CN117542507A - Method for noninvasively simulating patient-specific coronary artery iFR based on computed tomography - Google Patents
Method for noninvasively simulating patient-specific coronary artery iFR based on computed tomography Download PDFInfo
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- 210000004351 coronary vessel Anatomy 0.000 title claims abstract description 52
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000002591 computed tomography Methods 0.000 title claims abstract description 10
- 230000002107 myocardial effect Effects 0.000 claims abstract description 10
- 230000000004 hemodynamic effect Effects 0.000 claims abstract description 9
- 210000002302 brachial artery Anatomy 0.000 claims abstract description 6
- 238000004088 simulation Methods 0.000 claims abstract description 6
- 230000004872 arterial blood pressure Effects 0.000 claims abstract description 5
- 230000004089 microcirculation Effects 0.000 claims description 13
- 230000002792 vascular Effects 0.000 claims description 9
- 239000008280 blood Substances 0.000 claims description 7
- 210000004369 blood Anatomy 0.000 claims description 7
- 210000004204 blood vessel Anatomy 0.000 claims description 7
- 208000031481 Pathologic Constriction Diseases 0.000 claims description 3
- 238000005534 hematocrit Methods 0.000 claims description 3
- 230000036262 stenosis Effects 0.000 claims description 3
- 208000037804 stenosis Diseases 0.000 claims description 3
- OIRDTQYFTABQOQ-KQYNXXCUSA-N adenosine Chemical compound C1=NC=2C(N)=NC=NC=2N1[C@@H]1O[C@H](CO)[C@@H](O)[C@H]1O OIRDTQYFTABQOQ-KQYNXXCUSA-N 0.000 abstract description 10
- 239000002126 C01EB10 - Adenosine Substances 0.000 abstract description 5
- 229960005305 adenosine Drugs 0.000 abstract description 5
- 238000004364 calculation method Methods 0.000 abstract description 4
- 238000003745 diagnosis Methods 0.000 abstract description 3
- 210000004165 myocardium Anatomy 0.000 abstract description 2
- 238000005259 measurement Methods 0.000 description 3
- 201000000057 Coronary Stenosis Diseases 0.000 description 2
- 230000003205 diastolic effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 230000003902 lesion Effects 0.000 description 2
- 206010011089 Coronary artery stenosis Diseases 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 230000000544 hyperemic effect Effects 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 208000031225 myocardial ischemia Diseases 0.000 description 1
- 230000000284 resting effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/02—Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computerised tomographs
- A61B6/032—Transmission computed tomography [CT]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/50—Clinical applications
- A61B6/504—Clinical applications involving diagnosis of blood vessels, e.g. by angiography
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/50—ICT 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
Abstract
The technical scheme of the invention is to provide a method for noninvasively simulating patient-specific coronary arteries iFR based on computed tomography. The technical scheme disclosed by the invention is based on medical CTA images, and a patient-specific myocardial and coronary artery tree geometric model is segmented and reconstructed; establishing a patient-specific microvascular model based on cardiac muscle of a patient, calculating microvascular resistance as an outlet resistance boundary condition of a coronary artery tree, and setting a fitting pressure waveform of brachial artery pressure of the patient as an inlet pressure boundary condition of the coronary artery tree; the CT-iFR was calculated by performing hemodynamic simulation using CFD. The method disclosed by the invention has the advantages of high calculation speed, no wound, independence of adenosine, high accuracy, high repeatability and strong diagnosis efficiency.
Description
Technical Field
The invention relates to a method for measuring instantaneous non-waveform ratio (iFR).
Background
Invasive Fractional Flow Reserve (FFR) measurement under DSA can functionally assess coronary artery stenosis, a gold standard for diagnosing myocardial ischemia, but requires adenosine loading. The instantaneous waveform free ratio (iFR) under DSA is a physiological indicator of the hemodynamic severity of coronary stenosis detected in a resting state without hyperemic stimulus, and large scale randomized controlled studies demonstrate that the coronary intervention under iFR guidance is not inferior to the coronary intervention under FFR guidance and does not require an adenosine loading. But both are invasive measurement techniques and expensive, are not suitable for early and general diagnosis, and are limited in clinical popularization.
Disclosure of Invention
The purpose of the invention is that: the method replaces the invasive iFR measurement under the guidance of clinical DSA, avoids unnecessary invasive intervention operation, reduces the medical risk and economic burden of patients, and saves medical resources.
In order to achieve the above object, the technical solution of the present invention is to provide a method for noninvasively simulating a patient-specific coronary iFR based on computed tomography, which is characterized by comprising the following steps:
step 1, reconstructing a patient-specific myocardial and coronary artery tree geometric model based on a coronary artery CTA image of a patient, wherein each coronary artery parent vessel is bifurcated into two child vessels in a bifurcation process, and the diameter of the coronary artery parent vessel before bifurcation and the diameter of the child vessels after bifurcation satisfy the following relations:
(D 0 ) γ ＝(D 11 ) γ +(D 12 ) γ ＝2(D 11 ) γ
wherein D is 0 Is the diameter of the parent vessel of the coronary artery before bifurcation, D 1F And D 12 Is the diameter of the sub-vessel after bifurcation, and gamma is the growth index of bifurcation power law;
step 2, fitting the growth index gamma of the bifurcation power law and the patient-specific myocardial volume, establishing a microcirculation model, calculating the microcirculation resistance, and setting the calculated microcirculation resistance as the boundary condition of the coronary artery tree outlet resistance, wherein the growth volume of each capillary vessel is the same when the microcirculation model is established, and the volume V of a growth area distributed at the downstream of the ith coronary artery outlet i According to the corresponding cross-sectional equivalent diameter D i For allocation, there are:
wherein: v represents the volume of all coronary artery growing regions, i.e. the patient-specific myocardial volume; n represents the total number of coronary artery exits on the coronary arterial tree geometric model;
after the growth index gamma is determined, solving the resistance of each segment of blood vessel based on Poiseuille law to obtain microcirculation resistance;
step 3, setting the fitting pressure waveform of the brachial artery pressure of the patient as the inlet pressure boundary condition of the coronary artery tree;
step 4, simulating a coronary hemodynamic environment by using CFD;
step 5, calculating the pressure at 3cm downstream of the stenosis divided by the pressure at the coronary ostium, i.e. CT-iFR.
Preferably, in step 2, the growth index γ is determined using the following steps:
step 201, setting a growth index gamma as an initial value;
step 202, calculating the microvascular resistance value at each outlet of the coronary artery under the current growth index gamma;
step 203, performing numerical simulation to obtain hemodynamic parameters of a stenosed coronary artery;
step 204, determining the difference between CT-iFR downstream of the stenosed coronary and the actual measured iFR: if the difference is less than 1%, then step 206 is entered; if the difference is greater than 1%, go to step 205;
step 205, determining a new growth index gamma according to the Newton iteration method, and returning to step 202;
step 206, calculating the bifurcation dynamic method of a plurality of cases, and calculating the average value of all the obtained growth indexes gamma, namely the final growth index gamma.
Preferably, in step 2, the resistance of each segment of blood vessel is solved based on Poiseuille's law as follows:
wherein R is vascular resistance, L is vascular length, D is vascular diameter, and μ is blood viscosity.
Preferably, the blood viscosity is calculated using the formula:
wherein H is D Representing hematocrit.
Preferably, the growth area of the coronary artery before bifurcation corresponds to a sphere, a point A is taken on the sphere, the sphere is divided into two hemispheres by the plane of the point A, the center points of the two hemispheres are respectively B and C, at this time, the lengths of the line segment AB and the line segment AC are respectively the lengths of two bifurcated blood vessels, and the volumes of the two hemispheres correspond to the volumes of the two bifurcated blood vessel growth areas.
The technical scheme disclosed by the invention is based on medical CTA images, and a patient-specific myocardial and coronary artery tree geometric model is segmented and reconstructed; establishing a patient-specific microvascular model based on cardiac muscle of a patient, calculating microvascular resistance as an outlet resistance boundary condition of a coronary artery tree, and setting a fitting pressure waveform of brachial artery pressure of the patient as an inlet pressure boundary condition of the coronary artery tree; the CT-iFR was calculated by performing hemodynamic simulation using CFD. The method disclosed by the invention has the advantages of high calculation speed, no wound, independence of adenosine, high accuracy, high repeatability and strong diagnosis efficiency.
Detailed Description
The invention will be further illustrated with reference to specific examples. It is to be understood that these examples are illustrative of the present invention and are not intended to limit the scope of the present invention. Further, it is understood that various changes and modifications may be made by those skilled in the art after reading the teachings of the present invention, and such equivalents are intended to fall within the scope of the claims appended hereto.
The embodiment of the invention discloses a method for noninvasively simulating a patient-specific coronary artery iFR based on computed tomography, which specifically comprises the following steps of:
a) establishing a microvascular resistance model:
it is assumed that each parent coronary vessel is bifurcated into two child vessels during bifurcation, and the diameter of the vessel before bifurcation and the diameter of the vessel after bifurcation satisfy the following relationship:
(D 0 ) γ ＝(D 11 ) γ +(D 12 ) γ ＝2(D 11 ) γ
wherein D is 0 Is the diameter of the parent vessel before bifurcation, D 11 And D 12 Is the diameter of the sub-vessel after bifurcation, and gamma is the root of the bifurcation power lawLong index. The invention assumes that the growing area of the coronary artery before bifurcation is equivalent to a sphere, a point A is taken on the sphere, the sphere is divided into two hemispheres by the plane of the point A, and the center points of the two hemispheres are respectively B and C. At this time, the lengths of the line segment AB and the line segment AC are the lengths of the two bifurcated vessels, respectively. The volume of the two hemispheres is the volume of the two bifurcated vessel growth regions, corresponding to the volume of the bifurcated sphere.
The smallest capillary diameter after bifurcation was assumed to be 10 μm, and the growth volume of each capillary was the same. Thus, the volume V of the growth zone distributed downstream of the ith coronary outlet i According to the corresponding cross-sectional equivalent diameter D i To be assigned, the formula is as follows:
where V represents the volume of all coronary artery growing regions, which can be obtained from the CTA data, and n represents the total number of coronary artery exits on the geometric model. Thus, the growth index γ of the bifurcation power law is the only parameter that needs to be determined when modeling small vessels. When gamma is determined, the resistance of each segment of blood vessel can be solved according to Poiseuille's law, and the formula is as follows:
wherein R is vascular resistance, L is vascular length, D is vascular diameter, and μ is blood viscosity. Taking into account the change in blood viscosity in the microvasculature, the invention takes into account the Fain effect and the reversal of the Fain effect, the formula of which is as follows:
wherein H is D Representing hematocrit, 0.5 was taken in the present invention. The resistance value at the outlet of the coronary artery is obtained by the series-parallel rule of the circuit.
Two) determination of the growth exponent gamma of the bifurcation power law
Studies have shown a growth index gamma of the bifurcated power law of approximately 2.85. The growth index gamma iterative process for determining the bifurcation power law of the coronary artery is as follows:
step 1, supposing that the growth indexes gamma of the bifurcation power law of the coronary artery microvasculature are 2.8, 2.85 and 2.9 respectively;
step 2, calculating the microvascular resistance value at each outlet of the coronary artery under the current growth index gamma;
step 3, performing numerical simulation to obtain hemodynamic parameters of a narrow coronary artery;
step 4, determining the difference between CT-iFR and actual measurement iFR of the downstream of the narrow coronary artery: if the difference is less than 1%, step 6 is entered; if the difference is greater than 1%, step 5 is entered;
step 5, if 2.8, 2.85 and 2.9 are traversed, determining a new growth index gamma according to the Newton iteration method, and returning to the step 2;
step 6, calculating a bifurcation power method of 40 cases through the process, and calculating an average value of all the obtained growth indexes gamma, wherein the average value is the growth index gamma of bifurcation power law of coronary artery microvasculature under the intervention of adenosine established by the method;
third) establishment of numerical simulation model
Grid division is carried out on the coronary artery tree obtained by dividing based on CTA, 5 layers of triangular grids are adopted at the boundary of a fluid domain, tetrahedral grids are adopted inside the boundary, and grid independence test is carried out, namely when the maximum grid size is changed to be 0.9, the relative variation value of CT-iFR of each outlet is smaller than 1% through numerical calculation. Assuming that the blood is an incompressible Newtonian fluid of the mass1,050kg/m 3 The dynamic viscosity was 0.0035pa s. The measured brachial artery mean pressure fitting pressure waveform is set at the coronary inlet. Each coronary outlet is set as a pressure boundary condition related to resistance. When the maximum error of the numerical iteration is less than 10 -4 The calculation is considered to be convergent. The wave-free period (WFP) is set to begin 25% of the entry into the diastolic phase and end 5ms before the end of the diastolic phase. At WFP, the ratio of mean pressure (Pd) 3cm downstream of the lesion to the simulated mean aortic pressure (Pa) was considered to be lesion-specific CT-iFR.
Based on the above, the implementation manner of the embodiment of the invention includes the following steps:
step 1, reconstructing a patient-specific myocardial and coronary artery tree geometric model based on a coronary artery CTA image;
step 2, fitting a growth index gamma of a bifurcation power law and a patient-specific myocardial volume (namely, the volume V in the formula), establishing a microcirculation model, calculating microcirculation resistance, and setting the calculated microcirculation resistance as an outlet resistance boundary condition of a coronary artery tree;
step 3, setting the fitting pressure waveform of the brachial artery pressure of the patient as the inlet pressure boundary condition of the coronary artery tree;
step 4, simulating coronary hemodynamic environment by using CFD
Step 5, calculating the pressure at 3cm downstream of the stenosis divided by the pressure at the coronary ostium, i.e. CT-iFR.
Claims (5)
1. A method for noninvasively simulating patient-specific coronary iFR based on computed tomography, comprising the steps of:
step 1, reconstructing a patient-specific myocardial and coronary artery tree geometric model based on a coronary artery CTA image of a patient, wherein each coronary artery parent vessel is bifurcated into two child vessels in a bifurcation process, and the diameter of the coronary artery parent vessel before bifurcation and the diameter of the child vessels after bifurcation satisfy the following relations:
(D 0 ) γ ＝(D 11 ) γ +(D 12 ) γ ＝2(D 11 ) γ
wherein D is 0 Is the diameter of the parent vessel of the coronary artery before bifurcation, D 11 And D 12 Is the diameter of the sub-vessel after bifurcation, and gamma is the growth index of bifurcation power law;
step 2, fitting the growth index gamma of the bifurcation power law and the patient-specific myocardial volume, establishing a microcirculation model, calculating the microcirculation resistance, and setting the calculated microcirculation resistance as the boundary condition of the coronary artery tree outlet resistance, wherein the growth volume of each capillary vessel is the same when the microcirculation model is established, and the volume V of a growth area distributed at the downstream of the ith coronary artery outlet i According to the corresponding cross-sectional equivalent diameter D i For allocation, there are:
wherein: v represents the volume of all coronary artery growing regions, i.e. the patient-specific myocardial volume; n represents the total number of coronary artery exits on the coronary arterial tree geometric model;
after the growth index gamma is determined, solving the resistance of each segment of blood vessel based on Poiseuille law to obtain microcirculation resistance;
step 3, setting the fitting pressure waveform of the brachial artery pressure of the patient as the inlet pressure boundary condition of the coronary artery tree;
step 4, simulating a coronary hemodynamic environment by using CFD;
step 5, calculating the pressure at 3cm downstream of the stenosis divided by the pressure at the coronary ostium, i.e. CT-iFR.
2. A method for noninvasively simulating patient-specific coronary iFR based on computed tomography according to claim 1, wherein in step 2, the growth index γ is determined using the steps of:
step 201, setting a growth index gamma as an initial value;
step 202, calculating the microvascular resistance value at each outlet of the coronary artery under the current growth index gamma;
step 203, performing numerical simulation to obtain hemodynamic parameters of a stenosed coronary artery;
step 204, determining the difference between CT-iFR downstream of the stenosed coronary and the actual measured iFR: if the difference is less than 1%, then step 206 is entered; if the difference is greater than 1%, go to step 205;
step 205, determining a new growth index gamma according to the Newton iteration method, and returning to step 202;
step 206, calculating the bifurcation dynamic method of a plurality of cases, and calculating the average value of all the obtained growth indexes gamma, namely the final growth index gamma.
3. A method for noninvasively simulating patient-specific coronary iFR based on computed tomography according to claim 1, wherein in step 2, the resistance of each segment of blood vessel is solved based on Poiseuille's law as follows:
wherein R is vascular resistance, L is vascular length, D is vascular diameter, and μ is blood viscosity.
4. A method of non-invasively modeling patient-specific coronary iFR based on computed tomography according to claim 3, wherein the blood viscosity is calculated using the formula:
wherein H is D Representing hematocrit.
5. A method for noninvasively simulating patient-specific coronary iFR based on computed tomography according to claim 3, wherein the growth area of the pre-bifurcation coronary artery corresponds to a sphere, a point a is taken on the sphere, the sphere is divided into two hemispheres by the plane of the point a, the center points of the two hemispheres are B and C respectively, the lengths of the line segment AB and the line segment AC are the lengths of two bifurcated vessels respectively, and the volumes of the two hemispheres correspond to the volumes of the two bifurcated vessel growth areas.
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