CN1166344C - Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment - Google Patents

Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment Download PDF

Info

Publication number
CN1166344C
CN1166344C CNB011295589A CN01129558A CN1166344C CN 1166344 C CN1166344 C CN 1166344C CN B011295589 A CNB011295589 A CN B011295589A CN 01129558 A CN01129558 A CN 01129558A CN 1166344 C CN1166344 C CN 1166344C
Authority
CN
China
Prior art keywords
temperature
capacitive
tumor
heating
optimized
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related
Application number
CNB011295589A
Other languages
Chinese (zh)
Other versions
CN1331954A (en
Inventor
万柏坤
程晓曼
朱欣
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tianjin University
Original Assignee
Tianjin University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tianjin University filed Critical Tianjin University
Priority to CNB011295589A priority Critical patent/CN1166344C/en
Publication of CN1331954A publication Critical patent/CN1331954A/en
Application granted granted Critical
Publication of CN1166344C publication Critical patent/CN1166344C/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Images

Landscapes

  • Electrotherapy Devices (AREA)

Abstract

The present invention discloses a method of utilizing a computer system to carry out deep heat field optimizing control for a capacitive RF thermo-therapeutic device. The present invention uses a tissue structure model based on the tomoscan of a human body to introduce an objective function and relevant weighting coefficients according to the requirements of presetting the heating temperature of a target region of a tumor tissue and avoiding the normal tissue overheating, the objective functions reach the minimum via iterative correcting and heating physical parameters of a genetic algorithm, and then heating physical parameters for achieving ideal thermal field distribution are obtained. The present invention has an important guiding significance for the establishment and the implement of a tumor thermo-therapeutic clinic scheme and the design of a capacitive RF thermo-therapeutic device.

Description

The deep heat field optimizing control method of capacitive RF thermotherapeutic equipment
Technical field
The present invention relates to a kind of radio-frequency (RF) thermotherapeutic method, relate in particular to a kind of capacitive RF thermotherapeutic method.
Background technology
Capacitive RF thermotherapeutic (capacitive radio-frequency hyperthermia) is hyperthermia treatment of carcinoma (Hyperthermic Oncology) technology commonly used in the clinical tumor.Wherein polarity plate capacitor type and tri-electrode capacitor type are two kinds, and described two-plate capacitor type abbreviates two electric capacity thermotherapies as, and the tri-electrode capacitor type abbreviates three electric capacity thermotherapies as.The Capacitance Coupled heating mainly is to produce heat effect by the ohmic loss of radio-frequency current in tissue, and its main thermal field scope increases with electrode area and progressively deepens.But radio-frequency current causes electric current density to increase with the treatment degree of depth and reduce, so the effect of deep heating weakens along with increasing with electrode distance and dispersing.During two electric capacity thermotherapies, thermal field distributes and mainly adjusts by electrode size, its effective hot-zone is many near small size electrode one side, for reaching the deep heating purposes, need to use the larger area electrode, have only when the pole plate diameter equals or exceeds polar plate spacing, most of radio-frequency current could flow through in the cylinder of being made up of pole plate, its corresponding deep tissue just can be heated, but because of heating surface (area) (HS increases and the degree of depth increases electric current density is reduced, is difficult to satisfy the requirement that heat in the deep.Concerning three electric capacity thermotherapies, distribute though can adjust thermal field by the phase place, amplitude and the power division mode that change three polar plate voltages, but still being concentrated on, radio-frequency current organizes the deep.For these reasons, capacitive RF thermotherapeutic is controlled cancer to the deep and often is difficult to prove effective.Therefore, how to adjust effectively and control that deep heat field distributes is the difficult point that can capacitive RF thermotherapeutic obtain good efficacy when being used for the deep hyperthermia treatment of carcinoma, still do not have solution preferably so far.
One of most important also promptly the most difficult problem is in the tumor thermotherapy: how to control human body internal heating temperature field and distribute, make it both to cover the tumor tissues target area of desire heating, reach 43~45 ℃ of effective treatment high-temperature regions, but do not damage the normal structure around it, guarantee that its temperature is lower than 40 ℃.For this reason, selecting to add thermophysical parameter, as irradiator power, electrode position size and voltage-phase etc. with formulate before the clinical thermotherapy scheme, should carry out temperature field forecast of distribution in the human body.But the temperature field Non-Destructive Testing is still a still unsolved difficult problem in biomedical hot physical study and the clinical practice in the organism.
At present, the insider thinks that adopting the computer numerical emulation mode to carry out the harmless reconstruct in organism temperature field is the approach that application prospect is arranged most.Usually, find the solution thermal field by known heating physical condition and distribute, be called direct problem; Otherwise, find the solution the required thermophysical parameter that adds by the distribution of re-set target thermal field and be called inverse problem.Because tissue has anisotropy, up to now, in tumor thermotherapy, mostly be the direct problem prediction, do not see that inverse problem finds the solution.
Summary of the invention
The objective of the invention is to, overcome the deficiencies in the prior art, a kind of deep heat field optimizing control method of capacitive RF thermotherapeutic equipment is provided, the ideal that can reach the distribution of expection hyperthermia treatment of carcinoma target thermal field with direct acquisition adds thermophysical parameter.This all has great importance and practical value to relevant heat treatment therapeutic device design and the formulation of thermotherapy clinical protocol.
For achieving the above object, the present invention adopts following steps to realize: (1) organizes the image information behind the image film digitized to be input in the computer tomography; (2) thus handle the finite element subdivision image information that above-mentioned image information obtains section simplified structure model with having the processing image information functional programs, and it is stored in the storage device; (3) will be scheduled to the data storage of target temperature profiles of target area heating in storage device; (4) thermophysical parameter that adds with capacitive RF thermotherapeutic equipment is stored in the storage device; (5), obtain the data that accounting temperature distributes according to above-mentioned finite element subdivision with add thermophysical parameter and carry out direct problem and find the solution; (6) find the solution the temperature objectives function that is optimized according to the data of aforementioned calculation Temperature Distribution and target temperature profiles, the algorithm of the temperature objectives function of described optimization is expressed in the following way:
J = ∫ Ω λF T [ T ( φ ) ] dΩ
φ is a border Potential distribution to be optimized in the formula, and Ω is for optimizing the finite element divided region of finding the solution, and λ is the optimization weight of corresponding different divided regions in the object function; F TBe the temperature objectives function, comprise the temperature objectives function F of tumor tissues T1Temperature objectives function F with normal structure T2Two parts:
The temperature objectives function F TIntegration discrete be following form:
∫ Ω F T [ T ( φ ) ] dΩ = λ 1 Σ i = 1 N 1 F T 1 [ Ti ( φ ) ] + λ 2 Σ j = 1 N 2 F T 2 [ Tj ( φ ) ]
N in the formula 1Be the tumor tissues node number of needs heating, N 2For avoiding superheated normal structure node number, T 1And T 2Be respectively the respective nodes temperature, λ 1And λ 2Be respectively the optimization weight of tumor tissues and normal structure; (7) numerical value of the temperature objectives function of the above-mentioned optimization of foundation carries out following selection: if this numerical value keeps off 0, then adopt genetic algorithm to be optimized and find the solution, correction adds thermophysical parameter, and returns step (4), carries out circular treatment; If this numerical value is near 0, then the thermophysical parameter that adds described in the above-mentioned steps (4) is added thermophysical parameter output as the optimum of the deep heat field of capacitive RF device.
Described genetic algorithm preferably adopts following substep: (a) select five individualities or four individualities again together with the optimized individual of previous generation at random, constitute population of new generation; (b) calculate individual adaptability, optimized individual is designated as individual 5 directly sends into the next generation, do not lose to guarantee hereditary information; (c) all the other individualities are bred according to the rules of contest, and optimized individual also participates in the competition, and avoid inbreeding; (d) individuality of selecting in the population carries out copulation with certain probability; (e) detect population and whether restrain,, make circular treatment if convergence goes to step (b); If do not restrain, then carry out next step; (f) do following selection according to the numerical value of iteration algebraically:, carry out circular treatment if this numerical value then returns step (a) less than the maximum algebraically that allows; If this numerical value is equal to or greater than the maximum algebraically of permission, then finish genetic algorithm.The temperature objectives function F TThe integration discrete form described in tumor tissues and the ratio λ of the optimization weight of normal structure 1/ λ 2Be advisable with 8~14.
The invention has the beneficial effects as follows: when the thermotherapy of human body deep, no matter be to use the capacitive based capacitive RF thermotherapeutic equipment of two-plate capacitor type and tri-electrode, adopt method of the present invention all can effectively, accurately, directly obtain to reach and expect that the ideal that hyperthermia treatment of carcinoma target thermal field distributes adds thermophysical parameter.Thereby improve the overheating effect of electrode rim, can make the deep tumor position reach expection thermotherapy target temperature, can avoid damaging deep tumor normal structure on every side again.
Description of drawings
Fig. 1 is the workflow diagram of the deep heat field optimizing control method of capacitive RF thermotherapeutic equipment of the present invention;
Fig. 2 is that the present invention extracts the flow chart that tomography is simplified the finite element subdivision of organize models and model;
Fig. 3 is that direct problem of the present invention is found the solution the flow chart that the temperature field distributes;
Fig. 4 is that the present invention utilizes genetic Optimization Algorithm to obtain to add the flow chart of thermophysical parameter;
Fig. 5 (a) and Fig. 5 (b) are respectively that the present invention heats the section simplified structure model of body and the finite element subdivision sketch map of model;
Fig. 6 is the curve chart of temperature objectives function of the present invention;
Fig. 7 (a), Fig. 7 (b) and Fig. 7 (c) be respectively tumor of the present invention when being positioned at the deep two electric capacity thermotherapies optimize that heating condition electromotive force (φ) down distributes, SAR distributes and the sketch map of temperature (T) distribution;
Fig. 8 (a), Fig. 8 (b) and Fig. 8 (c) be respectively the present invention when having deep and superficial part tumor simultaneously two electric capacity thermotherapies optimize that heating condition electromotive force (φ) down distributes, SAR distributes and the sketch map of temperature (T) distribution;
Fig. 9 (a), Fig. 9 (b) and Fig. 9 (c) be respectively tumor of the present invention when being positioned at the deep two electric capacity thermotherapies optimize that heating condition electromotive force (φ) down distributes, SAR distributes and the sketch map of temperature (T) distribution;
Figure 10 (a), Figure 10 (b) and Figure 10 (c) be respectively the present invention when having deep and superficial part tumor simultaneously three electric capacity thermotherapies optimize that heating condition electromotive force (φ) down distributes, SAR distributes and the sketch map of temperature (T) distribution.
The specific embodiment
Below in conjunction with the drawings and specific embodiments the present invention is described in further detail.
Fig. 1 to Fig. 6 illustrates workflow of the present invention, in Fig. 1, utilizes the medical image device, and described medical image device can be X-ray tomograph, i.e. X-CT; Or nuclear magnetic resonance, i.e. MRI; And other medical imaging device, the tomography that obtains the heating target area is organized film, through the digitized Film scanner fault image is imported computer then, in machine by craft or program simplification organization structural model, determine section and organ boundaries, and finish the finite element subdivision of section structure model, shown in Fig. 5 (a) and Fig. 5 (b); Can analyze from Fig. 5 (a) and contain two tumors in this heating body, wherein one 7 is positioned at shallow table, and another piece 8 is positioned at the deep; The triangular unit number that draws the finite element subdivision from Fig. 5 (b) is 1555, and the node number is 826, but heating electrode needs to determine in optimizing process with the pairing node location of cooling water bag, number and magnitude of voltage in the boundary point.
Find the solution in order to carry out direct problem, establish human body initial temperature and blood heat and be 37 ℃, initial electrode position, size and magnitude of voltage are all obtained at random; According to thermotherapy theory and clinical experience, the final goal temperature of definition expection heating is: 43~45 ℃ of tumor tissues temperature, 30~40 ℃ of normal structure temperature.
Add thermophysical parameter and mainly be made of each battery lead plate position shape and heating power on the capacitive RF thermotherapeutic equipment, the battery lead plate position shape of saying here refers to the size dimension and the position of battery lead plate, draws polar plate voltage according to heating power.Polar plate voltage and position shape have determined the distribution of human body external boundary current potential φ, { φ }={ φ 1, φ 2...., φ m.Here φ 1~φ mFor each node potential of border in the finite element subdivision, comprising the node potential of battery lead plate place.In addition, between human body skin and battery lead plate, fill up usually with the cooling water bag to avoid the overheated of electrode edge electric field.Because recirculated water cooling effect cooling water bag has stable chilling temperature.
For the capacitive RF thermotherapeutic occasion of heating, carry out direct problem according to the finite element subdivision of Fig. 5 (b) and the initial heating physical parameter determined at random and find the solution to obtain the data that accounting temperature distributes.Its direct problem is found the solution and is comprised two parts as shown in Figure 3: electromagnetic problems---find the solution the Laplace equation to obtain the Electric Field Distribution in the biological tissue; The temperature field problem---find the solution the Temperature Distribution of biological heat transmission equation to produce by the electric field heating in obtaining organizing.
Because the radio frequency value is about 10MHz, its wavelength is much larger than the human body depth dimensions, can adopt the quasi-static electric field to describe electric field in the human body.Electromotive force φ in, satisfy the Laplace equation:
(-εφ)=0 (1)
ε is the dielectric constant of biological tissue in the formula.Distribution by electromotive force φ can solve electric field intensity
Figure C0112955800081
Distribution:
E → = - ▿ φ - - - - - - - - ( 2 )
Electric field
Figure C0112955800083
In biological tissue, cause radio-frequency current, produce the Ohmic heating effect.For tri-electrode radio frequency electric capacity heat treatment therapeutic device, the electromotive force φ of its three pole plates also should satisfy vector and be zero phase equilibrium:
φ 123=0 (3)
The heat that thermotherapy is absorbed the unit organization quality clinically is that electric field energy is referred to as specific absorption rate (SpecificAbsorption Rate-SAR), is designated as Q s, provide by following formula:
Q s = 1 2 σ t | E | 2 - - - - - ( 4 )
Heating region inner tissue temperature (T) distributes by the biological heat transfer equation decision of following Pennes:
ρ t C t ∂ T ∂ t - ▿ ( K t ▿ T ) = Q t + Q s - Q b - - - - - ( 5 )
ρ in the formula t, Ct, Kt are respectively tissue density, specific heat and thermal conductivity.Q tBe physiology heat production item, Q sBe SAR heat production item, Q bBe blood perfusion heat radiation item.Q bCan describe by following formula:
Q b=(F b) tbC b)(T-T b) (6)
(F in the formula b) tBe blood flow (b) groundwater increment in the tissue (t), ρ b, C bBe density of blood and specific heat, T bBe the blood perfusion temperature.Supposition (F in the calculating b) tBe the constant that does not change with heating-up temperature, blood heat is decided to be 37 ℃.Q generally speaking tCompare Q sAnd Q bMuch smaller, can omit.
The electricity of table 1 biological tissue and thermal parameters
Tissue ε r σ(s/m) κ(W/m/℃) ρ(kg/m 3) c(J/kg/℃) F b(m 3/kg/s)
Blood 118.0 1.1 0.0 1.06e3 3.96e3 --
Skeleton 7.3 0.028 0.436 1.79e3 1.30e3 4.20e-7
Fat 20.0 0.047 0.22 0.90e3 2.30e3 5.00e-7
Feces 113.0 0.6 0.6 1.00e3 3.90e3 0.0
Bone marrow 200.0 0.65 0.515 1.10e3 3.96e3 7.50e-6
Muscle 113.0 0.61 0.6 1.02e3 3.50e3 8.30e-6
Tumor (edge) 60.0 0.8 0.57 1.04e3 3.90e3 1.67e-6
Tumor (deep) 60.0 0.8 0.57 1.04e3 3.90e3 5.00e-7
Direct problem is promptly found the solution above (1)~(5) formula.The present invention adopts two-dimensional finite element method (2D-FEM) to carry out numerical solution, is applicable to two electric capacity and two kinds of thermal therapy systems of three electric capacity.Required electricity, thermophysical parameter when table 1 is calculating.
In Fig. 4, distribute the optimization temperature objectives function J that is defined as follows according to target temperature profiles and accounting temperature:
J = ∫ Ω λF T [ T ( φ ) ] dΩ - - - - - - - - - ( 7 )
φ is a border Potential distribution to be optimized in the formula, and Ω is for optimizing the finite element divided region of finding the solution, and λ is the optimization weight of corresponding different divided regions in the object function.F TBe the temperature objectives function, contain the temperature objectives function F of tumor tissues T1Temperature objectives function F with normal structure T2Two parts.
Figure C0112955800093
Fig. 6 illustrates, when tumor temperature is in 43~45 ℃, and F T1=0; When normal structure temperature during at 30~40 ℃, F T2=0.If carry out numerical computations this moment, F in the formula (6) TIntegration can disperse and be following form:
∫ Ω F T [ T ( φ ) ] dΩ = λ 1 Σ i = 1 N 1 F T 1 [ Ti ( φ ) ] + λ 2 Σ j = 1 N 2 F T 2 [ Tj ( φ ) ] - - - - - - - - ( 10 )
N in the formula 1Be the tumor tissues node number of needs heating, N 2For avoiding superheated normal structure node number, T iAnd T 2Be respectively the respective nodes temperature, λ 1And λ 2Be respectively the optimization weight of tumor tissues and normal structure.
Fig. 4 illustrates the processing procedure of optimizing algorithm, under the heating condition of given target temperature profiles, optimize the position shape parameter of electrode drive voltage and pole plate, make that finding the solution the distribution of gained accounting temperature through direct problem approaches the preset target temperature distribution as far as possible, in other words, find the solution the value of the temperature objectives function that obtains near 0 through direct problem exactly.The present invention adopts genetic algorithm, and (Genetic algorithms-GA) is optimized and finds the solution, and genetic algorithm is that a class adopts genetic mechanism to carry out the numerical optimization technique of parameter search.Be widely used in finding the solution all kinds of optimization problems in the fields such as engineering, science, economics because of it has good robustness in recent years, become multiple target, non-smooth, the complicated strong instrument of optimizing a difficult problem of solving.Genetic algorithm is used three operators such as selection, copulation, variation usually, goes through number for obtaining satisfied optimization result.Optimize finding the solution of task and be to use genetic algorithm that the border Potential Distributing is carried out the iteration correction, when the pairing object function of the optimum in adjacent generation changes less than a certain threshold value or reach the highest algebraically that allows to evolve, stop.
The step of genetic algorithm is as follows:
(a) select five individualities or four individualities again together with the optimized individual of previous generation at random, constitute population of new generation;
(b) calculate individual adaptability, optimized individual is designated as individual 5 directly sends into the next generation, do not lose to guarantee hereditary information;
(c) all the other individualities are bred according to the rules of contest, and optimized individual also participates in the competition, and avoid inbreeding;
(d), the individuality selected in the population carries out copulation with certain probability, post-coitum can not make a variation;
(e), whether restraining selection according to the detection population carries out: if convergence then goes to step (b), carry out circular treatment; If do not restrain, then carry out next step;
(f), do following selection according to the numerical value of iteration algebraically:, carry out circular treatment if this numerical value then returns step (a) less than the maximum algebraically that allows; Otherwise finish genetic algorithm.
For two electric capacity thermal therapy systems, less relatively because of its optimization aim, the present invention uses little genetic algorithm; Then use common genetic algorithm for three electric capacity thermal therapy systems.
Fig. 7 (a), Fig. 7 (b) and Fig. 7 (c) have provided the optimization result calculated of two electric capacity thermotherapies when only containing tumor in the deep.Wherein Fig. 7 (a) is for when alternating voltage is got maximum, and the electromotive force of optimizing under the heating condition (φ) distributes, and Fig. 7 (b) distributes for SAR, and Fig. 7 (c) is that temperature (T) distributes.Total 900 seconds heat time heating times.The heating target area is that the final temperature of tumor tissues is 43.7 ± 0.9 ℃; In non-heating target area is that the normal structure temperature is 37.7 ± 3.1 ℃; Consumed power is 2300W.The position dimension of optimizing the heating condition bottom electrode is shown in the peripheral thick black line in border among the figure.The deep tumor position has reached expection thermotherapy target substantially as we can see from the figure.
Fig. 8 (a), Fig. 8 (b) and Fig. 8 (c) have provided the optimization result of calculation of three electric capacity thermotherapies when tumor is positioned at the deep, wherein Fig. 8 (a) is for when alternating voltage is got maximum, the electromotive force of optimizing under the heating condition (φ) distributes, and Fig. 8 (b) distributes for SAR, and Fig. 8 (c) is that temperature (T) distributes.Total 900 seconds heat time heating times.The heating target area is that the final temperature of tumor tissues is 43.0 ± 0.7 ℃; In non-heating target area is that the normal structure temperature is 38.6 ± 3.0 ℃; Consumed power is 2880W, and consumed power increased to some extent when this power ratio tumor was positioned at shallow table.Compare with two electric capacity thermotherapies, when making the deep tumor position reach expection thermotherapy target, also improved the overheating effect of electrode rim during three electric capacity thermotherapies, it is more outstanding promptly to optimize the result.This mainly be because during three electric capacity thermotherapies not only the position dimension of electrode more adjustment leeway is arranged, and the electromotive force of three pole plates can also adjust phase assignments, makes it to have stronger optimization ability.
The result of the example that the optimization of two electric capacity thermotherapies was calculated when Fig. 9 (a), Fig. 9 (b) and Fig. 9 (c) had provided deep and superficial part and have tumor simultaneously, wherein Fig. 9 (a) distributes for the electromotive force of optimizing under the heating condition (φ), Fig. 9 (b) distributes for SAR, and Fig. 9 (c) is that temperature (T) distributes.Total 900 seconds heat time heating times.Deep tumor target area final temperature is 43.2 ± 0.7 ℃; The final temperature of tumor target area, edge is 43.2 ± 1.6 ℃; The temperature that in non-heating target area is normal structure is 38.7 ± 3.1 ℃; Consumed power is 3150W, needs to increase when only having single tumor consumed power.As can be seen from the figure the tumor of deep and superficial part has all entered effective high-temperature region, but still has the superheating phenomenon of local normal structure.What is interesting is when optimizing the effect ratio this moment only has deep tumor better.Its reason may be because dark, when there is tumor in superficial part simultaneously, deep tumor can distribute by means of the boundary electric potentials that the superficial part tumor heating optimization aim driving effect that is positioned at the border obtains to optimize heating; And when only deep tumor being arranged, the border only exists avoids the superheated constraints of normal structure, so heating is optimized the driving effect and is difficult to prove effective to deep tumor.
The optimization result of calculation of three electric capacity thermotherapies when Figure 10 (a), Figure 10 (b) and Figure 10 (c) have provided deep and superficial part and have tumor simultaneously, wherein Figure 10 (a) distributes for the electromotive force of optimizing under the heating condition (φ), Figure 10 (b) distributes for SAR, and Figure 10 (c) is that temperature (T) distributes.Total 900 seconds heat time heating times.The deep tumor finishing temperature is 43.2 ± 0.7 ℃; The final temperature of tumor target area, edge is 43.2 ± 1.6 ℃; The temperature that in non-heating target area is normal structure is 38.7 ± 3.1 ℃; Consumed power is 3150W, needs equally to increase when only having single tumor consumed power.It is good to optimize effect when this moment is than the individualism deep tumor equally as can be seen from figure, and the optimization better effects if of ratio two electric capacity thermotherapies.
The operating process of the optimization result of calculation shown in Fig. 7, Fig. 8, Fig. 9 and Figure 10 series is: the tomography that uses the X-CT device to obtain the heating target area is earlier organized film, through the digital scanning instrument film image is imported computer again; Operator can determine to organize section and organ boundaries by craft and program by keyboard, finish the finite element subdivision of section structure; The initial heating physical parameter of heat treatment therapeutic device is set then at random, i.e. electrode position, size and magnitude of voltage, and the final goal temperature of definition expection heating; Through starting thermal field optimal control program, according to initial heating physical parameter and the final goal temperature set, system adopts two-dimensional finite element method (2D-FEM) to carry out the direct problem in numerical solution electromagnetic field and temperature field, the then temperature field of finding the solution according to finite element subdivision and direct problem, using little heredity or common genetic algorithm to carry out inverse problem optimization calculates, under given target temperature profiles, optimize the position shape parameter of electrode drive voltage and pole plate, finally make genetic Optimization Algorithm draw the temperature objectives function, so just reached and found the solution the gained accounting temperature through direct problem and distribute and approach preset target temperature as far as possible and distribute near 0 result.
When optimization is found the solution, optimize weight factor λ 1And λ 2Choose outbalance.In principle, tumor tissues is heated and avoids the overheated of normal structure is a pair of contradiction, and being reflected to optimization is multi-objective optimization question when finding the solution.If λ 1 and λ 2 get close value, then optimizing process is very slow, almost is difficult to obtain result preferably.So λ 1And λ 2Which is more important need decide on optimization aim.Occasion of the present invention is optimized weights and is compared λ 1/ λ 2It is better to optimize the result when getting 8 to 14 value ranges.
Above example is a typical application technology effect of the present invention.Though the present invention's supposition blood perfusion rate does not vary with temperature, if the blood perfusion rate changes with temperature, optimization thought of the present invention and main algorithm stand good.Applying of the reconstruct in temperature field and optimal control technology will design and new way is opened up in the clinical protocol formulation for heat treatment therapeutic device in this organism that the present invention proposes.

Claims (3)

1. the control method that the deep heat field that utilizes computer system to carry out capacitive RF thermotherapeutic equipment is optimized comprises the following steps:
(1) tomography is organized the image information behind the image film digitized be input in the computer;
(2) thus handle the finite element that above-mentioned image information obtains section simplified structure model and cut partial image information with having the processing image information functional programs, and it is stored in the storage device;
(3) will be scheduled to the target temperature profiles data storage of target area heating in storage device;
(4) thermophysical parameter that adds with capacitive RF thermotherapeutic equipment is stored in the storage device;
(5), obtain the data that accounting temperature distributes according to above-mentioned finite element subdivision with add thermophysical parameter and carry out direct problem and find the solution;
It is characterized in that it is further comprising the steps of:
(6) find the solution the temperature objectives function that is optimized according to the above-mentioned accounting temperature distribution and the data of target temperature profiles, the temperature objectives function algorithm of described optimization is expressed in the following way:
J = ∫ Ω λ F T [ T ( φ ) ] dΩ
φ is a border Potential distribution to be optimized in the formula, and Ω is for optimizing the finite element divided region of finding the solution, and λ is the optimization weight of corresponding different divided regions in the object function; F TBe the temperature objectives function, comprise the temperature objectives function F of tumor tissues T1Temperature objectives function F with normal structure T2Two parts:
Figure C011295580002C2
Figure C011295580002C3
That is: when tumor temperature is between 43~45 ℃, F T1=0; When the normal structure temperature is between 30~40 ℃, F T2=0.
The temperature objectives function F TIntegration discrete be following form:
∫ Ω F T [ T ( φ ) ] dΩ = λ 1 Σ i = 1 N 1 F T 1 [ Ti ( φ ) ] + λ 2 Σ j = 1 N 2 F T 2 [ Tj ( φ ) ]
N in the formula 1Be the tumor tissues node number of needs heating, N 2For avoiding superheated normal structure node number, T 1And T 2Be respectively the respective nodes temperature, λ 1And λ 2Be respectively the optimization weight of tumor tissues and normal structure;
(7) numerical value of the temperature objectives function of the above-mentioned optimization of foundation carries out following selection:
If this numerical value keeps off 0, then to adopt genetic algorithm to be optimized and find the solution, correction adds thermophysical parameter, and returns step (4), carries out circular treatment;
If this numerical value is near 0, then the thermophysical parameter that adds described in the above-mentioned steps (4) is added thermophysical parameter output as the deep heat field optimum of capacitive RF device.
2. capacitive RF thermotherapeutic equipment deep heat field optimizing control method according to claim 1 is characterized in that described genetic algorithm comprises the following steps:
(a), at random select five individualities or four individualities again together with the optimized individual of previous generation, constitute population of new generation;
(b), calculate individual adaptability, optimized individual is designated as individual 5 directly sends into the next generation, do not lose to guarantee hereditary information;
(c), all the other individualities breed according to the rules of contest, optimized individual also participates in the competition, and avoids inbreeding;
(d), the individuality of selecting in the population carries out copulation with certain probability;
(e), whether restrain, do following selection according to detecting population:
If convergence goes to step (b), carry out circular treatment;
If do not restrain, then carry out next step;
(f), do following selection according to the numerical value of iteration algebraically:
If this numerical value then returns step (a) less than the maximum algebraically that allows, carry out circular treatment;
If this numerical value is equal to or greater than the maximum algebraically of permission, then finish genetic algorithm.
3. capacitive RF thermotherapeutic equipment deep heat field optimizing control method according to claim 1 is characterized in that the ratio λ of the optimization weight of described tumor tissues and normal structure 1/ λ 2Be 8~14.
CNB011295589A 2001-06-27 2001-06-27 Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment Expired - Fee Related CN1166344C (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CNB011295589A CN1166344C (en) 2001-06-27 2001-06-27 Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CNB011295589A CN1166344C (en) 2001-06-27 2001-06-27 Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment

Publications (2)

Publication Number Publication Date
CN1331954A CN1331954A (en) 2002-01-23
CN1166344C true CN1166344C (en) 2004-09-15

Family

ID=4669272

Family Applications (1)

Application Number Title Priority Date Filing Date
CNB011295589A Expired - Fee Related CN1166344C (en) 2001-06-27 2001-06-27 Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment

Country Status (1)

Country Link
CN (1) CN1166344C (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102013220933B3 (en) * 2013-10-16 2015-01-22 Bruker Biospin Ag Shim method with determination of the target field distribution by optimization in a parameter space of reduced dimension
CN115866825A (en) * 2023-02-20 2023-03-28 国电投核力电科(无锡)技术有限公司 Feedback control method for improving high-frequency heating efficiency

Also Published As

Publication number Publication date
CN1331954A (en) 2002-01-23

Similar Documents

Publication Publication Date Title
Wust et al. Simulation studies promote technological development of radiofrequency phased array hyperthermia
Seebass et al. Electromagnetic phased arrays for regional hyperthermia: optimal frequency and antenna arrangement
Roemer Engineering aspects of hyperthermia therapy
Kok et al. High-resolution temperature-based optimization for hyperthermia treatment planning
US20210232736A1 (en) Individual impedance-based radio-frequency heating temperature field prediction method and system
Tsuda et al. An inverse method to optimize heating conditions in RF-capacitive hyperthermia
Cappiello et al. Differential evolution optimization of the SAR distribution for head and neck hyperthermia
Kroeze et al. Regional hyperthermia applicator design using FDTD modelling
Chen et al. Optimisation-based thermal treatment planning for catheter-based ultrasound hyperthermia
Das et al. Electromagnetic thermal therapy power optimization for multiple source applicators
Bardati et al. Hyperthermia phased arrays pre-treatment evaluation
Canters et al. Complaint-adaptive power density optimization as a tool for HTP-guided steering in deep hyperthermia treatment of pelvic tumors
CN1166344C (en) Deep heat field optimizing control method for capacitive RF thermotherapeutic equipment
Gellermann et al. Simulation of different applicator positions for treatment of a presacral tumour
Hendrikx et al. POD-based recursive temperature estimation for MR-guided RF hyperthermia cancer treatment: a pilot study
Mestrom et al. A refined eigenvalue-based optimization technique for hyperthermia treatment planning
Pichardo et al. New design for an endoesophageal sector-based array for the treatment of atrial fibrillation: a parametric simulation study
Aghayan et al. An inverse problem of temperature optimization in hyperthermia by controlling the overall heat transfer coefficient
Khalil-Bustany et al. Minimax optimization-based inverse treatment planning for interstitial thermal therapy
Stauffer et al. Using a conformal water bolus to adjust heating patterns of microwave waveguide applicators
Mozerova et al. Monitoring regional hyperthermia via microwave imaging: a feasibility study
Van de Kamer et al. High-resolution SAR modelling for regional hyperthermia: testing quasistatic zooming at 10 MHz
Ma et al. Review of tumor hyperthermia technique in biomedical engineering frontier
Kroeze On the improvement of regional hyperthermia treatment
Iseki et al. A new heating method with dielectric bolus using resonant cavity applicator for brain tumors

Legal Events

Date Code Title Description
C06 Publication
C10 Entry into substantive examination
PB01 Publication
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
C19 Lapse of patent right due to non-payment of the annual fee
CF01 Termination of patent right due to non-payment of annual fee