Method for optimizing precision of electric pulse ablation model based on non-uniform reconstruction of active tissue electrical impedance information

Abstract

The application relates to a kind of precision optimization methods of electric pulse ablation model based on non-uniform reconstruction of active tissue electrical impedance information, organ tissue ablation model with population characteristics is first constructed according to patient case information characteristics;On this basis, ablation electrode is arranged in the ablation area of patient, impedance measurement data between needle arrangement electrode group is obtained through impedance measurement feedback module, and in-vivo tissue dielectric property parameter solving is carried out;Non-uniform reconstruction is carried out on tissue dielectric parameter between ablation electrodes in population characteristic model using the obtained in-vivo tissue dielectric property parameter, and individualized ablation optimization model with patient in-vivo tissue dielectric property is formed, while ablation electric pulse parameters output by high-voltage pulse source are corrected based on the optimization model.The method carries out non-uniform reconstruction on ablation zone tissue dielectric parameters in ablation model according to patient's own tissue dielectric property, has individualized characteristics, model precision is high, and it is beneficial to establish accurate preoperative surgical planning scheme.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, specifically to a method for optimizing the accuracy of an electrical pulse ablation model based on non-uniform reconstruction of active tissue impedance information. Background Technology

[0002] Irreversible electroporation ablation of tumors utilizes the mechanism by which high-voltage, ultrashort pulsed electric fields with pulse widths in the microsecond range and field strengths in the thousands of volts per centimeter can cause irreversible damage to cell membranes, thereby killing tumor cells. It is a novel physical tumor ablation technique that has emerged in recent years. This technique causes no thermal damage during treatment and results in significantly less damage to blood vessels, nerves, and the extracellular matrix compared to tumor cells. With further research, the clinical application of high-voltage pulsed ablation technology is continuously expanding, and it has been used for minimally invasive treatment of various tumors.

[0003] High-voltage pulsed ablation technology has broad clinical application prospects, but certain shortcomings still exist in its clinical application. Specifically, in the current clinical application of irreversible electroporation tumor ablation therapy, the treatment dosage (pulse parameters, duration, etc.) is usually judged by the physician based on experience, which easily leads to overtreatment (damaging normal tissue) or undertreatment (incomplete ablation). The main reason for this situation is that the preoperative planning scheme for individualized treatment in irreversible electroporation tumor ablation therapy is not yet perfect, i.e., the ablation model is not precise enough. The essence of pulsed ablation therapy is to apply a high-voltage pulsed electric field to the tumor area, causing irreversible damage to tumor cells through a high-voltage electric field of a certain strength. To achieve the ideal ablation effect, researchers at home and abroad mostly construct preoperative pulsed ablation models of patients to simulate the ablation process and effect, which plays a positive role in improving the precision of pulsed ablation therapy. One of the key elements in constructing a preoperative model for electro-pulse ablation is setting the dielectric parameters and their distribution characteristics of tissues. Existing models primarily derive their organ and tissue dielectric parameter data from literature reports (with some parameters derived from measurements of inactivated tissue dielectric properties), and often employ uniform distribution parameters for tumor tissue dielectric properties. However, the actual distribution of organ and tissue dielectric properties varies depending on the organ's classification. For example, different types of tumors within the same organ exhibit different dielectric properties, and different locations within the same tumor also show variations. Therefore, existing preoperative models for electro-pulse ablation cannot reflect the individualized characteristics of the non-uniform distribution of patient organ and tissue dielectric properties. Consequently, their simulation accuracy is insufficient, and the output of electrical pulse parameters is not precise enough in preoperative planning. Therefore, further optimization of the modeling methods for preoperative electro-pulse ablation models is needed to improve the accuracy of preoperative planning. Summary of the Invention

[0004] To address the technical problem of low simulation accuracy of organ and tissue ablation models in the preoperative planning of electro-pulse ablation, the present invention aims to provide a method for optimizing the accuracy of electro-pulse ablation models based on non-uniform reconstruction of active tissue impedance information. This method, based on the construction of an organ and tissue ablation model with population characteristics, optimizes the tissue impedance distribution between ablation electrodes in the model using in vivo tissue impedance measurement parameters of the patient, forming an individualized ablation model with non-uniform distribution of tissue impedance characteristics. This improves the accuracy of the ablation model. Furthermore, based on this optimized model, the ablation pulse parameters can be re-corrected, further enhancing the simulation accuracy of preoperative planning for electro-pulse ablation.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for optimizing the accuracy of an electropulse ablation model based on non-uniform reconstruction of active tissue impedance information is characterized by further non-uniform reconstruction of the dielectric properties of the ablation zone tissue after constructing a basic model with population characteristics, thereby obtaining an optimized model. The method specifically includes the following steps:

[0007] Step 1: First, extract the patient's case information features. Based on these features, construct a basic model for organ electro-pulse ablation with group characteristics, and obtain the initial values ​​of ablation pulse parameters and the electrode placement scheme for the ablation area.

[0008] Step 2: According to the electrode needle placement plan in the ablation zone, electrode needles are placed in the ablation zone. The impedance measurement feedback module is used to obtain the impedance measurement data between the electrode groups and to solve the dielectric properties parameters of the in vivo tissue.

[0009] Step three involves using the patient's in vivo tissue dielectric property parameters to non-uniformly reconstruct the dielectric property parameters of the basic organ electrical pulse ablation model established in step one, which exhibits population-based characteristics. This results in an individualized organ electrical pulse ablation model with non-uniform impedance distribution characteristics in the patient's in vivo tissue. The ablation pulse parameters are then optimized based on this model's pulse source.

[0010] According to the present invention, the method for extracting patient case information features in step one, and constructing a basic model of organ electro-pulse ablation with group characteristics based on these features, to obtain ablation pulse parameters and electrode placement scheme for the ablation area, is as follows:

[0011] (1) Feature extraction of patient case information

[0012] The key features of the patient's case information extracted include: imaging and histological information of the ablated organs and lesions / tumors;

[0013] (2) Three-dimensional reconstruction of ablation organ morphology model

[0014] Based on the patient's ablation organ imaging data, a three-dimensional model of the ablation organ is established using three-dimensional reconstruction technology. The model should include the main tissue areas of the organ.

[0015] The ablation organ's main tissue area includes at least a normal tissue area, a tumor tissue area, and a tumor margin tissue area;

[0016] (3) Assignment of dielectric property parameters of active biological tissues

[0017] Based on the histological classification and typing characteristics of the ablated organs and lesions in the patient's case, the data parameters of the active tissue dielectric properties database are called to assign values ​​to the morphological model of the ablated organ tissue, forming a basic model of organ electrical pulse ablation with population characteristics.

[0018] The aforementioned active tissue dielectric property database consists of tissue dielectric property parameters obtained using active tissue dielectric property measurement methods, and the database data is continuously enriched as the number of cases increases. The tissue dielectric property parameters are statistical calculation results after multi-sample measurement, reflecting the group characteristics of different age groups and different tissue classifications.

[0019] The dielectric properties parameters include those of the normal tissue region of the organ, the tissue dielectric properties of the tumor region, and the tissue dielectric properties of the tumor margin region.

[0020] (4) Solving for the distribution parameters of the ablation electrode

[0021] Based on the basic model of organ electropulse ablation, and according to the principle of setting up the electric field for electropulse ablation, combined with electromagnetic field simulation analysis methods, an organ electropulse ablation simulation was established. Based on the maximum cross-sectional area of ​​the tumor and the tumor tissue ablation threshold parameters, initial values ​​of ablation pulse parameters and electrode needle placement scheme parameters for the ablation zone were formed. At the same time, the boundaries of the effective ablation electric field area between the ablation electrodes were marked.

[0022] The needle placement parameters refer to the location information of the ablation electrode needle in the lesion area.

[0023] Specifically, the implementation method of step two, which involves placing electrodes in the ablation zone of the patient's organ according to the ablation zone electrode placement plan, obtaining impedance measurement data between the electrode pairs via the impedance measurement feedback module, and solving for the in vivo tissue dielectric property parameters, is as follows:

[0024] (1) In vivo measurement of tissue impedance between ablation electrode pairs

[0025] The impedance measurement feedback module uses a multi-frequency current excitation-voltage measurement mode to perform in vivo electrical impedance measurement on the tissue between the ablation electrode needles and obtain tissue electrical impedance parameters.

[0026] (2) Optimization solution of tissue dielectric property parameters between ablation electrode needle groups

[0027] Based on the in vivo electrical impedance parameters of the tissue between the ablation electrode needles, the effective ablation electric field region between the ablation electrode needle groups marked in Step 1 is taken as the optimization region for the tissue dielectric properties parameters. Combining finite element simulation and inverse problem optimization solution algorithm, the in vivo dielectric properties parameters of the tissue between the ablation electrode needle groups are obtained.

[0028] Furthermore, step three utilizes the patient's in vivo tissue dielectric property parameter data to non-uniformly reconstruct the dielectric property parameters of the organ electro-pulse ablation basic model with population characteristics established in step one, forming an individualized organ tissue electro-pulse ablation model with the patient's in vivo tissue impedance distribution characteristics. The implementation method is as follows:

[0029] (1) Non-uniform reconstruction of tissue dielectric properties parameters in the ablation region of the organ electropulse ablation basic model established in step one;

[0030] The aforementioned tissue dielectric property parameters are non-uniformly reconstructed, that is, the in vivo dielectric property parameters of the tissue between the electrode needle groups in the patient's ablation zone obtained in step two are replaced with the original model's corresponding regional tissue dielectric property parameters according to a set rule;

[0031] (2) Optimize the ablation pulse parameters based on the new model.

[0032] The technical innovation of the electropulse ablation model accuracy optimization method based on non-uniform reconstruction of active tissue impedance information in this invention compared with the prior art is that: the tissue dielectric property parameters in the model are obtained based on in vivo impedance measurement data of active tissue in the ablation area of ​​the patient's organ lesion; the dielectric parameters of the tissue in the ablation area of ​​the model are non-uniformly distributed, have individualized characteristics, and the model has high accuracy. It can realize the optimized output of ablation pulse parameters, which is conducive to establishing accurate preoperative surgical planning schemes. Attached Figure Description

[0033] Figure 1 This is a block diagram of the method for optimizing the accuracy of an electropulse ablation model based on non-uniform reconstruction of active tissue electrical impedance information according to the present invention;

[0034] Figure 2 This is a flowchart of the individualized organ ablation modeling process;

[0035] Figure 3 It involves three-dimensional modeling of organs and tissues and the division of tissue regions;

[0036] Figure 4 This is a distribution diagram of the ablation electrode needles;

[0037] Figure 5 This is a flowchart for solving the in vivo tissue dielectric parameters between ablation needle groups;

[0038] Figure 6This is a schematic diagram of the non-uniform reconstruction of tissue dielectric parameters between ablation needle groups in the model.

[0039] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Detailed Implementation

[0040] As mentioned earlier, existing pre-ablation models for electro-pulse ablation often use uniform distribution for setting the dielectric properties of tissue in the ablation zone, failing to reflect the individualized characteristics of the true non-uniform distribution of tissue dielectric properties. Therefore, their application in pre-ablation planning suffers from insufficient simulation accuracy and inaccurate ablation pulse parameter settings. To address this, this invention provides a method for optimizing the accuracy of electro-pulse ablation models based on non-uniform reconstruction of active tissue impedance information. The method's design involves first constructing a basic organ and tissue ablation model with population-based characteristics based on the patient's lesion features. Then, using in vivo tissue impedance measurement parameters, the impedance distribution parameters between ablation electrode pairs in the basic model are non-uniformly optimized and reconstructed, forming an individualized organ and tissue ablation model with in vivo tissue impedance distribution. Based on this optimized model, the ablation pulse parameters can be revised, improving the simulation accuracy of pre-ablation planning.

[0041] See Figure 1 This embodiment presents a method for optimizing the accuracy of an electropulse ablation model based on non-uniform reconstruction of active tissue electrical impedance information. The method is implemented in three steps, as shown in the flowchart below. Figure 2 As shown. Step one: First, extract the patient's case information features, and based on these features, construct a basic model of organ electro-pulse ablation with group characteristics, and obtain the initial values ​​of ablation pulse parameters and the electrode placement scheme for the ablation area.

[0042] In this embodiment, taking a prostate cancer patient as an example, the specific implementation method of step one is described, which is divided into the following implementation steps:

[0043] (1) Feature extraction of patient case information

[0044] The key features of the patient’s case information extracted include: imaging and histological information of the ablated organs and the lesion tumor; in this example, the patient has a prostate tumor, and the imaging data is the patient’s MRI image, and the tumor is a malignant tumor.

[0045] (2) Three-dimensional reconstruction of ablation organ morphology model

[0046] Based on the patient's ablation organ imaging data, a three-dimensional model of the ablation organ is established using three-dimensional reconstruction technology. The model should include the main tissue areas of the organ, which should at least include the normal tissue area, the tumor tissue area, and the tumor margin tissue area.

[0047] like Figure 3 As shown, in this embodiment, when performing morphological modeling of the prostate organ, the patient's prostate organ MRI sequence scan images are first processed. Then, the organ solid model is created using 3D reverse CAD software Geomagic and 3D CAD design software Solidworks. Based on the growth characteristics of the tumor mass, the organ is divided into regions, with the main tissue regions including normal tissue region, tumor marginal tissue region, and tumor tissue region.

[0048] (3) Based on the histological classification and typing characteristics of the ablated organs and lesions in the patient's case, the data parameters of the active tissue dielectric properties database are called to assign values ​​to the morphological model of the ablated organ tissue, forming a basic model of organ electropulse ablation with group characteristics.

[0049] In this embodiment, the prostate organ active tissue dielectric property database consists of tissue dielectric property parameters obtained using active tissue dielectric property measurement methods, and the database is continuously enriched as the number of cases increases. The tissue dielectric property parameters are statistical calculations based on multiple sample measurements, reflecting the group characteristics of different age groups and tissue classifications. In this embodiment, the patient is 62 years old and belongs to the T2 stage of prostate malignancy. The tissue dielectric property parameters include dielectric property parameters of the normal prostate tissue area, the tumor area, and the tumor margin area.

[0050] Some parameters are shown in Table 1 below:

[0051] Table 1: Dielectric properties of T2 stage prostate cancer tumor and surrounding tissue types

[0052]

[0053] For example Figure 3 The morphological model shown was subjected to finite element analysis and divided into normal tissue region, cancerous tissue region, and peritumoral tissue region. Dielectric parameters were assigned according to the parameters in Table 1 to form a basic model for organ electropulse ablation with group characteristics.

[0054] (4) Solving for the distribution parameters of the ablation electrode

[0055] Based on the fundamental model of organ electro-pulse ablation, and according to the principle of setting up the electric field for electro-pulse ablation, combined with electromagnetic field simulation analysis methods, an organ electro-pulse ablation simulation was established. Initial values ​​for the ablation pulse parameters and electrode placement parameters for the ablation zone were generated based on the maximum cross-sectional area of ​​the tumor and the tumor tissue ablation threshold parameters. Simultaneously, the boundaries of the effective ablation electric field regions between the ablation electrodes were marked. The electrode placement parameters refer to the positional information of the ablation electrodes within the lesion ablation zone.

[0056] To more clearly illustrate the needle placement and the effective ablation field area between electrode needle groups, a two-dimensional planar diagram is used for explanation, such as... Figure 4 As shown. In this embodiment, ablation electrodes 1, 2, 3, and 4 are used to ablate the lesion in the tumor area, forming an ablation electric field between the electrode groups. Based on the ablation threshold parameters of prostate tumor tissue, the boundaries of the ablation electric field region can be obtained between electrodes 1 and 2, between electrodes 2 and 3, and between electrodes 3 and 4 through electromagnetic field simulation calculations.

[0057] Step 2: According to the electrode needle placement plan in the ablation zone, electrode needles are placed in the ablation zone. The impedance measurement feedback module is used to obtain the impedance measurement data between the electrode groups and to solve for the dielectric properties of the in vivo tissue.

[0058] In this embodiment, after completing step one, the ablation electrode needles are placed on the patient's lesion ablation area according to the needle placement plan, and then the following steps are performed:

[0059] (1) Activate the impedance measurement feedback module to measure the tissue impedance between the ablation electrode pairs in vivo.

[0060] In this embodiment, the impedance measurement feedback module can be used as a module of the electropulse ablation device. It has the function of measuring the electrical impedance of biological tissue. This embodiment is based on the current excitation-voltage measurement mode and uses the "two-electrode method" to perform in vivo electrical impedance measurement on the tissue between the ablation electrode needles. The tissue impedance value between the ablation electrode needle groups obtained by measurement is defined as Z. s .

[0061] (2) Optimization solution of tissue dielectric property parameters between ablation electrode needle groups

[0062] In obtaining tissue in vivo electrical impedance data between ablation electrode needle groups Z s Subsequently, this embodiment presents a method for solving in vivo tissue dielectric parameters (including tissue conductivity σ and dielectric constant ε) based on inverse problem optimization. Specifically, the effective ablation electric field region between the ablation electrode needle groups marked in step one is used as the optimization region for tissue dielectric characteristic parameters. Figure 4 As shown, based on the principle of electromagnetic field analysis, combined with finite element simulation and inverse problem optimization algorithm, the in vivo dielectric properties parameters of tissue between ablation electrode needle groups (including tissue conductivity σ and dielectric constant ε) are obtained. The specific implementation process is as follows:

[0063] (i) Finite element model and calculation

[0064] By performing finite element analysis on the ablation region and based on the tissue electrical impedance measurement conditions (below 1 MHz), combined with Maxwell's equations, the following equations can be established:

[0065]

[0066] J(ω)=σE(ω)+jωD(ω)+J e (ω)

[0067]

[0068] nJ=0

[0069] In the equation, Q j This represents a current source, where σ is the conductivity, ω is the frequency, and J is the current source. e V represents the external current density, and V is the voltage.

[0070] The above equations can be solved using the finite element method. Furthermore, by utilizing the current-voltage relationship, the impedance Z between the ablation electrode needles in the finite element model can be obtained. M .

[0071] (ii) Optimization solution

[0072] The optimization equations are established as follows:

[0073] f(σ, ε) = ||Z s |-|Z M (σ,ε)||+K|Φ s -Φ M (σ,ε)|

[0074]

[0075] In the formula, f(σ, ε) is the objective optimization function for solving the electrical conductivity σ and dielectric constant ε of biological tissue, K is the weighting coefficient, and Z is the weighting coefficient. s This indicates the impedance value between the ablation electrode needle groups measured in vivo on the patient, |Z s | represents the corresponding impedance magnitude, Φs represents the corresponding impedance phase angle; Z M |Z represents the impedance value between ablation needle groups in the finite element model. M | represents the corresponding modulus, Φ M This represents the corresponding phase angle. σ L , σ U These represent the lower and upper bounds of the biological tissue conductivity σ in the optimization iteration solution, respectively; ε L , ε U These represent the lower and upper limits of the dielectric constant ε of biological tissue in the optimization iterative solution, respectively.

[0076] like Figure 5 The optimization process shown employs an optimization algorithm. In this embodiment, the optimization algorithm used is the TR trust region algorithm, and the weight coefficient in the optimization function is selected as 60. L , σ U ) and (ε L, ε U Parameter optimization is performed within the interval ) by iteratively refining the initial parameters (σ0, ε0). The optimal solution is obtained when f reaches its minimum value. Where (σ0, ε0) L , σ U ) and (ε L , ε U σ represents the possible range of dielectric properties of the tissue at the ablation site in the patient. To increase the solution speed and convergence of the algorithm optimization process, (σ) L , σ U ) and (ε L , ε U The settings can be configured based on empirical values, which can be derived from the collection of large-sample, multi-patient data.

[0077] This embodiment describes high-voltage electrical pulse ablation of prostate tumor tissue, where (σ L ,σ U ) and (ε L ,ε U The values ​​for ) can be found in the table below:

[0078]

[0079] Step 3: Using the patient's in vivo tissue dielectric property parameter data, the basic organ electrical pulse ablation model with population characteristics established in Step 1 is non-uniformly reconstructed to form an individualized organ electrical pulse ablation model with the non-uniform distribution characteristics of the patient's in vivo tissue impedance. The ablation pulse parameters are then further optimized.

[0080] In this embodiment, the method for step three, which utilizes the dielectric property parameter data of the patient's in vivo tissues to non-uniformly reconstruct the dielectric property parameters of the basic organ electrical pulse ablation model with population characteristics established in step one, and to form an individualized organ tissue electrical pulse ablation model with the impedance distribution characteristics of the patient's in vivo tissues, is as follows:

[0081] (1) Non-uniform reconstruction of tissue dielectric properties parameters of the organ electropulse ablation basic model established in step one.

[0082] The in vivo dielectric properties of the tissue between the electrode needle groups in the patient's ablation zone, obtained in step two, are then used to replace the dielectric properties of the corresponding tissue in the original model according to a set rule. For clarity, this embodiment uses... Figure 6 right Figure 4 The areas between ablation electrode needles 1 and 2, and between ablation electrode needles 2 and 3, will be further explained.

[0083] like Figure 6As shown, the dielectric properties of the tissue within the effective ablation electric field area between ablation electrode needles 1 and 2 and between electrode needles 2 and 3 marked in step one are reset and corrected. That is, the in vivo dielectric properties of the tissue between the electrode needle groups in the patient's ablation area obtained in step two are used to replace the dielectric properties of the original model, thereby forming an individualized ablation model of organ tissue with non-uniform distribution of tissue impedance.

[0084] Furthermore, the dielectric properties of the tumor tissue region are uniform in the population feature model constructed in step one. In step two, the in vivo tissue dielectric property values ​​P can be obtained between ablation electrode needles 1 and 2, and between ablation electrode needles 2 and 3, respectively. 12 =(σ 12 ,ε 12 ) and P 23 =(σ 23 ,ε 23 Because there is an overlap between the areas covered by electrode pins 1 and 2 and between electrode pins 2 and 3, three regions S1, S2, and S3 are formed. Their dielectric properties are set as follows: S1 is denoted as P. 12 S3 is set as P 12 S2 can be set as P 12 and P 23 The mean value was used to non-uniformly set the dielectric properties of the tumor tissue region according to the actual values ​​of the dielectric properties of in vivo tissue, thereby forming an individualized ablation model of organ tissue with non-uniform distribution of tissue impedance.

[0085] The method for resetting and correcting the dielectric properties of tissue within the effective ablation electric field area between ablation electrode needles 2 and 3 and between electrode needles 3 and 4 is the same as above, and will not be repeated here.

[0086] (2) Optimization of ablation pulse parameters based on the new model

[0087] Furthermore, based on the non-uniform individualized ablation model of dielectric properties established in step (1), combined with the electric pulse ablation electric field setting principle, and using the electromagnetic field simulation analysis solution method, the pulse source optimization pulse parameters are determined according to the ablation critical electric field strength threshold and the rule that the ablation zone covers the lesion area.

[0088] It should be noted that the embodiments given above are merely preferred examples for implementing the present invention, and are only intended to enable those skilled in the art to fully understand the present invention. The present invention is not limited to the above embodiments. Any non-essential additions or substitutions made by those skilled in the art based on the technical features of the present invention should fall within the protection scope defined by the present invention.

Claims

1. A method for precision optimization of an electrical pulse ablation model based on non-uniform reconstruction of active tissue electrical impedance information, impedance measurement data between needle electrode groups in an ablation zone having been acquired, wherein, The needle arrangement scheme of the needle electrode group is obtained according to an organ electric pulse ablation basic model with population characteristics constructed from case information characteristics of a patient; the case information characteristics of the patient include imaging and histological information of an ablation organ and a lesion tumor; and the method comprises the following steps: The implementation method of the organ electric pulse ablation basic model with population characteristics constructed from case information characteristics of a patient is as follows: (1) extraction of case information characteristics of a patient The extraction of case information characteristics of a patient includes imaging and histological information of an ablation organ and a lesion tumor; (2) three-dimensional reconstruction of an ablation organ morphological model Based on imaging data of an ablation organ of a patient, a three-dimensional model of the ablation organ is established by using three-dimensional reconstruction technology, and the model should include main tissue regions of the organ; The main tissue regions of the ablation organ at least include normal tissue regions, tumor tissue regions and tumor edge tissue regions; (3) assignment of dielectric property parameters of active biological tissues According to histological classification and typing characteristics of an ablation organ and a lesion tumor of a patient, dielectric property database data parameters of active tissues are called to assign values to the ablation organ tissue morphological model, so as to form an organ electric pulse ablation basic model with population characteristics; The dielectric property database of active tissues is composed of tissue dielectric property parameters obtained by using an active tissue dielectric property measurement method, and the database data are continuously enriched with an increase in the number of cases; the tissue dielectric property parameters are statistical calculation results after measurement of multiple samples, and reflect population characteristics of different age groups and different classification tissues; The dielectric property parameters include dielectric property parameters of normal tissue regions of an organ, dielectric property parameters of tumor region tissues and dielectric property parameters of tumor edge region tissues; (4) solution of ablation electrode distribution parameters Based on the organ electric pulse ablation basic model, according to the principle of electric pulse ablation electric field setting, combined with electromagnetic field simulation analysis method, an organ electric pulse ablation simulation is established, and according to the maximum cross-sectional area of a tumor and the ablation threshold parameters of tumor tissues, ablation electric pulse parameter initial values and ablation zone needle arrangement scheme parameters are formed; at the same time, the effective ablation electric field region between the ablation electrodes is marked; The needle arrangement scheme parameters refer to position information of the ablation electrodes in the lesion area; The method specifically comprises the following steps: Step one: in-vivo tissue dielectric property parameter solution according to impedance measurement data, including the following process: according to in-vivo tissue impedance parameter data between the ablation electrodes, the marked effective ablation electric field region between the ablation electrode groups is taken as an optimization area of tissue dielectric property parameters, combined with finite element simulation and inverse problem optimization solution algorithm, in-vivo tissue dielectric property parameters between the ablation electrode groups are obtained; Step two: using in-vivo tissue dielectric property parameter data of a patient, dielectric property parameter non-uniform reconstruction is performed on the organ electric pulse ablation basic model with population characteristics, so as to form an organ electric pulse ablation individualized model with in-vivo tissue impedance non-uniform distribution characteristics of a patient; based on the organ electric pulse ablation individualized model, pulse sources are used to optimize ablation electric pulse parameters.

2. The method of claim 1, wherein, The implementation method of the step two for reconstructing the dielectric characteristic parameters of the organ electric pulse ablation basic model with the population characteristics by using the dielectric characteristic parameter data of the patient in vivo tissue is: (1) The dielectric characteristic parameters of the ablation region of the organ electric pulse ablation basic model established in step one are non-uniformly reconstructed; The non-uniform reconstruction of the dielectric characteristic parameters is to replace the dielectric characteristic parameters of the corresponding region of the original model with the dielectric characteristic parameters of the patient in vivo tissue between the electrode needle groups in the ablation region obtained in step two according to the set rules; (2) The ablation electric pulse parameters are optimized based on the new model.

Images