CN110916640A - FFR-based coronary artery stenosis functional ischemia detection method and device - Google Patents
FFR-based coronary artery stenosis functional ischemia detection method and device Download PDFInfo
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Abstract
The invention discloses a method and a device for detecting functional ischemia of coronary artery stenosis based on FFR (fringe field resonance), wherein the method comprises the steps of determining characteristic parameters corresponding to each sub-virtual coronary artery in a virtual coronary artery after constructing a three-dimensional structure of the coronary artery; determining a pressure difference between the inlet pressure of the sub-virtual coronary artery and the outlet pressure of the sub-virtual coronary artery in the hyperemic state based on the characteristic parameters, and determining the hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state; calculating fractional flow reserve of each sub-virtual coronary artery based on the pressure difference of the sub-virtual coronary artery and the hyperemia average pressure of the virtual aorta, and analyzing functional ischemia caused by stenosis of the sub-virtual coronary artery based on the fractional flow reserve of each sub-virtual coronary artery. Therefore, the method can improve the accuracy of determining the Fractional Flow Reserve (FFR) and reduce the determination time to improve the detection accuracy of functional ischemia caused by the stenosis of the coronary artery and reduce the detection time.
Description
Technical Field
The invention relates to the technical field of medical treatment, in particular to a method and a device for detecting functional ischemia of coronary artery stenosis based on FFR.
Background
Coronary artery disease is a disease with high incidence, which is one of the key points harming human health, and the incidence age of coronary artery disease tends to be younger along with the change of life style of people such as diet, work and rest, so the prevention and treatment of coronary artery disease is not easy enough. Currently, coronary angiography, intravascular ultrasound, Fractional Flow Reserve (FFR), and the like are used as methods for assessing coronary artery disease. Among them, Fractional Flow Reserve (FFR) is currently the main method for quantifying and evaluating the function of coronary arteries, and is the gold standard for functional evaluation of coronary artery stenosis.
It has been found that the current Fractional Flow Reserve (FFR) is achieved by invasive measurement, i.e. by measuring the virtual aortic root mean pressure and the pressure distal to the coronary stenosis under drug (e.g. vasodilator) induced hyperemia by means of a pressure guide wire. However, since this method measures the virtual aortic root mean pressure and the distal stenosis pressure of the coronary artery in the drug-induced hyperemia state, it cannot reflect the specificity of each blood vessel included in the coronary artery, resulting in low accuracy of determining the Fractional Flow Reserve (FFR), and it takes a long time to calculate the Fractional Flow Reserve (FFR) of only one blood vessel for the whole blood vessel tree and each time, thereby reducing the accuracy and duration of detection of the stenosis functionality of the coronary artery. Therefore, it is important to provide a method for improving the accuracy of determining Fractional Flow Reserve (FFR) and reducing the determination time to improve the accuracy of detecting functional ischemia caused by coronary artery stenosis and reduce the detection time.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method and an apparatus for detecting functional ischemia due to coronary artery stenosis based on FFR, which can detect the fractional flow reserve of the coronary artery of a patient in a non-invasive manner, analyze the stenosis functionality of the coronary artery according to the fractional flow reserve, and improve the accuracy of determining the Fractional Flow Reserve (FFR) and reduce the determination time, so as to improve the accuracy of detecting functional ischemia due to coronary artery stenosis and reduce the detection time.
In order to solve the above technical problem, a first aspect of the embodiments of the present invention discloses a method for detecting functional ischemia due to coronary artery stenosis based on fractional flow reserve, the method including:
after constructing a coronary artery three-dimensional structure matched with a coronary artery, wherein the coronary artery three-dimensional structure comprises a virtual coronary artery matched with the coronary artery, and characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery are determined based on the coronary artery three-dimensional structure, and the coronary artery three-dimensional structure is a three-dimensional structure which is established in advance based on coronary artery image data of a patient;
determining a pressure difference between the inlet pressure of each sub-virtual coronary artery and the outlet pressure of the sub-virtual coronary artery in the hyperemic state based on the characteristic parameter corresponding to each sub-virtual coronary artery, and determining the hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state;
calculating fractional flow reserve of each of the sub-virtual coronary arteries based on the pressure difference of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta, and analyzing functional ischemia caused by stenosis of the sub-virtual coronary arteries based on the fractional flow reserve of each of the sub-virtual coronary arteries.
The second aspect of the embodiments of the present invention discloses a device for detecting functional ischemia of coronary artery stenosis based on FFR, which comprises:
a first determining module, configured to, after constructing a three-dimensional coronary structure matched with a coronary artery, the three-dimensional coronary structure including a virtual coronary artery matched with the coronary artery, determine, based on the three-dimensional coronary structure, a feature parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery, where the three-dimensional coronary structure is a three-dimensional structure established in advance based on image data of the coronary artery of a patient;
a second determination module, configured to calculate, based on the characteristic parameter corresponding to each of the sub-virtual coronary arteries, a pressure difference between an inlet pressure of the sub-virtual coronary artery and an outlet pressure of the sub-virtual coronary artery in a hyperemic state;
a third determination module, configured to determine a hyperemic mean pressure of a virtual aorta corresponding to the virtual coronary artery in the hyperemic state;
a calculating module for calculating fractional flow reserve of each of the sub-virtual coronary arteries based on the pressure difference of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta;
and the analysis module is used for analyzing functional ischemia caused by the stenosis of each sub-virtual coronary artery based on the fractional flow reserve of the sub-virtual coronary artery.
In a third aspect, the present invention discloses another FFR-based device for detecting functional ischemia in coronary artery stenosis, the device comprising:
a memory storing executable program code;
a processor coupled with the memory;
the processor calls the executable program code stored in the memory to execute the method for detecting functional ischemia based on FFR coronary artery stenosis disclosed by the first aspect of the invention.
In a fourth aspect, the present invention discloses a computer-readable storage medium storing computer instructions which, when invoked, perform the method for FFR-based detection of coronary stenosis functional ischemia as disclosed in the first aspect of the present invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a method and a device for detecting functional ischemia of coronary artery stenosis based on FFR (fringe field resonance), wherein the method comprises the steps of determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery after the virtual coronary artery is constructed, wherein the virtual coronary artery is a three-dimensional structure which is established in advance based on coronary artery image data of a patient; determining a pressure difference between the inlet pressure of each sub-virtual coronary artery and the outlet pressure of the sub-virtual coronary artery in the hyperemic state based on the characteristic parameter corresponding to each sub-virtual coronary artery, and determining the hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state; calculating a fractional flow reserve of each sub-virtual coronary artery based on the pressure difference of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta, and analyzing the stenosis functionality of the sub-virtual coronary artery based on the fractional flow reserve of each sub-virtual coronary artery. Therefore, by implementing the embodiment of the invention, the fractional flow reserve of the coronary artery of the patient can be detected in a non-invasive manner, the functional ischemia caused by the stenosis of the coronary artery can be analyzed according to the fractional flow reserve, the accuracy of determining the Fractional Flow Reserve (FFR) can be improved, the determination time can be shortened, the accuracy of detecting the functional ischemia caused by the stenosis of the coronary artery can be improved, the detection time can be shortened, and the Fractional Flow Reserve (FFR) can be promoted to enter clinical popularization and application.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for detecting functional ischemia due to FFR-based coronary artery stenosis according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another FFR-based method for detecting functional ischemia due to coronary artery stenosis according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a functional ischemia detection device for coronary artery stenosis based on FFR according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of another FFR-based coronary artery stenosis functional ischemia detection apparatus according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of another FFR-based coronary artery stenosis functional ischemia detection apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions, and the terms "blood vessel" and "artery" in the description and claims of the present invention and the above-described drawings mean the same. For example, a process, method, apparatus, product, or apparatus that comprises a list of steps or elements is not limited to those listed but may alternatively include other steps or elements not listed or inherent to such process, method, product, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention discloses a method and a device for detecting functional ischemia of coronary artery stenosis based on FFR (fractional flow reserve), which can detect the fractional flow reserve of coronary artery of a patient in a non-invasive mode through respective calculation, analyze the functional ischemia caused by coronary artery stenosis according to the fractional flow reserve, improve the accuracy of determining the Fractional Flow Reserve (FFR) and reduce the determination time length so as to improve the accuracy of detecting the functional ischemia caused by coronary artery stenosis and reduce the detection time length, thereby promoting the Fractional Flow Reserve (FFR) to enter clinical popularization and application. The following are detailed below.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for detecting functional ischemia due to coronary artery stenosis based on FFR according to an embodiment of the present invention. The method for detecting functional ischemia due to coronary artery stenosis based on FFR described in fig. 1 may be applied to all medical devices capable of detecting the functionality of coronary artery stenosis, and the embodiment of the present invention is not limited thereto. As shown in fig. 1, the method for detecting functional ischemia of FFR-based coronary artery stenosis may include the following operations:
101. after constructing a coronary three-dimensional structure matched with the coronary artery, the medical device determines characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the coronary three-dimensional structure, wherein the coronary three-dimensional structure is a three-dimensional structure which is established in advance based on the image data of the coronary artery of the patient, and the coronary three-dimensional structure comprises the virtual coronary artery matched with the coronary artery.
In the embodiment of the present invention, the coronary artery three-dimensional structure is specifically a three-dimensional structure (also referred to as a three-dimensional model) that is previously established by a medical device based on the coronary artery medical image data of the patient and is matched with the coronary artery of the patient. Namely: the medical device establishes a three-dimensional structure of a coronary artery based on pre-acquired coronary artery medical image data of a patient. And the three-dimensional structure of the coronary artery comprises a virtual coronary artery (also called a virtual coronary vessel) matching the coronary artery, wherein the coronary artery medical image data comprises, but is not limited to, any one of CTA coronary artery image data, MRA coronary artery image data, and DSA coronary artery image data. The embodiments of the present invention are not limited.
In an embodiment of the present invention, as an optional implementation manner, the determining, by the medical device, the characteristic parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery may include:
the medical equipment determines an inlet boundary condition of a virtual coronary artery and an outlet boundary condition of the virtual coronary artery based on a coronary three-dimensional structure, and solves a predetermined numerical algorithm based on the inlet boundary condition and the outlet boundary condition to obtain a first flow, a first inlet pressure and a first outlet pressure of each sub-virtual coronary artery in the virtual coronary artery;
the medical equipment changes the inlet boundary condition to obtain a changed inlet boundary condition, and solves the numerical algorithm based on the changed inlet boundary condition and the changed outlet boundary condition to obtain a second flow, a second inlet pressure and a second outlet pressure of each sub-virtual coronary artery in the virtual coronary artery;
the medical device determines a characteristic parameter corresponding to each sub-virtual coronary artery based on the first flow rate, the first inlet pressure and the first outlet pressure of the sub-virtual coronary artery and the second flow rate, the second inlet pressure and the second outlet pressure of the sub-virtual coronary artery.
It can be seen that, in this alternative embodiment, by obtaining the parameters of each sub-virtual coronary artery before and after the boundary condition of the virtual coronary artery changes, and implementing the calculation of the characteristic parameters corresponding to the sub-virtual coronary artery according to the parameters, the subsequent calculation of the pressure difference between the inlet end and the outlet end of the sub-virtual coronary artery is facilitated.
In an embodiment of the present invention, the medical device determining the boundary condition of the entrance of the virtual coronary artery may further include:
the medical equipment determines the coronary artery type of the coronary artery of the patient according to the coronary artery image data of the patient, wherein the coronary artery type comprises one of a left coronary artery dominant type, a right coronary artery dominant type and a left and right coronary artery balanced type;
the medical device calculates the total blood flow of the coronary arteries of the patient (i.e., the total blood flow at the entrances of the coronary arteries), and determines the entrance boundary conditions of the virtual coronary arteries based on the coronary type of the coronary arteries and the total blood flow of the coronary arteries.
The medical equipment acquires the myocardial volume of a patient according to the coronary artery image data of the patient and estimates the resting total blood flow of the coronary artery of the patient in a resting state according to the myocardial volume. Specifically, the total blood flow of the coronary artery in a resting state is determined according to the following total blood flow calculation formula;
Qt＝CMmyo
wherein Q istThe total blood flow of the virtual coronary artery in a resting state; mmyoIs the myocardial volume of the patient; c is a constant.
For example, the entrance boundary conditions of the virtual coronary artery of the left coronary artery dominant type are: the blood flow distribution of the left and right coronary arteries is 6: 4; the entrance boundary conditions of the right coronary artery dominant virtual coronary artery are as follows: the blood flow distribution of the left and right coronary arteries is 5: 5; the entrance boundary conditions of the left and right coronary artery equilibrium type virtual coronary artery are as follows: the blood flow distribution ratio of the left and right coronary arteries, which are distributed based on the total blood flow of the coronary arteries, is 4: 6.
It can be seen that, this alternative embodiment determines the inlet boundary condition of the virtual coronary artery of the patient according to the coronary artery type of the coronary artery of the patient and the total blood flow of the coronary artery, which can improve the accuracy and reliability of determining the inlet boundary condition, thereby facilitating the acquisition of the high-accuracy fractional flow reserve.
In the embodiment of the present invention, since the distal end of the outlet of the coronary artery is actually connected to the vein, and the blood flow is flowing from the coronary artery to the vein, the outlet boundary condition of each sub-virtual coronary artery is set as the zero-pressure outlet, that is, the outlet boundary condition of each sub-virtual coronary artery is that the outlet pressure of the sub-virtual coronary artery is 0. Therefore, the outlet boundary condition of the virtual coronary artery can be set according to the actual condition of the coronary artery of the patient, and the acquisition of the high-accuracy fractional flow reserve is further facilitated.
In the embodiment of the present invention, the medical device changes the boundary conditions of the inlet to obtain the changed boundary conditions of the inlet, which specifically includes: the total blood flow of each sub-virtual coronary artery after enlargement is the total blood flow Q of the sub-virtual coronary artery before enlargementtM times (e.g., 2< m < 5).
In the embodiment of the invention, the predetermined numerical algorithm is specifically based on any one of a finite element volume method, a finite element method, a finite difference method and a lattice wave Zeeman method to solve a continuity equation and a Navier-Stokes equation:
wherein, the flow velocity of U blood flow, rho is blood flow density, P is blood flow pressure, mu is blood flow viscosity,
is a gradient.
In an embodiment of the present invention, the medical device determines, based on the first flow rate, the first inlet pressure, and the first outlet pressure of each sub-virtual coronary artery and the second flow rate, the second inlet pressure, and the second outlet pressure of the sub-virtual coronary artery, a characteristic parameter corresponding to the sub-virtual coronary artery, specifically:
the medical equipment determines the characteristic parameters corresponding to the sub-virtual coronary artery according to the fitting relation between the pressure difference of the inlet pressure and the outlet pressure of the artery and the blood flow of the artery and the first flow, the first inlet pressure and the first outlet pressure of each sub-virtual coronary artery and the second flow, the second inlet pressure and the second outlet pressure of each sub-virtual coronary artery, wherein the fitting relation is as follows:
(Pa-Pd)＝AQ2+BQ
wherein, PaInlet pressure of the minor virtual coronary artery, PdThe outlet pressure of the sub-virtual coronary artery, Q the blood flow of the sub-virtual coronary artery, A the first characteristic parameter of the sub-virtual coronary artery and B the second characteristic parameter of the sub-virtual coronary artery. Wherein, each sub-virtual coronary artery has corresponding A and B parameter, and different sub-virtual coronary arteries A and B are different.
It can be seen that, by determining the characteristic parameters of each sub-virtual coronary artery respectively, the alternative embodiment is beneficial to improving the calculation accuracy and efficiency of the pressure difference between the inlet end and the outlet end of each subsequent sub-virtual coronary artery, thereby being beneficial to improving the calculation accuracy and reliability of the fractional flow reserve of each sub-virtual coronary artery.
In an optional embodiment, before the medical device determines the characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery, the method for detecting functional ischemia of coronary artery stenosis based on FFR may further include the following steps:
the medical equipment performs meshing on the coronary artery three-dimensional structure based on a predetermined meshing algorithm (such as Delaunay) to obtain a meshed coronary artery three-dimensional structure.
In this alternative embodiment, as an alternative implementation, the determining, by the medical device, the characteristic parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery may include:
the medical equipment determines characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the virtual coronary artery after meshing.
In this alternative embodiment, further, after obtaining the three-dimensional structure of the gridded coronary artery, the medical device respectively extends each sub-virtual coronary artery in the three-dimensional structure of the gridded coronary artery by a predetermined distance value along the exit direction of the sub-virtual coronary artery, wherein the predetermined distance value is n (for example, n > 100) times the exit diameter of the sub-virtual coronary artery. Therefore, the artery outlet of each sub-virtual coronary artery is respectively extended by a plurality of distances, so that the method is favorable for obtaining the more accurate coronary flow distribution ratio of each sub-virtual coronary artery in the left and right coronary arteries, is favorable for improving the obtaining accuracy of the characteristic parameters of each sub-virtual coronary artery, and is further favorable for further improving the calculation accuracy of the blood flow reserve fraction of each sub-virtual coronary artery.
Therefore, in the optional embodiment, before determining the characteristic parameters of each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery, the mesh division is performed on the three-dimensional structure of the coronary artery, so that the accuracy of the characteristic parameters of each sub-virtual coronary artery in the virtual coronary artery can be improved, and the calculation accuracy of the fractional flow reserve of each sub-virtual coronary artery is improved.
102. The medical device determines a pressure difference between an inlet pressure of each sub-virtual coronary artery and an outlet pressure of the sub-virtual coronary artery in the hyperemic state based on the corresponding characteristic parameter of the sub-virtual coronary artery.
In an embodiment of the present invention, as an optional implementation manner, the determining, by the medical device, the pressure difference between the inlet end of each sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery in the hyperemia state based on the characteristic parameter corresponding to the sub-virtual coronary artery, may include:
the medical device estimates the blood flow of each sub-virtual coronary artery under the hyperemic state, and determines the pressure difference between the inlet end of each sub-virtual coronary artery and the outlet end of each sub-virtual coronary artery under the hyperemic state according to the blood flow of each sub-virtual coronary artery under the hyperemic state and the corresponding characteristic parameters of the sub-virtual coronary artery.
In the embodiment of the present invention, it is assumed that the coronary artery of the patient has no ischemic lesion, that is, the pressure difference of each sub-virtual coronary artery is calculated based on the condition that the coronary artery has no ischemic lesion, and at this time, the medical device obtains the blood flow of each sub-virtual coronary artery in the hyperemic state, specifically:
the medical device determines the blood flow of each sub-virtual coronary artery under the resting state, and determines the blood flow of the sub-virtual coronary artery under the hyperemic state according to the blood flow of the sub-virtual coronary artery under the resting state. More specifically, the blood flow of each sub-virtual coronary artery under the hyperemic state is n1 times of the blood flow of the sub-virtual coronary artery under the resting state (for example, 3< n1< 5).
The medical equipment determines the pressure difference between the inlet end of each sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery under the hyperemia state according to the blood flow of each sub-virtual coronary artery and the characteristic parameters corresponding to the sub-virtual coronary artery, and specifically comprises the following steps:
the medical equipment inputs the blood flow of each sub-virtual coronary artery in the hyperemia state and the characteristic parameters corresponding to the sub-virtual coronary artery into a pressure difference calculation formula, and determines the pressure difference between the inlet end of the sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery in the hyperemia state, wherein the pressure difference calculation formula is as follows:
wherein Q ishypFor the blood flow of each sub-virtual coronary artery under the hyperemic state, please refer to the description of a and B in the above fitting relationship, and the description thereof is omitted here.
It can be seen that, by obtaining the blood flow of the sub-virtual coronary artery in the hyperemic state and the corresponding characteristic parameters of the sub-virtual coronary artery, the alternative embodiment can realize the pressure difference between the inlet end of the sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery, and improve the calculation efficiency of the pressure difference.
103. The medical device determines a hyperemic mean pressure of a virtual aorta corresponding to the virtual coronary artery in a hyperemic state.
It should be noted that step 103 may occur before step 101 or step 102, or may occur simultaneously with step 101 or step 102, and the implementation of the present invention is not limited.
In an embodiment of the present invention, as an optional implementation manner, the determining, by the medical device, a hyperemic mean pressure of a virtual aorta corresponding to the virtual coronary artery in a hyperemic state may include:
the medical equipment determines a first systemic circulation blood flow and a second systemic circulation blood flow in a hyperemic state of a virtual aorta corresponding to the virtual coronary artery, and obtains a static average pressure of the virtual aorta in the resting state;
the medical device calculates a hyperemic mean pressure of the virtual aorta in the hyperemic state based on the first systemic blood flow, the second systemic blood flow, and the static mean pressure.
In the embodiment of the invention, the static average pressure of the virtual aorta in the resting state is obtained by measuring the cuff.
Therefore, the alternative embodiment can realize the calculation of the hyperemic mean pressure of the virtual aorta in the hyperemic state by giving the volume of the blood flow of the body circulation in the hyperemic state and the resting mean pressure in the resting state, can realize the quick calculation of the hyperemic mean pressure and enrich the intelligent functions of the medical equipment.
In an embodiment of the present invention, as an optional implementation manner, the determining, by the medical device, a first body circulation blood flow of a virtual aorta corresponding to the virtual coronary artery in a resting state may include:
the medical equipment acquires the cardiac output of the patient, and subtracts the total blood flow of the virtual coronary artery in the resting state according to the cardiac output to obtain the first body circulation blood flow of the virtual aorta corresponding to the virtual coronary artery in the resting state.
In this alternative embodiment, the medical device obtaining cardiac output of the patient may include:
the medical device determining a cardiac output of the patient from the database;
alternatively, the first and second electrodes may be,
the medical equipment determines the body surface area and the age of a patient, and determines a cardiac output constant variable calculation formula corresponding to the patient according to the sex of the patient;
the medical device calculates the cardiac output constant of the patient according to a cardiac output constant calculation formula, and calculates the cardiac output of the patient according to the cardiac output constant of the patient and the body surface area.
Wherein, the calculation formula of the cardiac output constant variable is as follows:
CO＝CI*BSM
wherein CI is a cardiac output constant variable; CO is cardiac output; BSM is body surface area.
As can be seen, the alternative embodiment may determine the cardiac output of the patient in various ways, thereby improving the flexibility of determining the cardiac output, and determining the cardiac output of the patient from the database, thereby improving the efficiency of determining the cardiac output, or determining the cardiac output of the patient according to the parameters of the body surface area, the age, and the like of the patient, thereby improving the accuracy of determining the cardiac output of the patient, and further increasing the intelligent function of the medical device.
In an embodiment of the present invention, further, before determining the cardiac output of the patient from the database, the medical device determines whether medical data corresponding to the patient exists in the database, where the medical data at least includes the cardiac output of the patient;
when the judgment result is yes, the medical equipment executes the operation of determining the cardiac output of the patient from the database;
when the judgment result is negative, the medical equipment determines the body surface area and the age of the patient, determines a cardiac output constant variable calculation formula corresponding to the patient according to the sex of the patient, calculates the cardiac output constant variable of the patient according to the cardiac output constant variable calculation formula, and calculates the cardiac output of the patient according to the cardiac output constant variable and the body surface area of the patient.
Further, the medical device stores the cardiac output of the patient in a database. Therefore, the cardiac output of the patient is stored, so that medical personnel can check and use the cardiac output conveniently, and the acquisition efficiency of subsequent cardiac output is improved.
Therefore, in the optional embodiment, whether medical data of the patient exists in the database is firstly inquired, when the medical data of the patient exists, the medical data of the patient is directly obtained from the database, and when the medical data does not exist, the cardiac output of the patient is calculated according to the obtained parameters, so that the cardiac output of the patient is ensured to be obtained.
In yet another alternative embodiment, after performing the above-described operation of determining cardiac output of a patient from a database, the FFR-based method for detecting functional ischemia of coronary artery stenosis may further comprise the steps of:
the medical equipment determines the body surface area and the age of a patient, determines a cardiac output constant calculation formula corresponding to the patient according to the sex of the patient, and calculates the cardiac output constant of the patient according to the cardiac output constant calculation formula;
the medical device calculates the cardiac output of the patient according to the cardiac output constant and the body surface area of the patient, and obtains the calculated cardiac output and the mean cardiac output of the cardiac outputs screened from the database as the cardiac output of the patient.
Therefore, the alternative embodiment can improve the accuracy and reliability of obtaining the cardiac output of the patient by taking the calculated cardiac output and the mean cardiac output of the cardiac output screened from the database as the cardiac output of the patient, thereby being beneficial to improving the volume circulation blood flow of the sub-virtual coronary artery in the resting state.
In embodiments of the invention, the cardiac output of the patient is constant during the congestive state. And, as an alternative embodiment, the medical device determining a second systemic circulatory blood flow of the virtual aorta corresponding to the virtual coronary artery in a hyperemic state may include;
the medical equipment acquires the blood flow volume of each sub-virtual coronary artery in the hyperemia state, and adds the blood flow volumes of all the sub-virtual coronary arteries in the hyperemia state to obtain the total blood flow volume of the virtual coronary arteries in the hyperemia state;
the medical device acquires a volume circulation blood flow in a hyperemic state of a virtual aorta corresponding to the virtual coronary artery as a second volume circulation blood flow based on the acquired cardiac output of the patient and the total blood flow in the hyperemic state of the virtual coronary artery.
It can be seen that this alternative embodiment achieves the systemic blood flow of the virtual aorta corresponding to the virtual coronary artery by the blood flow of the virtual coronary artery in the hyperemic state and the cardiac output of the patient.
104. The medical device calculates the fractional flow reserve of each sub-virtual coronary artery based on the pressure difference between the pressure at the inlet end of the sub-virtual coronary artery and the pressure at the outlet end of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta.
In the embodiment of the present invention, the medical device obtains the fractional flow reserve of each sub-virtual coronary artery by a fractional flow reserve calculation formula, wherein the fractional flow reserve calculation formula is:
FFR＝1-ΔP/P′a
wherein:
P′a＝Pa*Q′s/Qs
Q′s＝CO-Q′t
Qs＝CO-Qt
wherein FFR is the fractional flow reserve of the sub-virtual coronary artery; Δ P is the pressure difference between the pressure at the inlet end of the sub-virtual coronary artery and the pressure at the outlet end of the sub-virtual coronary artery; p'aIs the hyperemic mean pressure of the virtual aorta in the hyperemic state; paFor static flattening of virtual aorta at restEqualizing the pressure; qsA body circulation blood flow (the first body circulation blood flow) of the virtual aorta in a resting state; q'sThe volume circulatory blood flow of the virtual coronary artery in the hyperemia state (the second volume circulatory blood flow); q'tThe total blood flow of the coronary artery under the hyperemia state is assumed.
105. The medical device analyzes functional ischemia caused by stenosis of each sub-virtual coronary artery based on the fractional flow reserve of the sub-virtual coronary artery.
In an embodiment of the present invention, the functional ischemia caused by stenosis of the virtual coronary artery is a stenosis functional ischemia condition of the virtual coronary artery.
In an embodiment of the present invention, as an optional implementation manner, the analyzing, by the medical device, the functional ischemia caused by stenosis of each sub-virtual coronary artery based on the fractional flow reserve of the sub-virtual coronary artery may include:
the medical device judges whether the fractional flow reserve of each sub-virtual coronary artery is larger than or equal to a predetermined fractional flow reserve threshold value (for example: 0.8);
when the fractional flow reserve of each sub-virtual coronary artery is judged to be greater than or equal to the fractional flow reserve threshold value, the medical device determines the sub-virtual coronary artery as a confident nonfunctional ischemic artery (also called confident nonfunctional ischemic vessel);
when the fractional flow reserve of each sub-virtual coronary artery is judged to be not more than the fractional flow reserve threshold, the medical equipment corrects the fractional flow reserve of the sub-virtual coronary artery to obtain the corrected fractional flow reserve, and the functional ischemia caused by the stenosis of the sub-virtual coronary artery is reanalyzed based on the corrected fractional flow reserve.
It can be seen that, in this alternative embodiment, by comparing the fractional flow reserve of each sub-virtual coronary artery with a predetermined fractional flow reserve threshold value, and when the fractional flow reserve is greater than or equal to the fractional flow reserve threshold value, determining the sub-virtual coronary artery as a confirmed nonfunctional ischemic artery, the detection efficiency and accuracy of functional ischemia caused by stenosis of the virtual coronary artery can be improved; when the flow reserve fraction is not more than the flow reserve fraction threshold, the flow reserve fraction of the sub-virtual coronary artery needs to be corrected, so that the detection accuracy of functional ischemia caused by the stenosis of the virtual coronary artery can be further improved, and the intelligent function of the medical equipment can be further enriched.
In an embodiment of the present invention, as a further optional implementation manner, the modifying, by the medical device, the fractional flow reserve of the sub-virtual coronary artery to obtain a modified fractional flow reserve may include:
the medical device acquires the blood flow of each sub-virtual coronary artery with ischemic lesion and in a hyperemic state, and re-executes the steps 103-105 based on the lesion blood flow of each sub-virtual coronary artery to obtain the corrected blood flow reserve fraction.
For example: the blood flow of each sub-virtual coronary artery in the ischemia lesion and in the hyperemia state is n2 times (for example, 2< n2<4) times of the blood flow of the sub-virtual coronary artery in the rest state. It should be noted that the blood flow of each sub-virtual coronary artery under ischemic condition is smaller than that of the sub-virtual coronary artery under non-ischemic condition, i.e. n2< n 1.
Therefore, the alternative embodiment realizes the recalculation of the fractional flow reserve of each sub-virtual coronary artery by changing the blood flow of each sub-virtual coronary artery under the hyperemia state and based on the changed blood flow, and is favorable for improving the detection accuracy and reliability of the functional ischemia caused by coronary artery stenosis.
In an embodiment of the present invention, further, the analyzing, by the medical device, the stenosis functionality of the sub-virtual coronary artery based on the corrected fractional flow reserve may include:
the medical equipment judges whether the corrected fractional flow reserve of each sub-virtual coronary artery is greater than or equal to the fractional flow reserve threshold value;
when the judgment result is negative, the medical equipment determines that the sub-virtual coronary artery is a confident functional ischemic artery (also called confident functional ischemic vessel), namely, the sub-virtual coronary artery needs to be subjected to coronary artery interventional operation and revascularization;
when the result of the determination is yes, the medical device determines that the sub-virtual coronary artery is a suspected ischemic artery (also called a suspected ischemic vessel).
Therefore, in the optional embodiment, by comparing the corrected fractional flow reserve of each sub-virtual coronary artery with the fractional flow reserve threshold, the accuracy of detecting functional ischemia caused by stenosis of the virtual coronary artery can be further improved, and corresponding medical guidance can be given according to the detection result of functional ischemia caused by stenosis of the virtual coronary artery, so that the experience of a patient is improved.
It should be noted that the medical device may calculate the fractional flow reserve of each sub-virtual coronary artery simultaneously. Further, the stenosis functionality of each sub-virtual coronary artery may also be analyzed simultaneously based on the fractional flow reserve of the sub-virtual coronary artery.
It can be seen that, by implementing the method for detecting functional ischemia due to coronary artery stenosis described in fig. 1, the fractional flow reserve of the coronary artery of a patient can be detected in a non-invasive manner through respective calculation, and functional ischemia due to coronary artery stenosis can be analyzed according to the fractional flow reserve, so that the accuracy of determining the Fractional Flow Reserve (FFR) can be improved, the determination duration can be reduced, the accuracy of detecting functional ischemia due to coronary artery stenosis can be improved, the detection duration can be reduced, and the Fractional Flow Reserve (FFR) can be promoted to enter clinical popularization and application. In addition, the flexibility and efficiency of determining the cardiac output can be improved; the intelligent function of the medical equipment can be enriched; and can also improve the detection accuracy of functional ischemia caused by coronary artery stenosis.
Example two
Referring to fig. 2, fig. 2 is a schematic flow chart of another FFR-based method for detecting coronary artery stenosis functional ischemia according to an embodiment of the present invention. The method for detecting functional ischemia due to coronary artery stenosis based on FFR described in fig. 2 can be applied to all medical devices capable of detecting the functionality of coronary artery stenosis, and the embodiment of the present invention is not limited thereto. As shown in fig. 2, the method for detecting functional ischemia of FFR-based coronary artery stenosis may include the following operations:
201. after acquiring the centerline set of the coronary arteries, the medical device constructs a number of virtual vessel cross-sections for each centerline in the centerline set.
In an embodiment of the present invention, the set of centerlines of the coronary artery includes a plurality of centerlines, wherein each centerline has a corresponding sub-coronary artery.
In an embodiment of the present invention, as an optional implementation manner, the constructing, by the medical device, a plurality of virtual vessel cross-sections of each centerline in the centerline set may include:
the medical equipment selects a plurality of center line points from each center line based on the predetermined interval distance, and constructs a virtual blood vessel cross section corresponding to the center line point based on each center line point selected from each center line to obtain a plurality of virtual blood vessel cross sections of each center line, wherein each center line point is the tangent plane center point of the virtual blood vessel cross section corresponding to the center line point.
In this alternative embodiment, the virtual vessel cross-section at which each centerline point is located is perpendicular to the tangent to the centerline at that centerline point.
In this alternative embodiment, the spacing distances may be equally spaced or unequally spaced, such as: the equal spacing distance is 1mm, namely the distance of the center line point of each center line is 1 mm; the unequal spacing distance is 0.5mm or 1mm, i.e. the distance of the centerline points of each centerline may be 0.5mm or 1 mm.
Therefore, in the alternative embodiment, a plurality of centerline points are selected from each centerline at a predetermined interval distance, and the virtual blood vessel cross section of each centerline is constructed based on the plurality of centerline points on each centerline, so that the efficiency and accuracy of constructing the virtual blood vessel cross section of each centerline can be improved.
In an alternative embodiment, the method for detecting functional ischemia of FFR-based coronary artery stenosis may further comprise the steps of:
the medical equipment performs segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricle myocardial image and a coronary artery image;
the medical equipment carries out thinning operation on the coronary artery image to extract a central line, and a central line set of the coronary artery is obtained.
In this alternative embodiment, the segmentation algorithm may include any one or a combination of Otsu threshold segmentation algorithm, adaptive threshold segmentation algorithm, maximum entropy threshold segmentation algorithm, Roberts threshold segmentation algorithm, Prewitt threshold segmentation algorithm, Sobel threshold segmentation algorithm, Marr-hilderrth threshold segmentation algorithm, Canny threshold segmentation algorithm, and morphological watershed algorithm, which is not limited in this alternative embodiment.
It can be seen that this alternative embodiment improves the efficiency and accuracy of centerline acquisition of the coronary arteries while achieving centerline acquisition of the coronary arteries by removing the left ventricular myocardium image from the coronary artery image data.
In another optional embodiment, after the medical device performs a segmentation process on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, and before the medical device performs a thinning operation on the coronary artery image to extract a centerline and obtain a centerline set of the coronary arteries, the method for detecting functional ischemia of coronary artery stenosis based on FFR may further include the following steps:
the medical equipment performs filtering operation on the coronary artery image based on a predetermined filtering algorithm to obtain a filtered coronary artery image;
in this alternative embodiment, the medical device performing a thinning operation on the coronary artery image to extract a centerline, and obtaining a centerline set of the coronary artery may include:
the medical equipment carries out thinning operation on the filtered coronary artery image to extract a central line, and a central line set of the coronary artery is obtained.
In this alternative embodiment, the filtering algorithm may include any one or a combination of filtering algorithms such as a Frangi filtering algorithm, a clipping filtering algorithm (also called a program judgment filtering algorithm), a median filtering algorithm, an arithmetic mean filtering algorithm, a recursive mean filtering algorithm (also called a moving average filtering algorithm), a median mean filtering algorithm (also called an anti-glitch mean filtering algorithm), and a weighted recursive mean filtering algorithm, which is not limited in this alternative embodiment.
Therefore, in the optional embodiment, before the centerline of the coronary artery is extracted, the coronary artery image is filtered, and the coronary artery image is distinguished from the background image, so that the coronary artery image can be enhanced, and the accuracy and efficiency of acquiring the centerline of the coronary artery can be further improved.
In yet another alternative embodiment, before the medical device performs a segmentation process on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, the method for detecting functional ischemia of coronary artery stenosis based on FFR may further include the following steps:
the medical equipment judges whether the acquired coronary artery image data of the patient contains interference image data or not, wherein the interference image data comprises lung image data and/or rib image data;
when the acquired coronary artery image data is judged to contain interference image data, the medical equipment performs segmentation operation on the coronary artery image data based on a threshold segmentation algorithm and/or a morphological segmentation algorithm, removes the interference image data, and obtains segmented coronary artery image data;
when it is determined that the acquired coronary artery image data does not include the interference image data, the medical device performs the operation of performing segmentation processing on the acquired coronary artery image data of the patient based on the predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image.
In this optional embodiment, as an optional implementation manner, the medical device performs segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, which may include:
the medical device performs segmentation processing on the segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricle myocardial image and a coronary artery image.
Therefore, in the optional embodiment, before the acquired coronary artery image data of the patient is segmented, whether the coronary artery image data has interference image data or not is judged, and when the interference image data exists, the interference image data is removed, so that the efficiency, the accuracy and the reliability of segmentation processing of the coronary artery image data can be improved, and the high-accuracy coronary artery three-dimensional structure can be further acquired.
In yet another alternative implementation, after performing a segmentation operation on the coronary artery image data based on a threshold segmentation algorithm and/or a morphological segmentation algorithm to remove the interference image data and obtain segmented coronary artery image data, and before performing a segmentation process on the segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, the method for detecting functional ischemia due to FFR-based coronary artery stenosis may further include the following steps:
the medical equipment performs Gaussian filtering smoothing operation on the segmented coronary artery image data to obtain Gaussian filtered segmented coronary artery image data.
In this optional embodiment, as an optional implementation manner, the medical device performs segmentation processing on the segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, which may include:
the medical equipment performs segmentation processing on the Gaussian filtered and segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricle myocardial image and a coronary artery image.
Therefore, in the alternative embodiment, before the segmentation processing is performed on the segmented coronary artery image data, the gaussian filtering operation is performed on the segmented coronary artery image data, so that the noise in the segmented coronary artery image data can be smoothed, the segmentation accuracy of the segmented coronary artery image data is improved, and the acquisition accuracy of the central line of the coronary artery is further improved.
202. The medical device determines the hydraulic diameter of each virtual vessel cross section corresponding to each central line, constructs the three-dimensional structure of the sub-coronary artery corresponding to the central line based on all the hydraulic diameters corresponding to each central line, and constructs the three-dimensional structure of the coronary artery based on the three-dimensional structures of all the sub-coronary arteries.
In an embodiment of the present invention, as an optional implementation manner, the determining, by the medical device, the hydraulic diameter of each virtual blood vessel cross section corresponding to each centerline may include:
the medical device calculates a segmented area and a circumference of each virtual vessel cross section of each centerline, and calculates a hydraulic diameter of the virtual vessel cross section according to the segmented area and the circumference.
Therefore, in the optional embodiment, the calculation of the hydraulic diameter of the virtual blood vessel cross section is realized by the dividing area of the virtual blood vessel cross section and the circumference, so that the calculation accuracy of the hydraulic diameter of the virtual blood vessel cross section can be improved, and the construction accuracy of the three-dimensional structure of the sub-coronary artery corresponding to the virtual blood vessel cross section is improved.
In yet another alternative embodiment, before performing step 202, the method for detecting FFR-based coronary artery stenosis functional ischemia may further comprise the steps of:
for each virtual blood vessel cross section in the plurality of virtual blood vessel cross sections of each central line, based on the center point of the section of the virtual blood vessel cross section as a seed point, the medical equipment performs segmentation operation on the virtual blood vessel cross section based on a predetermined segmentation algorithm to obtain a segmented virtual blood vessel cross section.
In this alternative embodiment, as an alternative implementation, the determining, by the medical device, the hydraulic diameter of each virtual vessel cross-section corresponding to each centerline may include:
the medical device determines a hydraulic diameter of each segmented virtual vessel cross-section for each centerline.
Therefore, in the optional embodiment, before the hydraulic diameter of each virtual blood vessel cross section of each central line is determined, the virtual blood vessel cross section is segmented, so that the sub-coronary artery corresponding to the virtual blood vessel cross section is closer to the blood vessel wall, the acquisition accuracy and the reliability of the hydraulic diameter of the virtual blood vessel cross section are improved, and the construction accuracy of the coronary artery three-dimensional structure of the coronary artery is improved.
In this optional embodiment, further, for each of the plurality of virtual blood vessel cross sections of each centerline, taking a tangent center point of the virtual blood vessel cross section as a seed point, the medical device performs a segmentation operation on the virtual blood vessel cross section based on a predetermined segmentation algorithm to obtain a segmented virtual blood vessel cross section, which may include:
the medical equipment primarily divides all the virtual blood vessel cross sections of each central line based on a threshold algorithm and/or a region growing algorithm to obtain divided virtual blood vessel cross sections, and finely divides the divided virtual blood vessel cross sections based on a predetermined active contour algorithm (such as a level set Levelset algorithm) to obtain finely divided virtual blood vessel cross sections.
Therefore, in the optional embodiment, by performing primary segmentation and fine segmentation on all the virtual vessel cross sections of each central line, the closeness between the sub-coronary artery corresponding to the virtual vessel cross section and the vessel wall can be improved, and the acquisition accuracy and reliability of the hydraulic diameter of the virtual vessel cross section are further improved, so that the construction accuracy of the coronary three-dimensional structure of the coronary artery is improved.
203. After the medical equipment constructs the virtual coronary artery, the characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery are determined, and the virtual coronary artery is a three-dimensional structure which is established in advance based on the coronary artery image data of the patient.
204. The medical device determines a pressure difference between an inlet pressure of each sub-virtual coronary artery and an outlet pressure of the sub-virtual coronary artery in the hyperemic state based on the corresponding characteristic parameter of the sub-virtual coronary artery.
205. The medical device determines a hyperemic mean pressure of a virtual aorta corresponding to the virtual coronary artery in a hyperemic state.
It should be noted that step 205 may occur before step 203 or step 204, or may occur simultaneously with step 203 or step 204, and the implementation of the present invention is not limited.
206. The medical device calculates fractional flow reserve for each sub-virtual coronary artery based on the pressure difference for that sub-virtual coronary artery and the hyperemic mean pressure for the virtual aorta.
207. The medical device analyzes functional ischemia caused by stenosis of each sub-virtual coronary artery based on the fractional flow reserve of the sub-virtual coronary artery.
In the embodiment of the present invention, for the related description of step 203 to step 207, refer to the detailed description of step 101 to step 105, which is not repeated herein.
It can be seen that, by implementing the method for detecting functional ischemia due to coronary artery stenosis described in fig. 2, it is possible to detect fractional flow reserve of coronary arteries of a patient in a non-invasive manner through respective calculation, and analyze functional ischemia due to coronary artery stenosis according to the fractional flow reserve, so as to improve accuracy of determining Fractional Flow Reserve (FFR) and reduce determination time, so as to improve accuracy of detecting functional ischemia due to coronary artery stenosis and reduce detection time, thereby promoting the Fractional Flow Reserve (FFR) to enter clinical popularization and application; and, the efficiency and accuracy of obtaining the centerline of the coronary artery can also be improved; and the accuracy and precision of constructing the three-dimensional coronary artery structure of the coronary artery can be improved.
EXAMPLE III
Referring to fig. 3, fig. 3 is a schematic structural diagram of a device for detecting functional ischemia due to coronary artery stenosis based on FFR according to an embodiment of the present invention. The FFR-based coronary artery stenosis functional ischemia detection apparatus described in fig. 3 can be applied to all medical devices capable of detecting coronary artery stenosis functionality, and the embodiment of the present invention is not limited thereto. As shown in fig. 3, the apparatus for detecting FFR-based coronary stenosis functional ischemia may comprise a first determining module 301, a second determining module 302, a third determining module 303, a calculating module 304, and an analyzing module 305, wherein:
the first determining module 301 is configured to determine, after constructing a coronary three-dimensional structure matched with a coronary artery, a feature parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the coronary three-dimensional structure, where the coronary three-dimensional structure is a three-dimensional structure that is established in advance based on image data of the coronary artery of the patient, and the coronary three-dimensional structure includes the virtual coronary artery matched with the coronary artery.
A second determining module 302, configured to calculate, based on the characteristic parameter corresponding to each sub-virtual coronary artery, a pressure difference between an inlet pressure of the sub-virtual coronary artery and an outlet pressure of the sub-virtual coronary artery in the hyperemic state.
A third determining module 303, configured to determine a hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state.
A calculating module 304 for calculating fractional flow reserve of each sub-virtual coronary artery based on the pressure difference of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta.
An analysis module 305 for analyzing functional ischemia caused by stenosis of each sub-virtual coronary artery based on the fractional flow reserve of the sub-virtual coronary artery.
It can be seen that, the detection apparatus for performing FFR-based coronary artery stenosis functional ischemia described in fig. 3 can detect fractional flow reserve of coronary arteries of a patient in a non-invasive manner by separately calculating, and analyze functional ischemia caused by coronary artery stenosis according to the fractional flow reserve, so that accuracy of determining Fractional Flow Reserve (FFR) can be improved, and determination duration can be reduced, so as to improve accuracy of detecting functional ischemia caused by coronary artery stenosis and reduce detection duration, thereby promoting clinical popularization and application of Fractional Flow Reserve (FFR).
In an alternative embodiment, the first determining module 301 may include a first determining sub-module 3011, a solving sub-module 3012, and a modifying sub-module 3013, in which case, the FFR-based detection apparatus for coronary artery stenosis functional ischemia may be as shown in fig. 4, where fig. 4 is another FFR-based detection apparatus for coronary artery stenosis functional ischemia, where:
the first determining submodule 3011 is configured to determine an entrance boundary condition of the virtual coronary artery and an exit boundary condition of the virtual coronary artery.
The solving submodule 3012 is configured to solve a predetermined numerical algorithm based on the inlet boundary condition and the outlet boundary condition to obtain a first flow rate, a first inlet pressure, and a first outlet pressure of each sub-virtual coronary artery in the virtual coronary artery.
And the modifying sub-module 3013 is configured to modify the import boundary condition to obtain a modified import boundary condition.
The solving submodule 3012 is further configured to solve a numerical algorithm based on the changed inlet boundary condition and outlet boundary condition, so as to obtain a second flow, a second inlet pressure, and a second outlet pressure of each sub-virtual coronary artery in the virtual coronary artery.
The first determining sub-module 3011 is further configured to determine a characteristic parameter corresponding to each sub-virtual coronary artery based on the first flow rate, the first inlet pressure, the first outlet pressure of each sub-virtual coronary artery and the second flow rate, the second inlet pressure, and the second outlet pressure of the sub-virtual coronary artery.
It can be seen that the apparatus for detecting functional ischemia due to FFR-based coronary artery stenosis depicted in fig. 4 can obtain the parameters of each sub-virtual coronary artery before and after the boundary condition of the virtual coronary artery changes, and implement the calculation of the characteristic parameters corresponding to the sub-virtual coronary artery according to the parameters, thereby facilitating the subsequent calculation of the pressure difference between the inlet end and the outlet end of the sub-virtual coronary artery.
In another alternative embodiment, as shown in fig. 4, the second determining module 302 determines the pressure difference between the inlet end of each sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery in the hyperemic state based on the characteristic parameter corresponding to the sub-virtual coronary artery by:
and estimating the blood flow of each sub-virtual coronary artery in a hyperemic state, and determining the pressure difference between the inlet end of each sub-virtual coronary artery and the outlet end of each sub-virtual coronary artery in the hyperemic state according to the blood flow of each sub-virtual coronary artery and the corresponding characteristic parameters of the sub-virtual coronary artery.
It can be seen that, the apparatus for detecting FFR-based coronary artery stenosis functional ischemia described in fig. 4 can also obtain the blood flow of a sub-virtual coronary artery in a hyperemic state and the corresponding characteristic parameters of the sub-virtual coronary artery, so as to realize the pressure difference between the inlet end of the sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery, and improve the calculation efficiency of the pressure difference.
In yet another alternative embodiment, as shown in fig. 4, the third determining module 303 may include a second determining submodule 3031, an obtaining submodule 3032, and a calculating submodule 3033, wherein:
the second determining submodule 3031 is configured to determine a first systemic circulatory blood flow in a resting state and a second systemic circulatory blood flow in a hyperemic state of a virtual aorta corresponding to the virtual coronary artery.
The obtaining sub-module 3032 is configured to obtain a static average pressure of the virtual aorta in a resting state.
A calculation submodule 3033 is configured to calculate a hyperemic mean pressure of the virtual aorta in the hyperemic state based on the first systemic circulatory blood flow, the second systemic circulatory blood flow, and the static mean pressure.
It can be seen that, the device for detecting functional ischemia of FFR-based coronary artery stenosis described in fig. 4 can also realize the calculation of the hyperemic mean pressure of the virtual aorta in the hyperemic state by giving the volume of blood flow of the body circulation in the hyperemic state and the resting state, and the resting mean pressure in the resting state, and can realize the rapid calculation of the hyperemic mean pressure and enrich the intelligent functions of the medical device.
In yet another alternative embodiment, as shown in fig. 4, the analysis module 305 may include a determination sub-module 3051, a third determination sub-module 3052, a modification sub-module 3053, and an analysis sub-module 3054, wherein:
a determination sub-module 3051, configured to determine whether the fractional flow reserve of each sub-virtual coronary artery is greater than or equal to a predetermined fractional flow reserve threshold.
The third determining sub-module 3052 is configured to, when the determining sub-module 3051 determines that the fractional flow reserve of each sub-virtual coronary artery is greater than or equal to the fractional flow reserve threshold, determine that the sub-virtual coronary artery is a confirmed nonfunctional ischemic vessel.
The correcting submodule 3053 is configured to, when the determining submodule 3051 determines that the fractional flow reserve of each sub-virtual coronary artery is not greater than the fractional flow reserve threshold, correct the fractional flow reserve of the sub-virtual coronary artery to obtain a corrected fractional flow reserve.
An analysis sub-module 3054 for analyzing the stenosis functionality of the sub-virtual coronary artery based on the modified fractional flow reserve.
It can be seen that the apparatus for detecting functional ischemia due to FFR-based coronary artery stenosis depicted in fig. 4 can also improve the efficiency and accuracy of detecting functional ischemia due to virtual coronary artery stenosis by comparing the fractional flow reserve of each sub-virtual coronary artery with a predetermined fractional flow reserve threshold value, and when the fractional flow reserve is greater than or equal to the fractional flow reserve threshold value, determining the sub-virtual coronary artery as a certain nonfunctional ischemic artery; when the flow reserve fraction is not more than the flow reserve fraction threshold, the flow reserve fraction of the sub-virtual coronary artery needs to be corrected, so that the detection accuracy of functional ischemia caused by the stenosis of the virtual coronary artery can be further improved, and the intelligent function of the medical equipment can be further enriched.
In yet another alternative embodiment, as shown in fig. 4, the apparatus for detecting FFR-based coronary artery stenosis functional ischemia may further include a constructing module 306, wherein:
a constructing module 306, configured to construct a plurality of virtual vessel cross-sections of each centerline in the centerline set after acquiring the centerline set of the coronary artery.
The second determining module 302 is further configured to determine a hydraulic diameter of each virtual vessel cross-section corresponding to each centerline.
And a construction module 306 for constructing a three-dimensional structure of the sub-coronary artery corresponding to each centerline based on all the hydraulic diameters corresponding to the centerline.
The construction module 306 is further configured to construct a coronary three-dimensional structure of the coronary artery based on the three-dimensional structures of all the sub-coronary arteries.
In this alternative embodiment, as an alternative implementation, the second determining module 302 determines the hydraulic diameter of each virtual blood vessel cross section corresponding to each centerline in a manner that:
and calculating the segmentation area and the perimeter of each virtual blood vessel cross section of each central line, and calculating the hydraulic diameter of the virtual blood vessel cross section according to the segmentation area and the perimeter.
Therefore, in the optional embodiment, the calculation of the hydraulic diameter of the virtual blood vessel cross section is realized by the dividing area of the virtual blood vessel cross section and the circumference, so that the calculation accuracy of the hydraulic diameter of the virtual blood vessel cross section can be improved, and the construction accuracy of the three-dimensional structure of the sub-coronary artery corresponding to the virtual blood vessel cross section is improved.
In this optional embodiment, as an optional implementation manner, the manner for constructing the plurality of virtual vessel cross sections of each centerline in the centerline set by the construction module 306 is specifically as follows:
selecting a plurality of center line points from each center line based on a predetermined interval distance, and constructing a virtual blood vessel cross section corresponding to the center line point based on each selected center line point on each center line to obtain a plurality of virtual blood vessel cross sections of each center line, wherein each center line point is a tangent plane center point of the virtual blood vessel cross section corresponding to the center line point.
In this alternative embodiment, the virtual vessel cross-section at which each centerline point is located is perpendicular to the tangent to the centerline at that centerline point.
Therefore, in the alternative embodiment, a plurality of centerline points are selected from each centerline at a predetermined interval distance, and the virtual blood vessel cross section of each centerline is constructed based on the plurality of centerline points on each centerline, so that the efficiency and accuracy of constructing the virtual blood vessel cross section of each centerline can be improved.
It can be seen that, by implementing the FFR-based detection apparatus for coronary artery stenosis functional ischemia described in fig. 4, the three-dimensional structure of the sub-coronary artery corresponding to the center line can be constructed based on all the hydraulic diameters of each center line by constructing a plurality of virtual blood vessel cross sections of each center line in the set of center lines of the coronary artery, and calculating the hydraulic diameter of each virtual blood vessel cross section of each center line, so that the three-dimensional structure of the coronary artery can be constructed, the acquisition efficiency and accuracy of the center line of the coronary artery can be improved, and the construction accuracy and precision of the three-dimensional structure of the coronary artery can be improved.
In yet another alternative embodiment, as shown in fig. 4, the apparatus for detecting FFR-based coronary artery stenosis functional ischemia may further comprise a segmentation module 307, wherein:
a segmentation module 307, configured to, after the construction module 306 acquires the centerline set of the coronary artery, construct a plurality of virtual blood vessel cross sections of each centerline in the centerline set, and before the second determination module 302 determines the hydraulic diameter of each virtual blood vessel cross section corresponding to each centerline, perform a segmentation operation on each virtual blood vessel cross section of the plurality of virtual blood vessel cross sections of each centerline based on a predetermined segmentation algorithm, with a tangent plane center point of the virtual blood vessel cross section being a seed point, to obtain a segmented virtual blood vessel cross section;
the second determining module 302 determines the hydraulic diameter of each virtual blood vessel cross section corresponding to each centerline in a specific manner:
and determining the hydraulic diameter of each segmented virtual blood vessel cross section corresponding to each central line.
It can be seen that, by implementing the FFR-based detection apparatus for coronary artery stenosis functional ischemia described in fig. 4, before determining the hydraulic diameter of each virtual blood vessel cross section of each centerline, the virtual blood vessel cross section is segmented, so that the sub-coronary artery corresponding to the virtual blood vessel cross section is closer to the blood vessel wall, which is beneficial to improving the acquisition accuracy and reliability of the hydraulic diameter of the virtual blood vessel cross section, and thus improving the construction accuracy of the coronary artery three-dimensional structure.
In yet another alternative embodiment, as shown in fig. 4, the dividing module 308 is configured to, before the first determining module 301 determines the feature parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the coronary artery three-dimensional structure, perform meshing on the coronary artery three-dimensional structure based on a predetermined meshing algorithm to obtain a meshed coronary artery three-dimensional structure.
In this optional embodiment, as an optional implementation manner, the manner of determining the characteristic parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery by the first determining module 301 is specifically:
and determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the virtual coronary artery after the meshing.
It can be seen that, by implementing the FFR-based detection apparatus for coronary stenosis functional ischemia described in fig. 4, before determining the characteristic parameters of each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery, the three-dimensional structure of the coronary artery can be gridded, so that the accuracy of the characteristic parameters of each sub-virtual coronary artery in the virtual coronary artery can be improved, and the accuracy of calculating the fractional flow reserve of each sub-coronary artery can be improved.
In yet another alternative embodiment, as shown in fig. 4, the apparatus for detecting FFR-based coronary artery stenosis functional ischemia may further include an extraction module 309, wherein:
the segmentation module 307 is further configured to perform segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image;
the extracting module 309 is configured to perform a thinning operation on the coronary artery image to extract a centerline, so as to obtain a centerline set of the coronary artery.
It can be seen that the apparatus for detecting functional ischemia due to FFR-based coronary artery stenosis depicted in fig. 4 can also improve the efficiency and accuracy of obtaining the centerline of the coronary artery while achieving the centerline of the coronary artery by removing the left ventricular myocardium image from the coronary artery image data.
In yet another alternative embodiment, as shown in fig. 4, the apparatus for detecting FFR-based coronary artery stenosis functional ischemia may further include a filtering module 310, wherein:
a filtering module 310, configured to, after the segmentation module 307 performs segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, and before the extraction module 309 performs thinning operation on the coronary artery image to extract a centerline and obtain a centerline set of the coronary artery, perform filtering operation on the coronary artery image based on a predetermined filtering algorithm to obtain a filtered coronary artery image;
in this optional embodiment, the extracting module 309 performs a thinning operation on the coronary artery image to extract the centerline, and the manner of obtaining the centerline set of the coronary artery specifically is as follows:
and performing thinning operation on the filtered coronary artery image to extract a central line, and obtaining a central line set of the coronary artery.
It can be seen that, by implementing the FFR-based detection apparatus for coronary artery stenosis functional ischemia described in fig. 4, the coronary artery image can be filtered before the centerline of the coronary artery is extracted, so that the coronary artery image can be distinguished from the background image, the coronary artery image can be enhanced, and the accuracy and efficiency of obtaining the centerline of the coronary artery can be further improved.
In yet another alternative embodiment, as shown in fig. 4, the apparatus for detecting functional ischemia of FFR-based coronary artery stenosis may further include a determining module 311, wherein:
a determining module 311, configured to determine whether the acquired coronary artery image data of the patient includes interference image data before the segmentation module 307 performs segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image, where the interference image data includes lung image data and/or rib image data;
the segmentation module 307 is further configured to, when the judgment module 311 judges that the acquired coronary artery image data includes interference image data, perform a segmentation operation on the coronary artery image data based on a threshold segmentation algorithm and/or a morphological segmentation algorithm, remove the interference image data, and obtain segmented coronary artery image data;
the segmentation module 307 is further configured to, when the judgment module 311 judges that the acquired coronary artery image data does not include the interference image data, perform segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image.
In this optional embodiment, as an optional implementation manner, the segmentation module 307 performs segmentation processing on the acquired coronary artery image data of the patient based on a predetermined segmentation algorithm, and a manner of obtaining the left ventricular myocardium image and the coronary artery image is specifically:
and performing segmentation processing on the segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricle myocardial image and a coronary artery image.
It can be seen that, the detection apparatus for coronary artery stenosis functional ischemia based on FFR described in fig. 4 can also determine whether there is interference image data in the acquired coronary artery image data of the patient before performing segmentation processing on the coronary artery image data, and when there is interference image data, remove the interference image data first, so as to improve the efficiency, accuracy and reliability of the segmentation processing performed on the coronary artery image data, and further facilitate obtaining a high-accuracy coronary artery three-dimensional structure.
In yet another alternative implementation, as shown in fig. 4, the filtering module 310 is further configured to perform a gaussian filtering smoothing operation on the segmented coronary artery image data to obtain gaussian filtered segmented coronary artery image data after the segmentation module 307 performs a segmentation operation on the coronary artery image data based on a threshold segmentation algorithm and/or a morphological segmentation algorithm to remove the interference image data to obtain the segmented coronary artery image data, and before the segmentation module 307 performs a segmentation process on the segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricular myocardium image and a coronary artery image.
In this optional embodiment, as an optional implementation manner, the segmentation module 307 performs segmentation processing on the segmented coronary artery image data based on a predetermined segmentation algorithm, and a manner of obtaining the left ventricular myocardium image and the coronary artery image is specifically as follows:
and performing segmentation processing on the Gaussian filtered and segmented coronary artery image data based on a predetermined segmentation algorithm to obtain a left ventricle myocardial image and a coronary artery image.
It can be seen that the apparatus for detecting functional ischemia due to FFR-based coronary artery stenosis depicted in fig. 4 can smooth noise in the segmented coronary artery image data by performing gaussian filtering on the segmented coronary artery image data before performing segmentation processing on the segmented coronary artery image data, thereby improving segmentation accuracy of the segmented coronary artery image data and further improving acquisition accuracy of the centerline of the coronary artery.
Example four
Referring to fig. 5, fig. 5 is a schematic diagram illustrating another apparatus for detecting functional ischemia due to coronary artery stenosis based on FFR according to an embodiment of the present invention. As shown in fig. 5, the FFR-based detection apparatus for coronary artery stenosis functional ischemia may include:
a memory 501 in which executable program code is stored;
a processor 502 coupled to a memory 501;
the processor 502 invokes executable program code stored in the memory 501 for performing the steps in the method for detecting FFR-based coronary stenosis functional ischemia described in embodiment one or embodiment two.
EXAMPLE five
The embodiment of the invention discloses a computer-readable storage medium for storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the detection method for the functional ischemia based on the FFR coronary artery stenosis described in the first embodiment or the second embodiment.
EXAMPLE six
The embodiment of the invention discloses a computer program product, which comprises a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to make a computer execute the steps of the detection method for functional ischemia based on FFR coronary artery stenosis described in the first embodiment or the second embodiment.
The above-described embodiments of the apparatus are merely illustrative, and the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above detailed description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. Based on such understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, wherein the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable rewritable Read-Only Memory (EEPROM), a compact disc-Read-Only Memory (CD-ROM) or other magnetic disk memories, a magnetic tape Memory, a magnetic disk, a magnetic tape Memory, a magnetic tape, and a magnetic tape, Or any other medium which can be used to carry or store data and which can be read by a computer.
Finally, it should be noted that: the method and apparatus for detecting functional ischemia due to coronary artery stenosis based on FFR disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used for illustrating the technical solutions of the present invention, not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for FFR-based detection of coronary stenosis functional ischemia, the method comprising:
after constructing a coronary artery three-dimensional structure matched with a coronary artery, wherein the coronary artery three-dimensional structure comprises a virtual coronary artery matched with the coronary artery, and characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery are determined based on the coronary artery three-dimensional structure, and the coronary artery three-dimensional structure is a three-dimensional structure which is established in advance based on coronary artery image data of a patient;
determining a pressure difference between the inlet pressure of each sub-virtual coronary artery and the outlet pressure of the sub-virtual coronary artery in the hyperemic state based on the characteristic parameter corresponding to each sub-virtual coronary artery, and determining the hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state;
calculating fractional flow reserve of each of the sub-virtual coronary arteries based on the pressure difference of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta, and analyzing functional ischemia caused by stenosis of the sub-virtual coronary arteries based on the fractional flow reserve of each of the sub-virtual coronary arteries.
2. The method for detecting FFR-based coronary artery stenosis functional ischemia according to claim 1, wherein the determining the feature parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery comprises:
determining inlet boundary conditions of the virtual coronary arteries and outlet boundary conditions of the virtual coronary arteries, and solving a predetermined numerical algorithm based on the inlet boundary conditions and the outlet boundary conditions to obtain a first flow, a first inlet pressure and a first outlet pressure of each sub-virtual coronary artery in the virtual coronary arteries;
changing the inlet boundary condition to obtain a changed inlet boundary condition, and solving the numerical algorithm based on the changed inlet boundary condition and the changed outlet boundary condition to obtain a second flow, a second inlet pressure and a second outlet pressure of each sub-virtual coronary artery in the virtual coronary artery;
and determining the characteristic parameters corresponding to the sub-virtual coronary artery based on the first flow, the first inlet pressure and the first outlet pressure of each sub-virtual coronary artery and the second flow, the second inlet pressure and the second outlet pressure of the sub-virtual coronary artery.
3. The method of claim 1 or 2, wherein the determining the pressure difference between the inlet end of the sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery under hyperemia based on the characteristic parameters corresponding to each sub-virtual coronary artery comprises:
and estimating the blood flow of each sub-virtual coronary artery under the hyperemic state, and determining the pressure difference between the inlet end of the sub-virtual coronary artery and the outlet end of the sub-virtual coronary artery under the hyperemic state according to the blood flow of each sub-virtual coronary artery under the hyperemic state and the corresponding characteristic parameters of the sub-virtual coronary artery.
4. The method for detecting FFR-based coronary artery stenosis functional ischemia as recited in any of claims 1-3, wherein the determining the hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state comprises:
determining a first systemic circulation blood flow and a second systemic circulation blood flow in the hyperemic state of a virtual aorta corresponding to the virtual coronary artery in a resting state, and acquiring a static average pressure of the virtual aorta in the resting state;
calculating a hyperemic mean pressure of the virtual aorta in the hyperemic state based on the first systemic circulatory blood flow, the second systemic circulatory blood flow, and the static mean pressure.
5. The method for detecting FFR-based coronary artery stenosis functional ischemia as claimed in any one of claims 1-4, wherein the analyzing the functional ischemia due to stenosis of each sub-virtual coronary artery based on fractional flow reserve of the sub-virtual coronary artery comprises:
judging whether the fractional flow reserve of each sub-virtual coronary artery is larger than or equal to a predetermined fractional flow reserve threshold value or not;
when the fractional flow reserve of each sub-virtual coronary artery is judged to be greater than or equal to the fractional flow reserve threshold value, determining the sub-virtual coronary artery as a confident nonfunctional ischemic vessel;
and when the fractional flow reserve of each sub-virtual coronary artery is judged to be not more than the fractional flow reserve threshold, correcting the fractional flow reserve of the sub-virtual coronary artery to obtain a corrected fractional flow reserve, and re-analyzing the functional ischemia caused by the stenosis of the sub-virtual coronary artery based on the corrected fractional flow reserve.
6. The method for detecting FFR-based coronary artery stenosis functional ischemia as claimed in any of claims 1-5, further comprising:
after acquiring a centerline set of coronary arteries, constructing a plurality of virtual vessel cross sections of each centerline in the centerline set;
determining the hydraulic diameter of each virtual vessel cross section corresponding to each central line, constructing the three-dimensional structure of the sub-coronary artery corresponding to the central line based on all the hydraulic diameters corresponding to each central line, and constructing the three-dimensional structure of the coronary artery based on the three-dimensional structures of all the sub-coronary arteries.
7. The FFR-based method for detecting coronary artery stenosis functional ischemia according to claim 6, wherein after obtaining the set of centerlines of coronary arteries, after constructing a plurality of virtual vessel cross-sections for each centerline in the set of centerlines, and before determining the hydraulic diameter of each virtual vessel cross-section corresponding to each centerline, the method further comprises:
for each virtual blood vessel cross section in the plurality of virtual blood vessel cross sections of each central line, based on the center point of the section of the virtual blood vessel cross section as a seed point, based on a predetermined segmentation algorithm, executing segmentation operation on the virtual blood vessel cross section to obtain a segmented virtual blood vessel cross section;
wherein said determining a hydraulic diameter of each of said virtual vessel cross-sections for each of said centerlines comprises:
determining the hydraulic diameter of each segmented virtual blood vessel cross section corresponding to each central line.
8. A device for FFR-based detection of coronary stenosis functional ischemia, the device comprising:
a first determining module, configured to, after constructing a three-dimensional coronary structure matched with a coronary artery, the three-dimensional coronary structure including a virtual coronary artery matched with the coronary artery, determine, based on the three-dimensional coronary structure, a feature parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery, where the three-dimensional coronary structure is a three-dimensional structure established in advance based on image data of the coronary artery of a patient;
a second determination module, configured to calculate, based on the characteristic parameter corresponding to each of the sub-virtual coronary arteries, a pressure difference between an inlet pressure of the sub-virtual coronary artery and an outlet pressure of the sub-virtual coronary artery in a hyperemic state;
a third determination module, configured to determine a hyperemic mean pressure of a virtual aorta corresponding to the virtual coronary artery in the hyperemic state;
a calculating module for calculating fractional flow reserve of each of the sub-virtual coronary arteries based on the pressure difference of the sub-virtual coronary artery and the hyperemic mean pressure of the virtual aorta;
and the analysis module is used for analyzing functional ischemia caused by the stenosis of each sub-virtual coronary artery based on the fractional flow reserve of the sub-virtual coronary artery.
9. An apparatus for FFR-based detection of coronary artery stenosis functional ischemia, the apparatus comprising:
a memory storing executable program code;
a processor coupled with the memory;
the processor invokes the executable program code stored in the memory to perform the FFR-based coronary artery stenosis functional ischemia detection method of any one of claims 1 to 7.
10. A computer-readable medium storing computer instructions which, when invoked, perform the method for FFR-based coronary stenosis functional ischemia detection of any of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113100737A (en) * | 2021-04-06 | 2021-07-13 | 复旦大学附属中山医院 | Coronary artery CTA-based quantitative evaluation system for ischemic myocardial load |
| CN113940651A (en) * | 2020-12-28 | 2022-01-18 | 深圳北芯生命科技股份有限公司 | Method and system for determining diagnosis mode based on blood vessel congestion state |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100125197A1 (en) * | 2008-11-18 | 2010-05-20 | Fishel Robert S | Method and apparatus for addressing vascular stenotic lesions |
| CN105249954A (en) * | 2014-06-30 | 2016-01-20 | 西门子公司 | Method and system for prediction of post-stenting hemodynamic metrics for treatment planning of arterial stenosis |
| CN106327487A (en) * | 2016-08-18 | 2017-01-11 | 苏州润心医疗科技有限公司 | Coronary artery blood flow reserve fraction calculation method based on X ray coronary artery angiographic image |
| CN106473731A (en) * | 2016-10-25 | 2017-03-08 | 北京工业大学 | FFR based on personalized coronary arterial tree blood flowCTComputational methods |
| CN107411767A (en) * | 2017-06-28 | 2017-12-01 | 西北工业大学 | A kind of non-invasive methods based on coronary artery CT angiographic assessment stenotic lesions resistances of blood flow |
| CN107978371A (en) * | 2017-11-30 | 2018-05-01 | 博动医学影像科技（上海）有限公司 | The quick method and system for calculating microcirculation resistance |
| CN108186038A (en) * | 2018-02-11 | 2018-06-22 | 杭州脉流科技有限公司 | The system that Coronary Blood Flow Reserve score is calculated based on angiography image |
-
2019
- 2019-11-06 CN CN201911077893.9A patent/CN110916640B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100125197A1 (en) * | 2008-11-18 | 2010-05-20 | Fishel Robert S | Method and apparatus for addressing vascular stenotic lesions |
| CN105249954A (en) * | 2014-06-30 | 2016-01-20 | 西门子公司 | Method and system for prediction of post-stenting hemodynamic metrics for treatment planning of arterial stenosis |
| CN106327487A (en) * | 2016-08-18 | 2017-01-11 | 苏州润心医疗科技有限公司 | Coronary artery blood flow reserve fraction calculation method based on X ray coronary artery angiographic image |
| CN106473731A (en) * | 2016-10-25 | 2017-03-08 | 北京工业大学 | FFR based on personalized coronary arterial tree blood flowCTComputational methods |
| CN107411767A (en) * | 2017-06-28 | 2017-12-01 | 西北工业大学 | A kind of non-invasive methods based on coronary artery CT angiographic assessment stenotic lesions resistances of blood flow |
| CN107978371A (en) * | 2017-11-30 | 2018-05-01 | 博动医学影像科技（上海）有限公司 | The quick method and system for calculating microcirculation resistance |
| CN108186038A (en) * | 2018-02-11 | 2018-06-22 | 杭州脉流科技有限公司 | The system that Coronary Blood Flow Reserve score is calculated based on angiography image |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113940651A (en) * | 2020-12-28 | 2022-01-18 | 深圳北芯生命科技股份有限公司 | Method and system for determining diagnosis mode based on blood vessel congestion state |
| CN113951842A (en) * | 2020-12-28 | 2022-01-21 | 深圳北芯生命科技股份有限公司 | Diagnostic mode determination system based on blood vessel congestion state |
| CN113951842B (en) * | 2020-12-28 | 2022-04-29 | 深圳北芯生命科技股份有限公司 | Diagnostic mode determination system based on blood vessel congestion state |
| CN113940651B (en) * | 2020-12-28 | 2022-06-21 | 深圳北芯生命科技股份有限公司 | Method and system for determining diagnosis mode based on blood vessel congestion state |
| CN113100737A (en) * | 2021-04-06 | 2021-07-13 | 复旦大学附属中山医院 | Coronary artery CTA-based quantitative evaluation system for ischemic myocardial load |
| CN113100737B (en) * | 2021-04-06 | 2023-10-27 | 复旦大学附属中山医院 | Ischemia myocardial load quantitative evaluation system based on coronary artery CTA |
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| GR01 | Patent grant |