CN114400098A - Linear model construction method and system based on hemodynamics analysis - Google Patents

Linear model construction method and system based on hemodynamics analysis Download PDF

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CN114400098A
CN114400098A CN202210150523.9A CN202210150523A CN114400098A CN 114400098 A CN114400098 A CN 114400098A CN 202210150523 A CN202210150523 A CN 202210150523A CN 114400098 A CN114400098 A CN 114400098A
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洪振鑫
刘欣
丁贺宇
赵鹏飞
龚树生
王振常
范劲松
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Foshan University
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Abstract

The invention discloses a linear model construction method and a system based on hemodynamic analysis, wherein the method comprises the following steps: constructing a three-dimensional geometric model according to the magnetic resonance imaging image data of the user; performing hemodynamic analysis and parameter extraction based on the three-dimensional geometric model; and determining a linear model according to the parameters based on a Monte Carlo simulation method. The system comprises: the device comprises a three-dimensional model building module, an analysis module and a linear model building module. By using the invention, quantitative assessment of the correlation of diseases and blood flow parameters can be realized. The invention is used as a linear model construction method and system based on the hemodynamic analysis, and can be widely applied to the field of medical data analysis.

Description

Linear model construction method and system based on hemodynamics analysis
Technical Field
The invention relates to the field of medical data analysis, in particular to a linear model construction method and system based on hemodynamic analysis.
Background
The main blood flow parameter analysis at present mainly comprises: the computational fluid dynamics blood flow analysis is based on Magnetic Resonance Imaging (MRI), Computed Tomography (CT), two-dimensional Digital Subtraction Angiography (DSA), catheter-guided pressure measurement based on a guide wire, and an image imaging technique, and various methods for observing blood flow analysis have advantages and disadvantages, so in practice, the image diagnosis method is still limited to the visual observation and personal experience of doctors, and quantitative evaluation is difficult to realize.
Disclosure of Invention
In order to solve the above technical problems, an object of the present invention is to provide a linear model construction method and system based on hemodynamic analysis, which can achieve quantitative assessment of correlation between diseases and blood flow parameters.
The first technical scheme adopted by the invention is as follows: a linear model construction method based on hemodynamic analysis comprises the following steps:
constructing a three-dimensional geometric model according to the magnetic resonance imaging image data of the user;
performing hemodynamic analysis and parameter extraction based on the three-dimensional geometric model;
and determining a linear model according to the parameters based on a Monte Carlo simulation method.
Further, before the step of constructing the three-dimensional geometric model from the magnetic resonance imaging image data of the user, the method further includes:
and acquiring basic information of the user and carrying out preliminary judgment to obtain the user after preliminary investigation.
Further, the step of constructing a three-dimensional geometric model from the magnetic resonance imaging image data of the user specifically includes:
performing nuclear magnetic resonance imaging analysis on the user subjected to the preliminary investigation to obtain magnetic resonance imaging image data;
and reconstructing a three-dimensional geometric model according to the magnetic resonance imaging image data and simplifying the region of interest to obtain the three-dimensional geometric model.
Further, the step of performing hemodynamic analysis and parameter extraction based on the three-dimensional geometric model specifically includes:
discretizing the three-dimensional geometric model by adopting an unstructured grid with tetrahedral units to obtain a corresponding grid and an entrance boundary;
simplifying the binary windows model into a linear function according to the corresponding grids and the set inlet boundary conditions and combining the blood flow condition;
parameters were recorded based on a linear function.
Further, the parameters include structural parameters of the model and blood flow parameters of the result of the hemodynamic analysis.
Further, the step of determining the linear model according to the parameters based on the monte carlo simulation method specifically includes:
determining a linear model according to the parameters and extracting probability distribution;
sampling parameters based on a Gibbs sampling method according to probability distribution and solving corresponding mean values to obtain parameter estimation values;
the parameter estimates are substituted into the linear model.
Further, still include:
and verifying the linear model.
The second technical scheme adopted by the invention is as follows: a linear model construction system based on hemodynamic analysis, comprising:
the three-dimensional model building module is used for building a three-dimensional geometric model according to the magnetic resonance imaging image data of the user;
the analysis module is used for performing hemodynamic analysis and extracting parameters based on the three-dimensional geometric model;
and the linear model building module is used for determining a Monte Carlo simulation method and determining a linear model according to the parameters.
The method and the system have the beneficial effects that: the invention establishes a method for constructing a three-dimensional geometric model and a parametric linear model, can further expand the application of a vascular simulation model for analyzing more structural abnormal expressions, and can realize quantitative evaluation of the correlation between diseases and blood flow parameters.
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FIG. 1 is a flow chart illustrating the steps of a method for constructing a linear model based on hemodynamic analysis according to the present invention;
fig. 2 is a block diagram of a linear model construction system based on hemodynamic analysis according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and the specific embodiments. The step numbers in the following embodiments are provided only for convenience of illustration, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.
As shown in fig. 1, the present invention provides a linear model construction method based on hemodynamic analysis, which includes the following steps:
and S0, acquiring the basic information of the user and carrying out preliminary judgment to obtain the user after preliminary investigation.
Specifically, the possibility of disease induction is artificially judged according to disease feedback of a patient, personal basic information of the patient is extracted, the past medical history and other conditions of the patient are recorded, and whether other causes of disease induction (tinnitus classification) or family history and the like exist is checked; and (4) carrying out nuclear magnetic resonance imaging technology diagnosis on the user which is preliminarily judged to be the user needing subsequent operation, and making basic investigation.
S1, constructing a three-dimensional geometric model according to the magnetic resonance imaging image data of the user;
s1.1, performing nuclear magnetic resonance imaging analysis on the user subjected to the preliminary investigation to obtain magnetic resonance imaging image data;
s1.2, reconstructing a three-dimensional geometric model according to the magnetic resonance imaging image data and simplifying the region of interest to obtain the three-dimensional geometric model.
Specifically, from the obtained image, three-dimensional model reconstruction is performed by anatomical knowledge, and the superior sagittal sinus, the confluent sinus, the left and right transverse sinuses, and the left and right sigmoid sinuses of the cerebral venous sinus are studied, simplified for the region of interest. And the accuracy of three-dimensional geometric reconstruction is improved by combining manual operation.
Knowing the blood flow direction, according to the medical blood flow analysis, the blood flow direction of the cerebral venous sinus is from the superior sagittal sinus to the confluent sinus, then from the confluent sinus to the left and right transverse sinuses, and then to the left and right sigmoid sinuses. Because of the problems of pathological changes, congenital problems and the like, the left transverse sinus and the right transverse sinus can not be connected with the confluent sinus at the same time, and the blood flow can only flow to the transverse sinus at one side and then to the sigmoid sinus in the case of some case analyses.
S2, performing hemodynamic analysis and parameter extraction based on the three-dimensional geometric model;
s2.1, discretizing the three-dimensional geometric model by adopting an unstructured grid with tetrahedral units to obtain a corresponding grid and an entrance boundary;
specifically, the three-dimensional geometric model is discretized by adopting an unstructured grid with tetrahedral units. The boundary layer is generated by two layers of hexahedral units and is used for solving the blood flow near the wall surface without a slip boundary along the blood vessel. Mesh refinement is performed on segments with curvature and narrowness to capture details of the flow pattern.
S2.2, simplifying the binary windows model into a linear function according to the corresponding grids and the set inlet boundary conditions and combining the blood flow condition;
specifically, an entrance boundary condition is set according to the obtained mesh, a pulsating waveform of the mass flow boundary condition changing with time is applied to the entrance according to the past blood flow condition, the binary window model is simplified into a linear function by taking the upper sagittal sinus as the entrance, the exit periodic blood pressure of the cerebral venous sinus under the exit boundary condition is obtained, and the initial pressure value is 2 mmHg. The windkessel model has proven effective in simulating blood flow for hemodynamic analysis, using two modes, laminar and turbulent (k-w), respectively. At the sigmoid sinus truncation as an exit boundary condition.
The binary windows model is a method for simulating cardiovascular systems and other systems into circuits under boundary conditions.
The accuracy of hemodynamics is ensured through 4D flow MRI, the maximum blood flow velocity is measured at the position of the cerebral venous sinus stenosis, and the maximum blood flow velocity is compared with simulation parameters through an instrument.
And S2.3, recording parameters based on a linear function.
The parameters are reported in the following table:
Figure BDA0003510207150000031
Figure BDA0003510207150000041
specifically, parameters are recorded mainly by structural parameters of the established model and blood flow parameters of the results of the hemodynamic analysis.
And S3, determining a linear model according to the parameters based on the Monte Carlo simulation method.
Specifically, parameters are extracted. Extracting main parameters according to computational fluid dynamics analysis in a laminar flow mode and the established structure of the cerebral venous sinus model,
Y＝a0+b1*x1+b2*x2+b3*x3+b4*x4+b5*x5+b6*x6+σ＝bX+a0+σ
wherein X is (X)1x2x3x4x5x6)，b＝(b1b2b3b4b5b6)
S3.1, determining a linear model according to the parameters and extracting probability distribution;
specifically, the probability distribution formula is expressed as follows:
P＝(σ,a0,b|X,Y)
s3.2, sampling parameters based on a Gibbs sampling method according to probability distribution and solving corresponding mean values to obtain parameter estimation values;
based on the probability distribution, gibbs sampling will be employed. Sequentially obtaining parameters sigma, a through the obtained X and Y values0,b。
From conditional probability distributions
Figure BDA0003510207150000042
Sampling the parameter b to obtain b(1)(ii) a From conditional probability distributions
Figure BDA0003510207150000043
For parameter a0Is sampled to obtain
Figure BDA0003510207150000044
From conditional probability distributions
Figure BDA0003510207150000045
For parameter a0Sampling to obtain sigma2(1)(ii) a And repeating the sampling of the parameters for T times, obtaining sample values after the parameters are balanced, and solving the mean value to obtain the estimated value of the parameters.
And S3.3, substituting the parameter estimation value into the linear model.
Specifically, the obtained parameters are substituted, and the calculation formula is as follows:
Y＝67.128+48.805*x1+1.134*x2-26.36*x3-28.459*x4+0.139*x5-1294*x6
in addition, according to the anatomical knowledge, it can be known whether the left and right transverse sinuses are communicated or not, which has a great influence on the overall blood flow parameters, and whether the left and right transverse sinuses are communicated or not is separated by separately considering the influence. Wherein, the left and right transverse sinus communicating group is group a, and the non-communicating group is group b. Substituting the parameters into the step b, the parameters of the group a and the group b can be respectively obtained, and the calculation formulas of the two groups are as follows:
group a:
Y＝900.488+9.29*x1-12.23*x2-697.869*x3+176.919*x4-3.776*x5-13.404*x6
group b:
Y＝-299.11-74.426*x1+41.678*x2+423.734*x3-4.812*x4-0.09*x5-1.954*x6
and S4, verifying the linear model.
Specifically, it was verified through experiments that the difference rate was 10% or less when the parameters were taken by performing the calculation in the turbulent flow mode.
As shown in fig. 2, a linear model building system based on hemodynamic analysis includes:
the three-dimensional model building module is used for building a three-dimensional geometric model according to the magnetic resonance imaging image data of the user;
the analysis module is used for performing hemodynamic analysis and extracting parameters based on the three-dimensional geometric model;
and the linear model building module is used for determining a Monte Carlo simulation method and determining a linear model according to the parameters.
Further as a preferred embodiment of the present system, the present system further comprises:
and the troubleshooting module is used for acquiring the basic information of the user and carrying out preliminary judgment to obtain the user after preliminary troubleshooting.
Further as a preferred embodiment of the present system, the present system further comprises:
and the verification module is used for verifying the linear model.
The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiment, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method embodiment.
A linear model building device based on hemodynamic analysis:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement a method for linear model construction based on hemodynamic analysis as described above.
The contents in the above method embodiments are all applicable to the present apparatus embodiment, the functions specifically implemented by the present apparatus embodiment are the same as those in the above method embodiments, and the advantageous effects achieved by the present apparatus embodiment are also the same as those achieved by the above method embodiments.
A storage medium having stored therein instructions executable by a processor, the storage medium comprising: the processor-executable instructions, when executed by the processor, are for implementing a hemodynamic analysis-based linear model construction method as described above.
The contents in the above method embodiments are all applicable to the present storage medium embodiment, the functions specifically implemented by the present storage medium embodiment are the same as those in the above method embodiments, and the advantageous effects achieved by the present storage medium embodiment are also the same as those achieved by the above method embodiments.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (8)

1. A linear model construction method based on hemodynamic analysis is characterized by comprising the following steps:
constructing a three-dimensional geometric model according to the magnetic resonance imaging image data of the user;
performing hemodynamic analysis and parameter extraction based on the three-dimensional geometric model;
and determining a linear model according to the parameters based on a Monte Carlo simulation method.
2. The method of claim 1, wherein the step of constructing the three-dimensional geometric model from the magnetic resonance imaging image data of the user further comprises:
and acquiring basic information of the user and carrying out preliminary judgment to obtain the user after preliminary investigation.
3. The method of claim 2, wherein the step of constructing the three-dimensional geometric model from the mri image data of the user comprises:
performing nuclear magnetic resonance imaging analysis on the user subjected to the preliminary investigation to obtain magnetic resonance imaging image data;
and reconstructing a three-dimensional geometric model according to the magnetic resonance imaging image data and simplifying the region of interest to obtain the three-dimensional geometric model.
4. The method according to claim 3, wherein the step of performing the hemodynamic analysis and extracting parameters based on the three-dimensional geometric model specifically comprises:
discretizing the three-dimensional geometric model by adopting an unstructured grid with tetrahedral units to obtain a corresponding grid and an entrance boundary;
simplifying the binary windows model into a linear function according to the corresponding grids and the set inlet boundary conditions and combining the blood flow condition;
parameters were recorded based on a linear function.
5. The method of claim 4, wherein the parameters include structural parameters of the model and blood flow parameters of the hemodynamic analysis result.
6. The method of claim 5, wherein the step of determining the linear model from the parameters based on the Monte Carlo simulation method comprises:
determining a linear model according to the parameters and extracting probability distribution;
sampling parameters based on a Gibbs sampling method according to probability distribution and solving corresponding mean values to obtain parameter estimation values;
the parameter estimates are substituted into the linear model.
7. The method for constructing a linear model based on hemodynamic analysis according to claim 6, further comprising:
and verifying the linear model.
8. A linear model construction system based on hemodynamic analysis, comprising:
the three-dimensional model building module is used for building a three-dimensional geometric model according to the magnetic resonance imaging image data of the user;
the analysis module is used for performing hemodynamic analysis and extracting parameters based on the three-dimensional geometric model;
and the linear model building module is used for determining a Monte Carlo simulation method and determining a linear model according to the parameters.
CN202210150523.9A 2022-02-18 2022-02-18 Linear model construction method and system based on hemodynamics analysis Pending CN114400098A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116919374A (en) * 2023-07-19 2023-10-24 西安交通大学 Intracranial aneurysm and method and system for evaluating blood flow dynamics parameters in aneurysm-carrying artery

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116919374A (en) * 2023-07-19 2023-10-24 西安交通大学 Intracranial aneurysm and method and system for evaluating blood flow dynamics parameters in aneurysm-carrying artery
CN116919374B (en) * 2023-07-19 2024-04-12 西安交通大学 Intracranial aneurysm and method and system for evaluating blood flow dynamics parameters in aneurysm-carrying artery

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