CN110584696B

CN110584696B - Fractional flow reserve evaluation method and device and storage medium

Info

Publication number: CN110584696B
Application number: CN201910894411.2A
Authority: CN
Inventors: 刘星利; 魏润杰; 高琪; 吴鹏
Original assignee: Hangzhou Shengshi Technology Co ltd
Current assignee: Hangzhou Shengshi Technology Co ltd
Priority date: 2019-09-20
Filing date: 2019-09-20
Publication date: 2023-05-30
Anticipated expiration: 2039-09-20
Also published as: CN110584696A

Abstract

The embodiment of the invention discloses a fractional flow reserve evaluation method, a fractional flow reserve evaluation device and a storage medium, wherein the fractional flow reserve evaluation method comprises the steps of determining target arterial parameter information of a target coronary artery according to target contrast image data when the target contrast image data of the target coronary artery is acquired; matching the target arterial parameter information with a blood flow reserve evaluation model to obtain first arterial parameter information corresponding to the target arterial parameter information, wherein a plurality of groups of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of groups of sample arterial parameter information comprise the first arterial parameter information; and determining the fractional flow reserve corresponding to the target artery parameter information according to the first artery parameter information.

Description

Fractional flow reserve evaluation method and device and storage medium

Technical Field

The invention relates to the technical field of biomedical engineering, in particular to a fractional flow reserve evaluation method and device and a storage medium.

Background

Coronary artery disease (coronary arterial disease, CAD) is the most common type of cardiovascular disease, and insufficient blood supply to the coronary arteries can cause myocardial ischemia, angina, and even myocardial infarction. In recent years, CAD has been evaluated non-invasively, typically using coronary fractional flow reserve (Fractional Flow Reserve, FFR).

In the prior art, based on an electronic computed tomography (Computed Tomography Angiography, CTA) image of a coronary artery of a patient, reconstructing a three-dimensional geometric model of the coronary artery, constructing relatively real and personalized physiological flow boundary conditions, performing three-dimensional (3D) hemodynamic simulation of the coronary artery by using a numerical simulation method, and finally obtaining FFR according to the calculated pressure ratio of the far end and the near end of a narrow focus.

However, when performing three-dimensional (3D) hemodynamic simulation of coronary arteries by the numerical simulation method, it is necessary to grid-divide the coronary arteries, and the step of grid division is complicated, the number of grids is large, and the speed of calculating FFR by the terminal is reduced.

Disclosure of Invention

In order to solve the above technical problems, an embodiment of the present invention is expected to provide a fractional flow reserve evaluation method, a fractional flow reserve evaluation device, and a storage medium, which can improve the speed of calculating FFR by a terminal.

The technical scheme of the invention is realized as follows:

an embodiment of the present application provides a fractional flow reserve evaluation method, the method including:

when target contrast image data of a target coronary artery are acquired, determining target arterial parameter information of the target coronary artery according to the target contrast image data;

Matching the target arterial parameter information with a blood flow reserve evaluation model to obtain first arterial parameter information corresponding to the target arterial parameter information, wherein a plurality of groups of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of groups of sample arterial parameter information comprise the first arterial parameter information;

and determining the fractional flow reserve corresponding to the target artery parameter information according to the first artery parameter information.

In the above aspect, before the matching the target arterial parameter information with the blood flow reserve evaluation model to obtain the first arterial parameter information corresponding to the target arterial parameter information, the method further includes:

acquiring a plurality of groups of sample arterial parameter information and a plurality of sample blood flow reserve fractions corresponding to the plurality of groups of sample arterial parameter information;

and obtaining the blood flow reserve evaluation model according to the multiple groups of sample arterial parameter information and the multiple sample blood flow reserve scores.

In the above aspect, the obtaining the blood flow reserve evaluation model according to the multiple sets of sample arterial parameter information and the multiple sample blood flow reserve scores includes:

Establishing a plurality of first functional relationships between the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve;

fusing the plurality of first functional relationships to obtain an objective functional relationship;

determining a target coefficient in the target function according to the multiple groups of sample artery parameter information;

substituting the target coefficient into the target function relation to obtain the blood flow reserve evaluation model.

In the above scheme, the determining the target coefficient in the target function according to the multiple sets of sample arterial parameter information includes:

carrying out parameter estimation on the initial coefficient by utilizing the multiple groups of sample artery parameter information to obtain a first coefficient;

when the error value between the first coefficient and the initial coefficient meets a preset threshold value, determining the first coefficient as the target coefficient;

when the error value between the first coefficient and the initial coefficient does not meet the preset threshold value, continuing to perform parameter estimation on the first coefficient by utilizing the multiple groups of sample artery parameter information to obtain a second coefficient;

and determining the second coefficient as the target coefficient until the error value between the second coefficient and the third coefficient meets a preset threshold value, wherein the third coefficient is the coefficient determined before the second coefficient.

In the above aspect, the determining, according to the target contrast image data, target arterial parameter information of the target coronary artery includes:

establishing a three-dimensional coronary artery model according to the target contrast image data;

determining central line information of the coronary artery from the three-dimensional coronary artery model, wherein the central line information is data information of points forming a central line;

and determining the target artery parameter information according to the central line information and the target contrast image data.

In the above aspect, the determining the target arterial parameter information according to the centerline information and the target contrast image data includes:

obtaining initial target artery parameter information by utilizing the central line information and the target contrast image data;

and carrying out parameter adjustment on the initial target artery parameter information by taking a sample parameter range as an adjustment reference to determine the target artery parameter information, wherein the sample parameter range is a parameter adjustment range determined according to the plurality of groups of sample artery parameter information.

In the above solution, the target artery parameter information at least includes: target tissue volume, lesion tip resistance, narrowest diameter, stenosis rate, lesion branch number, and lesion length.

An embodiment of the present application provides a fractional flow reserve evaluation device, the device including:

a determining unit, configured to determine, when target contrast image data of a target coronary artery is acquired, target arterial parameter information of the target coronary artery according to the target contrast image data; determining fractional flow reserve corresponding to the target artery parameter information according to the first artery parameter information;

the matching unit is used for matching the target arterial parameter information with a blood flow reserve evaluation model to obtain the first arterial parameter information corresponding to the target arterial parameter information, wherein a plurality of groups of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of groups of sample arterial parameter information comprise the first arterial parameter information.

In the above aspect, the apparatus further includes an acquisition unit;

the acquisition unit is further used for acquiring the multiple groups of sample arterial parameter information and multiple sample blood flow reserve fractions corresponding to the multiple groups of sample arterial parameter information;

the determining unit is further configured to obtain the blood flow reserve evaluation model according to the multiple sets of sample arterial parameter information and the multiple sample blood flow reserve scores.

In the above aspect, the determining unit is specifically configured to establish a plurality of first functional relationships between the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve; fusing the plurality of first functional relationships to obtain an objective functional relationship; determining a target coefficient in the target function according to the multiple groups of sample artery parameter information; substituting the target coefficient into the target function relation to obtain the blood flow reserve evaluation model.

In the above scheme, the determining unit is specifically configured to perform parameter estimation on the initial coefficient by using the multiple sets of sample arterial parameter information to obtain a first coefficient; when the error value between the first coefficient and the initial coefficient meets a preset threshold value, determining the first coefficient as the target coefficient; when the error value between the first coefficient and the initial coefficient does not meet the preset threshold value, continuing to perform parameter estimation on the first coefficient by utilizing the multiple groups of sample artery parameter information to obtain a second coefficient; and determining the second coefficient as the target coefficient until the error value between the second coefficient and the third coefficient meets a preset threshold value, wherein the third coefficient is the coefficient determined before the second coefficient.

In the above scheme, the determining unit is specifically configured to establish a three-dimensional coronary artery model according to the target contrast image data; determining central line information of the coronary artery from the three-dimensional coronary artery model, wherein the central line information is data information of points forming a central line; and determining the target artery parameter information according to the central line information and the target contrast image data.

In the above scheme, the determining unit is specifically configured to obtain initial target arterial parameter information by using the centerline information and the target contrast image data; and carrying out parameter adjustment on the initial target artery parameter information by taking a sample parameter range as an adjustment reference to determine the target artery parameter information, wherein the sample parameter range is a parameter adjustment range determined according to the plurality of groups of sample artery parameter information.

The embodiment of the application provides a storage medium, on which a computer program is stored, applied to a fractional flow reserve evaluation device, which computer program, when being executed by a processor, implements a method as described in any of the preceding claims.

The embodiment of the invention provides a fractional flow reserve evaluation method and device and a storage medium, wherein the fractional flow reserve calculation method comprises the following steps: when target contrast image data of a target coronary artery is acquired, determining target arterial parameter information of the target coronary artery according to the target contrast image data; matching the target arterial parameter information with a blood flow reserve evaluation model to obtain first arterial parameter information corresponding to the target arterial parameter information, wherein a plurality of groups of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of groups of sample arterial parameter information comprise the first arterial parameter information; and determining the fractional flow reserve corresponding to the target artery parameter information according to the first artery parameter information. According to the implementation scheme of the method, the blood flow reserve estimating model is built in the blood flow reserve estimating device, a plurality of groups of sample artery parameter information are stored in the blood flow reserve estimating device, when the blood flow reserve estimating device obtains the target artery parameter information of the target coronary artery, the target artery parameter information can be directly matched with the plurality of groups of sample artery parameter information in the blood flow reserve estimating model, the blood flow reserve estimating device determines the standard blood flow reserve score corresponding to the plurality of groups of sample artery parameter information according to the plurality of groups of sample artery parameter information and the blood flow reserve estimating model, when the first artery parameter information corresponding to the target artery parameter information is determined from the plurality of groups of sample artery parameter information, the blood flow reserve score estimating device can determine the blood flow reserve score of the target coronary artery according to the blood flow reserve score corresponding to the first artery parameter information, three-dimensional blood flow dynamics simulation is not needed by the blood flow reserve score estimating device, the time for calculating the blood flow reserve score of the target coronary artery is reduced, and the speed for calculating the blood flow reserve score by the calculating device is improved.

Drawings

FIG. 1 is a flowchart of a fractional flow reserve evaluation method according to an embodiment of the present application;

FIG. 2 is an exemplary target coronary artery CTA image provided by an embodiment of the present application;

FIG. 3 is a schematic illustration of an exemplary coronary artery centerline provided in accordance with an embodiment of the present application;

FIG. 4 is a flowchart II of a fractional flow reserve evaluation method according to an embodiment of the present application;

fig. 5 is a schematic diagram of a composition structure of a fractional flow reserve evaluation device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

Currently, coronary artery CT imaging (CTA) and coronary angiography (invasive coronary angiography, ICA) are often used clinically to diagnose coronary heart disease. Both methods infer myocardial ischemic lesions from contrast-confirmed stenosis, however there is no necessarily link between stenosis and ischemic heart disease and myocardial infarction. How to better evaluate and guide the treatment of coronary heart disease is a focus of attention in the medical field.

Coronary fractional flow reserve (Fractional Flow Reserve, FFR) is a gold standard for assessing ischemic coronary heart disease today. FFR is defined as the ratio of the maximum blood flow available to a vessel in the presence of a stenotic lesion to the maximum blood flow available to a vessel in a normal state. The myocardial microcirculation is clinically engorged to the greatest extent by adenosine injection, with resistance as small as negligible. According to the hydrodynamic formula, the blood flow of myocardial tissue is proportional to the perfusion pressure, so that FFR can be calculated by the ratio of the pressure at the distal end of the stenosis to the pressure upstream of the stenosis. FFR in the prior art is interventional by using a pressure guide wire, and adenosine needs to be injected to fully expand the coronary microcirculation, and this way is often accompanied by a plurality of adverse reactions, which cause discomfort to the patient, and these factors cause that the FFR in the prior art has a great limitation in clinical application. Therefore, the present invention will replace FFR in the prior art with a non-invasive evaluation method of FFR, and representative FFR non-invasive evaluation methods are coronary FFRCT technology based on hemodynamic simulation and coronary FFR evaluation technology based on machine learning.

The method is based on coronary artery CTA images of patients with each characteristic, a three-dimensional geometric model of the coronary artery is obtained through reconstruction, relatively real physiological flow boundary conditions are built, and three-dimensional hemodynamic simulation is carried out on the coronary artery to obtain the FFRCT. The method mainly has the following problems: (1) The steps for constructing grids required by computational fluid dynamics (Computational Fluid Dynamics, CFD) computation are complicated, and the difficulty is high; (2) The method has the advantages that the calculation model is complex, the number of grids is large, the calculation time is long, and the method is not suitable for clinical rapid diagnosis; (3) The method has high requirements on terminal performance, and generally, the calculation task needs to be completed on a workstation or a server.

The coronary FFR evaluation technology based on machine learning evaluates the coronary FFR according to a patient vessel geometric model and by combining specific physiological information of a patient and bionic boundary conditions. The method is based on a large number of training samples and a plurality of input parameters, so that the machine learns to obtain morphological characteristics and most of flowing physical quantities of the coronary arteries. Therefore, when calculating the FFR of the coronary artery of the patient, detailed patient information, physical parameters of the body, coronary artery morphological data, physiological parameters and the like need to be determined first, and the complexity of clinical evaluation of whether the coronary artery is ischemic is increased due to the complex acquisition modes of the parameters.

In response to the above-described problems, the present application proposes a fractional flow reserve evaluation method, and the fractional flow reserve evaluation method is specifically described in embodiment one and embodiment two.

Example 1

An embodiment of the present application provides a fractional flow reserve evaluation method, fig. 1 is a flowchart of a fractional flow reserve evaluation method provided in an embodiment of the present application, and as shown in fig. 1, the fractional flow reserve evaluation method may include:

s101, when target contrast image data of a target coronary artery is acquired, determining target arterial parameter information of the target coronary artery according to the target contrast image data.

The blood flow reserve score evaluation method provided by the embodiment of the application is suitable for the situation that the blood flow reserve score evaluation device evaluates the target artery parameter information by utilizing the blood flow reserve evaluation model to obtain the blood flow reserve score corresponding to the target artery parameter information.

It should be noted that the target contrast image data may be target coronary artery CTA image data, as shown in fig. 2, where the area 1 identified in fig. 2 is the aorta, the lumen of the left and right branches of the coronary artery, and the area outside this area is the myocardium and other organs.

In the embodiment of the present application, when the fractional flow reserve evaluation device obtains the CTA image data of the target coronary artery, that is, the fractional flow reserve evaluation device obtains the target contrast image data, the fractional flow reserve evaluation device reconstructs a target three-dimensional coronary artery model of the target coronary artery by using the CTA image data, determines the target central line information of the target coronary artery from the target three-dimensional coronary artery model, and obtains the target arterial parameter information of the target coronary artery according to the target central line information.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the target contrast image data of the target coronary artery, the fractional flow reserve evaluation device may determine that the target arterial parameter of the target coronary artery has been obtained according to the target contrast image data.

The target arterial parameter information may be information such as diameter information of the narrowest part of the target coronary artery, stenosis rate information, lesion branch number information, lesion branch end resistance information, lesion length information, and target tissue volume.

In the embodiment of the application, the fractional flow reserve evaluation device establishes a three-dimensional coronary artery model according to the target contrast image data.

In the embodiment of the present application, when the fractional flow reserve estimating device obtains the target contrast image data of the target coronary artery, the fractional flow reserve estimating device establishes a three-dimensional coronary artery model according to the target contrast image data.

In the embodiment of the present application, when the fractional flow reserve evaluation device obtains the target contrast image data of the target coronary artery, the fractional flow reserve evaluation device may build a three-dimensional coronary artery model according to the target contrast image data.

It should be noted that, the manner of establishing the three-dimensional coronary artery model by the fractional flow reserve evaluation device according to the target contrast image data may be a gray value, a connected domain or a region growing manner, or may be other manners, and may specifically be determined according to an actual situation, which is not limited in the embodiment of the present application.

It should be noted that, the data format of the target contrast image data may be a data format specified by digital imaging and communication in medicine (Digital Imaging and Communications in Medicine, DICOM), or may be another data format, and the specific data format of the target contrast image data may be determined according to the actual situation, which is not limited in the embodiment of the present application.

In the embodiment of the present application, the fractional flow reserve evaluation device determines centerline information of the coronary artery from the three-dimensional coronary artery model, the centerline information being data information of points constituting the centerline.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the three-dimensional coronary artery model, the fractional flow reserve evaluation device may determine central line information of the coronary artery from the three-dimensional coronary artery model, as shown in fig. 3, fig. 3 is a central line of the coronary artery determined according to the three-dimensional coronary artery model, where the central line of the coronary artery is composed of a plurality of central points, as shown in an upper right corner circular area of fig. 3, the central line of the coronary artery is composed of central points of innumerable coronary arteries, each central point includes central point information, the central point information together constitutes central line information, the central point information includes coordinate information of the central point, and a position of the central point may be determined correspondingly according to the coordinate information of the central point.

The central line information is data information of points constituting the central line, and the central line information may be coordinate information at the central point, an equivalent area of the target coronary artery at the central point, an equivalent diameter of the target coronary artery at the central point, a blood flow direction of the target coronary artery at the central point, a parent-child node relationship of the target coronary artery at the central point, and the like.

It should be further noted that the equivalent area of the target coronary artery at the center point may be an area surrounded by a vertical interface of the target coronary artery vessel, and the equivalent diameter of the target coronary artery at the center point may be obtained by using a relationship between the equivalent area and the equivalent diameter.

It should be further noted that, the current node of the target coronary artery is the node closest to the current node in the opposite direction of blood flow, and is the father node of the current node, and the current node of the target coronary artery is the child node of the father node, where the entry point of the target coronary artery is not provided with the father node, the exit point of the target coronary artery is not provided with the child node, and the bifurcation point of the target coronary artery is the father node of the first child nodes in the branch target coronary artery, and according to the father-child node relationship of the target coronary artery, the entry of the target coronary artery and the exit of the target coronary artery can be determined.

It should be noted that, the fractional flow reserve evaluation device may extract the centerline information from the three-dimensional coronary artery model by using a centerline extraction algorithm, and may also extract the centerline information from the three-dimensional coronary artery model by using other manners, which may be specifically determined according to the actual situation, which is not limited in the embodiment of the present application.

In the embodiment of the application, the fractional flow reserve evaluation device determines target artery parameter information according to the central line information and the target contrast image data.

In this embodiment of the present application, after the fractional flow reserve evaluation device obtains the target contrast image data, the fractional flow reserve evaluation device may determine that the target arterial parameter information is based on the centerline information and the target contrast image data.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the target contrast image data of the target coronary artery, the fractional flow reserve evaluation device further performs preprocessing on the target contrast image data to determine a central position of the target tissue, and reconstructs the target tissue using the central position, thereby obtaining an initial target tissue volume.

It should be noted that the target tissue may be ventricular myocardium, and the initial target tissue volume may be a myocardial volume.

The pretreatment may be a deboning treatment and a peeling treatment, that is, the fractional flow reserve evaluation device performs deboning treatment and peeling treatment on the target contrast image data of the target coronary artery, removes a skeleton portion in the target contrast image data, and peels off the heart, the aorta, and the target coronary artery structure. Wherein, the deboning treatment mode can be realized by a deboning algorithm; the stripping treatment mode can be implemented by a stripping algorithm, and specific deboning treatment mode and stripping treatment mode can be determined by practical conditions, which are not limited in the embodiment of the present application.

It should be noted that, the method of reconstructing the target tissue by using the center position may be implemented by using a region growing algorithm, or may be implemented by using other algorithms, which may be specifically determined according to actual situations, and the embodiment of the present application is not limited to this.

In the embodiment of the present application, when the fractional flow reserve evaluation device obtains the initial target tissue volume, the fractional flow reserve evaluation device determines that the target artery parameter information is based on the centerline information and the initial target tissue volume.

In the embodiment of the application, the fractional flow reserve evaluation device obtains initial target artery parameter information by using the central line information and the target contrast image data.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains target contrast image data of a target coronary artery, the fractional flow reserve evaluation device further performs preprocessing on the target contrast image data to determine a central position of a target tissue, and reconstructs the target tissue using the central position, thereby obtaining an initial target tissue volume, the fractional flow reserve evaluation device determines a target tissue mass according to the initial target tissue volume, determines a total flow rate of the target coronary artery according to a differential growth relationship between the target tissue mass and a blood flow rate of the target coronary artery, and determines blood flow rates of left and right target coronary arteries according to the total flow rate of the coronary artery and a distribution type (left-dominant type, balanced type, right-dominant type) of the coronary artery. The fractional flow reserve evaluation device determines the flow rate in any branch of the target coronary artery by using the blood flow rates of the left and right target coronary arteries and the relationship between the blood flow rates in any branch of the target coronary arteries and the diameters of the corresponding branches.

It should be noted that, the relationship between the blood flow in any branch of the target coronary artery and the corresponding branch diameter may be a relationship in which the blood flow in any branch of the target coronary artery is proportional to the third power of the corresponding branch diameter, i.e. poiseuille law.

In the embodiment of the application, when the fractional flow reserve evaluation device determines the flow in any branch of the target coronary artery, the fractional flow reserve evaluation device obtains the pressure difference from the tail end of the branch of the target coronary artery to the far end of the microcirculation of the target coronary artery according to the inlet pressure of the target coronary artery and the far end pressure of the microcirculation of the target coronary artery, and determines the resistance of the tail end of the initial lesion according to the pressure difference, the vascular resistance calculation formula and the central line information.

The coronary inlet pressure may be the mean pressure of the aorta, and the distal pressure of the coronary microcirculation may be the central venous pressure.

In this embodiment of the present application, after the fractional flow reserve evaluation device repairs the stenosed target coronary artery, the fractional flow reserve evaluation device may determine that the initial diameter of the narrowest point, the initial stenosis rate, the initial lesion length, and the number of branches of the initial lesion of the target coronary artery are determined by using the repaired target coronary artery, the stenosed target coronary artery, and the centerline information.

It should be noted that, the initial target artery parameter information at least includes: initial target tissue volume, initial lesion tip resistance, initial narrowest diameter, initial stenosis rate, initial lesion branch number, and initial lesion length.

In this embodiment of the present application, the fractional flow reserve evaluation device adjusts the initial target arterial parameter information with the sample parameter range as an adjustment reference, so as to determine the target arterial parameter information, where the sample parameter range is a parameter adjustment range determined according to multiple sets of sample arterial parameter information.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the initial target arterial parameter information, the fractional flow reserve evaluation device may adjust the initial target arterial parameter information by using the sample parameter range as an adjustment reference, so as to determine the target arterial parameter information.

It should be noted that, the sample parameter range may be a parameter adjustment range determined according to multiple sets of sample arterial parameter information, that is, an average value of the multiple sets of sample arterial parameter information and a standard deviation of the multiple sets of sample arterial parameter information are determined, and then the average value and the standard deviation are used to determine the sample parameter range.

The average value and standard deviation of the multiple sets of sample artery parameter information can be divided into average value and standard deviation of the multiple sets of sample artery parameter information of men and average value and standard deviation of the multiple sets of sample artery parameter information of women, the average value and standard deviation of the multiple sets of sample artery parameter information of men are utilized to determine the sample parameter range of men, and the average value and standard deviation of the multiple sets of sample artery parameter information of women are utilized to determine the sample parameter range of women; the average value and standard deviation of the arterial parameter information of the multiple groups of samples can be directly calculated without separating the sex of the male and female, the range of the sample parameters can be determined according to the average value and standard deviation, and the specific mode for determining the range of the sample parameters can be determined according to the actual situation.

It should be noted that, the average value of multiple sets of sample arterial parameter information may be used as a reference, and the standard deviation of preset arterial parameter information may be used as a gap range, so as to determine the initial target arterial parameter information range. Specifically, the gap range may be a multiple of the standard deviation, e.g., the gap range may be 1.5 times the standard deviation.

Illustratively, when the target arterial parameter information is specifically the target tissue volume, the mean μ of the male sample tissue volumes is determined _male And standard deviation sigma _male And average μ of tissue volumes of female samples _female And standard deviation sigma _female Then, the average value mu of the tissue volume of the male sample is used _male Based on 1.5 times standard deviation sigma _male For the gap range, the range of the tissue volume of the male sample can be determined to be mu _male ±1.5σ _male Then the average value mu of the female target tissue volume is taken _female Based on 1.5 times standard deviation sigma _female For the gap range, it can be determined that the range of the target tissue volume of the male is mu _female ±1.5σ _female 。

Illustratively, when the initial target arterial parameter information is specifically lesion tip resistance, an average μ of the plurality of sample lesion tip resistances is determined ₁ And standard deviation sigma ₁ Mean value mu of resistance of lesion ends of a plurality of samples ₁ Based on one time standard deviation sigma ₁ For the gap range, the range of the resistance of the pathological tail end is determined as mu ₁ ±σ ₁ 。

S102, matching the target arterial parameter information with a blood flow reserve evaluation model to obtain first arterial parameter information corresponding to the target arterial parameter information, wherein a plurality of groups of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of groups of sample arterial parameter information comprise the first arterial parameter information.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the target arterial parameter information of the target coronary artery, the fractional flow reserve evaluation device matches the target arterial parameter information with the fractional flow reserve evaluation model, thereby obtaining the first arterial parameter information corresponding to the target arterial parameter information.

It should be noted that, a plurality of sets of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of sets of sample arterial parameter information includes first arterial parameter information.

When the fractional flow reserve evaluation device obtains the target arterial parameter information of the target coronary artery, the fractional flow reserve evaluation device matches the target arterial parameter information with the multiple groups of sample arterial parameter information, and determines arterial parameter information identical to the target arterial parameter information from the multiple groups of sample arterial parameter information to obtain first arterial parameter information.

S103, determining the fractional flow reserve corresponding to the target artery parameter information according to the first artery parameter information.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the first arterial parameter information, the fractional flow reserve evaluation device may determine that the fractional flow reserve corresponding to the target arterial parameter information has been scored according to the first arterial parameter information.

It should be noted that, the fractional flow reserve evaluation device is provided with a corresponding relation between preset arterial parameter information and a preset fractional flow reserve, when the fractional flow reserve evaluation device obtains first arterial parameter information, the fractional flow reserve evaluation device can determine the fractional flow reserve corresponding to the first arterial parameter information according to the corresponding relation between the preset arterial parameter information and the preset fractional flow reserve, so as to determine the fractional flow reserve corresponding to the target arterial parameter information.

It can be understood that, because the current reserve estimating device establishes the current reserve estimating model in the current reserve estimating device, a plurality of groups of sample artery parameter information are stored in the current reserve estimating device, when the current reserve estimating device obtains the target artery parameter information of the target coronary artery, the target artery parameter information can be directly matched with the plurality of groups of sample artery parameter information in the current reserve estimating device, and the current reserve estimating device determines the standard current reserve score corresponding to the plurality of groups of sample artery parameter information according to the plurality of groups of sample artery parameter information and the current reserve estimating model, when the first artery parameter information corresponding to the target artery parameter information is determined from the plurality of groups of sample artery parameter information, the current reserve estimating device can determine the current reserve score of the target coronary artery according to the current reserve score corresponding to the first artery parameter information, the current reserve score estimating device does not need to perform three-dimensional current dynamic simulation on the coronary artery, so that the time for calculating the current reserve score of the target coronary artery by the current reserve score estimating device is reduced, and the speed for calculating the current reserve score by the current reserve calculating device is improved.

Example two

The embodiment of the present application further provides a fractional flow reserve evaluation method, which is a process of obtaining a fractional flow reserve evaluation model before step 102, and the specific implementation steps are as shown in fig. 4, including:

s201, the blood flow reserve score evaluation device acquires a plurality of groups of sample artery parameter information and a plurality of sample blood flow reserve scores corresponding to the plurality of groups of sample artery parameter information.

In this embodiment of the present application, before the fractional flow reserve evaluation device matches the target arterial parameter information with the fractional flow reserve evaluation model, the fractional flow reserve evaluation device needs to acquire a plurality of sets of sample arterial parameter information and a plurality of sample fractional flow reserve corresponding to the plurality of sets of sample arterial parameter information from CTA images of a plurality of sample coronary arteries.

It should be noted that, if one set of arterial parameter information corresponds to one sample fractional flow reserve, then multiple sets of arterial parameter information correspond to multiple sample fractional flow reserve.

It should also be noted that the plurality of sample fractional flow reserve may be fractional flow reserve obtained by performing interventional measurements using a pressure guidewire.

It should be noted that, the multiple sets of sample arterial parameter information at least includes: a plurality of sample tissue volumes, a plurality of lesion tip resistances, a plurality of narrowest site diameters, a plurality of stenosis rates, a plurality of lesion branch numbers, and a plurality of lesion lengths.

In an embodiment of the present application, the fractional flow reserve evaluation device establishes a plurality of three-dimensional coronary artery models according to a plurality of sets of contrast image data, wherein the plurality of sets of contrast image data correspond to the plurality of three-dimensional coronary artery models.

It should be noted that, the manner of establishing the plurality of three-dimensional coronary artery models by the fractional flow reserve evaluation device according to the plurality of sets of contrast image data may be a manner of gray value, connected domain or region growth, or may be another manner, and may specifically be determined according to actual conditions, which is not limited in the embodiment of the present application.

The data format of the plurality of sets of contrast image data may be a DICOM format, or may be another format, and the specific data format of the plurality of sets of contrast image data may be determined according to practical situations, which is not limited in the embodiments of the present application.

In an embodiment of the present application, the fractional flow reserve evaluation device determines a plurality of sample tissue volumes from a plurality of sets of contrast image data.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains a plurality of sample contrast image data of a plurality of sample coronary arteries, the fractional flow reserve evaluation device first pre-processes the plurality of sample contrast image data, determines a center position of a plurality of sample tissues, and reconstructs the plurality of sample tissues using the center position, thereby obtaining a plurality of sample tissue volumes.

It should be noted that the plurality of sample tissue volumes may be volumes of a plurality of sample left ventricular myocardium, i.e., a plurality of sample myocardial volumes.

In an embodiment of the present application, the fractional flow reserve evaluation device determines, from a plurality of three-dimensional coronary artery models, a plurality of sample centerline information of a plurality of sample coronary arteries, wherein the plurality of sample centerline information is data information of points constituting the plurality of sample centerlines.

The plurality of sample center line information is data information of points constituting the plurality of sample center lines, and the plurality of sample center line information may be coordinate information at the plurality of sample center points, equivalent areas of the plurality of sample coronary arteries at the plurality of sample center points, equivalent diameters of the plurality of sample coronary arteries at the plurality of sample center points, blood flow directions of the plurality of sample coronary arteries at the plurality of sample center points, parent-child node relationships of the plurality of sample coronary arteries at the plurality of sample center points, and the like.

It should be noted that, the fractional flow reserve evaluation device may extract a plurality of centerline information from a plurality of three-dimensional coronary artery models by using a centerline extraction algorithm, and may also extract a plurality of centerline information from a plurality of three-dimensional coronary artery models by using other manners, which may be specifically determined according to actual situations, and the embodiment of the present application is not limited thereto.

In an embodiment of the present application, the fractional flow reserve evaluation device determines a plurality of sets of first sample arterial parameter information according to the plurality of sample centerline information and the plurality of sample tissue volumes.

It should be noted that, the plurality of sets of first sample arterial parameter information at least includes: a plurality of sample lesion end resistances, a plurality of sample narrowest diameters, a plurality of sample stenosis rates, a plurality of sample lesion branch numbers, and a plurality of sample lesion lengths.

In an embodiment of the present application, the fractional flow reserve evaluation device determines a plurality of sets of second sample arterial parameter information according to the plurality of sample centerline information and the plurality of sample tissue volumes.

In this embodiment of the present application, after the fractional flow reserve evaluation device obtains a plurality of sample tissue volumes, the fractional flow reserve evaluation device determines a plurality of sample tissue masses according to the plurality of sample tissue volumes, determines a plurality of sample coronary artery total flow according to a different-speed growth relationship between the plurality of sample tissue masses and a plurality of sample coronary artery blood flow, and determines blood flow of left and right sample coronary arteries according to the plurality of sample coronary artery total flow and distribution patterns (left dominant type, balanced type, right dominant type) of the plurality of sample coronary arteries. The fractional flow reserve evaluation device determines the flow rate in any branch of the plurality of sample coronary arteries by using the blood flow rates of the left and right sample coronary arteries of the plurality of samples and the relationship between the blood flow rate in any branch of the plurality of sample coronary arteries and the corresponding branch diameter.

In this embodiment, when the fractional flow reserve evaluation device determines the flow in any branch of the plurality of sample coronary arteries, the fractional flow reserve evaluation device obtains the pressure difference from the end of the branch of the plurality of sample coronary arteries to the end of the microcirculation of the plurality of sample coronary arteries according to the inlet pressure of the plurality of sample coronary arteries and the pressure of the microcirculation distal end of the plurality of sample coronary arteries, and determines the initial lesion end resistance of the plurality of samples according to the pressure difference, the vascular resistance calculation formula and the central line information.

In this embodiment of the present application, after the fractional flow reserve evaluation device repairs the plurality of sample stenosed coronary arteries, the fractional flow reserve evaluation device may determine that the diameters of the plurality of sample initial narrowest points, the plurality of sample initial stenosis rates, the plurality of sample initial lesion lengths, and the plurality of sample initial lesion branches of the plurality of sample coronary arteries are determined using the repaired plurality of sample coronary arteries, the plurality of stenosed sample coronary arteries, and the plurality of sample centerline information.

It should be noted that, the plurality of sets of second sample arterial parameter information at least includes: a plurality of sample initial narrowest diameters, a plurality of sample initial stenosis rates, a plurality of sample initial lesion lengths, a plurality of sample initial lesion score end resistances, and a plurality of sample initial lesion branch numbers.

In this embodiment of the present application, the fractional flow reserve evaluation device determines, with the sample parameter range as a reference, a plurality of sets of second sample arterial parameter information as parameter information satisfying the sample parameter range, and obtains a plurality of sets of first sample arterial parameter information.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains multiple sets of second sample arterial parameter information, the fractional flow reserve evaluation device determines the multiple sets of second sample arterial parameter information as parameter information satisfying the sample parameter range based on the sample parameter range, and obtains multiple sets of first sample arterial parameter information.

It should be noted that, the plurality of sets of first sample arterial parameter information at least includes: a plurality of sample tissue volumes, a plurality of sample narrowest diameters, a plurality of sample stenosis rates, a plurality of sample lesion lengths, a plurality of sample lesion end-of-score resistances, and a plurality of sample lesion branch numbers.

In an embodiment of the present application, the fractional flow reserve evaluation device uses a plurality of sets of first sample arterial parameter information and a plurality of sample tissue volumes as a plurality of sets of sample arterial parameter information.

It should be noted that, when each of the plurality of sample coronary arteries has only one stenosis, the plurality of sample lesion lengths in the plurality of sets of sample arterial parameter information may be the length of the stenosis, when each of the plurality of sample coronary arteries has a plurality of stenosis, the plurality of sample lesion lengths in the plurality of sets of sample arterial parameter information may be the sum of the lengths of the plurality of stenosis, and when the plurality of sample coronary arteries are diffuse lesions, the plurality of sample lesion lengths in the plurality of sets of sample arterial parameter information are the length of the diffuse lesion.

It should be noted that, the multiple stenosis rates in the multiple sets of sample arterial parameter information may be the minimum stenosis rate of the multiple sample coronary arteries, or may be the equivalent stenosis rate of the multiple sample coronary arteries, which may be specifically determined according to the actual situation, and the embodiment of the present application is not limited to this.

When the plurality of stenosis rates are equivalent stenosis rates of the plurality of sample coronary arteries, if the blood flow reserve score evaluation device determines that the plurality of sample coronary arteries have only one stenosis rate, the stenosis rate may be the stenosis rate of the stenosis location, and when the plurality of sample coronary arteries have more than one stenosis rate, the stenosis rates of all the stenosis locations of the plurality of sample coronary arteries are determined, and a plurality of maximum stenosis rates of the plurality of sample coronary arteries are selected therefrom, and fusion is performed between the plurality of maximum stenosis rates and the plurality of stenosis rates of the plurality of sample coronary arteries, thereby determining the equivalent stenosis rate of the plurality of sample coronary arteries, wherein the specific fusion method may be determined according to the actual situation.

Illustratively, when S ₁ ,S ₂ ,…,S _n In characterizing the stenosis rate in a single sample coronary artery, where n represents the number of stenosis in a single sample coronary artery, the maximum stenosis rate can be determined by equation (1).

S _max ＝Max(S ₁ ,S ₂ ,…,S _n ) (1)

According to the maximum stenosis rate S _max And other stenosis rates of single sample coronary arteries (S ₁ ,S ₂ ,…,S _n ) And determining the equivalent stenosis rate S' of the coronary artery of the single sample.

S202, the blood flow reserve score evaluation device obtains a blood flow reserve evaluation model according to a plurality of groups of sample artery parameter information and a plurality of sample blood flow reserve scores.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains a plurality of sets of sample arterial parameter information of a plurality of sample coronary arteries and a plurality of sample fractional flow reserve corresponding to the plurality of sets of sample arterial parameter information, the fractional flow reserve evaluation device may obtain a fractional flow reserve evaluation model according to the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve.

In an embodiment of the present application, the fractional flow reserve evaluation device establishes a plurality of first functional relationships between a plurality of sets of sample arterial parameter information and a plurality of sample fractional flow reserve.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains a plurality of sets of sample arterial parameter information of a plurality of sample coronary arteries and a plurality of sample fractional flow reserve corresponding to the plurality of sets of sample arterial parameter information, the fractional flow reserve evaluation device may establish a plurality of first functional relationships between the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve.

It should be noted that, the plurality of first functional relationships between the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve may be an exponential relationship, a logarithmic relationship, a quadratic relationship, and the like, which may be specifically determined according to actual situations, which is not limited in the embodiments of the present application.

In the embodiment of the present application, the fractional flow reserve evaluation device fuses the plurality of first functional relationships to obtain the objective functional relationship.

In the embodiment of the present application, when the fractional flow reserve evaluation device obtains a plurality of first functional relationships, the fractional flow reserve evaluation device fuses the plurality of first functional relationships, thereby obtaining the objective functional relationship.

It should be noted that, the manner in which the fractional flow reserve evaluation device fuses the plurality of first functional relationships may be additive fusion or multiplicative fusion, and the specific fusion manner may be according to the actual situation, which is not limited in the embodiment of the present application.

Illustratively, the fusing manner is additive fusing, and the plurality of first functional relationships may be respectively shown in formulas (2) - (6):

FFR＝α ₇ ln(x ₂ )+C ₂ (3)

FFR＝α ₈ ln(x ₃ )+C ₃ (4)

wherein FFR can be fractional flow reserve, x ₁ ...x ₆ Alpha is arterial parameter information ₁ ,α ₂ ,...α ₁₅ ,C ₁ ,C ₂ ,...C ₆ Coefficients and constant terms for a plurality of first functional relationships. Then the above formulas (2) - (7) are fused by using an additive fusion method, and the obtained objective function relationship may be represented by formula (8):

Wherein C is a plurality of constant terms C ₁ ,C ₂ ,...C ₆ A kind of electronic device.

In the embodiment of the application, the fractional flow reserve evaluation device determines a target coefficient in the target function according to multiple groups of sample artery parameter information.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the objective function relationship, the fractional flow reserve evaluation device determines the objective coefficient of the objective function according to the multiple sets of sample arterial parameter information.

In the embodiment of the application, the fractional flow reserve evaluation device utilizes a plurality of groups of sample artery parameter information to perform parameter estimation on the initial coefficient to obtain a first coefficient.

In this embodiment of the present application, when the fractional flow reserve evaluation device obtains the objective function relationship, the fractional flow reserve evaluation device performs parameter estimation on the initial coefficient by using the multiple sets of sample arterial parameter information, so as to obtain the first coefficient.

It should be noted that, the initial coefficient may be a coefficient set in advance for the fractional flow reserve estimating device.

In the embodiment of the present application, the fractional flow reserve evaluation device may determine the first coefficient by using a least square regression estimation coefficient, or may determine the first coefficient by using other methods, and the specific method for determining the first coefficient may be determined according to the actual situation, which is not limited in the embodiment of the present application.

For example, the fractional flow reserve evaluation device may determine the target coefficient in the target function using equation (9), where ε is an error term characterizing the target function.

FFR＝FFRreg(x ₁ ,x ₂ ,…,x _i ；α ₁ ,α ₂ ,...,α _j )+ε (9)

When the application adopts least square regression to estimate coefficient to determine the first coefficient, alpha is used ₁₄ Instead of the constant term C, the target coefficient alpha can be ₁ ,α ₂ ,...α ₁₃ C as least squares estimation, then alpha ₁ ,α ₂ ,...α ₁₃ C should minimize the sum of squares of the residuals as shown in equation (10).

Equation (10) is solved using a gaussian-newton iterative algorithm to obtain a first coefficient.

In the embodiment of the present application, the fractional flow reserve evaluation device determines the first coefficient as the target coefficient when the error value between the first coefficient and the initial coefficient satisfies a preset threshold.

In the embodiment of the present application, when the fractional flow reserve evaluation device determines that the error value between the first coefficient and the initial coefficient satisfies the preset threshold, the fractional flow reserve evaluation device determines the first coefficient as the target coefficient.

It should be noted that the first coefficient may be a plurality of coefficients, and the number of coefficients in the first coefficient is the same as the number of coefficients in the initial coefficient.

It should be noted that, the error value between the first coefficient and the initial coefficient satisfies the preset threshold, and the error of each coefficient between the first coefficient and the initial coefficient may satisfy the preset threshold, where the error satisfies the preset threshold and the error of each coefficient between the first coefficient and the initial coefficient may be smaller than the preset threshold.

Illustratively, when the number of initial coefficients and the number of first coefficients are both 5, wherein the initial coefficients are (12.583697, 13.436985,1.243679,8.535621,5.488569), the first coefficients are (12.5836971, 13.4369849,1.2436786,8.5356213,5.4885696), and the preset threshold is 1e-6, then the error of each coefficient between the first coefficients and the initial coefficients is (1 e-7,4e-7,3e-7,6 e-7), and the error of each coefficient between the first coefficients and the initial coefficients is less than the preset threshold 1e-6, i.e., the error of each coefficient between the first coefficients and the initial coefficients satisfies the preset threshold, the fractional flow reserve evaluation device determines the first coefficients as the target coefficients (12.5836971, 13.4369849,1.2436786,8.5356213,5.4885696).

In the embodiment of the present application, when the error value between the first coefficient and the initial coefficient does not meet the preset threshold, the fractional flow reserve evaluation device uses multiple sets of sample arterial parameter information to continue parameter estimation on the first coefficient, so as to obtain the second coefficient.

In the embodiment of the present application, when the fractional flow reserve evaluation device determines that the error value between the first coefficient and the initial coefficient does not meet the preset threshold, the fractional flow reserve evaluation device uses multiple sets of sample arterial parameter information to continue parameter estimation on the first coefficient, so as to obtain the second coefficient.

It should be noted that, the fractional flow reserve estimating device may utilize the least square regression estimation coefficient to continue parameter estimation on the first coefficient to obtain the second coefficient, and may also utilize other methods to parameter estimate the first coefficient to obtain the second coefficient, and the specific manner of parameter estimation on the first coefficient may be determined according to the actual situation, which is not limited in the embodiment of the present application.

In this embodiment of the present application, until the error value between the second coefficient and the third coefficient meets a preset threshold, the fractional flow reserve evaluation device determines the second coefficient as the target coefficient, and the third coefficient is a coefficient determined before the second coefficient.

In the embodiment of the present application, when the fractional flow reserve evaluation device determines that the error value between the second coefficient and the third coefficient satisfies the preset threshold, the fractional flow reserve evaluation device determines the second coefficient as the target coefficient.

The third coefficient is a coefficient determined before the fractional flow reserve estimating means obtains the second coefficient.

In the embodiment of the application, the fractional flow reserve evaluation device substitutes the target coefficient into the target function relation to obtain a fractional flow reserve evaluation model.

In this embodiment of the present application, when the fractional flow reserve estimation device obtains the target coefficient, the fractional flow reserve estimation device may substitute the target coefficient into the objective function relationship, thereby obtaining the fractional flow reserve estimation model.

It should be noted that the blood flow reserve evaluation model may be a function equation, where an argument in the function equation may be the target arterial parameter information, a coefficient in the function equation may be the target coefficient, and a dependent variable in the function equation may be a blood flow reserve score corresponding to the target arterial parameter information.

It should be noted that, when the fractional flow reserve evaluation device obtains the fractional flow reserve evaluation model, the fractional flow reserve evaluation device may determine the variable coefficient through the target coefficient, determine the adjustment coefficient through the variable coefficient and the parameter estimation times of the initial coefficient, and when the variable coefficient satisfies the adjustment coefficient, determine that the goodness of fit of the fractional flow reserve evaluation model is higher, that is, the fractional flow reserve evaluation model is a gold standard for evaluating the fractional flow reserve evaluation method. The fractional flow reserve evaluation device may further determine the goodness of fit of the fractional flow reserve evaluation model directly according to the variable coefficient, and determine that the goodness of fit of the fractional flow reserve evaluation model is higher when the value of the variable coefficient is closer to 1, and determine that the goodness of fit of the fractional flow reserve evaluation model is lower when the value of the variable coefficient is closer to 0. The specific way of determining the goodness of fit of the blood flow reserve assessment model may be determined according to practical situations, which is not limited in the embodiments of the present application.

Illustratively, the functional equation of the blood flow reserve assessment model is shown as equation (11):

in equation (11), FFR is the blood flow reservoir corresponding to the target arterial parameter informationThe score, a, is the dependent variable of the function equation ₁ .....α ₁₄ C is the target coefficient of the function equation, x ₁ ...x ₆ For 6 arterial parameter information, i.e. the argument of the function equation, in particular, x ₁ Myocardial volume that may be the target coronary artery; x is x ₂ The number of lesion branches that may be the target coronary artery; x is x ₃ May be the narrowest diameter of the target coronary artery; x is x ₄ The stenosis rate of the target coronary artery can be; x is x ₅ Resistance at the end of a lesion branch of a target coronary artery; x is x ₆ May be the lesion length of the target coronary artery.

It can be understood that, by using the multiple sets of sample arterial parameter information of the multiple sample coronary arteries and multiple sample arterial scores corresponding to the multiple sets of sample arterial parameter information, a blood flow reserve evaluation model is established, multiple sets of sample arterial parameter information are stored in the blood flow reserve evaluation model, when the blood flow reserve score estimation device obtains the target arterial parameter information of the target coronary arteries, the target arterial parameter information can be directly matched with the multiple sets of sample arterial parameter information in the blood flow reserve evaluation model, since the blood flow reserve score estimation device determines the standard blood flow reserve score corresponding to the multiple sets of sample arterial parameter information according to the multiple sets of sample arterial parameter information and the blood flow reserve evaluation model, when the first arterial parameter information corresponding to the target arterial parameter information is determined from the multiple sets of sample arterial parameter information, the blood flow reserve score estimation device can determine the blood flow reserve score of the target coronary arteries according to the blood flow reserve score corresponding to the first arterial parameter information, and the blood flow reserve score estimation device does not need to perform three-dimensional blood flow dynamics simulation on the coronary arteries, so that the time for calculating the blood flow reserve score of the target coronary arteries is reduced, and the speed of calculating the blood flow reserve score of the blood flow reserve score is increased.

Example III

An embodiment of the present application provides a fractional flow reserve estimating device 1, fig. 5 is a schematic diagram of a composition structure of the fractional flow reserve estimating device provided in the embodiment of the present application, where the fractional flow reserve estimating device 1 may include:

a determining unit 11, configured to determine, when target contrast image data of a target coronary artery is acquired, target arterial parameter information of the target coronary artery according to the target contrast image data; determining fractional flow reserve corresponding to the target artery parameter information according to the first artery parameter information;

and a matching unit 12, configured to match the target arterial parameter information with a blood flow reserve evaluation model, to obtain the first arterial parameter information corresponding to the target arterial parameter information, where multiple sets of sample arterial parameter information corresponding to multiple sample coronary arteries are stored in the blood flow reserve evaluation model, and the multiple sets of sample arterial parameter information include the first arterial parameter information.

In some embodiments of the present application, the apparatus further comprises an acquisition unit 13;

the acquiring unit 13 is further configured to acquire the multiple sets of sample arterial parameter information and multiple sample fractional flow reserve corresponding to the multiple sets of sample arterial parameter information;

The determining unit 11 is further configured to obtain the blood flow reserve evaluation model according to the multiple sets of sample arterial parameter information and the multiple sample blood flow reserve scores.

In some embodiments of the present application, the determining unit 11 is specifically configured to establish a plurality of first functional relationships between the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve; fusing the plurality of first functional relationships to obtain an objective functional relationship; determining a target coefficient in the target function according to the multiple groups of sample artery parameter information; substituting the target coefficient into the target function relation to obtain the blood flow reserve evaluation model.

In some embodiments of the present application, the determining unit 11 is specifically configured to perform parameter estimation on the initial coefficient by using the multiple sets of sample arterial parameter information to obtain a first coefficient; when the error value between the first coefficient and the initial coefficient meets a preset threshold value, determining the first coefficient as the target coefficient; when the error value between the first coefficient and the initial coefficient does not meet the preset threshold value, continuing to perform parameter estimation on the first coefficient by utilizing the multiple groups of sample artery parameter information to obtain a second coefficient; and determining the second coefficient as the target coefficient until the error value between the second coefficient and the third coefficient meets a preset threshold value, wherein the third coefficient is the coefficient determined before the second coefficient.

In some embodiments of the present application, the determining unit 11 is specifically configured to establish a three-dimensional coronary artery model according to the target contrast image data; determining central line information of the coronary artery from the three-dimensional coronary artery model, wherein the central line information is data information of points forming a central line; and determining the target artery parameter information according to the central line information and the target contrast image data.

In some embodiments of the present application, the determining unit 11 is specifically configured to obtain initial target arterial parameter information by using the centerline information and the target contrast image data; and carrying out parameter adjustment on the initial target artery parameter information by taking a sample parameter range as an adjustment reference to determine the target artery parameter information, wherein the sample parameter range is a parameter adjustment range determined according to the plurality of groups of sample artery parameter information.

The embodiment of the application provides a storage medium, on which a computer program is stored, applied to a fractional flow reserve evaluation device, the computer program implementing the method according to any one of the preceding claims when being executed by a processor.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention.

Claims

1. A fractional flow reserve assessment method, the method comprising:

determining fractional flow reserve corresponding to the target arterial parameter information according to the first arterial parameter information;

wherein, before the matching the target arterial parameter information with the blood flow reserve evaluation model to obtain the first arterial parameter information corresponding to the target arterial parameter information, the method further comprises:

Substituting the target coefficient into the target function relation to obtain the blood flow reserve evaluation model;

wherein, the determining the target coefficient in the target function according to the multiple sets of sample artery parameter information includes:

2. The method of claim 1, wherein said determining target arterial parameter information for the target coronary artery from the target contrast image data comprises:

3. The method of claim 2, wherein said determining said target arterial parameter information from said centerline information and said target contrast image data comprises:

4. The method of claim 2, wherein the target arterial parameter information comprises at least: target tissue volume, lesion tip resistance, narrowest diameter, stenosis rate, lesion branch number, and lesion length.

5. A fractional flow reserve assessment device, the device comprising:

the matching unit is used for matching the target arterial parameter information with a blood flow reserve evaluation model to obtain the first arterial parameter information corresponding to the target arterial parameter information, wherein a plurality of groups of sample arterial parameter information corresponding to a plurality of sample coronary arteries are stored in the blood flow reserve evaluation model, and the plurality of groups of sample arterial parameter information comprise the first arterial parameter information;

the acquisition unit is also used for acquiring the multiple groups of sample arterial parameter information and multiple sample blood flow reserve scores corresponding to the multiple groups of sample arterial parameter information;

the determining unit is specifically configured to establish a plurality of first functional relationships between the plurality of sets of sample arterial parameter information and the plurality of sample fractional flow reserve; fusing the plurality of first functional relationships to obtain an objective functional relationship; determining a target coefficient in the target function according to the multiple groups of sample artery parameter information; substituting the target coefficient into the target function relation to obtain the blood flow reserve evaluation model;

The determining unit is specifically configured to perform parameter estimation on the initial coefficient by using the multiple sets of sample arterial parameter information to obtain a first coefficient; when the error value between the first coefficient and the initial coefficient meets a preset threshold value, determining the first coefficient as the target coefficient; when the error value between the first coefficient and the initial coefficient does not meet the preset threshold value, continuing to perform parameter estimation on the first coefficient by utilizing the multiple groups of sample artery parameter information to obtain a second coefficient; and determining the second coefficient as the target coefficient until the error value between the second coefficient and the third coefficient meets a preset threshold value, wherein the third coefficient is the coefficient determined before the second coefficient.

6. The apparatus of claim 5, wherein the device comprises a plurality of sensors,

the determining unit is specifically configured to establish a three-dimensional coronary artery model according to the target contrast image data; determining central line information of the coronary artery from the three-dimensional coronary artery model, wherein the central line information is data information of points forming a central line; and determining the target artery parameter information according to the central line information and the target contrast image data.

7. The apparatus of claim 6, wherein the device comprises a plurality of sensors,

the determining unit is specifically configured to obtain initial target artery parameter information by using the centerline information and the target contrast image data; and carrying out parameter adjustment on the initial target artery parameter information by taking a sample parameter range as an adjustment reference to determine the target artery parameter information, wherein the sample parameter range is a parameter adjustment range determined according to the plurality of groups of sample artery parameter information.

8. A storage medium having stored thereon a computer program for use in fractional flow reserve evaluation apparatus, which computer program, when executed by a processor, implements the method of any of claims 1 to 4.