Microwave ablation thermal field visualization method and system based on noninvasive CT temperature measurement imaging and multi-physical field simulation

Abstract

The invention provides a microwave ablation thermal field visualization method and system based on noninvasive CT temperature measurement imaging and multi-physics field simulation. The method comprises the following steps that 1, CT image data in the microwave ablation process are obtained; 2, establishing a temperature mapping model based on the relationship between the HU value of the CT image and the temperature; 3, performing three-dimensional visualization on the temperature field; 4, constructing a multi-physical field simulation model based on a frequency domain Maxwell equation and a Pennes equation; 5, predicting a tissue damage range in combination with an Arrhenius model; and step 6, performing bidirectional verification on the CT temperature measurement result and the simulation result. According to the technical scheme, the accuracy and visualization effect of microwave ablation boundary judgment can be remarkably improved, and the method has important clinical application value.

Description

Technical Field

[0001] This invention relates to the fields of medical imaging and thermotherapy, and in particular to a method and system for visualizing microwave ablation thermal fields based on non-invasive CT thermometry imaging and multi-physics simulation. Background Technology

[0002] Microwave ablation (MWA) relies on precise thermal field control in the treatment of solid tumors. However, since the thermal field cannot be directly observed during the procedure, existing methods often depend on experience or simple simulations, which can easily lead to insufficient ablation area or damage to adjacent tissues.

[0003] Current technology lacks a solution that can combine medical imaging and physical modeling to achieve non-invasive, real-time, quantitative visualization and prediction of intraoperative thermal fields. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a microwave ablation thermal field visualization method and system based on non-invasive CT thermography and multi-physics simulation, which can significantly improve the accuracy of microwave ablation boundary determination and visualization effect, and has important clinical application value.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for visualizing the thermal field of microwave ablation based on non-invasive CT thermography and multiphysics simulation, comprising the following steps:

[0006] Step 1: Acquire CT image data during microwave ablation;

[0007] Step 2: Establish a temperature mapping model based on the relationship between HU value and temperature in CT images;

[0008] Step 3: Perform three-dimensional visualization of the temperature field;

[0009] Step 4: Construct a multiphysics simulation model based on the frequency domain Maxwell's equations and Pennes' equations;

[0010] Step 5: Predict the extent of tissue damage using the Arrhenius model;

[0011] Step 6: Verify the CT temperature measurement results with the simulation results.

[0012] In a preferred embodiment, step 1 specifically includes: acquiring CT image data of the target tissue during microwave ablation: using isolated pig liver at 4°C under refrigeration as the target tissue, heating the isolated pig liver to 37°C in a water bath before the experiment to meet the initial temperature requirements of the experiment; inserting the microwave ablation needle used in the surgery into the isolated pig liver, setting the surgical ablation power and surgical ablation time; after the isolated pig liver is ablated, placing it in a CT scanner for scanning, and simultaneously using the control group isolated pig liver, performing the same ablation scheme on it, cutting along the plane where the ablation needle is located after the ablation, and using a thermal imager to obtain the temperature value and thermal field distribution of the plane.

[0013] In a preferred embodiment, step 2 specifically includes: after obtaining the data through the experiment in step 1, delineating the ROI and creating a new DICOM file in the oblique section state of the CT image; then, resampling the CT image to obtain the distribution matrix information of the CT value of the section, which is used for data fitting; establishing a database with [T,HU] pairing information by registering the CT value matrix with the temperature field matrix of the thermal imager; and using linear fitting, nonlinear fitting, and deep learning algorithms for fitting, comparing the fitting function with its fitting parameters, and selecting the best mathematical model.

[0014] In a preferred embodiment, step 3 specifically includes: visualizing the temperature distribution results in 3D software and constructing an interactive 3D thermal field visualization system: establishing a mapping framework in a 3D slicer based on the mathematical model established in step 2, and drawing thermal field distribution maps of cross-sections, sagittal planes, and coronal planes; generalizing and evolving the thermal field in units of voxels to construct a 3D thermal field model, that is, users can simultaneously observe thermal field files and CT image information in a 3D slicer; and determining the thermal field evolution within the biological tissue at this moment.

[0015] In a preferred embodiment, step 4, constructing a multiphysics model based on the frequency domain Maxwell's equations and Pennes' biological heat transfer equations, specifically includes:

[0016] 1) Input conditions: The model input includes the structural parameters of the microwave ablation needle, surgical operation parameters, histological parameters, and boundary conditions;

[0017] 2) Model structure: In COMSOL software, the frequency domain Maxwell's equations are first solved to obtain the spatial distribution of the electromagnetic field in the tissue; the dissipated power density generated by the electromagnetic field is used as a heat source term and coupled to the Pennes biological heat transfer equation to calculate the distribution of tissue temperature over time; further, the Arrhenius damage integral model is used to transform the temperature-time integral result into the probability distribution of irreversible tissue damage.

[0018] The propagation of electromagnetic waves in liver tissue is considered using a transverse magnetic field and described by equation (1).

[0019] (1)

[0020] in, This represents the relative permittivity of liver tissue. Indicates the electrical conductivity of liver tissue. This represents the angular frequency of microwaves. Represents the vacuum permittivity. Represents relative permeability. This represents the free space wavenumber, and j represents the imaginary unit. Represents the angular component of the magnetic field strength;

[0021] The interaction between electromagnetic waves and liver tissue The definition is as follows: SAR represents specific absorptivity, specifically the electromagnetic radiation energy absorbed per unit mass of liver tissue. The density of liver tissue is represented by , and E represents the electric field intensity vector within the tissue. When the coaxial slot antenna emits electromagnetic waves, the electromagnetic waves pass through the liver tissue and then propagate throughout the region. The electromagnetic waves are absorbed in the liver tissue and converted into heat.

[0022] The SAR is converted into heat Q generated in the liver tissue. ext Defined as:

[0023] (2)

[0024] Heat transfer analysis within liver tissue was described using the Pennes biothermal equation, which is written as:

[0025] (3)

[0026] The denoted represents the specific heat capacity of liver tissue, T represents the temperature of liver tissue, t represents time, and k represents the thermal conductivity of liver tissue. Indicates the density of blood, This indicates the specific heat capacity of blood. Indicates blood perfusion rate, Indicates arterial blood temperature, This indicates the metabolic heat production of liver tissue. The term represents the external heat source generated by microwave energy precipitation; thermal damage is the thermal damage to tissues, which is represented by the damage model proposed by Henriques & Moritz, namely the Arrhenius damage equation; thermal damage in tissues is defined as the denaturation of proteins in the tissue, as shown in equation (4):

[0027] (4)

[0028] This indicates the degree of thermal damage to liver tissue, where A represents the frequency factor. R represents the activation energy, and R represents the universal gas constant.

[0029] The proportion of necrotic tissue Represented as:

[0030]

[0031] A mathematical model coupling electromagnetic wave propagation and heat transfer within biological tissues was developed. The equations were solved using the COMSOL multiphysics finite element method. The calculation scheme first calculates the external heat source by solving the electromagnetic wave propagation equation, and then solves the time-varying temperature at each point under the biological heat equation.

[0032] 3) Output results: The model output is a three-dimensional temperature field distribution matrix and the corresponding tissue damage probability field, which can automatically generate the predicted ablation range under a specified isothermal boundary or a specific damage threshold.

[0033] 4) Prediction and application: By inputting the patient's individualized parameters before surgery, the model simulates the diffusion trend of thermal and damage fields during surgery; after comparison with in vitro experiments and clinical validation, it serves as a reference for preoperative path planning and risk assessment.

[0034] In a preferred embodiment, step 5 specifically includes: performing a consistency model of surgical parameters and experimental objects in COMSOL software, and simulating the distribution of thermal field and tissue damage field before surgery.

[0035] In a preferred embodiment, step 6 specifically includes: comparing the accuracy of CT thermography and COMSOL simulation results again through in vitro pig liver experiments; further iterating the design of ablation parameters and the dynamic updating of tissue biological parameters in experimental and clinical practice; further reducing the prediction range error of COMSOL; and further reducing the temperature error of CT thermography.

[0036] This invention also provides a microwave ablation thermal field visualization system based on non-invasive CT temperature imaging and multiphysics simulation, including a processor, a memory, and a bus. The memory stores machine-readable instructions executed by the processor. When the system is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the microwave ablation thermal field visualization method based on non-invasive CT temperature imaging and multiphysics simulation is described.

[0037] Compared with existing technologies, this invention has the following advantages: It enables non-invasive temperature field reconstruction and prediction, and by combining multiphysics simulation methods, improves the visualization and accuracy of microwave ablation boundaries. This method can reduce errors caused by empirical judgment, improve the safety and effectiveness of tumor treatment, and has significant clinical application value. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the overall process of a preferred embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the fitting curve of the relationship between HU value and temperature in a preferred embodiment of the present invention; wherein, (a) is a linear regression prediction model, (b) is a cubic polynomial fitting prediction model, (c) is a support vector regression prediction model, and (d) is a random forest regression prediction model.

[0040] Figure 3 This is a schematic diagram of the three-dimensional thermal field visualization effect of a preferred embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram showing the comparison between simulation prediction and CT verification results of a preferred embodiment of the present invention. Detailed Implementation

[0042] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0043] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0044] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations according to this application; as used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise; furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0045] A visualization method for microwave ablation thermal field based on non-invasive CT thermography and multiphysics simulation, referenced Figure 1-4 This includes the following steps:

[0046] Step 1: Acquire CT image data during microwave ablation;

[0047] Step 2: Establish a temperature mapping model based on the relationship between HU value and temperature in CT images;

[0048] Step 3: Perform three-dimensional visualization of the temperature field;

[0049] Step 4: Construct a multiphysics simulation model based on the frequency domain Maxwell's equations and Pennes' equations;

[0050] Step 5: Predict the extent of tissue damage using the Arrhenius model;

[0051] Step 6: Verify the CT temperature measurement results with the simulation results.

[0052] Step 1 specifically includes: acquiring CT image data of the target tissue during microwave ablation; using isolated pig liver at 4°C (refrigerated temperature) as the target tissue, the isolated pig liver was heated to 37°C in a water bath before the experiment to meet the initial temperature requirements. The microwave ablation needle was inserted into a suitable location in the isolated pig liver, and an appropriate ablation power of 50W and a suitable ablation time of 5 minutes were selected. After ablation, the isolated pig liver was immediately placed in a CT scanner for scanning, with the time controlled within 2 minutes to avoid temperature loss or thermal field diffusion. Simultaneously, a control group of isolated pig liver was used, and the same ablation protocol was applied. After the ablation, the liver was cut along the plane of the ablation needle, and the temperature value and thermal field distribution of the plane were obtained using a thermal imager.

[0053] Step 2 specifically includes: establishing a temperature mapping model based on the linear or nonlinear relationship between the HU value and temperature of CT images. After obtaining the data through experiments in Step 1, the CT images are used to delineate ROIs and create new DICOM files in oblique section states to obtain CT images along the plane where the ablation needle is located. The CT images are then resampled to obtain the distribution matrix information of the CT values ​​at this section, which is used for data fitting. A database with [T, HU] pairing information is established by registering the CT value matrix with the temperature field matrix of the thermal imager. Linear fitting, nonlinear fitting, deep learning algorithms such as convolutional neural networks, and machine learning algorithms such as random forests are used to fit the two-dimensional array. The fitting function and its fitting parameters are compared to select the optimal mathematical model.

[0054] Step 3 specifically includes: visualizing the temperature distribution results in 3D software and constructing an interactive 3D thermal field visualization system; based on the mathematical model established in step 2, constructing a mapping framework in a 3D slicer, and drawing thermal field distribution maps of cross-sections, sagittal planes, and coronal planes. The thermal field is generalized and evolved using voxels as units to construct a 3D thermal field model, allowing users to simultaneously observe thermal field files and CT image information in the 3D slicer. This determines the current thermal field evolution within the biological tissue.

[0055] Step 4, which involves constructing a multiphysics model based on the frequency domain Maxwell's equations and Pennes' biological heat transfer equations, specifically includes:

[0056] (1) Input conditions: The input of the model includes the structural parameters of the microwave ablation needle (needle length, diameter, position of the radiating antenna), surgical operation parameters (input power, working frequency, action time), histological parameters (dielectric constant, electrical conductivity, density, specific heat capacity, thermal conductivity) and boundary conditions (initial temperature, heat dissipation environment).

[0057] (2) Model Structure: In COMSOL software, the frequency domain Maxwell's equations are first solved to obtain the spatial distribution of the electromagnetic field within the tissue. The dissipated power density generated by the electromagnetic field is used as a heat source term and coupled to the Pennes biological heat transfer equation to calculate the distribution of tissue temperature over time. Furthermore, the Arrhenius damage integral model is used to transform the temperature-time integral result into the probability distribution of irreversible tissue damage.

[0058] The propagation of electromagnetic waves in liver tissue is considered in terms of a transverse magnetic field and is described by the following formula:

[0059]

[0060] The interaction between electromagnetic waves and liver tissue can be used By definition, when a coaxial slot antenna emits electromagnetic waves, the electromagnetic waves pass through liver tissue and then propagate throughout the region. The electromagnetic waves are absorbed within the liver tissue and converted into heat.

[0061] The SAR is converted into heat generated in the liver tissue (Q). ext ), defined as:

[0062]

[0063] Heat transfer analysis within liver tissue can be described using the Pennes biothermal equation, which can be written as:

[0064]

[0065] Thermal injury refers to damage to tissues caused by heat, which is addressed using the damage model proposed by Henriques & Moritz, namely the Arrhenius damage equation. Thermal damage in tissues can be defined as the denaturation of proteins within the tissue, as shown below:

[0066]

[0067] The proportion of necrotic tissue can be expressed as:

[0068]

[0069] A mathematical model coupling electromagnetic wave propagation and heat transfer within biological tissues was developed. The COMSOL multiphysics finite element method was used to solve the equations. This computational scheme first calculates the external heat source by solving the electromagnetic wave propagation equation, and then solves for the time-varying temperature at each point under the biological heat equation.

[0070] (3) Output results: The model output is a three-dimensional temperature field distribution matrix and the corresponding tissue damage probability field, which can automatically generate the predicted ablation range under a specified isothermal boundary (such as 60 ℃) or a specific damage threshold.

[0071] (4) Prediction and application: By inputting the patient's individualized parameters before the operation (such as lesion size, location and tissue characteristics), the model can quickly simulate the diffusion trend of thermal field and damage field during the operation. After comparing in vitro experiments and clinical verification, the error between the predicted ablation boundary and the actual boundary is less than 1 cm, which can be used as a reference for preoperative path planning and risk assessment.

[0072] Step 5 specifically includes: constructing a multiphysics model based on the frequency domain Maxwell's equations and Pennes' biological heat transfer equations to simulate the electromagnetic wave propagation and heat diffusion process within the tissue, and predicting the tissue damage range using the Arrhenius model. Microwave ablation is an application evolution of the electromagnetic-biological heat conduction model, and its thermal field and tissue damage field diffusion trends are driven by Maxwell's equations and Pennes' biological heat transfer equations. Consistent modeling of surgical parameters and experimental objects is performed within the COMSOL software, simulating the distribution of the thermal field and tissue damage field preoperatively. Clinical verification shows that its prediction range error is <1cm, providing assistance for preoperative path planning. Step 6 specifically includes: bidirectional verification of CT temperature imaging results and simulation results to achieve higher accuracy thermal field reconstruction. The accuracy of CT temperature imaging and COMSOL simulation results is compared again through an in vitro pig liver experiment. Further iterations of ablation parameter design and dynamic updates of tissue biological parameters are conducted in experimental and clinical practice to further reduce the prediction range error of COMSOL and the temperature error of CT temperature imaging.

Claims

1. A method for microwave ablation heat field visualization based on non-invasive CT thermography and multi-physical field simulation, characterized in that, The method comprises the following steps: Step 1: obtaining CT image data in a microwave ablation process; Step 2: establishing a temperature mapping model based on the relationship between HU value and temperature of the CT image; Step 3: three-dimensional visualization of the temperature field; Step 4: constructing a multi-physical field simulation model based on the frequency domain Maxwell equation and the Pennes equation; Step 5: combining the Arrhenius model to predict the tissue damage range; Step 6: bidirectional verification of the CT temperature measurement result and the simulation result.

2. The microwave ablation heat field visualization method based on non-invasive CT thermography and multi-physical field simulation according to claim 1, characterized in that, The step 1 specifically comprises: obtaining CT image data of the target tissue in the microwave ablation process; using a refrigerated temperature of 4℃ of the ex vivo pig liver as the target tissue, using a water bath heating pot to heat the ex vivo pig liver at 37℃ before the experiment to meet the initial temperature requirement of the experiment; puncturing the microwave ablation needle used in the operation into the ex vivo pig liver, setting the operation ablation power and operation ablation time; after the ex vivo pig liver is ablated, it is placed in a CT machine for scanning, and a control group of ex vivo pig liver is subjected to the same ablation scheme, and after the end, it is cut along the plane where the ablation needle is located, and the temperature value thermal field distribution of the plane is obtained by using a thermal imager.

3. The microwave ablation heat field visualization method based on non-invasive CT thermography and multi-physical field simulation according to claim 1, characterized in that, The step 2 specifically comprises: after the experiment of step 1, the CT image is subjected to ROI delineation and DICOM new file creation in the state of oblique section; then the CT image is subjected to secondary sampling to obtain the distribution matrix information of the section CT value for data fitting; the matrix of the CT value and the thermal imager temperature field matrix are registered to establish a database with [T, HU] pairing information; and linear fitting, nonlinear fitting and deep learning algorithm are used for fitting, the fitting function and its fitting parameters are compared, and the best mathematical model is selected.

4. The microwave ablation heat field visualization method based on non-invasive CT thermography and multi-physical field simulation according to claim 1, characterized in that, The step 3 specifically comprises: visualizing the temperature distribution result in a three-dimensional software to construct an interactive three-dimensional thermal field visualization system: through the mathematical model of step 2, a mapping framework is constructed in 3D slicer, and the thermal field distribution graphs of the transverse section, the sagittal section and the coronal section are drawn; the thermal field is extended and evolved in units of voxels to construct a three-dimensional thermal field model, that is, the user can simultaneously observe the thermal field file and the CT image information in the 3D slicer; the thermal field evolution in the biological tissue at the moment is judged.

5. The microwave ablation heat field visualization method based on non-invasive CT thermography and multi-physical field simulation according to claim 1, characterized in that, The multi-physical field model based on the frequency domain Maxwell equation and the Pennes biological heat transfer equation in the step 4 specifically comprises: 1) input condition: the input of the model includes the structural parameters of the microwave ablation needle, the operation parameters, the histological parameters and the boundary conditions; 2) model structure: in the COMSOL software, the frequency domain Maxwell equation is first solved to obtain the spatial distribution of the electromagnetic field in the tissue; the dissipation power density generated by the electromagnetic field is taken as a heat source term and coupled to the Pennes biological heat transfer equation to calculate the distribution of the tissue temperature with time; further, the Arrhenius damage integral model is used to convert the temperature-time integral result into the irreversible damage probability distribution of the tissue; The propagation of electromagnetic waves in liver tissue is considered by transverse magnetic field, which is described by formula (1) （1） wherein, denotes the relative permittivity of the liver tissue, denotes the conductivity of the liver tissue, denotes the angular frequency of the microwaves, denotes the vacuum permittivity, denotes the relative permeability, denotes the free space wave number, j denotes the imaginary unit, denotes the angular component of the magnetic field strength; The interaction of electromagnetic waves with liver tissue is defined by where SAR represents the specific absorption rate, specifically the electromagnetic radiation energy absorbed per unit mass of liver tissue, where p represents the density of the liver tissue and E represents the electric field strength vector within the tissue; when the coaxial slot antenna emits electromagnetic waves, the electromagnetic waves pass through the liver tissue and then propagate throughout the region; the electromagnetic waves are absorbed in the liver tissue and converted into heat generation; SAR is converted into heat Q produced in the liver tissue ext defined as: （2） The heat transfer analysis in the liver tissue is described by the Pennes biological heat equation, which is written as: （3） represents the specific heat capacity of the liver tissue, T represents the temperature of the liver tissue, t represents time, k represents the thermal conductivity of the liver tissue, represents the density of the blood, represents the specific heat capacity of the blood, represents the blood perfusion rate, represents the arterial blood temperature, represents the metabolic heat production of the liver tissue, represents the external heat source term due to the microwave energy deposition; thermal damage is the thermal damage of the tissue, for which the damage model proposed by Henriques & Moritz, i.e. the Arrhenius damage equation, is adopted; the thermal damage in the tissue is defined as the denaturation of the protein in the tissue, as shown in equation (4): （4） represents the degree of thermal injury of the liver tissue, A represents a frequency factor, represents the activation energy, R represents the universal gas constant; the proportion of necrotic tissue is represented as: Mathematical model coupling electromagnetic wave propagation and heat transfer in biological tissue; solve the equation set by COMSOL multi-physics finite element method; the calculation scheme firstly calculates the external heat source by solving the electromagnetic wave propagation equation, and then solves the time-varying temperature of each point under the biological heat equation; 3) Output results: The model output is a three-dimensional temperature field distribution matrix and the corresponding tissue damage probability field, which can automatically generate the predicted ablation range under the specified isothermal boundary or specific damage threshold; 4) Prediction and application: By inputting the individualized parameters of the patient before the operation, the model simulates the diffusion trend of the heat field and the damage field during the operation; through comparison with ex vivo experiments and clinical verification, it is used as a reference for preoperative path planning and risk assessment.

6. The microwave ablation heat field visualization method based on non-invasive CT thermography and multi-physical field simulation according to claim 1, characterized in that, The step 5 specifically comprises: consistent modeling of surgical parameters and experimental objects in the comsol software, preoperative simulation of the distribution of the heat field and the tissue damage field.

7. The microwave ablation heat field visualization method based on non-invasive CT thermography and multi-physical field simulation according to claim 1, characterized in that, The step 6 specifically comprises: through the ex vivo pig liver experiment, the accuracy of the CT temperature imaging and the comsol simulation results are compared again, the design of the ablation parameters and the dynamic update of the tissue biological parameters are further iterated in the experiment and the clinical practice, the prediction range error of the comsol is further reduced, and the temperature error of the CT temperature imaging is further reduced. 8.A microwave ablation heat field visualization system based on non-invasive CT thermography and multi-physical field simulation, comprising a processor, a memory and a bus, the memory storing machine readable instructions executed by the processor; characterized in that, When the system is running, the processor and the memory communicate through the bus, and the machine readable instructions are executed by the processor to realize the microwave ablation heat field visualization method based on non-invasive CT temperature imaging and multi-physics simulation according to any one of claims 1 to 7.

Images