CN110916640B - 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 PDF

Info

Publication number
CN110916640B
CN110916640B CN201911077893.9A CN201911077893A CN110916640B CN 110916640 B CN110916640 B CN 110916640B CN 201911077893 A CN201911077893 A CN 201911077893A CN 110916640 B CN110916640 B CN 110916640B
Authority
CN
China
Prior art keywords
coronary artery
virtual
sub
determining
dimensional structure
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201911077893.9A
Other languages
Chinese (zh)
Other versions
CN110916640A (en
Inventor
区初斌
钱逸
李洲健
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Weizhi Medical Technology Foshan Co ltd
Original Assignee
Weizhi Medical Technology Foshan Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Weizhi Medical Technology Foshan Co ltd filed Critical Weizhi Medical Technology Foshan Co ltd
Priority to CN201911077893.9A priority Critical patent/CN110916640B/en
Publication of CN110916640A publication Critical patent/CN110916640A/en
Application granted granted Critical
Publication of CN110916640B publication Critical patent/CN110916640B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026Measuring blood flow
    • A61B5/0261Measuring blood flow using optical means, e.g. infrared light
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/02007Evaluating blood vessel condition, e.g. elasticity, compliance
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/725Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Data Mining & Analysis (AREA)
  • Animal Behavior & Ethology (AREA)
  • Databases & Information Systems (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Physics & Mathematics (AREA)
  • Physiology (AREA)
  • Veterinary Medicine (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Cardiology (AREA)
  • Artificial Intelligence (AREA)
  • Hematology (AREA)
  • Signal Processing (AREA)
  • Psychiatry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Vascular Medicine (AREA)
  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

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

FFR-based coronary artery stenosis functional ischemia detection method and device
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 rate, which becomes one of the key points endangering human health, and the incidence age of coronary artery pathological changes tends to be younger along with the change of life styles of people such as diet, work and rest, so that the prevention and treatment of the coronary artery disease are reluctant. 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 to quantify and evaluate the function of coronary arteries, 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 Fractional Flow Reserve (FFR) obtained by measuring the virtual aortic root mean pressure and the pressure at the distal end of the coronary stenosis under the drug (e.g. vasodilator) induced hyperemia state by 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, the specificity of each blood vessel included in the coronary artery cannot be reflected, the accuracy of determining the Fractional Flow Reserve (FFR) is low, and the time consumption is long for calculating the Fractional Flow Reserve (FFR) of only one blood vessel for each time and the whole blood vessel tree, thereby reducing the accuracy and duration of the 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 three-dimensional structure of coronary artery matched with coronary artery, the three-dimensional structure of coronary artery comprises 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 three-dimensional structure of coronary artery, wherein the three-dimensional structure of coronary artery is a three-dimensional structure established in advance based on image data of coronary artery 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 embodiment of the 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 determining 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 the 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 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, 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 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 coronary artery stenosis based on FFR according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another FFR-based method for detecting coronary stenosis functional ischemia, 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 necessarily for describing a particular sequential or chronological 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 may 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 flow chart illustrating 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 described in fig. 1 may be applied to all medical devices capable of detecting the functionality of coronary artery stenosis, and the embodiments of the present invention are 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 coronary arteries 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, the first inlet pressure and the first outlet pressure of the sub-virtual coronary artery and the second flow, 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;
Q t =CM myo
wherein Q is t The total blood flow of the virtual coronary artery in a resting state; m is a group of myo Is 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: blood flow distribution of the left and right coronary arteries is 6; the entrance boundary conditions of the right coronary artery dominant type virtual coronary artery are as follows: blood flow distribution of the left and right coronary arteries is 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.
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 to obtain 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 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 enlargement t M times (e.g., 2< m < 5).
In the embodiment of the invention, the predetermined numerical algorithm is specifically to solve the continuity equation and the Navier-Stokes equation based on any one of a finite element volume method, a finite element method, a finite difference method and a lattice wave Zehnder method:
Figure BDA0002263044710000061
Figure BDA0002263044710000062
wherein, the flow velocity of U blood flow, rho is blood flow density, P is blood flow pressure, mu is blood flow viscosity,
Figure BDA0002263044710000063
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:
(P a -P d )=AQ 2 +BQ
wherein, P a Inlet pressure, P, of the subclinical coronary artery d The 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. In this way, by respectively extending a plurality of distances to the artery outlet of each sub-virtual coronary artery, the method is favorable for obtaining a more accurate coronary flow distribution ratio of each sub-virtual coronary artery in the left and right coronary arteries, thereby being favorable for improving the obtaining accuracy of the characteristic parameters of each sub-virtual coronary artery and further being 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 in a hyperemic state is n1 times of the blood flow of the sub-virtual coronary artery in a resting state (for example: 3-n 1-5).
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 a hyperemic 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 hyperemic state, wherein the pressure difference calculation formula is as follows:
Figure BDA0002263044710000081
/>
wherein Q is hyp For 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 is not repeated herein.
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 cuff measurement.
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:
Figure BDA0002263044710000091
Figure BDA0002263044710000092
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 the medical personnel can conveniently check and use the cardiac output, 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 of each sub-virtual coronary artery under the hyperemia state, and adds the blood flow of all sub-virtual coronary arteries under the hyperemia state to obtain the total blood flow of the virtual coronary arteries under the hyperemia state;
the medical device acquires a volume circulatory blood flow in a hyperemic state of a virtual aorta corresponding to the virtual coronary artery as a second volume circulatory blood flow based on the cardiac output of the patient and the total blood flow in the hyperemic state of the virtual coronary artery, which are acquired as described above.
As can be seen, 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 =P a *Q′ s /Q s
Q′ s =CO-Q′ t
Q s =CO-Q t
wherein FFR is 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' a Is the hyperemic mean pressure of the virtual aorta in the hyperemic state; p a Is the static mean pressure of the virtual aorta in the resting state; q s A body circulation blood flow (the first body circulation blood flow) of the virtual aorta in a resting state; q' s A volume circulatory blood flow of the virtual coronary artery in a hyperemic state (the second volume circulatory blood flow); q' t The 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 which is subjected to ischemic lesion and is in a hyperemic state, and executes the steps 103-105 again 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 which is ischemia-diseased and in a hyperemic state is n2 (for example: 2< -n 2< -4 >) times of the blood flow of the sub-virtual coronary artery in a resting state. It should be noted that the blood flow of each sub-virtual coronary artery in the case of ischemic lesion is smaller than the blood flow of the sub-virtual coronary artery in the case of non-ischemic lesion, i.e., n2< n1.
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 still further embodiments of the present invention, the analyzing, by the medical device, the stenosis functionality of the sub-virtual coronary artery based on the modified 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 the functional ischemia caused by the stenosis of the virtual coronary artery can be further improved, and the corresponding medical guidance can be given according to the detection result of the functional ischemia caused by the stenosis of the virtual coronary artery, so that the experience of the 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, 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 Fractional Flow Reserve (FFR) to enter clinical popularization and application. In addition, the flexibility and the 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 described in fig. 2 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. 2, the method for detecting functional ischemia of FFR-based coronary artery stenosis may include the following operations:
201. after obtaining a set of centerlines of the coronary artery, the medical device constructs a number of virtual vessel cross-sections for each centerline in the set of centerlines.
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 on each center line to obtain a plurality of virtual blood vessel cross sections of each center line, wherein each center line point is the section 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 1mm; 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 1mm.
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 the acquisition of the centerline of the coronary arteries while achieving the acquisition of the centerline of the coronary arteries by removing the left ventricular myocardium image from the coronary 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 multiple 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, 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 ventricle myocardial 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 segmentation processing is performed on the acquired coronary artery image data of the patient, whether interference image data exists in the coronary artery image data 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 the segmentation processing performed on the coronary artery image data can be improved, and the high-accuracy coronary artery three-dimensional structure can be further acquired.
In yet another optional 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 coronary artery stenosis functional ischemia based on FFR may further include the following steps:
and the medical equipment executes Gaussian filtering smoothing operation on the segmented coronary artery image data to obtain the segmented coronary artery image data subjected to Gaussian filtering.
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 device performs segmentation processing on the gaussian-filtered 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 fact that the center point of the section of the virtual blood vessel cross section is 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 performs primary segmentation on all the virtual blood vessel cross sections of each central line based on a threshold algorithm and/or a region growing algorithm to obtain segmented virtual blood vessel cross sections, and performs fine segmentation on the segmented virtual blood vessel cross sections based on a predetermined active contour algorithm (such as a level set Levelset algorithm) to obtain the finely segmented 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 the 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 by separately calculating and analyzing functional ischemia due to coronary artery stenosis according to the fractional flow reserve, so as to improve accuracy of determination of Fractional Flow Reserve (FFR) and reduce the determination time, so as to improve accuracy of detection of functional ischemia due to coronary artery stenosis and reduce the detection time, thereby promoting 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 coronary three-dimensional 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 functional ischemia due to FFR-based coronary artery stenosis 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 functional ischemia due to coronary artery stenosis described in fig. 3 can detect fractional flow reserve of coronary arteries of a patient in a non-invasive manner by separately calculating and analyzing functional ischemia due to 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, accuracy of detecting functional ischemia due to coronary artery stenosis can be improved and detection duration can be reduced, and thus, fractional Flow Reserve (FFR) is promoted to enter clinical popularization and application.
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 functional ischemia due to FFR-based coronary artery stenosis depicted in fig. 4 can also achieve 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 by obtaining the blood flow of the sub-virtual coronary artery under the hyperemic state and the characteristic parameters corresponding to the sub-virtual coronary artery.
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 blood flow reserve fraction is not more than the blood flow reserve fraction threshold, the blood 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 blood 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 constructing module 306 is further configured to construct a three-dimensional coronary 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 in which each centerline point is located is perpendicular to the tangent of 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 construction efficiency and accuracy of 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, for each of the plurality of virtual blood vessel cross-sections of each centerline after the construction module 306 acquires the centerline set of the coronary artery, constructs 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 the virtual blood vessel cross-section based on a predetermined segmentation algorithm, based on a center point of a tangent plane of the virtual blood vessel cross-section as 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, thereby improving the accuracy of constructing 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 three-dimensional structure of the coronary artery, perform meshing on the three-dimensional structure of the coronary artery based on a predetermined meshing algorithm to obtain a meshed three-dimensional structure of the coronary artery.
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 perform, 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, a 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
Embodiments of the present invention disclose a computer program product comprising a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps of the method for detecting FFR-based coronary stenosis functional ischemia described in embodiment one or embodiment two.
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 each embodiment may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. With this understanding in mind, the above technical solutions may essentially or in part contribute to the prior art, be embodied in the form of a software product, which may be stored in a computer-readable storage medium, including 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 electronically Erasable Programmable Read-Only Memory (EEPROM), an optical Disc-Read (CD-ROM) or other storage medium capable of storing data, a magnetic tape, or any other computer-readable medium capable of storing data.
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 solution depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (15)

1. A device for FFR-based detection of coronary artery stenosis functional ischemia, the device comprising:
a first determining module, configured to, after constructing a three-dimensional coronary artery structure matching with a coronary artery, the three-dimensional coronary artery structure including a virtual coronary artery matching with the coronary artery, determine, based on the three-dimensional coronary artery structure, a feature parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery, where the three-dimensional coronary artery structure is a three-dimensional structure established in advance based on coronary artery image data 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 the 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 for analyzing functional ischemia caused by stenosis of each of the sub-virtual coronary arteries based on the fractional flow reserve of the sub-virtual coronary artery;
the device further comprises:
a dividing module, configured to, before the first determining module determines, based on the coronary artery three-dimensional structure, a feature parameter corresponding to each sub-virtual coronary artery in the virtual coronary artery, perform mesh division on the coronary artery three-dimensional structure based on a predetermined mesh division algorithm to obtain a mesh-divided coronary artery three-dimensional structure, and extend, along an exit direction of the sub-virtual coronary artery, a predetermined distance value for each sub-virtual coronary artery in the mesh-divided coronary artery three-dimensional structure, to obtain a distance-extended coronary artery three-dimensional structure, where the predetermined distance value is n times of an exit diameter of the sub-virtual coronary artery;
the manner for determining 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 by the first determining module is specifically as follows:
determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery after the distance is prolonged;
the device further comprises:
the system comprises a construction module, a calculation module and a display module, wherein the construction module is used for constructing a plurality of virtual vessel cross sections of each central line in a central line set after the central line set of coronary arteries is obtained;
the second determining module is used for determining the hydraulic diameter of each virtual blood vessel cross section corresponding to each central line;
the construction module is further used for constructing the three-dimensional structure of the sub-coronary artery corresponding to each central line based on all the hydraulic diameters corresponding to the central lines;
the construction module is also used for constructing a coronary three-dimensional structure of the coronary artery based on the three-dimensional structures of all the sub-coronary arteries;
the device further comprises:
a segmentation module, configured to, after the centerline set of a coronary artery is obtained, construct a plurality of virtual vessel cross sections of each centerline in the centerline set, and before the hydraulic diameter of each virtual vessel cross section corresponding to each centerline is determined, perform a segmentation operation on each virtual vessel cross section of the plurality of virtual vessel cross sections of each centerline based on a predetermined segmentation algorithm, with a tangent plane center point of the virtual vessel cross section being a seed point, to obtain a segmented virtual vessel cross section;
wherein the second determining module determines the hydraulic diameter of each virtual vessel cross section corresponding to each centerline in a manner that:
and determining the hydraulic diameter of each segmented virtual blood vessel cross section corresponding to each central line.
2. The FFR-based detection apparatus of coronary artery stenosis functional ischemia according to claim 1, wherein the first determining module comprises:
a first determination submodule for determining an entry boundary condition of the virtual coronary artery and an exit boundary condition of the virtual coronary artery;
the solving submodule is used for solving 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 modification submodule is used for modifying the import boundary condition to obtain a modified import boundary condition;
the solving submodule is further configured to solve the numerical algorithm based on the changed inlet boundary condition and the changed outlet boundary condition to obtain a second flow rate, a second inlet pressure, and a second outlet pressure of each sub-virtual coronary artery in the virtual coronary artery;
the first determining submodule is used for 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 apparatus for detecting FFR-based coronary stenosis functional ischemia as claimed in claim 1, wherein the second determining module determines 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 corresponding characteristic parameter of each of the sub-virtual coronary arteries by:
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 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.
4. The FFR-based detection apparatus of coronary artery stenosis functional ischemia according to any of claims 1-3, wherein the third determination module comprises:
a second determining submodule, configured to determine a first systemic blood flow volume in a resting state and a second systemic blood flow volume in the hyperemic state of a virtual aorta corresponding to the virtual coronary artery;
an obtaining sub-module, configured to obtain a static average pressure of the virtual aorta in the resting state;
a calculation submodule 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.
5. The FFR-based detection apparatus of coronary artery stenosis functional ischemia according to any of claims 1-3, wherein the analysis module further comprises:
the judgment submodule is used for 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;
the third determining submodule is used for determining each sub-virtual coronary artery as a confident nonfunctional ischemic vessel when the judging submodule judges that the fractional flow reserve of each sub-virtual coronary artery is greater than or equal to the fractional flow reserve threshold;
the correction submodule is used for correcting the fractional flow reserve of each sub-virtual coronary artery when the judgment submodule judges that the fractional flow reserve of each sub-virtual coronary artery is not more than the fractional flow reserve threshold value;
an analysis sub-module for re-analyzing the functional ischemia caused by stenosis of the sub-virtual coronary artery based on the corrected fractional flow reserve.
6. 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 calls the executable program code stored in the memory and executes the following operations:
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 processor may further perform the following operations:
before determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery, performing grid division on the three-dimensional structure of the coronary artery based on a predetermined grid division algorithm to obtain a grid-divided three-dimensional structure of the coronary artery, and respectively extending each sub-virtual coronary artery in the grid-divided three-dimensional structure of the coronary artery by a predetermined distance value along the outlet direction of the sub-virtual coronary artery to obtain a distance-extended three-dimensional structure of the coronary artery, wherein the predetermined distance value is n times of the outlet diameter of the sub-virtual coronary artery;
wherein the determining 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 comprises:
determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery after the distance is prolonged;
the processor may further perform the following operations:
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 blood 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;
after said constructing a number of virtual vessel cross-sections for each centerline in said set of centerlines after acquiring a set of centerlines of coronary arteries and before said determining a hydraulic diameter for each said virtual vessel cross-section for each said centerline, said processor may further perform the following operations:
for each virtual blood vessel cross section in the plurality of virtual blood vessel cross sections of each central line, based on the fact that the center point of the section of the virtual blood vessel cross section is a seed point, performing segmentation operation on the virtual blood vessel cross section based on a predetermined segmentation algorithm 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.
7. The apparatus of claim 6, wherein the processor determines the characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery by:
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 each 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.
8. The apparatus of claim 6, wherein the processor determines 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 state based on the characteristic parameters corresponding to each of the sub-virtual coronary artery, and specifically:
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.
9. The apparatus of any of claims 6-8, wherein the processor determines a hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary artery in the hyperemic state by:
determining a first systemic blood flow volume of a virtual aorta corresponding to the virtual coronary artery in a resting state and a second systemic blood flow volume of the virtual aorta in the hyperemic 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.
10. The apparatus for detecting FFR-based coronary artery stenosis functional ischemia as claimed in any one of claims 6-8, wherein the processor analyzes the functional ischemia due to stenosis of each of the sub-virtual coronary arteries based on fractional flow reserve of the sub-virtual coronary artery by:
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 on the basis of the corrected fractional flow reserve.
11. A computer storage medium having stored thereon computer instructions that, when invoked, perform the following:
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 a hyperemic state based on the characteristic parameter corresponding to each sub-virtual coronary artery, and determining a hyperemic mean pressure of a 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 computer instructions, when invoked, are further operable to:
before determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery, performing meshing on the three-dimensional structure of the coronary artery based on a predetermined meshing algorithm to obtain a meshed three-dimensional structure of the coronary artery, and respectively prolonging each sub-virtual coronary artery in the meshed three-dimensional structure of the coronary artery along the outlet direction of the sub-virtual coronary artery by a predetermined distance value to obtain a distance-prolonged three-dimensional structure of the coronary artery, wherein the predetermined distance value is n times of the outlet diameter of the sub-virtual coronary artery;
wherein the determining 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 comprises:
determining characteristic parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery based on the three-dimensional structure of the coronary artery after the distance is prolonged;
the computer instructions, when invoked, are further operable to:
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;
after said constructing a plurality of virtual vessel cross-sections for each centerline in said set of centerlines after acquiring a set of centerlines of coronary arteries and before said determining a hydraulic diameter for each said virtual vessel cross-section for each said centerline, said computer instructions when invoked are further operable to:
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 the hydraulic diameter of each of said virtual vessel cross-sections for each of said centerlines comprises:
and determining the hydraulic diameter of each segmented virtual blood vessel cross section corresponding to each central line.
12. The computer storage medium of claim 11, wherein the computer instructions, when invoked, perform the determining the feature parameters corresponding to each sub-virtual coronary artery in the virtual coronary artery by:
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 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 each 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.
13. The computer storage medium of claim 11, wherein the computer instructions, when invoked, perform 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 corresponding characteristic parameter of each of the sub-virtual coronary arteries by:
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 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.
14. The computer storage medium of any one of claims 11-13, wherein the computer instructions, when invoked, perform the determining the hyperemic mean pressure of the virtual aorta corresponding to the virtual coronary arteries in the hyperemic state by:
determining a first systemic blood flow volume of a virtual aorta corresponding to the virtual coronary artery in a resting state and a second systemic blood flow volume of the virtual aorta in the hyperemic 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.
15. The computer storage medium according to any one of claims 11-13, wherein the computer instructions, when invoked, perform the analysis of functional ischemia due to stenosis of each of the sub-virtual coronary arteries based on their fractional flow reserve by:
judging whether the fractional flow reserve of each sub-virtual coronary artery is greater 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.
CN201911077893.9A 2019-11-06 2019-11-06 FFR-based coronary artery stenosis functional ischemia detection method and device Active CN110916640B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911077893.9A CN110916640B (en) 2019-11-06 2019-11-06 FFR-based coronary artery stenosis functional ischemia detection method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911077893.9A CN110916640B (en) 2019-11-06 2019-11-06 FFR-based coronary artery stenosis functional ischemia detection method and device

Publications (2)

Publication Number Publication Date
CN110916640A CN110916640A (en) 2020-03-27
CN110916640B true CN110916640B (en) 2023-04-14

Family

ID=69853484

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911077893.9A Active CN110916640B (en) 2019-11-06 2019-11-06 FFR-based coronary artery stenosis functional ischemia detection method and device

Country Status (1)

Country Link
CN (1) CN110916640B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112617771B (en) * 2020-12-28 2021-11-09 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
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

Citations (7)

* Cited by examiner, † Cited by third party
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

Patent Citations (7)

* Cited by examiner, † Cited by third party
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

Also Published As

Publication number Publication date
CN110916640A (en) 2020-03-27

Similar Documents

Publication Publication Date Title
US11576626B2 (en) Systems and methods for numerically evaluating vasculature
EP3723038B1 (en) Fast calculation method and system employing plaque stability index of medical image sequence
JP6667999B2 (en) Image processing apparatus, image processing method, and program
WO2019210553A1 (en) Microcirculation resistance index calculation method based on angiogram image and hydrodynamics model
WO2017047819A1 (en) Blood vessel shape analysis device, method for same, and computer software program for same
EP3323064A1 (en) Systems and methods for estimating hemodynamic forces acting on plaque and monitoring risk
CN110916640B (en) FFR-based coronary artery stenosis functional ischemia detection method and device
CN110223271B (en) Automatic level set segmentation method and device for blood vessel image
CN116236150A (en) Arteriovenous blood vessel image segmentation method based on fundus image
CN112184656A (en) Method and device for determining fetus section based on ultrasonic dynamic image
CN115049807A (en) Method and device for establishing pulmonary blood vessel model and server
CN112308845B (en) Left ventricle segmentation method and device and electronic equipment
CN112651984A (en) Blood vessel lumen intimal contour extraction method and device, ultrasonic equipment and storage medium
CN109363661B (en) Fractional flow reserve determination system, method, terminal, and storage medium
CN112233167A (en) Automatic measurement method and device for structural characteristics of fetus
US20230260133A1 (en) Methods for acquiring aorta based on deep learning and storage media
Hemmati et al. Segmentation of carotid arteries in computed tomography angiography images using fast marching and graph cut methods
KR102000615B1 (en) A method for automatically extracting a starting point of coronary arteries, and an apparatus thereof
CN110929604A (en) Screening method, device and system based on flow velocity of contrast image and storage medium
WO2017047135A1 (en) Blood flow analysis device, method, and computer software program
CN113744246B (en) Method and apparatus for predicting fractional flow reserve from a vessel tomographic image
CN116524548B (en) Vascular structure information extraction method, device and storage medium
EP4369290A1 (en) Determining estimates of hemodynamic properties based on an angiographic x-ray examination
CN116564525B (en) Fractional flow reserve prediction method and system based on coronary blood flow distribution
Bruyninckx et al. Segmentation of lung vessel trees by global optimization

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right

Effective date of registration: 20230323

Address after: 1301, Floor 13, Building 3, Block 2, Heyang Plaza, No. 13, Changjiang Road, Guicheng Street, Nanhai District, Foshan City, Guangdong Province, 528000

Applicant after: Weizhi medical technology (Foshan) Co.,Ltd.

Address before: 510000 room 3025, No. 95, Jinling North Road, Nansha street, Nansha District, Guangzhou City, Guangdong Province

Applicant before: GUANGZHOU XINMAI TECHNOLOGY Co.,Ltd.

TA01 Transfer of patent application right
GR01 Patent grant
GR01 Patent grant