiment of the exemplary system, the memory is and receiving image data for each of the anatomical regions of the patient from the processor. and creating the electronic model based on the received image data. The instruction to combine the two is further stored.

[0020] In one embodiment of the exemplary system, the set of boundary condition model values ​​is Inlet flow rates at the inlets of the coronary arteries, representing a resting state, and the inlet flow rates and flow splitting models and two or more outlet flow rates calculated in accordance with the method.

[0021] In one embodiment of the exemplary system, the memory is The processor then calculates the flow distribution according to the shape of the three-dimensional model of the coronary artery. calculating a flow split model for the two or more outlets according to the inlet flow rate and the flow split model; and calculating the mouth flow rate.

[0022] A second exemplary method for providing hemodynamic information for each of a patient includes: and obtaining a boundary condition model representing the patient's resting state. and determining a first time within the patient's cardiac cycle based on the three-dimensional model and the boundary condition model. calculating a first pressure drop across a portion of the anatomical region of the patient at a time point; The second exemplary method may include: at a second time point within the patient's cardiac cycle that is different from the first time point based on the calculating a second pressure drop across a portion of the anatomical region; and measuring the cardiac pressure of the patient. For a certain range of time in the cycle, the previous pressure drop is determined according to the first pressure drop and the second pressure drop. calculating a respective pressure drop across the region; and calculating said pressure drop for said range of time points. indicating the presence of a lesion at said location based on the measured pressure drop and based on the baseline pressure. The method may further include determining a hemodynamic index value.

[0023] In one embodiment of the second exemplary method, the anatomical region is a blood vessel, and the analysis A portion of an anatomical region extends from an entrance to the blood vessel to a location within the artery.

[0024] In one embodiment of the second exemplary method, the anatomical region is a coronary artery.

[0025] In one embodiment of the second exemplary method, the method comprises: receiving image data of each of the plurality of pixels; and and creating a child model. [Brief explanation of the drawings]

[0026] [Figure 1] FIG. 1 is a diagram of an exemplary embodiment of an electronic system for determining hemodynamic information of a patient. [Figure 2] 1 is a flow chart illustrating one exemplary embodiment of a method for determining patient hemodynamic information based on electronic patient data. [Figure 3] 1 is a flow chart illustrating an exemplary embodiment of a method for determining hemodynamic information based on a single set of values ​​of a boundary condition model representing average flow conditions for a single point in time within a cardiac cycle or a portion of a cardiac cycle. [Figure 4] 10 is a flow chart illustrating an embodiment of a method for determining hemodynamic information based on two sets of boundary condition model values ​​representing two different cardiac cycle states. [Figure 5] FIG. 1 illustrates an exemplary geometric model of an anatomical region of a patient that may be identified and find use in the methods of the present disclosure. [Figure 6]10 is a plot showing exemplary ranges of pressure drop for exemplary ranges of flow rates for a set of patients. [Figure 7] FIG. 1 illustrates an example embodiment of a user computing environment. DETAILED DESCRIPTION OF THE INVENTION

[0027] Given the diagnostic accuracy of invasive IWFR and other diastolic pressure ratio indices, noninvasive imaging and Methods for calculating these using numerical hemodynamics should advance invasive diagnostic angiography. Known hemodynamic indices can be useful as a tool in selecting patients who should or should not proceed. For example, FFR, dPR, and IWFR are measured invasively, and such invasive Approximately 50 percent of patients undergoing invasive testing are found to have no obstructive disease. Therefore, non-invasive methods to identify IWFR and similar diastolic indices as screening tools are being developed. There is a clinical need for aggressive diagnostic methods.

[0028] Non-invasively acquired image data, such as CT images and computational fluid dynamics (CFD), The range of anticipated blood flow requirements that a particular individual is likely to experience during daily activities to rapidly calculate the hemodynamic relationship between pressure and coronary flow over a wide range of This relationship can be used to determine the IWFR and the flow rate caused by coronary artery disease. Noninvasively measure specific indices of intra-arterial pressure loss, including diastolic pressure ratio and others, which describe the degree of obstruction. It can be calculated automatically in combination with other clinically derived information to facilitate invasive diagnostic procedures. A decision can be made as to whether a technique or intervention is advisable.

[0029] Current methods for calculating FFR assume hyperemic flow, which for a given individual This requires the assumption of an increase in flow from the resting condition to the hyperemic condition. Depending on the pathophysiological state and depending on the individual, it can range from a factor as large as 4 or 5 to slightly above 1. Therefore, the assumed hyperemic flow (for FFR) Using an assumed rest flow (as required for IWFR) rather than This reduces the uncertainty in the assumed inflow conditions, and therefore the CFD-based FF It can provide improved accuracy for R.

[0030] Individuals vary in resting fluid requirements depending on their physical condition and metabolic needs. Estimating resting flow in a population with a disease may be useful for understanding the underlying pathophysiology, e.g. Due to microvascular disease and other factors, there is more variability in estimating flow under hyperemic conditions. Calculations based on hyperemic flow conditions may be used to guide the decision to recommend an invasive diagnostic procedure. The basis may not be appropriate for the general population. A non-invasive computational method to simulate pressure drops during diastolic flow to provide diagnostic information to provide.

[0031] The present disclosure improves upon known CFD-based FFR measurements by considering patient-specific metabolic demands. In some embodiments, the method may further provide an improvement over conventional methods. By incorporating information from various metabolic activities, a more accurate CFD-based analysis can be performed for that patient. This patient-specific metabolic workload information can be used to calculate the IWFR. This can be used to provide the flow rate utilized in the calculations.

[0032] IWFR and other hemodynamic indices can be calculated based on the flow field in the patient's vasculature. This can be based on the Navier-Stokes equations of fluid motion. The flow field within, for example, in some forms as a function of time and three-dimensional (3D) space, and other formats, intravascular pressure within a region of interest (ROI) as a function of 3D space only. The Navier-Stokes equations can be used to describe the velocities. For example, pressure drop, FFR, fractional flow reserve (IWFR), other diastolic pressure indices, blood pressure The pressure fluctuations in the pipe and the viscous shear stress (wall shear stress (WSS)) It is possible to calculate quantities of clinical interest, such as the force on the arterial wall caused by the CFD is used to solve the Bies-Stokes equation, and the solution is This includes imposing boundary conditions, such as inlet flow rate (e.g., at a selected inlet boundary) and vessel Subjects with any combination of flow distributions in the branches (e.g., one or more outflow streams) The vessel lumen geometry (obtained from CT or other imaging) is also included in the CFD. The pressure field within I can be calculated as the deviation from a reference pressure and hence The absolute level of pressure, e.g., Pa, may not be necessary when calculating the pressure field. If a pressure (e.g., Pa) is specified, the deviation from the reference is calculated and the internal insulation of the field is calculated. Counter pressure can be specified.

[0033] Many clinical applications of coronary flow, such as pressure drop, FFR, and IWFR, are addressed by navigation. The Estoques equation is considered to be time-independent (i.e., independent of the time dimension, For example, the time average of the pressure ratio Pd / Pa can be calculated by where Pd is the pressure within the ROI and Pa is the reference pressure. This is because a 3D CFD model is suitable for calculating these pressure exponents, and therefore However, it is faster than a four-dimensional model (i.e., a model that incorporates the three dimensions of space and time). This means that calculations become possible.

[0034] The pressure field within the ROI can be determined based on, for example, the flow rate within and around the ROI. For coronary artery flow and pressure, the flow rate and the proximal and distal locations within the region of interest can be measured. The relationship between the pressure gradient (ΔP) between the Therefore, a sufficient approximation can be achieved. ΔP=aQ+bQ 2 (Formula 1) Here, a and b depend on the vascular geometry and blood viscosity of the individual patient, and are calculated by the method described below. is a constant that can be calculated for a given patient in Both have a mathematical basis. Physically, the aQ term is the pressure loss due directly to blood viscosity. is related to bQ 2 The term is the pressure resulting from flow separation and turbulence (if present). Related to losses. bQ 2 The term is when the constriction is large enough to cause flow separation. , can be considered significant. Mathematically, this formula can be expressed as a polynomial for ΔP=fcn(Q) Equation (1) can be regarded as the first two terms in a series expansion. The pressure drop across a region of the vasculature of a subject patient through which the flow field is identified is determined.

[0035] To calculate a and b, we solve the three-dimensional Navier-Stokes equations for two values ​​of Q. For example, the first value Q1 may be a flow rate for the start of diastole (or another time point). The second value Q2 can represent the flow rate for the end of diastole (or another time point). In other embodiments, Q1 can represent a first physiological state, and Q 2 can represent different second physiological states. These calculations are performed using Q1, Q2, and ΔP Once 1 and ΔP2 are known, the following equations (2) and (3) can be solved for a and b. This gives two values ​​for ΔP so that ΔP1=aQ1+bQ1 2 (Formula 2) ΔP2=aQ2+bQ2 2 (Formula 3)

[0036] Once the coefficients a and b for a given patient are known, the patient's blood pressure can be calculated for a range of flow conditions (e.g., Further CFD is required for each flow condition within the range of physiologically relevant flow conditions. It is possible to calculate ΔP over that range without

[0037] The clinical definition of IWFR is shown in equation (4) below. IWFR=Pd / Pa (Equation 4) where Pd and Pa are the distal coronary artery pressures averaged over the waveless period of diastole, respectively. Alternatively, IWFR can be calculated by multiplying the IWFR by the wave-free period as shown in equation (5) below: It can be defined using an interval value. IWFR=1-ΔP / Pa (Equation 5)

[0038] Equations (4) and (5) are used to calculate Pd and Pa (Equation (4)) at different parts or points in the cardiac cycle. Calculate other indices by calculating ΔP and Pa (in the case of equation (5)) or ΔP and Pa (in the case of equation (6)). For example, the diastolic pressure ratio (dPR) is the pressure across the entire diastole. It can be calculated by performing the calculation on

[0039] (In the case of IWFR, ΔP is calculated at the beginning and end of the wave-free period in diastole. Q1 and Q2 are calculated for the start and end of the diastolic wave-free period, and Pa is calculated for the start and end of the diastolic wave-free period. Once the IWFR is calculated, the IWFR value can then be calculated. The pressure versus flow curve for the IWF can be calculated and integrated and averaged to obtain the IWF The R-value can be calculated non-invasively.

[0040] As mentioned above, IWFR values ​​can be calculated under two different conditions (e.g., two different times within the cardiac cycle). Alternatively, in one embodiment, Based on a single representative Q value and a single representative Pa value for the diastolic waveless period, To non-invasively calculate IWFR in a typical The Q factor can be calculated in some embodiments (as discussed below with respect to equation (9)) by The calculation can be performed according to the shape of the region of interest.

[0041] As described above, one or more Pa values ​​are used as the reference pressure for IWFR calculation. In one embodiment, brachial cuff pressure measurements are used to estimate this mean diastolic pressure. The cuff pressure is the peak systolic pressure (SP) and the maximum Provides low diastolic pressure (DP) during wave-free period Resting mean aortic diastolic pressure (Pa dmean or dPa) (This is for IWFR calculations (which can be used for this purpose) is, in some embodiments, described in Equation 6 below: It can be estimated from the SP and DP cuff values ​​according to the transfer function. Pa dmean =(SP+3DP) / 4 (Equation 6) In other embodiments, other transfer functions may be used to relate the cuff pressure value to the reference pressure. can be done.

[0042] In another embodiment, the mean aortic diastolic pressure at rest, Pa (Pa dmean or dPa) is It can be calculated from the cuff pressure as shown in Equation 7 below. dPa=Pc+offset (Equation 7) where Pc is the resting upper arm cuff pressure given by Equation 8 below. Pc=dPc+FF*PP (Equation 8) where dPc is the diastolic cuff pressure, FF is the scalar form factor, and PP is the cuff pulse pressure (e.g., the systolic (SP) cuff pressure and the diastolic (DP) cuff pressure of a patient at rest). The scalar form factor FF is a value between 0.15 and 0.45. For example, heart rate, age, height, systolic pressure, and / or amplification index (AUGM) In some embodiments, the patient's specific characteristics, including the cognition index, may be relied upon. In some cases, FF can be approximately 0.2, 0.25, or 0.33. In an embodiment, the offset value in Equation 7 may be between about 0 mmHg and -10 mmHg. In one embodiment, the offset value in Equation 7 may be approximately -7 mmHg. The value of TT may, in some embodiments, be the value of the form factor FF, the desired hemodynamic index, (and therefore the portion of the cardiac cycle under examination), and the physiological state of the patient. Cut.

[0043] In another embodiment, mean aortic diastolic pressure relates cuff pressure to aortic pressure during diastole. For example, diastolic Pa can be estimated using a transfer function based on the invasively measured The formula is fitted to a dataset containing the cuff pressures and central diastolic resting pressures of the patient population. By finding the value of the pressure factor FF and / or the offset value, the cuff pressure of the test patient can be Once this function is known, it can be determined from the non-invasively measured This can be used to obtain an estimate of the diastolic resting pressure from the measured cuff pressure.

[0044] In another embodiment, mean aortic diastolic pressure is measured using an optical finger device or other wearable device. A combination of a radial pressure measurement device (e.g., a radial tonometry device) and an upper arm cuff pressure device For example, the Fourier analysis of the optical finger device output can be used to estimate the This can be performed and mathematically combined with the brachial cuff pressure to determine the Pa value.

[0045] Referring to the drawings, in which like reference numerals refer to the same or similar features in various drawings, 1 is a diagram of an exemplary embodiment of an electronic system 10 for determining hemodynamic information. The system 10 includes a patient image source 12, a user input device 14, and a hemodynamic information computer. The system may include a computing system 16 and a display 18. As will be described in detail, the system 10 collects electronic patient data (e.g., patient area of ​​interest data) Calculating the patient's hemodynamic information based on the patient's blood pressure (including blood pressure, blood flow, and other data) and / or identifying the patient's blood pressure. Based on the hemodynamic information obtained, the patient may be recommended for further testing (e.g., further noninvasive evaluation or may find use in making recommendations regarding interventional evaluations and / or interventional treatments. can.

[0046] In one embodiment, deploying one or more aspects of system 10 in a clinical environment For example, in some embodiments, the patient image source 12, the user input device 1 4. The hemodynamic information computing system 16 and the display 18 are used in hospitals, etc. In some embodiments, the system The 10 components are a laptop or desktop computer or workstation. In some embodiments, some of the systems 10 may be implemented in a components, such as the hemodynamic information computing system 16, can be remotely accessed from the clinical setting. and can be remote, for example in cloud computing-based embodiments. do.

[0047] A patient image source 12 is configured to acquire one or more medical images of the vasculature of a patient under examination. For example, the patient image source 12 may include a medical image acquisition device configured to: In some embodiments, the patient image source may be a non-invasive image acquisition device. The 12th is a device that can acquire, among other things, computed tomography (CT) imaging, intravascular ultrasound (IVUS), and other imaging modalities. VUS), biplane angiography, optical coherence tomography (OCT), magnetic resonance imaging (MRI), or It may include, but is not limited to, combinations of these.

[0048] Additionally or alternatively, patient image source 12 may include a store of existing image data of patients under study. In some embodiments, the patient image source 12 may include a medical image store. device, such as a database or other local electronic data storage device, or a medical imaging device. a remote storage device (e.g., a cloud-based storage device) configured to store the image; It can include.

[0049] User input device 14 is one or more input devices for input to the computing system. devices, e.g., mouse, touchpad, touchscreen, keyboard, microphone The input device may be or include a smartphone, camera, or other input device. Cut.

[0050] The hemodynamic information computing system 16 includes a processor 20 and data and instructions. and a non-transitory computer-readable memory 22 configured to store In one embodiment, the memory 22 can store images from a patient under test, and thus The processor 20 may function as the patient image source 12, or an aspect thereof. memory 22 for executing one or more of the steps, methods, algorithms, etc. of the present disclosure. In particular, the memory 22 may be configured to execute instructions stored in the memory 22. determination module 24, boundary condition determination module 26, flow field determination module 28, pressure determination module Various functions in the form of instructions, including a module 30 and a hemodynamic information identification module 32. The module can be configured to store.

[0051] The various modules 24, 26, 28, 30, 32 within memory 22 will be described individually. However, such individualization is merely for the sake of argumentation. It should be understood that the instructions implemented by the various modules may be shared among common files, storage, and The modules described herein may be included in a device or the like. One or more of these may be individualized into multiple individual files, storage devices, etc.

[0052] The shape identification module 24 identifies an anatomical region of interest ( The method can be configured to generate an electronic geometric representation (e.g., a model) of the ROI. In some embodiments, the ROI is a portion of the cardiovascular system of the subject patient, e.g., one or more arteries. One or more arterial segments may be segments of one or more arteries and their It may include portions of one or more branches extending therefrom.

[0053] In some embodiments, the one or more arterial segments include one or more coronary artery segments. The one or more coronary artery segments may include one or more coronary artery segments emanating from the aorta of the subject. One or more coronary arteries and one or more branches extending therefrom. The above coronary artery segments are the left coronary artery (LCA) and / or It may include one or more parts of the right coronary artery (RCA). , including but not limited to, one or more coronary artery segments of the left coronary artery (LCA), and In particular, the left main coronary artery (LM), left anterior descending artery (LAD), left the circumflex artery (also called the "circumflex branch"), or a combination thereof, Not limited to these.

[0054] This disclosure will refer to coronary artery segments. However, more than one artery The segments are not limited to the coronary artery segments discussed, but may also include other coronary artery segments, among others. The arterial segments may include other types of arterial segments, or combinations thereof. For example, one or more arterial segments may be a cerebral artery segment (multiple femoral artery segment(s), iliac artery segment(s) (may be multiple), popliteal artery segment(s), carotid artery segment(s) The renal artery segment(s) may include one or more renal artery segments, etc.

[0055] In some embodiments, the shape representation generated by shape identification module 24 may be It can be a three-dimensional (3D) electronic model of the spatial volume of one or more arterial segments. For example, the shape representation of one or more artery segments may be represented as a 3D volumetric mesh, e.g., a polyhedron ( In some embodiments, the shape representation can be discretized into discrete points (e.g., tetrahedra). It may include a surface mesh representing the luminal boundary of the arterial segment.

[0056] In some embodiments, the boundary condition identification module 26 identifies the boundary conditions for each arterial segment. The "boundary" refers to a cross section of the representation of an arterial segment. In particular, the inflow boundary corresponds to the cross section through which the blood flows, one or more cross sections corresponding to cross sections located downstream or distal from the inflow boundary, which are directed outwardly from the inflow boundary. Outflow boundary, one or more vessel walls corresponding to the interface between the inner surface of the arterial wall and the flowing blood These may include, but are not limited to, a boundary, a perimeter ...

[0057] In some embodiments, one or more outflow boundaries are junctions (e.g., bifurcated, trifurcated, etc.). and combinations thereof) In some embodiments, the one or more outflow boundaries may be located in the left circumflex artery. In some embodiments, the outflow boundary may be located at or adjacent to the outflow boundary. The at least one outflow boundary is a first outflow boundary and is located between the inflow boundary and the first outflow boundary. In some embodiments, the first outgoing boundary may include a second outgoing boundary. corresponding to the distal boundary of the ment (i.e., the cross section located downstream or distal from the inflow boundary). In some embodiments, for example, if the shape representation includes the left coronary artery, The second outflow boundary can correspond to the circumflex artery. In some embodiments, the first outflow The boundary and the second outflow boundary may be connected to one or more further outflow boundaries, e.g., at least a third outflow boundary. The third outflow boundary corresponds to a junction, such as a branch or bifurcation. It may be adjacent to or adjacent to the

[0058] In some embodiments, the boundary condition identification module 26 may be configured to and configuring the shape representation generated by the method to identify shape data for each boundary. In some embodiments, the shape data may include, among other things, the radius, diameter, The measurements may include the circumference, length, area, volume of the epicardial coronary arteries, or a combination thereof. However, the present invention is not limited to these.

[0059] In some embodiments, the boundary condition identification module 26 identifies the boundary conditions for each arterial segment. For example, the boundary conditions for each segment can be specified. The boundary conditions may include, among others, an inflow boundary condition, an outflow boundary condition, one or more vessel wall boundary conditions, or The inflow boundary conditions may include velocity, flow rate, pressure or other specific Each outflow boundary condition can be a value or range of values ​​for the velocity, flow rate, pressure, inflow It can be a percentage of a condition, or a value or range of values ​​of other characteristics. Boundary conditions are values ​​or ranges of values ​​for velocity, flow rate, pressure, a combination of these, or other properties. It can be said that:

[0060] In some embodiments, the specification of the inflow boundary conditions and / or outflow boundary conditions may include, among other things: Patient information, relevant physiological state (e.g., resting state, hyperemic state), segment type ( For example, LCA or RCA), or a combination of these. In some embodiments, the inflow boundary conditions are determined based on the expected patient activity level (e.g., patient In some embodiments, the information provided by In , the inflow boundary conditions can be stored values ​​and / or specified by the user.

[0061] In some embodiments, the inflow boundary condition is determined by the shape of the anatomical ROI, e.g., the vascular portion. Identifying according to radius, diameter, length, or volume (e.g., the volume of an epicardial coronary artery) For example, the flow rate can be calculated based on the lumen volume of the region of interest, as shown in Equation 9 below: It can be calculated according to the model. Q in = αV β (Formula 9) Here, Q in is the flow rate at the inlet of the anatomical model, and V is the flow rate of the luminal body of the region of interest. is a product, where α is a coefficient that depends on the physiological state of the patient, β is the vascular tree structure, and In some embodiments, the resolution of the images used to generate the 3D model of the anatomical region This is a coefficient that depends on the image quality.

[0062] In embodiments where the region of interest is the coronary artery tree, V is segmented from its proximal origin. The luminal volume of the LCA or RCA is defined up to the point where the diameter of the vessel is a specific diameter. The particular diameter may be used to create a model of the patient's anatomy. For example, the position may depend on the resolution of the image being displayed. , can be defined as the diameter of three or four voxels in the image dataset. In examples, the location may be where the lumen has a diameter of 1 mm or 1.5 mm.

[0063] In some embodiments, the parameters α and β are constant across all patients. Both non-invasive and invasive data can be used to verify the values ​​of α and β. This can be determined from an exemplary data set that includes:

[0064] In some embodiments, the outflow boundary conditions may be identified using an outflow distribution model. The outflow distribution model can be calculated using geometric data and / or stored hemodynamic data. The stored hemodynamic data can be used to determine the shape of the outflow boundary (e.g., radius, One can define empirical relationships between the diameter, length, volume, etc. and the respective flow rates, The stored hemodynamic data can also be used to define this. For example: The boundary condition generation module generates a boundary condition based on the stored hemodynamic data and the first outflow of the segment. Specify runoff distribution model using radius, diameter, length, volume, etc. of boundary and secondary runoff boundary In another example, the boundary condition generation module may generate geometric data, e.g., the radius, diameter, and length of the first outflow boundary (distal boundary) of the cemetery or the portion of the vessel proximal to the boundary; A runoff distribution model can be specified using only the volume, etc. Used to identify the outflow (e.g., velocity, flow rate, percentage of inflow) for each outflow boundary. can be used to specify each outflow boundary condition.

[0065] Illustratively, the boundary conditions identified by the boundary condition identification module 26 may be determined by the flow field (e.g., Identify blood flow, wall shear stress, and hemodynamic information (e.g., FFR, IWFR, etc.) It can be used for steady and / or unsteady flow calculations to The module also uses optimization techniques to define the flow partitioning of arterial segments. Thus, the boundary condition generation module 26 provides flexibility, accuracy, and efficiency in specifying boundary conditions. It can provide efficiency.

[0066] The flow field identification module 28 uses the shape representation identified by the shape identification module 24, One or more boundary conditions identified by the boundary condition identification module 26 and each of the patient's The pressure data is used to determine the flow field for each arterial segment. The pressure data can be, for example, the cuff pressure of the patient in a resting state. In some embodiments, the flow field may include, among other things, a pressure field, a velocity field, a wall shear stress field, an axial pressure field, a flow ... These may include, but are not limited to, pressure, pressure, lamellar stress, or combinations thereof.

[0067] In some embodiments, flow field parameters (e.g., pressure field, velocity, etc.) are calculated from geometric data. In this way, the flow field characterization module can be based only on the parameters and boundary conditions. It is configured to identify flow fields based solely on spatial position (i.e., independent of time). It is possible.

[0068] The pressure determination module 30 uses the flow field determined by the flow field determination module 28. and configured to determine blood pressure at one or more points within the patient's anatomy using the In some embodiments, the pressure data can be used, among other things, to calculate the flow field / pressure. Non-invasive determination of a patient's mean blood pressure as determined by a force field, e.g., a blood pressure cuff, or It can be determined from the combination.

[0069] The pressure determination module 30 determines the pressure of a user (e.g., a physician) at a particular location within the patient's anatomy. and configuring the pressure sensor to identify a particular pressure at the particular location in response to the selection. The user can then visualize the shape of the patient's region of interest (e.g., artery) on the display 18. In response to the display, the user can input the selection using the user input device 14. In an embodiment, the pressure determination module is configured to determine the pressure drop at a user-selected location. can be configured to identify pressures upstream and / or downstream from a user-selected location, such as Cut.

[0070] The hemodynamic information computing system 32 calculates one or more hemodynamic information for each of the patients. The device may be configured to calculate a state parameter, such as IWFR or dPR. Calculating the patient's IWFR may, in some embodiments, be performed over a range of flow rates, for example. Calculate the range of pressure drop for one or more points in the patient's anatomy In other embodiments, the patient's IWFR, dPR, or other diastolic index may be measured. Calculating the number of diastolic waves may be done by calculating the average for part or all of the diastolic wave-free period. The patient may be provided with a single pressure drop calculated using the average flow rate. Based on the calculated IWFR value, the system 16 or a clinician may perform further diagnostic procedures and / or It can be determined whether an interventional procedure should be performed.

[0071] FIG. 2 is a flow diagram illustrating an exemplary embodiment of a method 40 for determining hemodynamic information about a patient. Method 40, or one or more aspects of method 40, may, in embodiments, include: This can be performed by the hemodynamic information computing system 16 of FIG.

[0072] The method 40 may include, at block 42, receiving patient data. The patient data includes, for example, basic information about the patient, such as the patient's age, sex, and upper arm cuff blood pressure. The patient data may include, in an embodiment, the patient's metabolic data, e.g., the user's typical activity level (e.g., sedentary) or active, the amount of exercise per week, the amount of specific activities per week, e.g. The patient data may further include the amount of exercise performed (e.g., walking and running). In some embodiments, the patient data may further include patient data from one or more diagnostic tests, for example, a cardiac ultrasound. This can be done.

[0073] The method 40 further comprises receiving an image of the patient's anatomy at block 44. In an embodiment, the received patient images may include CT images, MRI images, or other non-invasively obtained images. The images may be of an anatomical region of interest of the patient. In one embodiment, for example, the received images may include one or more coronary arteries. or other vasculature of interest. The images may be taken from a patient image source, e.g., an imaging device. The information may be received from a device or database or other computer memory.

[0074] The method 40, in block 46, performs a step of: It may further include creating an anatomical model of each of the patient regions of interest. In an embodiment, the anatomical model is generated from the image received in block 44 to represent the anatomy of interest. The anatomical structure of interest can be created by segmenting the anatomical structure. For example, it may be one or more coronary arteries. Figure 5 shows an exemplary anatomical diagram of a coronary artery. The anatomical model is shown in FIG. 1 as a model 58. In one embodiment, the anatomical model is In some embodiments, the anatomical model can be created by computer. a computing system (e.g., hemodynamic information computing system 16) It can be obtained by a computer or created by a computing system. This can be obtained by receiving a pre-existing model of the patient. do.

[0075] The method 40, at block 48, includes generating one or more diastolic-based boundary condition model value sets. The one or more sets of boundary condition values ​​may further include identifying a set of boundary condition values. can be each set of values ​​for the same boundary condition model (e.g. , the same set of condition values ​​for inflow boundary, outflow boundary, wall boundary, etc.). In some embodiments, sub-portions 48a and 48b may be included. The method 40 may include, at block 48a, obtaining an incoming flow rate. The volume may in some embodiments be the flow rate at the entrance of the patient's anatomical ROI. In other embodiments, the blood flow rate can be the flow rate in another portion of the ROI.

[0076] The inflow rate obtained in block 48a may represent a particular physiological condition of the patient. For example, in some embodiments, the input flow rate obtained in block 48a can be calculated as: It can represent the patient's resting state.

[0077] The inflow flow rate obtained in block 48a may, in some embodiments, be determined based on the patient's cardiac cycle. For example, in some embodiments, block 4 The inflow flow rate obtained in 8a represents the average flow rate over the patient's diastolic waveless period. In other embodiments, the inflow flow rate may represent the overall average flow rate during the patient's diastole. In other embodiments, the inflow rate can be measured at a specific point in time during diastole, e.g., The midpoint can be represented.

[0078] In some embodiments, obtaining the inlet flow rate at block 48a may be performed using the above formula ( Calculate the inflow flow rate according to the shape of the patient's anatomical model as discussed in relation to 9) In one embodiment, the value of α selected for the inflow rate is determined based on the pericardial Specific periods or points within a period (e.g., the beginning of diastole, the end of diastole, the end of the diastolic wave-free period) The time intervals can represent the beginning of the diastolic wave-free period, the end of the diastolic wave-free period, etc.

[0079] In another embodiment, instead of calculating the inlet flow rate according to Equation 9 above, block 48a obtaining the blood flow rate in the The inlet flow rate may be determined via manual user input (e.g., via a user input device 11 of the system 10). In one embodiment, the incoming flow rate in block 48a can be received using the The specific It can be determined.

[0080] Block 48 calculates the inflow flow rate obtained in block 48a in block 48b. and in accordance with a flow splitting model. The flow segmentation model is calculated or modeled according to the geometry of a 3D electronic model of the patient's anatomical region. You can specify it differently, or you can do this already. In some embodiments, the relative radius, diameter, circumference, length, and volume of the blood vessels are measured in the electronic model. , and / or can be calculated according to surface area.

[0081] In relation to the flow rate obtained in block 48a, a flow rate is calculated in block 48b. The outlet flow rate may include a boundary condition model of the patient's anatomical region. Therefore, the patient's particular physiological state (e.g., resting state) and the patient's cardiac cycle A specific portion or point (e.g., the entire diastole, the waveless portion of the diastole, a certain point within the diastole, etc.) It can be expressed as:

[0082] In an embodiment where the anatomical region is a patient's coronary artery, the The inflow flow rate can be the inlet flow rate of the coronary artery, and the flow partitioning model is The flow partitioning model can be calculated according to the shape of the coronary artery portion downstream of the inlet. , according to the relative radius, diameter, circumference, length, surface area, or volume of the coronary artery portion downstream of the inlet In some embodiments, the flow partitioning model can be calculated using the electronic model's extracardiac flow. It can be calculated according to the volume of the membranous coronary artery.

[0083] The method 40 includes, in block 50, providing an anatomical model (e.g., model 58), one or more Based on the above boundary condition model value set and, in some embodiments, the patient data, calculating one or more hydrodynamic flow fields of blood flow through the subject's anatomy. Block 50 is the anatomical model, boundary conditions, and the respective pressure data of the patient. Identifying the flow field for each arterial segment using data (e.g., aortic pressure data) In some embodiments, the pressure data may include, for example, The cuff pressure can be obtained and / or can be a stored value. In some embodiments, the flow field may include, among other things, a pressure field, a velocity field, or a combination thereof. The fluid dynamics can be, but are not limited to, the flow field specific module of FIG. This can be calculated by the module 28.

[0084] In some embodiments, the velocity field and / or pressure field may be calculated without regard to time. and boundary conditions alone. For example, the velocity and / or pressure fields can be specified as , the velocity and pressure variables are functions of spatial position only (i.e., time is not taken into account). The steady-flow Navier-Stokes equations can be used to determine the pressure. and speed in near real time to enable point-of-care analysis by clinicians. This allows accurate and efficient identification of

[0085] Based on the patient data and the calculated fluid dynamics, the method 40 proceeds to block 52 by: The method may further include calculating diastolic-based hemodynamic information for each of the patients. The behavioral information may in one embodiment be a diastolic-based index, e.g., IWFR; Calculating the IWFR may involve measuring one or more blood pressures in the patient's vascular system. The method may include calculating one or more pressure drops for the above positions. The set can be analyzed for aortic pressure during diastole to determine hemodynamic index values. can.

[0086] Block 52 includes, in block 52a, displaying one or more clinical images on an anatomical model of a patient. The method may include receiving a user designation of a distal point associated with the target. For example, the user may using a user input device to select one or more distal points on an anatomical model of the patient's vasculature; Annotations can be entered, which allows the hemodynamic information computing system , may receive one or more annotations from the user. The indicated points may be, for example, coronary arteries The location of the stenosis may be one or more locations distal to the suspected location of the stenosis in the esophagus.

[0087] Block 52 then determines, in block 52b, a user-specified point for the first cardiac cycle state. The method may further include calculating a respective pressure drop across each of the first The state can be, for example, the onset of diastole. The pressure drop can be determined by one or more user-specified can be calculated based on the flow field calculated for the first cardiac cycle at point The remaining aspects of method 80, in one embodiment, determine whether the indicated point is likely to have clinically significant stenosis. A test can be run for each point to determine whether it is highly relevant.

[0088] The method 60 displays flow rate, pressure, and / or hemodynamic information at block 54. The display may further include, for example, overlaying a geometric model of the patient's anatomy. flow velocity at one or more locations in the patient's vasculature adjacent to or adjacent to the model; It may include one or more indicators of pressure and / or hemodynamic information.

[0089] The method 40, at block 56, determines a patient's hemodynamic status based on the calculated hemodynamic information. For example, the hemodynamic information may be used to recommend a further procedure. If the blood pressure is below the threshold that indicates the presence of a stenosis in the ductal system, the patient is not referred for further diagnostic procedures. techniques, such as invasive angiography and pressure measurements at the site of suspected stenosis, may be recommended. Additionally or alternatively, to address the stenosis, corrective procedures, e.g. Recommendations such as the placement of a stent at the suspected location may be recommended.

[0090] Figure 3 shows a boundary condition model that represents the average flow conditions at a single time point within the cardiac cycle or at a portion of the cardiac cycle. 6 shows an exemplary embodiment of a method 60 for determining hemodynamic information based on a single value set of a 6 is a flowchart illustrating the method 60, or one or more aspects of the method 60, in an embodiment. and can be performed by the hemodynamic information computing system 16 of FIG. Method 60 can be considered an embodiment of blocks 48, 50, and 52 of method 40. Cut.

[0091] The method 60 begins at block 62 with a boundary condition model representing the average flow conditions during diastole. For example, in one embodiment, block 6 2 specifies a set of boundary condition model values ​​that represent the mean flow throughout the diastole. In another embodiment, block 62 may include a boundary line representing the diastolic wave-free period. The boundary condition model may include specifying a set of boundary condition model values. In an embodiment, this may be determined as discussed with respect to block 48 of method 40 .

[0092] At block 64, the method 60 selects a single point in diastole, e.g., a midpoint in diastole. The method may further include identifying a boundary condition model value set. In some embodiments, the target is identified as discussed with respect to block 48 of method 40. It is possible.

[0093] In some embodiments, one or both of blocks 62 and 64 may be used for calculations. The calculation can be performed according to the desired hemodynamic index desired for the purpose. For example, IWFR calculation If desired, block 62 can be performed for the diastolic waveless period, dP If an R calculation is desired, block 62 can be performed for the entire diastole, d PR mid If calculation is desired, block 64 may be performed for the mid-diastole. can.

[0094] The method 60 may, at block 66, generate a single set of boundary condition model values ​​(e.g., Calculating the flow rate and pressure based on the calculated flow rate and pressure (either 62 or 64). The flow velocity can be calculated in block 66 in a single time-independent CFD simulation. For example, the velocity field and / or pressure field can be calculated using the velocity and pressure variables is a function of spatial position only (i.e., time is not taken into account), The flow rate and pressure can be determined using equations such as those used in the system 10 of FIG. The flow field can be identified by the flow field identification module 28. Multiple instances of the 66 may be implemented, each of which may be a separate Hemodynamic index calculations can be provided.

[0095] The method 60 may further include calculating a baseline pressure at block 68. The reference pressure may be the aortic pressure in some embodiments. As disclosed herein, one or more aortic pressures are determined based on the patient's respective cuff pressures. The aortic pressure may, in one embodiment, be measured at the beginning, end, and / or mid-diastole. The basis calculated in block 68 can be the aortic pressure for the diastole. The semi-pressure is a boundary condition model value set used as the basis for the calculation in block 66. A point in a cardiac cycle can represent the same point or portion as a point in a cardiac cycle.

[0096] The method 60, in block 70, performs a single time-independent CFD and block The method may further include calculating hemodynamic information based on the baseline pressure of the block 68. The dynamic information may be or include hemodynamic index values. In one embodiment, the hemodynamic index value may be an IWFR value. can be the average ratio of local pressure to aortic pressure over diastole, where The local pressure is characterized by the calculated pressure field at a location of interest, such as a location distal to the stenosis. It is determined.

[0097] Figure 4 shows the blood circulation based on two sets of boundary condition model values ​​representing two different cardiac cycle states. 1 is a flow chart illustrating one embodiment of a method 80 for determining activity information. One or more aspects of the method 80 may, in embodiments, be implemented using the hemodynamic information computing system of FIG. The method 80 may be performed by the operating system 16. 50 and 52.

[0098] The method 80 begins at block 82 by obtaining an inflow flow rate for a first cardiac cycle state of the patient. The first blood flow may include, for example, measuring the blood flow rate for a patient at the beginning of diastole. The flow rate in block 62 may be a user manual setting of the flow rate. receiving via input (e.g., using user input device 14 of system 10); In one embodiment, the flow rate in block 62 can be determined by a The therapeutic agent can be specified based on metabolic needs and patient condition (by the stem).

[0099] The method 80 begins at block 84 by measuring the flow in the region of interest at a first cardiac cycle state of the patient. The first cardiac cycle state may further include calculating a diastolic velocity and a pressure. In some embodiments, the velocity field and / or pressure field may be related to Based on the defined boundaries and boundary conditions of each of the central regions (which in turn The flow rate may be determined based on the flow rate received at block 82.

[0100] The method 80 may, at block 86, include determining a first cardiac cycle state (e.g., one or more and calculating a first pressure drop (at the user-specified point and / or other points). The pressure drop can be measured from the vessel inlet to a relevant point (e.g., user-specified or otherwise). The first state may be, for example, the onset of diastole. The pressure drop is calculated based on the flow field calculated for the first cardiac cycle state. It is possible.

[0101] The method 80 continues at block 88 by determining a second cardiac cycle of the patient that is different from the first cardiac cycle state. The second inflow rate may further include obtaining an inflow rate at a first state. , which may be the expected flow rate for the patient at the end of diastole. Block 8 The flow rate at 8 may be determined via a user manual input of the flow rate (e.g., a user input of the system 10). In one embodiment, the signal at block 88 may be received using the device 14. The inflow rate is adjusted (e.g., by the clinician or an electronic system) based on metabolic demand and patient condition. It can be identified based on the

[0102] The method 80 includes, at block 90, determining the flow velocity in the region of interest at a second cardiac cycle state of the patient. and pressure. The flow rate and pressure may be calculated by 84, except that the second blood flow rate is calculated as described above. Therefore, the specified boundary conditions are used.

[0103] The method 80 continues at block 92 with a step of determining the time at one or more points for a second cardiac cycle state. The second cardiac cycle state may further include calculating a second pressure drop resulting from the second cardiac cycle state, for example, , the end of diastole. The pressure drop can be a second drop at one or more user-specified points. The flow field can be calculated based on the flow field calculated for the cardiac cycle state.

[0104] The method 94 determines a range of cardiac cycle states based on the first pressure drop and the second pressure drop. and further calculate the range of pressure drops at relevant (e.g., user-specified) points. The pressure drop range can be from Q1 to Q2 (or between these). A range of cycle states can be calculated, where Q1 is the cardiac cycle state at the first cardiac cycle state. Q2 is the inflow rate at the second cardiac cycle state. The pressure drop in the gas is a quadratic equation shown in this disclosure as equation (1) and repeated below: It can be calculated according to the formula: ΔP=aQ+bQ 2 where Q is the flow rate at a given cardiac cycle state, and a and b are patient-specific constants. As explained above, to calculate a and b, the three-dimensional Navier-Stokes equation The equation can be expanded to include two values ​​of Q ( For example, the flow rate at the first cardiac cycle state and the flow rate at the second cardiac cycle state can be solved for Once the coefficients a and b are known, we can calculate the ΔP over diastole can be calculated. Then, that range of ΔP is can be used to calculate average values ​​to determine hemodynamic indices such as IWFR. can.

[0105] FIG. 6 shows an example graph of pressure drop for an example range of activity levels for a set of patients. 6 is a plot 100 showing the range of pressure drop (mm on the horizontal axis (units Hg / 100), and flow rate (units ml / sec). The six plot lines 102, 104, 106, 108, 110, 112, and 2 Horizontal threshold lines 114, 116 are shown. The first threshold line 114 is generally The second threshold line 116 may indicate a clinically significant pressure drop for the flow. In practice, clinically significant pressure drops for resting flow can be demonstrated.

[0106] As a result of the method 80, one or more vasculature signals of the patient are obtained for one or more locations in the patient's vasculature. Calculate (and, in embodiments, display) flow and / or pressure fields for the cardiac cycle state. For example, in one embodiment, the flow field and pressure field can be output as a diffusion field. The start and end of the diastolic phase can be calculated and output. The hemodynamic information of each of the can be used to determine

[0107] The method 80 continues at block 96 by identifying a reference pressure, e.g., one or more aortic pressures. The aortic pressure may further include measuring the aortic pressure of the patient as described herein. The aortic pressure can be determined based on the respective cuff pressures. The aortic pressure may be for end, mid-diastole, and / or mid-diastole. In this state, the reference pressure calculated in block 96 is the reference pressure calculated in blocks 82, 84, 86, and 88. , 90, 92 representing a portion of a cardiac cycle spanning a first cardiac cycle state and a second cardiac cycle state. can be done.

[0108] The method 80 determines, at block 98, the blood flow rate based on the range of pressure drop and the reference pressure. In one embodiment, the hemodynamic index value is determined by the I The index value may be a WFR value. In one embodiment, the index value is a function of the local pressure over diastole. The ratio of the local pressure to the aortic pressure can be calculated as follows: In one embodiment, the pressure field is determined by a calculated pressure field at a location of interest, such as a point. The pressure versus flow curve for diastole (e.g., as shown in Figure 6) is integrated and averaged to obtain I WFR values ​​can be calculated. For example, referring to FIG. 6, for a given plot line (e.g., For example, plot line 104) represents the IWFR for the patient associated with plot line 104. To calculate the value, it can be integrated and averaged.

[0109] FIG. 7 illustrates a general-purpose computing system environment 190, such as a desktop computer. computer, laptop, smartphone, tablet, or non-transitory computer-readable medium Any other such device capable of executing instructions, such as stored instructions within the body. FIG. 1 is a diagram of an exemplary embodiment of a user computing environment including: Although described and illustrated in the context of a computing system 190, those skilled in the art will recognize that For example, various tasks described below may be performed by multiple computing systems 190. and associating executable instructions with one or more of the plurality of computing systems 190. Local or wide area networks that can be implemented and / or run by them It will also be understood that the present invention may be practiced in a distributed environment, linked via a In some embodiments, computing environment 190, or portions thereof, may be implemented as the system of FIG. It may include a system 10.

[0110] In its most basic configuration, the computing system environment 190 typically includes comprises at least one processing unit 192 and at least one memory 194; These may be linked by a bus 196. Depending on the exact configuration and type of environment, memory 194 may be volatile (such as RAM 200), non-volatile (such as RAM 200), or non-volatile (such as RAM 200). Volatile (ROM198, flash memory, etc.), or some combination of the two The computing system environment 190 may also include additional features and / or functionality. For example, the computing system environment 190 may have limited No, but magnetic or optical disks, tape drives and / or flash drives It may also include additional storage (removable and / or non-removable) including: Further memory devices such as, for example, hard disk drive interface 20 2. Magnetic disk drive interface 204 and / or optical disk drive-in accessible to the computing system environment 190 by the interface 206 It will be appreciated that these may be linked to the system bus 196. The devices are capable of reading and writing data from and removing data from the hard disk 208. Read or write to a removable magnetic disk 210 and / or a removable optical disk Read or write to a disk 212, such as a CD / DVD ROM or other optical media The drive interfaces and their associated computer-readable media are Computer-readable instructions, data structures, program modules and computing systems It also allows for non-volatile storage of other data for the system environment 190. Other types of computer-readable media capable of storing data may be used for this same purpose. It will be further understood that such media devices may be used. magnetic cassettes, flash memory cards, digital video discs, Bernoulli cars Bernoulli cartridge, random access memory, nanodrive, memory tick, other read / write and / or read-only memory and / or computer Other devices for storing information such as readable instructions, data structures, program modules, or other data. Any such computer-aided method or technique may be used. The computer storage media may be part of the computing system environment 190 .

[0111] Storing many program modules in one or more of the memories / media devices For example, during startup, etc., communication between elements within the computing system environment 190 may occur. a basic input / output system (BIOS) 214 containing basic routines that aid in the transfer of information between the , can be stored in ROM 198. Similarly, RAM 200, hard drive 208 , and / or the peripheral memory device may include an operating system 216, one or more applications application program 218 (e.g., modules 24, 26, 28, 30, 31 of FIG. 1) 2) other program modules 220 and / or program data 222 It can be used to store computer-executable instructions. The executable instructions may be transmitted to a computing device, for example, via a network connection, as needed. It can be downloaded to the logging environment 190.

[0112] An end user, e.g., a clinician, may use a keyboard 224 and / or pointing device. A command is input to the computing system environment 190 through an input device such as a Although not shown, other input devices can be used to input information. These may include smartphones, joysticks, gamepads, scanners, etc. These and other input devices are typically connected to a peripherals interface 228. The peripheral interface 228 is connected to the processing unit 192 via the bus 196. The input device can be, for example, a parallel port, a game port, a firewire processor 1 via an interface such as a re or Universal Serial Bus (USB) 92. The computing system environment 190 a monitor 230 or other type of display device for viewing information from A video adapter 232 or other interface may also be connected to the bus 196. In addition to the monitor 230, the computing system environment 190 may also include speakers and Other peripheral output devices (not shown) may also be provided, such as printers.

[0113] The computing system environment 190 may include one or more computing system environments. A logical connection may also be used for the computing system environment 190. Communication between remote computing system environments is performed through network routing. The data may be exchanged via a further processing device, such as a network router 242. Communication using the network router 242 requires a network interface configuration. Therefore, in such a networked environment, For example, the Internet, the World Wide Web, a LAN, or other similar types of wired or in a wireless network, as illustrated with respect to a computing system environment 190. The program modules, or portions thereof, may be implemented in the computing system environment 190. It will be appreciated that the information may be stored in memory storage device(s). Deaf.

[0114] The computing system environment 190 is Location determination hardware 186 for determining location may also be provided. Location hardware 246 may include, by way of example only, a GPS antenna, an RFID chip, or or identify the location of the reader, WiFi antenna, or computing system environment 190. Other devices that can be used to capture or transmit signals that can be used to determine It may include computing hardware.

[0115] While this disclosure has described certain embodiments, the claims are intended to cover all aspects of the invention. Except as expressly recited herein, the present invention is not intended to be limited to these embodiments. To the contrary, it will be understood that the present disclosure does not include, within the spirit and scope of the present disclosure, It is intended to cover alternatives, modifications, and equivalents which may be included. In the detailed description of the present disclosure, numerous references are made to the present disclosure in order to provide a thorough understanding of the disclosed embodiments. Many specific details are described. However, systems and methods consistent with this disclosure It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. In other instances, known methods, procedures, components, and circuits may be incorporated into various aspects of the present disclosure. It is not explained in detail to avoid any ambiguity.

[0116] Some portions of the detailed description of this disclosure are presented as procedures, logic blocks, processes, and computer programs. Other symbolic representation aspects of operations on data bits in data or digital system memory These descriptions and representations have been presented in a manner that is easy to understand by those skilled in the data processing arts. the means used to most effectively convey the substance of their work to others skilled in the art. Procedures, logic blocks, processes, etc. are used herein and generally to refer to processes that perform a desired result. A step is assumed to be a self-consistent sequence of steps or instructions that result in , which require physical manipulations of physical quantities. Usually, but not necessarily, these The logical operations are performed in a computer system or similar electronic computing device. Electrical or magnetic data capable of being stored, transferred, combined, compared, and otherwise manipulated For reasons of convenience and in accordance with common usage, such data will be referred to herein as With reference to the various embodiments disclosed herein, bits, values, elements, symbols, characters, , terms, numbers, etc.

[0117] However, these terms should be construed as referring to physical operations and quantities, and should not be construed as limiting the scope of the invention. Convenient labels that should be further interpreted in light of terms commonly used in the field Unless specifically stated otherwise, As is clear from the discussion in this section, the term "identifying / determining" is used throughout the discussion of this embodiment. / requesting / determining" or "outputting" or "transmitting" or "recording" "to store" or "to display" or "to receive" or "to recognize" "Use" or "Generate" or "Provide" or "Access" or "Children" Statements using terms such as "check" or "notify" or "communicate" data manipulation and transformation applications of a computer system or similar electronic computing device It is understood that data refers to operations and processes in a computer system. The memory of a computer system is expressed as a physical (electronic) quantity in the or register, or as described herein or otherwise understood by those skilled in the art. as physical quantities within other such information storage, transmission, or display devices, are converted into other data that are similarly represented.

Claims

1. 1. A method of operating a system for providing hemodynamic information for each of a patient, comprising: The system includes a processor, and the method of operation includes: the processor obtaining a three-dimensional electronic model of the patient's anatomical region; the processor obtaining a boundary condition model representing a resting state of the patient; the processor calculating a first pressure drop across a portion of the patient's anatomical region at a first time point within the patient's cardiac cycle based on the three-dimensional electronic model and a first set of values ​​for the boundary condition model; the processor calculating a second pressure drop across the portion of the anatomical region at a second time point in the patient's cardiac cycle different from the first time point based on the three-dimensional electronic model and a second set of values ​​for the boundary condition model; the processor calculating, for a plurality of points in the patient's cardiac cycle, respective pressure drops across the anatomical region according to the first pressure drop and the second pressure drop; determining a hemodynamic index value indicative of the presence of a lesion based on the calculated pressure drops and baseline pressures for the plurality of time points; A method of operation comprising:

2. the anatomical region is a blood vessel; The method of claim 1 , wherein the portion of the anatomical region extends from an entrance to the blood vessel to a location within an artery.

3. The method of claim 1 , wherein the anatomical region is a coronary artery.

4. The method of claim 3, further comprising: receiving image data of the anatomical region of the patient; generating the three-dimensional electronic model based on the received image data; The method of claim 1 further comprising:

5. The first value set includes a first inflow flow rate; The method of claim 1 , wherein the second set of values ​​includes a second inlet flow rate that is different from the first inlet flow rate.

Images