阅读说明：本技术 脉冲电场肿瘤消融参数优化系统 (Pulsed electric field tumor ablation parameter optimization system ) 是由 姚陈果 董守龙 赵亚军 余亮 郑爽 于 2019-09-20 设计创作，主要内容包括：本发明公开脉冲电场肿瘤消融参数优化系统,主要包括图像处理模块、物理参数测量模块、脉冲电极参数设置模块、脉冲序列形成模块、若干脉冲电极和数据库；图像处理模型获取用户生物组织图像；图像处理模型对用户生物组织图像进行优化处理,得到生物组织三维结构。脉冲电极参数选择模型对接收到的物理参数进行处理,计算得到脉冲电压、脉冲数目、脉冲电极位置参数和脉冲电极插入用户生物组织的深度,并发送至脉冲序列形成模块；所述脉冲电极对用户生物组织进行脉冲刺激。本系统可以通过设置最优的电极布置和脉冲参数,实现肿瘤组织完全消融、正常组织伤害最小和热损伤最小。(The invention discloses a pulsed electric field tumor ablation parameter optimization system which mainly comprises an image processing module, a physical parameter measuring module, a pulsed electrode parameter setting module, a pulse sequence forming module, a plurality of pulsed electrodes and a database; the image processing model acquires a biological tissue image of a user; the image processing model carries out optimization processing on the biological tissue image of the user to obtain a three-dimensional structure of the biological tissue. The pulse electrode parameter selection model processes the received physical parameters, calculates the pulse voltage, the pulse number, the pulse electrode position parameters and the depth of the pulse electrode inserted into the biological tissue of the user, and sends the parameters to the pulse sequence forming module; the pulsed electrode pulses biological tissue of a user. The system can realize complete ablation of tumor tissues, minimum damage to normal tissues and minimum thermal damage by setting optimal electrode arrangement and pulse parameters.)

1. Pulsed electric field tumour ablation parameter optimization system which characterized in that: the device mainly comprises a database, an image processing module, a physical parameter measuring module, a pulse electrode parameter setting module, a pulse sequence forming module and a plurality of pulse electrodes.

The database stores data of the image processing module, the physical parameter measuring module, the pulse electrode parameter setting module and the pulse sequence forming module;

the image processing model acquires a biological tissue image; the image processing model processes the biological tissue image to obtain a three-dimensional structure of the biological tissue, and determines the volume V of the tumor tissue in the three-dimensional structure_TAnd a location;

the physical parameter measuring module measures physical parameters of the biopsy biological tissue and sends the physical parameters to the pulse electrode parameter setting module;

the pulse electrode parameter setting module stores the pulse electrode parameter selection model and the tissue ablation statistical model;

the pulse electrode parameter selection model processes the received physical parameters, calculates the optimized pulse voltage, the pulse number, the pulse electrode position parameters and the depth of the pulse electrode inserted into the biological tissue, and sends the parameters to the pulse sequence forming module;

the tissue ablation statistical model judges the tissue cell ablation degree;

the pulse sequence forming module determines the position of the pulse electrode according to the optimized pulse electrode position parameter;

the pulse sequence forming module drives the pulse electrode to be inserted into the biological tissue according to the optimized depth of the pulse electrode to be inserted into the biological tissue;

the pulse sequence forming module outputs pulse voltage to the pulse electrode according to the optimized pulse voltage;

the pulse sequence forming module determines the number of pulse output by the pulse electrode according to the optimized number of pulses;

the pulse electrode applies a pulse electric field to the biological tissue to realize tissue ablation.

2. The pulsed electric field tumor ablation parameter optimization system of claim 1, wherein: the physical parameters mainly comprise tumor tissue dielectric parameters, normal biological tissue dielectric parameters, electrical conductivity, thermal conductivity, specific heat capacity, density, activation energy barrier and metabolic heat.

3. The pulsed electric field tumor ablation parameter optimization system of claim 1, wherein: the biological tissue image is a CT image, an ultrasonic image or an MRI image.

4. The pulsed electric field tumor ablation parameter optimization system of claim 1, wherein: the biological tissues comprise tumor tissues and normal biological tissues; the normal biological tissue has a conduit system including tissue vessels.

5. The pulsed electric field tumor ablation parameter optimization system of claim 1, wherein: the pulse electrodes output pulse voltages in a cyclic single or multiple manner.

6. The pulsed electric field tumor ablation parameter optimization system of claim 1, wherein the main steps of establishing the pulsed electrode parameter selection model are as follows:

1) binary coding is carried out on the parameters to be optimized;

2) randomly generating an initial population of parameters to be optimized; the parameters to be optimized are pulse voltage, pulse number, pulse electrode position parameters or the depth of the pulse electrode inserted into the biological tissue; setting a maximum iteration number m;

3) a fitness function F is determined, namely:

in the formula, V_TirreIs the irreversible electroporation volume of the tumor tissue; v_TTumor tissue volume; v_HirreIs the irreversible electroporation volume of normal biological tissue; fitness F>0; k is an empirical value;

4) calculating the fitness value F and the fitness average F of any individual_meanDetermining the number a of times the individual is selected; the value of the selected number of times a is equal to the individual fitness value F and the fitness mean F_meanThe quotient of the division; individual fitness value F and fitness mean F_meanThe remainder of the division is noted as y;

5) sequentially arranging all remainders, and selecting individuals corresponding to the first j remainders;

6) and crossing the selected j individuals, and mainly comprising the following steps:

6.1) calculating the Cross probability value P for each individual_cNamely:

in the formula, F_maxThe maximum fitness value of the individuals in the population; f_mean1The maximum value of the fitness values of the two individuals to be crossed is obtained;

6.2) generating a random number g₁(ii) a If the cross probability value P_c>g₁Then cross, if the cross probability value P_c≤g₁If so, no crossing is performed;

7) performing mutation operation on the crossed j individuals, which mainly comprises the following steps:

7.1) calculating the variation probability value P of each individual_mNamely:

7.2) generating a random number g₂(ii) a If the probability value P is varied_m>g₂Then, mutation is performed, if the probability value P is mutated_m≤g₂If so, the change is not changed;

8) judging termination condition, namely inputting the individual into a tissue ablation statistical model, and judging cell survival rate S is 0 and biological tissue damage K_TDMinimum sum of V_Tirre/V_TAnd if the condition of 1 is met, outputting the individual value as the value of the parameter to be optimized, and if the condition of 1 is not met, returning to the step 3 and repeating iteration.

Technical Field

The invention relates to the field of pulsed electric field application, in particular to a pulsed electric field tumor ablation parameter optimization system.

Background

The global cancer survival trend monitoring plan report (year 2000-: the 5-year survival rate of most cancer patients in China is lower than the average level in the world, the life quality is poor, and the cancer treatment situation is still not optimistic. The latest research finds that: in the process of tumor growth, after multiple division and proliferation, daughter cells of the tumor have obvious differences in the aspects of tumor growth speed, invasion capacity, drug sensitivity, prognosis and the like, show high tumor heterogeneity on average of patients, tissues, cells and molecules, and reduce and kill the curative effects of a plurality of traditional therapies. Currently, personalized precise medicine is the development direction of modern medicine, however, tumor heterogeneity seriously hinders the clinical realization of precise tumor therapy.

The pulsed electric field tumor therapy has the advantages of nonheat, rapidness, selectivity and the like, and becomes a research hotspot in the field of tumor therapy in recent years. From the viewpoint of bioelectromagnetism, the dielectric properties of cells or tissues are fundamental physical characteristics of organisms, and play an important role in the field of biomedical research. A large number of researches show that dielectric properties of tumors of the same type of different patients, tumors of different parts of the same patient and even different development stages of the same tumor tissue are obviously different, and electrical response effects (corresponding treatment effects) under the action of different pulse parameters have obvious difference. The current method for treating tumor by pulse electric field is to couple pulse electric field to act on biological dielectric medium and induce the transmembrane potential of inner and outer membranes of cell to change sharply, break the balance between inside and outside of cell, thus achieving the purpose of killing tumor cells. How to combine tumor tissue form and dielectric parameter specificity, determine the optimal electrode parameters and pulse parameters for realizing complete ablation of tumor tissues and protecting normal tissues as much as possible through simulation, construct an effective preoperative tumor ablation system for realizing accurate ablation of tumors, and is a key problem to be solved at present in pulsed electric field tumor therapy.

Disclosure of Invention

The present invention is directed to solving the problems of the prior art.

The technical scheme adopted for achieving the purpose of the invention is that the pulsed electric field tumor ablation parameter optimization system mainly comprises an image processing module, a physical parameter measuring module, a pulsed electrode parameter setting module, a pulse sequence forming module, a plurality of pulsed electrodes and a database.

The database stores data of the image processing module, the physical parameter measuring module, the pulse electrode parameter setting module and the pulse sequence forming module.

The image processing model obtains a user biological tissue image. The image processing model carries out optimization processing on the biological tissue image of the user to obtain a three-dimensional structure of the biological tissue and determine the volume V of the tumor tissue in the three-dimensional structure_TAnd a location.

Further, the biological tissue image of the user is a medical image such as a CT image, an MRI image, and an ultrasound image.

Further, the biological tissue includes tumor tissue and normal biological tissue. The normal biological tissue has a conduit system including tissue vessels.

The physical parameter measuring module measures physical parameters of the biopsy biological tissue and sends the physical parameters to the pulse electrode parameter setting module.

Preferably, the physical parameters mainly include tumor tissue dielectric parameters, normal biological tissue dielectric parameters, electrical conductivity, thermal conductivity, specific heat capacity, density, activation energy barrier and metabolic heat.

The pulse electrode parameter setting module stores a pulse electrode parameter selection model and a tissue ablation statistical model.

Further, the main steps for establishing the pulse electrode parameter selection model are as follows:

1) and carrying out binary coding on the parameters to be optimized.

2) And randomly generating an initial population of the parameters to be optimized. The parameter to be optimized is pulse voltage, pulse number, pulse electrode position parameter or depth of the pulse electrode inserted into the biological tissue of the user. The maximum number of iterations m is set.

3) A fitness function F is determined, namely:

in the formula, V_TirreIs the irreversible electroporation volume of tumor tissue. V_TTumor tissue volume. V_HirreIs the irreversible electroporation volume of normal biological tissue. Fitness F>0. The k value is related to the importance degree of the target ablation tumor, and is larger near the important organs, blood vessels and other pipeline systems.

4) Calculating the fitness value F and the fitness average F of any individual_meanAnd determining the number a of times the individual is selected. The value of the selected number of times a is equal to the individual fitness value F and the fitness mean F_meanThe quotient of the divisions. Individual fitness value F and fitness mean F_meanThe remainder of the division is denoted y.

5) And sequentially arranging all remainders, and selecting individuals corresponding to the first j remainders.

6) And crossing the selected j individuals, and mainly comprising the following steps:

6.1) calculating the Cross probability value P for each individual_cNamely:

in the formula, F_maxThe maximum fitness value of the individual in the population. F_mean1Is the maximum of the two individual fitness values to be crossed.

6.2) generating a random number g₁. If the cross probability value P_c>g₁Then cross, if the cross probability value P_c≤g₁Then there is no crossover.

7) Performing mutation operation on the crossed j individuals, which mainly comprises the following steps:

7.1) calculating the variation probability value P of each individual_mNamely:

7.2) generating a random number g₂. If the probability of variationValue P_m>g₂Then, mutation is performed, if the probability value P is mutated_m≤g₂Then there is no variation.

8) Judging termination condition, namely inputting the individual into a tissue ablation statistical model, and if the cell survival rate S is 0, the biological tissue is damaged K_TDMinimum sum of V_Tirre/V_TAnd if not, returning to the step 3 and repeating the iteration.

And the tissue ablation statistical model judges the tissue cell ablation degree.

Further, the main steps for establishing the tissue ablation statistical model are as follows:

1) calculating the survival rate S of the tumor tissue cells, namely:

wherein S is cell survival rate. And E is a pulse voltage. E_c(n) is the electric field strength corresponding to 50% of the tumor tissue cells dead. A. the_c(n) is the corresponding pulse amplitude at which 50% of the tumor tissue cells die.

Wherein 50% of the tumor tissue cells die corresponding to the electric field intensity E_c(n) and pulse amplitude A corresponding to 50% of tumor tissue cell death_c(n) are respectively as follows:

in the formula, E₀Is the initial value of the pulse voltage. k1 is the electric field strength calculation coefficient. n is the number of pulses.

2) Calculating the tumor tissue ablation percentage K_EPNamely:

K_EP＝(1-S)·100。 (6)

3) determining the thermal damage of the biological tissue, namely:

wherein R is a general gas constant. Zeta is an index factor used to represent the effective collision frequency of the reacting molecules in the biological reaction. E_aReflecting the activation energy barrier that the molecule needs to overcome.

4) Determining biological tissue damage, namely:

K_TD＝100·(1-exp(-Ω(t)))。 (8)

in the formula, Ω (t) represents thermal damage to the biological tissue.

The pulse electrode parameter selection model processes the received physical parameters, calculates the pulse voltage, the pulse number, the pulse electrode position parameters and the depth of the pulse electrode inserted into the biological tissue of the user, and sends the parameters to the pulse sequence forming module.

And the pulse sequence forming module determines the position of the pulse electrode according to the optimized pulse electrode position parameter.

The pulse sequence forming module drives the pulse electrode to be inserted into the biological tissue of the user according to the optimized depth of the pulse electrode to be inserted into the biological tissue of the user.

And the pulse sequence forming module outputs pulse voltage to the pulse electrode according to the optimized pulse voltage.

Further, the plurality of pulse electrodes output pulse voltages in a cyclic single/multiple manner or a direct application manner.

And the pulse sequence forming module determines the number of output pulses of the pulse electrode according to the optimized number of pulses.

The pulsed electrode pulses biological tissue of a user.

The database stores an image processing module, a physical parameter measuring module, a pulse electrode parameter setting module and a pulse sequence forming module.

It is worth noting that whether tumor tissue can be effectively ablated is closely related to the electric field distribution within the tissue. When the electric field intensity of a certain area reaches or exceeds the ablation threshold field intensity, the tissue of the area can be effectively ablated. Researches show that under the action of a pulse electric field, the electrical parameters of biological tissues can be obviously changed, the tissue performance changes caused by different pulse amplitudes and pulse widths are different, and the changes present a nonlinear accumulation effect with the continuous application of pulses, so that the final electrical parameters of the tissues present a non-uniform distribution. Along with the dynamic change of the electrical parameters of the biological tissue, the electric field in the tissue can change correspondingly, so that the distribution of the electric field and the electrical parameters in the tissue presents a coupled change process, and finally, a dynamic balance is achieved. Therefore, the research on the electric field distribution in the tissue under the action of the pulse electric field can be closer to the actual condition only by considering the mutual coupling effect of the electric field distribution and the electrical characteristics of the tissue, and an important basis is laid for accurately determining the ablation region. Furthermore, the pulsed electrode arrangement is also a major factor affecting the electric field distribution within the tissue. Therefore, the final determination of the ablation range requires a comprehensive consideration of the tissue electrical parameter distribution, the treatment electrode arrangement, and the selection of pulse parameters.

The technical effect of the present invention is undoubted. The invention proposes a system with optimal electrode placement and pulse parameter configuration by mathematical optimization algorithm based on tumor location, size and electrical characteristic information. For tumors with specific forms and parameters and normal tissues around the tumors, the system can obtain optimal electrode arrangement and pulse parameter configuration, and can achieve the effects of complete tissue ablation, minimum damage to normal tissues and minimum thermal damage.

Therefore, the invention provides a new system which optimizes and controls the pulse parameters and the electrode parameters through a genetic algorithm according to the difference between the tumor cell morphology and the dielectric parameters of each patient, obtains the optimal treatment parameters meeting the clinical treatment requirements through simulation calculation, and enables the optimal treatment parameters to selectively and efficiently act on tumor tissues, thereby establishing a personalized treatment strategy and realizing accurate tumor ablation.

Drawings

FIG. 1 is a flow chart of a pulse electrode parameter selection model establishment;

FIG. 2 is a diagram of the outline of each part of the liver;

FIG. 3 is a three-dimensional model of the liver and its surroundings;

FIG. 4 is a tumor and electrode arrangement;

FIG. 5 is a tissue mesh generation;

FIG. 6 is a schematic diagram of a single application of a pulse;

FIG. 7 is a schematic diagram of multiple applications of pulses;

FIG. 8 shows the electric field distribution under the action of composite pulses;

FIG. 9 is a composite pulse irreversible electroporation tumor ablation scenario;

FIG. 10 is a graph showing temperature distribution under the effect of conventional pulsing and composite pulsing;

FIG. 11 illustrates the thermal injury of conventional pulse and composite pulse irreversible electroporation tumors;

FIG. 12 is an original CT slice;

FIG. 13 is a tumor and liver outline marker;

FIG. 14 is a tumor segmentation;

FIG. 15 is liver segmentation;

FIG. 16 is a polygon stage liver;

fig. 17 is a polygonal stage tumor image;

FIG. 18 is a graph of a slice of a liver;

FIG. 19 is a curved slice tumor map;

FIG. 20 is a three-dimensional liver map;

FIG. 21 is a three-dimensional tumor map;

FIG. 22 is a tumor model map;

FIG. 23 is a liver model diagram;

FIG. 24 is a diagram of tumor and liver models;

FIG. 25 is a model view of tumor and liver after placement of electrodes.

Detailed Description

The present invention is further illustrated by the following examples, but it should not be construed that the scope of the above-described subject matter is limited to the following examples. Various substitutions and alterations can be made without departing from the technical idea of the invention and the scope of the invention is covered by the present invention according to the common technical knowledge and the conventional means in the field.