WO2020007245A1 - 基于个体阻抗的射频加热温度场预测方法及其系统 - Google Patents

基于个体阻抗的射频加热温度场预测方法及其系统 Download PDF

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WO2020007245A1
WO2020007245A1 PCT/CN2019/093702 CN2019093702W WO2020007245A1 WO 2020007245 A1 WO2020007245 A1 WO 2020007245A1 CN 2019093702 W CN2019093702 W CN 2019093702W WO 2020007245 A1 WO2020007245 A1 WO 2020007245A1
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region
radio frequency
impedance
ablation needle
temperature field
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PCT/CN2019/093702
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French (fr)
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张爱丽
秦方雨
张康伟
徐学敏
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上海交通大学
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101—Computer-aided simulation of surgical operations
    • A61B2034/102—Modelling of surgical devices, implants or prosthesis
    • A61B2034/104—Modelling the effect of the tool, e.g. the effect of an implanted prosthesis or for predicting the effect of ablation or burring
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation

Definitions

  • the present application relates to the field of biomedical engineering, and in particular, to a technique for predicting a radio frequency heating temperature field based on an individual impedance.
  • Percutaneous radiofrequency ablation is a hyperthermia method that replaces surgical resection of liver cancer.
  • RFA percutaneous radiofrequency ablation
  • ions and polar molecules oscillate in an alternating magnetic field
  • high-frequency alternating current will cause frictional heating, which will cause the temperature to rise above 60 ° C, make the protein and the nucleus transiently degenerate, and the tumor cells will directly necrosis. Or apoptosis.
  • the key to achieving effective RFA treatment is to precisely control the size and shape of the ablation zone (pyrocoagulation zone), so as to avoid tumor tissue residue and collateral damage to normal tissue.
  • Mathematical modeling provides an effective way to predict the temperature field and the corresponding tissue damage range, which is of great significance for making more accurate treatment plans.
  • researchers have been working to improve the accuracy and rate of simulations.
  • the purpose of this application is to provide a method and system for predicting a radio frequency heating temperature field based on individual impedance, which greatly improves the accuracy of predicting the temperature distribution.
  • the present application discloses a method for predicting a radio frequency heating temperature field based on an individual impedance, including:
  • the conductivity in the second region is kept constant, and the conductivity in the first region is adjusted so that the impedance between the ablation needle and the ground electrode is consistent with the actual impedance of the individual actually measured by the treatment system;
  • the combination of the first region and the second region is meshed, and coupling calculations are performed by using a radio frequency field model and a biological heat transfer model, thereby obtaining space-time information of the temperature field.
  • the first region is an elliptical cylinder
  • the second region is a cylinder
  • the second region covers an ablation range of the ablation needle.
  • the ablation needle includes unipolar, bipolar, and multipolar ablation needles.
  • the ablation needle is vertically inserted into the first region.
  • the radio frequency field model uses a quasi-electrostatic field model.
  • the biological heat transfer model is a Pennes biological heat transfer model.
  • This application also discloses a radio frequency heating temperature field prediction system based on individual impedance, including:
  • a first area establishing unit configured to establish a first area
  • a second region establishing unit configured to obtain an ablation needle position, and establish a second region in the first region with the ablation needle as a center;
  • a conductivity setting unit configured to keep the conductivity in the second region constant, and adjust the conductivity in the first region so that the impedance between the ablation needle and the ground electrode is consistent with the actual impedance of the individual actually measured by the treatment system;
  • the calculation unit meshes the combination of the first region and the second region, and performs coupling calculation by using a radio frequency field model and a biological heat transfer model, thereby obtaining the space-time information of the temperature field.
  • This application also discloses a radio frequency heating temperature field prediction system based on individual impedance, including:
  • Memory for storing computer-executable instructions
  • a processor for implementing steps in the method as described above when the computer-executable instructions are executed.
  • the present application also discloses a computer-readable storage medium.
  • the computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the steps in the method described above are implemented.
  • the calculation process is greatly simplified and the calculation speed is accelerated.
  • FIG. 1 is a schematic flowchart of a method for predicting an RF heating temperature field based on an individual impedance according to a first embodiment of the present application
  • FIG. 2 is a schematic diagram of a geometric model established in an embodiment of the present application.
  • FIG. 3 is a cross-sectional view of the geometric model of FIG. 2 in one direction;
  • FIG. 4 is a cross-sectional view of the geometric model of FIG. 2 in another direction;
  • FIG. 5 is a schematic diagram of mesh division of the geometric model of FIG. 2;
  • FIG. 6 is a schematic diagram of spatiotemporal information of a temperature field predicted by an embodiment of the present application.
  • FIG. 7 is a comparison diagram between a model established in an embodiment of the present application and a temperature predicted by an existing model and an experimentally measured temperature;
  • FIG. 8 is a comparison diagram between the temperature predicted by the model established in an embodiment of the present application and the model predicted by the prior art and the experimentally measured temperature error.
  • the inventor of the present application found that during the simulation of RFA treatment, the existing modeling methods generally do not consider individual differences between patients, set the tissue conductivity to a constant value, or set the position of the negative electrode at the bottom of the liver.
  • the simulation only considers the electrical conductivity of the liver.
  • the position of the negative electrode is often attached to the buttocks or back of the individual. Therefore, the simulation method of placing the negative electrode at the bottom of the liver or irrespective of the difference in electrical properties of the individual will cause great deviation.
  • individual impedance is often recorded and used to determine whether the tissue is carbonized during RF heating.
  • the impedance reflects the impedance between the positive and negative electrodes, including the impedance of the liver and the impedance of the individual's trunk. Due to the differences between individuals and tissues, the impedance between different individuals is not the same, which has a great impact on the study of RF energy distribution in liver tissues. Therefore, based on the above information, the inventor creatively proposed a method for predicting the temperature field of radio frequency heating based on individual impedance, and verified the accuracy of the model with experimental measurement results.
  • This application first establishes a large geometry (ie, the first region) based on the size of the human body, which represents the body tissue of the ablated object (such as the human or animal body), and then uses the ablation needle as the center to establish a small geometry (that is, the first Area 2), which represents the tissue of the target ablation area.
  • the conductivity of the small internal geometry remains constant (for example, the conductivity of the tissue used in the literature is uniformly set).
  • the conductivity of the large external geometry is adjusted so that the The impedance is consistent with the real impedance of the individual measured by the treatment system, and then the model of the combination of the above two geometries is meshed and calculated.
  • the technical solution fully takes into account the differences in individual impedances, greatly improving the accuracy of predicting temperature distribution, and on the other hand, cleverly designs simple geometric structures, eliminating the tedious steps of skin and tissue segmentation and reconstruction, greatly simplifying
  • the speed of modeling and calculation will help to develop faster and more accurate clinical radiofrequency treatment plans or predict treatment results.
  • FIG. 1 is a schematic flowchart of the method for predicting an RF heating temperature field based on an individual impedance. The method includes the following steps:
  • a first area is established.
  • the first region is a large geometry based on the size of the human body, and represents the human torso tissue.
  • the first region is established in the body of an individual who needs radio frequency heating, such as in a human body or in an animal body that needs radio frequency heating.
  • a small part of the first region may not fit the person, for example, it is outside the human body, as long as the error caused is within the allowable range.
  • the method proceeds to step 102 to obtain the position of the ablation needle, and uses the ablation needle as the center to establish a second region in the first region.
  • the first area and the second area in the embodiments of the present application are both three-dimensional areas, or three-dimensional space areas.
  • the first region includes a second region.
  • the first region is much larger than the second region.
  • the second region is an ablation needle as a center, and a small geometry established in the large geometry body of the first region represents the tissue of the target ablation region.
  • the second region covers the ablation range of the ablation needle.
  • step 103 is performed, and the conductivity in the second region is kept constant.
  • the conductivity in the first region is adjusted so that the impedance between the ablation needle and the ground electrode is consistent with the actual impedance of the individual measured by the treatment system.
  • step 104 where the combination of the first region and the second region is meshed, and coupling calculation is performed by using a radio frequency field model and a biological heat transfer model, thereby obtaining space-time information of the temperature field.
  • the shapes of the first region and the second region may be various.
  • the first region is an elliptical cylinder and the second region is a cylinder. Setting the first region as an elliptical cylinder and the second region as a cylinder can greatly simplify the calculation process on the premise that the calculation accuracy requirements can be achieved.
  • the first region and the second region may also have other shapes.
  • the shape of the first region may be a cylinder, an elliptical cylinder, a rectangular parallelepiped, or other geometry that simulates the shape of a human torso. The size is close to that of a normal human torso.
  • the shape of the second region may also be a cylinder, a sphere, a cuboid, or other geometry that simulates the ablation region, and its size is required to exceed the ablation range of the RF probe.
  • the form of ablation needles can be various, such as unipolar, bipolar, multipolar ablation needles, and the like.
  • the ablation needle is inserted vertically into the first area.
  • the ablation needle can be inserted into the first region at any angle.
  • the radio frequency field models used in step 104 can be diverse.
  • the radio frequency field model adopts a quasi-electrostatic field model.
  • the radio frequency field model adopts a radio frequency electric field model.
  • the radio frequency field model uses an electromagnetic wave theoretical model.
  • the biological heat transfer model used in step 104 may be diverse.
  • the biological heat transfer model adopts a Pennes biological heat transfer model.
  • the biological heat transfer model adopts a modified biological heat transfer model.
  • the biological heat transfer model uses the Weinbaum JJ equation.
  • the biological heat transfer model uses a heat conduction equation.
  • the coupling calculation in step 104 is a numerical calculation.
  • the finite element method can be used for numerical calculation.
  • the coupling calculation may use a finite difference method.
  • the coupling calculation may be calculated using calculation software.
  • This embodiment takes radiofrequency ablation as an example, and fully considers the difference in individual impedance.
  • a large elliptical cylinder 23 (ie, the first region) with a major axis of 30 cm, a minor axis of 18 cm, and a length of 45 cm is established in a finite element simulation software (such as Comsol), as shown in Figs. 2, 3, and 4 shown.
  • a finite element simulation software such as Comsol
  • the position of the ablation needle 21 is obtained.
  • a small cylinder 22 that is, the second area
  • the anode of the ablation needle is placed in the small area.
  • the insertion depth H is 6 cm.
  • the negative electrode plate was placed on one bottom surface of the large oval cylinder, and the diameter of the negative electrode was 6.2 cm.
  • the distance L between the positive electrode and the negative electrode was 35 cm.
  • the internal small cylinder is set as the heated liver tissue, and the actual ablation needle model is selected for the ablation needle.
  • the conductivity of the inner small cylinder is kept constant.
  • the liver conductivity used in the literature is set to 0.53S / m.
  • the impedance measured in the example is 45 ohms.
  • the conductivity of the individual's trunk should be set to 0.48S / m; in the models of the prior art, the conductivity of these two tissues is usually set without considering the impedance.
  • the fourth step is to mesh the combination of the above two cylinders (as shown in FIG. 5), and refine the mesh of the ablation needle and the liver tissue part.
  • the quasi-electrostatic field model and the Pennes bio-heat transfer model are used for coupling calculation to obtain the space-time information of the temperature field, as shown in Figure 6.
  • ⁇ is the density
  • c is the specific heat capacity
  • k is the thermal conductivity
  • ⁇ is the electrical conductivity
  • t is the time
  • subscript b is the blood.
  • thermodynamic and Electrical properties are set as a function of temperature.
  • q m is the heat generated by tissue metabolism and is a temperature-related parameter, but because it generates less heat than RF heating energy, it can be ignored in most studies.
  • T is the tissue temperature and T b is the blood temperature, which is usually set to 37 ° C.
  • ⁇ b is the blood flow perfusion rate, which can be described by the following equation:
  • ⁇ b can also be set as a function of the degree of tissue damage.
  • the electrical conductivity of the individual's trunk is determined by the measured total impedance.
  • this application can eliminate the tedious skin and tissue segmentation and reconstruction steps, which can reduce the modeling burden, speed up the modeling speed, and reduce the calculation time; on the other hand, this application The application fully considers the differences in individual impedances. As shown in Figures 7 and 8, the temperature data predicted by this application is compared with experimentally measured data and there is only a 3.8% difference between the two. There is a difference of 5.8% between the temperature data and the experimentally measured data, which can prove that the temperature field prediction method proposed in this application has achieved better results than the model of the prior art.
  • FIG. 7 is a comparison between the model established in this embodiment and the temperature predicted by the model of the prior art and the temperature measured by radiofrequency ablation experiments of live piglets, where Tc is the temperature measured by the tip of the RF probe, and T1 and T2 are two thermoelectric The temperature was measured by inserting (different positions) into a live piglet.
  • reference numeral 71 represents the Tc curve of the prior art model
  • reference numeral 72 represents the T1 curve of the prior art model
  • reference numeral 73 represents the T2 curve of the prior art model
  • reference numeral 74 represents the present invention.
  • the Tc curve of the model of the embodiment of the application reference numeral 75 represents the T1 curve of the model of the embodiment of the application, the reference numeral 76 represents the T2 curve of the model of the embodiment of the application, and the reference numeral 77 represents the experimentally measured Tc curve (square data points) ),
  • Reference numeral 78 represents the T1 curve (circular data points) of the model of the embodiment of the present application, and reference numeral 79 represents the T2 curve (triangular data points) of the model of the embodiment of the present application. It can be seen from FIG. 7 that the curve of the embodiment of the present application is significantly closer to the experimental data.
  • FIG. 8 is a comparison chart between the temperature predicted by the model established in this embodiment and the temperature predicted by the model in the prior art and the experimentally measured temperature error.
  • reference numeral 81 represents the Tc error percentage curve of the prior art model
  • reference numeral 82 represents the T1 error percentage curve of the prior art model
  • reference numeral 83 represents the T2 error percentage curve of the prior art model
  • 84 represents the Tc error percentage curve of the embodiment model of the present application
  • reference numeral 85 represents the T1 error percentage curve of the embodiment model of the present application
  • reference numeral 86 represents the T2 error percentage curve of the embodiment model of the present application.
  • the error percentage curve of the embodiment of the present application is significantly more X-axis, and the error is significantly smaller.
  • the volume of the ablation region is predicted based on other impedance and power conditions. As shown in Table 2, if the prior art model does not consider the impedance, the ablation region will be greatly overestimated or underestimated. This indicates that the accuracy of the temperature distribution prediction will be greatly improved after considering the actual impedance in this application, which will help to formulate a more accurate clinical radiofrequency treatment plan or predict the treatment result.
  • the second embodiment of the present application relates to a radio frequency heating temperature field prediction system based on individual impedance.
  • the radio frequency heating temperature field prediction system based on individual impedance includes:
  • the first area establishing unit is configured to establish a first area.
  • a second region establishing unit is configured to obtain an ablation needle position, and establish a second region in the first region with the ablation needle as a center.
  • the conductivity setting unit is configured to keep the conductivity in the second region constant, and adjust the conductivity in the first region so that the impedance between the ablation needle and the ground electrode is consistent with the actual impedance of the individual actually measured by the treatment system.
  • the calculation unit meshes the combination of the first region and the second region, and performs coupling calculation by using a radio frequency field model and a biological heat transfer model, thereby obtaining the space-time information of the temperature field.
  • the first embodiment is a method embodiment corresponding to this embodiment, and this embodiment can be implemented in cooperation with the first embodiment.
  • the relevant technical details mentioned in the first embodiment (such as the shape and size of the first and second regions, the radio frequency field model, the biological heat transfer model, the numerical calculation method, etc.) are still valid in this embodiment, in order to reduce repetition I wo n’t repeat them here. Accordingly, the related technical details mentioned in this embodiment can also be applied in the first embodiment.
  • the implementation functions of the modules shown in the embodiment of the above-mentioned individual impedance-based RF heating temperature field prediction system can refer to the correlation of the foregoing method based on individual impedance RF heating temperature field prediction. Describe and understand.
  • the functions of the modules shown in the embodiment of the radio frequency heating temperature field prediction system based on the individual impedance described above may be implemented by a program (executable instructions) running on a processor, or may be implemented by a specific logic circuit.
  • the radio frequency heating temperature field prediction system based on the individual impedance is implemented in the form of a software function module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.
  • the technical solution of the embodiments of the present application that is essentially or contributes to the existing technology can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium and includes several instructions for A computer device (which may be a personal computer, a server, or a network device) is caused to execute all or part of the methods described in the embodiments of the present application.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read Only Memory), a magnetic disk, or an optical disk, and other media that can store program codes. In this way, the embodiments of the present application are not limited to any specific combination of hardware and software.
  • the embodiment of the present application further provides a computer storage medium in which computer-executable instructions are stored.
  • the computer-executable instructions are executed by a processor, the method embodiments of the present application are implemented.
  • an embodiment of the present application further provides a radio frequency heating temperature field prediction system based on an individual impedance, which includes a memory for storing computer-executable instructions, and a processor; the processor is configured to execute a computer-executable memory in the memory.
  • a radio frequency heating temperature field prediction system based on an individual impedance, which includes a memory for storing computer-executable instructions, and a processor; the processor is configured to execute a computer-executable memory in the memory.
  • an action is performed according to an element, it means that the action is performed at least according to the element, which includes two cases: performing the action based on the element only, and according to the element and Other elements perform the action.
  • Multiple, multiple, and multiple expressions include two, two, two, and more than two, two or more, and two or more.

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Abstract

本申请涉及生物医学工程领域，公开了一种基于个体阻抗的射频加热温度场预测方法及其系统，大大提高了预测温度分布的速率和准确性。本申请的方法包括：建立第一区域；取得消融针位置，以消融针为中心，在第一区域内建立第二区域；第二区域内的导电率保持恒定，调整第一区域的导电率，使得消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致；对第一区域和第二区域的组合体进行网格划分，利用射频场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。

Description

基于个体阻抗的射频加热温度场预测方法及其系统 技术领域
本申请涉及生物医学工程领域，特别涉及基于个体阻抗的射频加热温度场预测技术。
背景技术
随着现代影像技术和计算机化手术指导技术的发展，微创热消融技术在肿瘤治疗中得到了广泛的重视，经皮射频消融(RFA)是一种替代肝癌手术切除的热疗方式。在RFA治疗过程中，当离子和极性分子在交变磁场中的振荡时，高频交流电会引起摩擦加热，将导致温度上升至60℃以上，使蛋白质和细胞核的瞬时变性，肿瘤细胞直接坏死或凋亡。
实现有效的RFA治疗的关键是精确控制消融区(热凝区)的大小和形状，从而避免肿瘤组织残留和对正常组织的附带损害。数学建模为其提供了一种有效的方法来预测温度场和相应的组织损伤范围，对于制定更精确的治疗计划具有重大意义，研究人员一直致力于提高模拟的准确性和速率。
然然，本申请的发明人发现，在模拟RFA治疗过程中，现有的建模方法的计算结果往往与实际情况有较大的偏差。
发明内容
本申请的目的在于提供一种基于个体阻抗的射频加热温度场预测方法及其系统，大大提高了预测温度分布的准确性。
为了解决上述问题，本申请公开了一种基于个体阻抗的射频加热温度场 预测方法，包括：
建立第一区域；
取得消融针位置，以消融针为中心，在该第一区域内建立第二区域；
该第二区域内的导电率保持恒定，调整该第一区域的导电率，使得该消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致；
对该第一区域和第二区域的组合体进行网格划分，利用射频场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。
在一优选例中，该第一区域为椭圆柱体，该第二区域为圆柱体。
在一优选例中，该第二区域覆盖该消融针的消融范围。
在一优选例中，该消融针包括单极、双极、多极消融针。
在一优选例中，该消融针垂直插入该第一区域。
在一优选例中，该射频场模型采用准静电场模型。
在一优选例中，该生物传热模型采用Pennes生物传热模型。
在一优选例中，该利用射频场模型和生物传热模型进行耦合计算的步骤中，采用有限元方法进行数值计算。
本申请还公开了一种基于个体阻抗的射频加热温度场预测系统，包括：
第一区域建立单元，用于建立第一区域；
第二区域建立单元，用于取得消融针位置，以消融针为中心，在该第一区域内建立第二区域；
导电率设置单元，用于保持该第二区域内的导电率恒定，调整该第一区域的导电率，使得该消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致；
计算单元，对该第一区域和第二区域的组合体进行网格划分，利用射频 场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。
本申请还公开了一种基于个体阻抗的射频加热温度场预测系统，包括：
存储器，用于存储计算机可执行指令；以及，
处理器，用于在执行该计算机可执行指令时实现如前文描述的方法中的步骤。
本申请还公开了一种计算机可读存储介质，该计算机可读存储介质中存储有计算机可执行指令，该计算机可执行指令被处理器执行时实现如前文描述的方法中的步骤。
本申请实施方式中，通过巧妙设计简单的几何结构，同时充分考虑个体阻抗的差异性，大大提高了预测温度分布的速率和准确性，将有利于制定更精确的临床射频治疗计划、治疗过程术中监控以及治疗结果的预测与评估。
进一步地，将第一区域设置为椭圆柱体，第二区域设置为圆柱体，在可以达到计算精度要求的前提下，大大简化了计算过程，加快了计算速度。
本申请的说明书中记载了大量的技术特征，分布在各个技术方案中，如果要罗列出本申请所有可能的技术特征的组合(即技术方案)的话，会使得说明书过于冗长。为了避免这个问题，本申请上述发明内容中公开的各个技术特征、在下文各个实施方式和例子中公开的各技术特征、以及附图中公开的各个技术特征，都可以自由地互相组合，从而构成各种新的技术方案(这些技术方案均因视为在本说明书中已经记载)，除非这种技术特征的组合在技术上是不可行的。例如，在一个例子中公开了特征A+B+C，在另一个例子中公开了特征A+B+D+E，而特征C和D是起到相同作用的等同技术手段，技术上只要择一使用即可，不可能同时采用，特征E技术上可以与特征C相组合，则，A+B+C+D的方案因技术不可行而应当不被视为已经记载，而A+B+C+E 的方案应当视为已经被记载。
附图说明
图1是本申请第一实施方式中一种基于个体阻抗的射频加热温度场预测方法的流程示意图；
图2是本申请一个实施例中所建立的几何模型示意图；
图3是图2几何模型在一个方向的剖视图；
图4是图2几何模型在另一个方向的剖视图；
图5是图2几何模型的网格划分示意图；
图6为本申请一个实施例所预测的温度场时空信息示意图；
图7为本申请一个实施例所建立的模型以及现有技术的模型预测的温度与实验测量的温度对比图；
图8为本申请一个实施例所建立的模型以及现有技术的模型预测的温度与实验测量的温度误差比较图。
具体实施方式
在以下的叙述中，为了使读者更好地理解本申请而提出了许多技术细节。但是，本领域的普通技术人员可以理解，即使没有这些技术细节和基于以下各实施方式的种种变化和修改，也可以实现本申请所要求保护的技术方案。
下面概要说明本申请的部分创新点：
本申请的发明人发现，在模拟RFA治疗过程中，现有的建模方法通常不考虑患者之间的个体差异，将组织的导电性设置为恒定值，或者将负电极位置设置在肝脏底部，模拟过程只考虑肝脏的导电率。然而在实际临床手术中， 负电极位置常常贴在个体的臀部或背部，因此将负电极设置在肝脏底部或者不考虑个体电学性质差异的模拟方法将产生极大偏差。在临床RFA手术中，个体阻抗常常被记录，并用作判断射频加热过程中组织是否碳化。同时，该阻抗反应的是正负电极之间的阻抗大小，包含肝脏阻抗以及个体躯干的阻抗。由于个体和组织之间的差异性，不同个体之间的阻抗并不相同，这对于研究肝脏组织中的射频能量分布有很大的影响。因此，基于以上信息，发明人创新性地提出了一种基于个体阻抗的射频加热温度场预测的方法，并与实验测量结果验证了模型的准确性。
本申请先建立一个基于人体尺寸大小的大几何体(即第一区域)，代表被消融对象(如人体或动物身体)躯干组织，再以消融针为中心，在大几何体内建立小几何体(即第二区域)，代表目标消融区域的组织，内部小几何体的导电率保持恒定(例如统一设置为文献中使用的组织导电率)，调整外部大几何体的导电率，使得消融针与地极之间的阻抗与治疗系统测得的个体真实阻抗一致，然后对上述两个几何体组合的模型进行网格划分和计算。该技术方案一方面充分考虑了个体阻抗的差异性，大大提高了预测温度分布的准确性，另一方面巧妙设计了简单的几何结构，省去了繁琐的皮肤、组织分割重建步骤，大大简化了建模和计算速度，将有利于制定更快速、更精确的临床射频治疗计划或预测治疗结果。通过将本申请计算结果和实验测量的结果向比较，验证了本申请技术方案的准确性。通过将本申请计算结果与现有技术中的温度场预测数值模型进行对比，一方面本申请的计算更准确，另一方面计算的速度更快。
为使本申请的目的、技术方案和优点更加清楚，下面将结合附图对本申请的实施方式作进一步地详细描述。
本申请第一实施方式涉及一种基于个体阻抗的射频加热温度场预测方 法。图1是该基于个体阻抗的射频加热温度场预测方法的流程示意图。该方法包括以下步骤：
步骤101，建立第一区域。优选地，第一区域是一个基于人体尺寸大小的大几何体，代表人体躯干组织。优选地，第一区域在需要射频加热的个体的体内建立，例如需要接受射频加热的人体内，或动物体内。可选地，第一区域也可以有一小部分不与人体重合，例如落在人体之外，只要所引起的误差在允许范围之内就可以。
此后进入步骤102，取得消融针位置，以消融针为中心，在第一区域内建立第二区域。本申请各实施方式中的第一区域、第二区域都是三维立体的区域，或者说是三维立体空间区域。其中第一区域包含了第二区域，优选地，第一区域远大于第二区域。优选地，第二区域是以消融针为中心，在第一区域的大几何体内建立的小几何体，代表目标消融区域的组织。优选地，第二区域覆盖消融针的消融范围。
此后进入步骤103，第二区域内的导电率保持恒定，调整第一区域的导电率，使得消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致。
此后进入步骤104，对第一区域和第二区域的组合体进行网格划分，利用射频场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。
第一区域和第二区域的形状可以是多种多样的。优选地，第一区域为椭圆柱体，第二区域为圆柱体。将第一区域设置为椭圆柱体，第二区域设置为圆柱体，在可以达到计算精度要求的前提下，大大简化了计算过程。在本申请的其他实施方式中，第一区域和第二区域还可以是其他的形状，例如第一区域的形状可以是圆柱体，椭圆柱体，长方体，或者其他模拟人体躯干形状的几何体，其尺寸大小与正常人体躯干的尺寸大小接近。第二区域的形状还可以是圆柱体，球体，长方体，或其他模拟消融区域的几何体，其尺寸大小 要求超出射频探针的消融范围。
消融针的形式可以是多种多样的，例如单极、双极、多极消融针等。
优选地，消融针垂直插入第一区域。可选地，消融针可以以任意角度插入第一区域。
在步骤104中使用的射频场模型可以是多种多样的。优选地，射频场模型采用准静电场模型。可选地，射频场模型采用射频电场模型。可选地，射频场模型采用电磁波理论模型。
在步骤104中使用的生物传热模型可以是多种多样的。优选地，生物传热模型采用Pennes生物传热模型。可选地，生物传热模型采用修正的生物传热模型。可选地，生物传热模型采用Weinbaum JJ方程。可选地，生物传热模型采用热传导方程。
步骤104中的耦合计算是一种数值计算。该数值计算的实现方法也可以是多种多样的。优选地，可以采用有限元方法进行数值计算。可选地，耦合计算可以采用有限差分法。可选地，耦合计算可以采用计算软件计算。
通过与现有研究模型对比，结果表明一方面我们通过巧妙设计简单几何结构，大大加快了建模和计算速度，省去了繁琐的皮肤、组织分割重建步骤，另一方面我们考虑实际阻抗后会大大提高温度分布预测的准确性，有助于制定更精确的临床射频治疗计划或预测治疗结果。
下面说明本实施方式的一个具体实施例，本实施例以射频消融治疗伞针为例，充分考虑了个体阻抗的差异性。
本实施例包括以下步骤：
第一步，在有限元仿真软件(例如Comsol)中建立一长轴为30cm，短轴为18cm，长度为45cm的大椭圆柱体23(即第一区域)，如图2、图3和 图4所示。将外部大椭圆柱体设置为个体躯干部分。
第二步，取得消融针21位置，以消融针为中心，在大椭圆柱体内建立高和底面圆直径均为5.5cm的小圆柱体22(即第二区域)；消融针的正极放置于小圆柱体中心，插入的深度H为6cm。负极板放置于大椭圆柱体的一个底面，负极直径为6.2cm。正极与负极之间的距离L为35cm。将内部小圆柱体设置为加热的肝脏组织，消融针选择实际采用的消融针型号。
第三步，内部小圆柱体的导电率保持恒定，采用文献中使用的肝脏导电率，设置为0.53S/m。调整外部大椭圆柱体即个体躯干部分的导电率，使得消融针与地极之间的阻抗与治疗系统测得的个体真实阻抗一致。实例中测量得到的阻抗为45欧姆，根据调整结果，个体躯干的导电率应设置为0.48S/m；在现有技术的模型中，通常不考虑阻抗大小而将这两部分组织的导电率设定为统一值，即0.53S/m。
第四步，对上述两个柱体组合结合进行网格划分(如图5所示)，并对消融针以及肝脏组织部分的网格进行细化。利用准静电场模型以及Pennes生物传热模型进行耦合计算，从而获得温度场时空信息，如图6所示。
控制方程如下所示：
Figure PCTCN2019093702-appb-000001
其中，ρ是密度,c是比热容,k是导热率，σ是导电率，t代表时间，下标b表示血液，为了增加模型的准确性，根据文献研究以及实验测量，可以将组织的热力学和电学性质设置为温度的函数。q m为组织新陈代谢产生热量，是一个与温度有关的参数，但是由于其产生热量相比于射频加热能量很小，在绝大部分研究中可以忽略。T是组织温度，T b是血液温度，通常设定为37℃。ω b是血流灌注率，它可由以下方程描述：
Figure PCTCN2019093702-appb-000002
除此之外，ω b也可以设置为组织损伤程度的函数。
本实施例中，建模所使用的各参数如表1所示。
表1
结构 密度(kg/m 3) 比热容(J/kg·K) 导热率(W/m·K) 导电率(S/m)
肝脏组织 1060 3600 0.52 0.53
个体躯干 1060 3600 0.52 0.365*
消融针的有效部分 6450 840 18 1e8
消融针的绝缘部分 70 1045 0.026 1e-5
                            *个体躯干导电率由测量到的总阻抗决定
综上所述，一方面，本申请通过巧妙设计简单几何结构，省去了繁琐的皮肤、组织分割重建步骤，可以减轻建模负担，加快建模速度，降低计算耗时；另一方面，本申请充分考虑个体阻抗的差异性，如图7、图8所示，本申请预测的温度数据和实验测量的数据对比以及二者之间仅存在3.8％的差异性，而现有技术的模型预测的温度数据和实验测量的数据存在5.8％的差异性，可以证明相比于现有技术的模型本申请提出的温度场预测方法取得了更加良好的效果。
图7是本实施例建立的模型以及现有技术的模型预测的温度与活体小猪肝脏射频消融实验测量的温度对比图，其中Tc是射频探针尖端测量的温度，T1和T2是两根热电偶(位置不同)插入活体小猪体内测量的温度。在图7中，附图标记71代表现有技术模型的Tc曲线，附图标记72代表现有技术模型的T1曲线，附图标记73代表现有技术模型的T2曲线，附图标记74代表本申请实施例模型的Tc曲线，附图标记75代表本申请实施例模型的T1曲线，附图标记76代表本申请实施例模型的T2曲线，附图标记77代表实验测量的Tc曲线(方形数据点)，附图标记78代表本申请实施例模型的T1曲线(圆形数据点)，附图标记79代表本申请实施例模型的T2曲线(三角形数据点)。从图7可以看出，本申请实施例的曲线与实验数据明显更为接近。
图8是本实施例建立的模型以及现有技术的模型预测的温度与实验测量的温度误差比较图。其中，附图标记81代表现有技术模型的Tc误差百分比曲线，附图标记82代表现有技术模型的T1误差百分比曲线，附图标记83代表现有技术模型的T2误差百分比曲线，附图标记84代表本申请实施例模型的Tc误差百 分比曲线，附图标记85代表本申请实施例模型的T1误差百分比曲线，附图标记86代表本申请实施例模型的T2误差百分比曲线。从图8可以看出，本申请实施例的误差百分比曲线明显更X轴，误差明显更小。
另外通过对其他阻抗和功率的条件进行消融区域体积预测，如表2所示，若不考虑阻抗大小现有技术的模型会大大的高估或低估消融区域。这表明本申请考虑实际阻抗后会大大提高温度分布预测的准确性，有助于制定更精确的临床射频治疗计划或预测治疗结果。
表2本实施例提出的模型与现有技术的模型预测消融区域体积对比结果
Figure PCTCN2019093702-appb-000003
本申请第二实施方式涉及一种基于个体阻抗的射频加热温度场预测系统。该基于个体阻抗的射频加热温度场预测系统包括：
第一区域建立单元，用于建立第一区域。
第二区域建立单元，用于取得消融针位置，以消融针为中心，在第一区域内建立第二区域。
导电率设置单元，用于保持第二区域内的导电率恒定，调整第一区域的导电率，使得消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致。
计算单元，对第一区域和第二区域的组合体进行网格划分，利用射频场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。
第一实施方式是与本实施方式相对应的方法实施方式，本实施方式可与第一实施方式互相配合实施。第一实施方式中提到的相关技术细节(例如第一和第二区域的形状和大小、射频场模型、生物传热模型、数值计算方法等 等)在本实施方式中依然有效，为了减少重复，这里不再赘述。相应地，本实施方式中提到的相关技术细节也可应用在第一实施方式中。
需要说明的是，本领域技术人员应当理解，上述基于个体阻抗的射频加热温度场预测系统的实施方式中所示的各模块的实现功能可参照前述基于个体阻抗的射频加热温度场预测方法的相关描述而理解。上述基于个体阻抗的射频加热温度场预测系统的实施方式中所示的各模块的功能可通过运行于处理器上的程序(可执行指令)而实现，也可通过具体的逻辑电路而实现。本申请实施方式上述基于个体阻抗的射频加热温度场预测系统如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实施方式的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本申请各个实施方式所述方法的全部或部分。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read Only Memory)、磁碟或者光盘等各种可以存储程序代码的介质。这样，本申请实施方式不限制于任何特定的硬件和软件结合。
相应地，本申请实施方式还提供一种计算机存储介质，其中存储有计算机可执行指令，该计算机可执行指令被处理器执行时实现本申请的各方法实施方式。
此外，本申请实施方式还提供一种基于个体阻抗的射频加热温度场预测系统，其中包括用于存储计算机可执行指令的存储器，以及，处理器；该处理器用于在执行该存储器中的计算机可执行指令时实现上述方法实施方式中的步骤。
需要说明的是，在本专利的申请文件中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定 要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。本专利的申请文件中，如果提到根据某要素执行某行为，则是指至少根据该要素执行该行为的意思，其中包括了两种情况：仅根据该要素执行该行为、和根据该要素和其它要素执行该行为。多个、多次、多种等表达包括2个、2次、2种以及2个以上、2次以上、2种以上。
在本申请提及的所有文献都在本申请中引用作为参考，就如同每一篇文献被单独引用作为参考那样。此外应理解，在阅读了本申请的上述讲授内容之后，本领域技术人员可以对本申请作各种改动或修改，这些等价形式同样落于本申请所要求保护的范围。

Claims (11)

  1. 一种基于个体阻抗的射频加热温度场预测方法，其特征在于，包括：
    建立第一区域；
    取得消融针位置，以消融针为中心，在所述第一区域内建立第二区域；
    所述第二区域内的导电率保持恒定，调整所述第一区域的导电率，使得所述消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致；
    对所述第一区域和第二区域的组合体进行网格划分，利用射频场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。
  2. 根据权利要求1所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述第一区域为椭圆柱体，所述第二区域为圆柱体。
  3. 根据权利要求1所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述第二区域覆盖所述消融针的消融范围。
  4. 根据权利要求1所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述消融针是单极、或双极、或多极消融针。
  5. 根据权利要求1所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述消融针垂直插入所述第一区域。
  6. 根据权利要求1至5中任一项所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述射频场模型采用准静电场模型。
  7. 根据权利要求1至5中任一项所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述生物传热模型采用Pennes生物传热模型。
  8. 根据权利要求1至5中任一项所述的基于个体阻抗的射频加热温度场预测方法，其特征在于，所述利用射频场模型和生物传热模型进行耦合计算的步骤中，采用有限元方法进行数值计算。
  9. 一种基于个体阻抗的射频加热温度场预测系统，其特征在于，包括：
    第一区域建立单元，用于建立第一区域；
    第二区域建立单元，用于取得消融针位置，以消融针为中心，在所述第一区域内建立第二区域；
    导电率设置单元，用于保持所述第二区域内的导电率恒定，调整所述第一区域的导电率，使得所述消融针与地极之间的阻抗与治疗系统实际测得的个体真实阻抗一致；
    计算单元，对所述第一区域和第二区域的组合体进行网格划分，利用射频场模型和生物传热模型进行耦合计算，从而获得温度场时空信息。
  10. 一种基于个体阻抗的射频加热温度场预测系统，其特征在于，包括：
    存储器，用于存储计算机可执行指令；以及，
    处理器，用于在执行所述计算机可执行指令时实现如权利要求1至8中任意一项所述的方法中的步骤。
  11. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机可执行指令，所述计算机可执行指令被处理器执行时实现如权利要求1至8中任意一项所述的方法中的步骤。
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Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108830017B (zh) * 2018-07-05 2022-06-24 上海美杰医疗科技有限公司 基于个体阻抗的射频加热温度场预测系统
CN111529051B (zh) * 2020-04-16 2021-05-07 上海睿刀医疗科技有限公司 一种预测电脉冲消融区域的系统
CN113768484B (zh) * 2020-06-10 2022-06-24 上海美杰医疗科技有限公司 生物组织个性化血流灌注率评估方法及系统
CN113139310B (zh) * 2021-03-29 2023-02-21 韶关东阳光自动化设备有限公司 基于fdtd模拟仿真聚焦超声温度场的方法、模拟器、系统
CN113409286B (zh) * 2021-06-28 2023-08-25 杭州佳量医疗科技有限公司 一种基于磁共振引导的激光消融评估系统
CN113693708B (zh) * 2021-07-15 2023-04-07 上海美杰医疗科技有限公司 射频消融设备的射频输出调整方法、装置及计算机存储介质
CN113952023B (zh) * 2021-09-10 2024-04-30 中国医学科学院肿瘤医院 一种用于消融针的动态模拟方法、装置、存储介质及设备
CN113806934A (zh) * 2021-09-16 2021-12-17 浙江衡玖医疗器械有限责任公司 半球形温度传感器预测模型构建方法、装置及电子设备
CN115220496B (zh) * 2022-09-20 2022-12-20 南京伟思医疗科技股份有限公司 一种分段式射频治疗设备的温度控制方法、装置和设备
CN116983075B (zh) * 2023-09-28 2023-12-22 海杰亚（北京）医疗器械有限公司 消融针的温度监测补偿算法及系统

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150366613A1 (en) * 2014-06-20 2015-12-24 Perseon Corporation Ablation probe with metalized ceramic component
CN106073890A (zh) * 2016-07-11 2016-11-09 北京大学第医院 一种阻抗温度数字化控制式静脉消融仪
CN107049476A (zh) * 2017-04-20 2017-08-18 北京工业大学 一种基于单针实测反馈的电压源表征方法
CN107578820A (zh) * 2017-08-21 2018-01-12 北京工业大学 一种基于单针实测的生物组织特性参数表征方法
CN108830017A (zh) * 2018-07-05 2018-11-16 上海交通大学 基于个体阻抗的射频加热温度场预测方法及其系统

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6575969B1 (en) * 1995-05-04 2003-06-10 Sherwood Services Ag Cool-tip radiofrequency thermosurgery electrode system for tumor ablation
CA2550846C (en) * 2003-12-24 2018-01-23 The Regents Of The University Of California Tissue ablation with irreversible electroporation
CN1278654C (zh) * 2004-12-23 2006-10-11 上海交通大学 水冷式射频肿瘤消融治疗系统的智能化控制方法
US7467075B2 (en) * 2004-12-23 2008-12-16 Covidien Ag Three-dimensional finite-element code for electrosurgery and thermal ablation simulations
US8267927B2 (en) * 2007-01-24 2012-09-18 Koninklijke Philips Electronics N.V. Advanced ablation planning
US9198733B2 (en) * 2008-04-29 2015-12-01 Virginia Tech Intellectual Properties, Inc. Treatment planning for electroporation-based therapies
US8600719B2 (en) * 2010-02-09 2013-12-03 Fraunhofer Gesellschaft zur Förderung der angewandten Forschung e.V. Ablated object region determining apparatuses and methods
US9846765B2 (en) * 2012-11-09 2017-12-19 Siemens Healthcare Gmbh System and method for patient specific modeling of liver tumor ablation
US9259287B2 (en) * 2013-04-02 2016-02-16 Siemens Aktiengesellschaft Patient specific planning and simulation of ablative procedures
US11426080B2 (en) * 2016-07-22 2022-08-30 University Of Southern California Real-time imaging system for monitoring and control of thermal therapy treatments
CN107526928B (zh) * 2017-08-21 2021-06-25 北京工业大学 一种基于特性参数反馈的微波热消融温度场仿真方法
CN109498155B (zh) * 2019-01-10 2022-09-30 上海美杰医疗科技有限公司 消融治疗术中快速规划系统及方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150366613A1 (en) * 2014-06-20 2015-12-24 Perseon Corporation Ablation probe with metalized ceramic component
CN106073890A (zh) * 2016-07-11 2016-11-09 北京大学第医院 一种阻抗温度数字化控制式静脉消融仪
CN107049476A (zh) * 2017-04-20 2017-08-18 北京工业大学 一种基于单针实测反馈的电压源表征方法
CN107578820A (zh) * 2017-08-21 2018-01-12 北京工业大学 一种基于单针实测的生物组织特性参数表征方法
CN108830017A (zh) * 2018-07-05 2018-11-16 上海交通大学 基于个体阻抗的射频加热温度场预测方法及其系统

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