WO2022100019A1 - 一种脉冲电场消融参数优化系统 - Google Patents

一种脉冲电场消融参数优化系统 Download PDF

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WO2022100019A1
WO2022100019A1 PCT/CN2021/090042 CN2021090042W WO2022100019A1 WO 2022100019 A1 WO2022100019 A1 WO 2022100019A1 CN 2021090042 W CN2021090042 W CN 2021090042W WO 2022100019 A1 WO2022100019 A1 WO 2022100019A1
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patient
current
muscle
ablation
field strength
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PCT/CN2021/090042
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English (en)
French (fr)
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罗中宝
王海峰
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上海睿刀医疗科技有限公司
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Publication of WO2022100019A1 publication Critical patent/WO2022100019A1/zh

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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
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B18/04—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating
    • A61B18/12—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating by passing a current through the tissue to be heated, e.g. high-frequency current
    • 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
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • 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
    • 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
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00571—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for achieving a particular surgical effect
    • A61B2018/00577—Ablation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00636—Sensing and controlling the application of energy
    • A61B2018/00773—Sensed parameters
    • A61B2018/00875—Resistance or impedance

Definitions

  • the invention belongs to the technical field of medical devices, in particular to a pulse electric field ablation parameter optimization system.
  • Cancer is a major disease endangering human health.
  • the growth process of tumors has undergone multiple divisions and proliferations, and its daughter cells have obvious differences in tumor growth rate, invasive ability, and drug sensitivity.
  • different patients have different tumor shapes, so traditional treatment methods are used. Its efficacy is weak.
  • personalized precision treatment has become the development direction of modern medicine.
  • the heterogeneity of tumors seriously reduces the accuracy of tumor treatment.
  • an embodiment of the present invention proposes a pulsed electric field ablation parameter optimization system, which, for different individual patients, fully considers the biological conditions of individual patients, and provides personalized treatment plan, improve the accuracy of tumor ablation, reduce the experience requirements of medical personnel, and can effectively reduce overtreatment.
  • an estimation module for estimating the basic data of the current patient based on the basic data of the historical patient; the basic data is used to characterize the electrical properties and muscle shaking properties of the patient's tissue under the pre-pulse field strength;
  • An optimization module configured to use an optimization strategy to select an optimal ablation parameter combination for the current patient from multiple sets of ablation parameter combinations based on the basic data of the current patient.
  • the base data includes: a conductivity ratio and a muscle jitter constant; the conductivity ratio is used to characterize the electrical properties of the patient's tissue under a pre-pulse field strength, and the muscle jitter constant is used to characterize Muscle shake characteristics of the patient's tissue under pre-pulse field strengths; and,
  • the ablation parameters in the ablation parameter combination at least include: electric field strength, pulse width and physical parameters of needle application.
  • the estimating the current patient's basal data based on the historical patient's basal data comprises:
  • the muscle shake constant for the current patient is estimated based on the muscle shake constant of the historical patient, which includes:
  • the average value of the electrical conductivity ratios corresponding to the second number of basal current ratios is calculated as the electrical conductivity ratio of the current patient.
  • the historical patient database includes at least a third number of basic data of the historical patients, where the first number is less than the third number and greater than or equal to 2.
  • the second number is less than the third number and greater than or equal to two.
  • the optimization strategy includes reducing muscle shaking of the current patient, and reducing the ablated normal tissue area of the current patient on the premise that the ablation area covers the lesion area.
  • the muscle shaking acceleration of the current patient is characterized by the muscle shaking acceleration of the current patient; the muscle shaking acceleration of the current patient is represented by the current patient's basic muscle shaking acceleration and the muscle shaking acceleration of the current patient.
  • the jitter constant is calculated and obtained;
  • the ablated normal tissue region of the current patient is characterized by the difference between the ablation region of the current patient and the lesion region of the current patient.
  • the optimization strategy is characterized by a cost function, and the cost function is denoted by C, and the expression of the cost function is:
  • ⁇ is the relative pulse width
  • ⁇ is the relative field strength
  • w is the weight coefficient, and its value range is 0 ⁇ w ⁇ 1
  • F( ⁇ ) represents the muscle shaking acceleration of the current patient, which is the difference between the relative pulse width ⁇ function
  • a e ( ⁇ , ⁇ ) represents the difference between the ablation area of the current patient and the lesion area of the current patient, and is a function of the relative pulse width ⁇ and the relative field strength ⁇ .
  • the ablation parameter combination corresponding to the minimum cost function value is used as the optimal ablation parameter combination.
  • the optimization strategy includes: under a constraint condition, the area of the ablation region of the current patient is the smallest;
  • the constraints include that the ablation area of the current patient covers the lesion area of the current patient, and the muscle shaking of the current patient is within a threshold.
  • system further includes:
  • a preset module configured to preset the multiple sets of ablation parameter combinations based on the needle placement scheme for the current patient.
  • system further includes a database building module for building the historical patient database.
  • the database building module constructs the historical patient database comprising:
  • the historical patient database is constructed based on the constructed simulation database, the calculated conductivity ratios, and the calculated muscle shaking constants.
  • the calculating, based on the simulation database and the base current ratio, the electrical conductivity ratio of the historical patient under a pre-pulse field strength comprising:
  • n is a natural number greater than or equal to 2;
  • the electrical conductivity ratio of the historical patient at the pre-pulse field strength is calculated.
  • the calculating the muscle shaking constant of the historical patient based on the basic muscle shaking acceleration of the historical patient includes:
  • ⁇ is the relative pulse width
  • ⁇ is the relative field strength
  • F( ⁇ )' is the muscle shaking acceleration of the historical patient
  • f( ⁇ )' is the basic muscle shaking acceleration of the historical patient.
  • the pulse electric field ablation parameter optimization system proposed in the embodiment of the present invention is based on the basic data of historical patients and uses an optimization strategy to provide individualized treatment plans for different individual patients, thereby improving tumor
  • the accuracy of ablation reduces the experience requirements of medical personnel, helps medical personnel to quickly form clinical treatment experience, and can effectively reduce excessive treatment.
  • FIG. 1 shows a functional block diagram of a pulsed electric field ablation parameter optimization system proposed by an embodiment of the present invention
  • Fig. 2a shows a schematic diagram of a wrap-around needle distribution scheme in the pulsed electric field ablation parameter optimization system proposed by an embodiment of the present invention
  • Fig. 2b shows a schematic diagram of a filling needle placement scheme in a pulsed electric field ablation parameter optimization system proposed by an embodiment of the present invention
  • Fig. 3 shows the relationship between the number of pulse trains and the current during a pre-pulse in the pulse electric field ablation parameter optimization system proposed by the embodiment of the present invention
  • Fig. 4 shows the relationship between the number of pulse trains and the current during two pre-pulses in the pulse electric field ablation parameter optimization system proposed by the embodiment of the present invention
  • Fig. 5 shows a schematic diagram of needle arrangement of a single group of electrode needles in the pulse electric field ablation parameter optimization system proposed by the embodiment of the present invention
  • FIG. 6 shows a schematic diagram of needle arrangement of multiple groups of electrode needles in the pulse electric field ablation parameter optimization system proposed in the embodiment of the present invention.
  • an embodiment of the present invention proposes a pulsed electric field ablation parameter optimization system, which is based on the basic data of historical patients, uses an optimization strategy to automatically optimize the ablation parameters, fully considers the biological condition of the individual patient, and improves the performance of tumor ablation. Accuracy, reduce the experience requirements for medical personnel, and can effectively reduce over-treatment, and can more conveniently provide medical personnel with scientific medical solutions before ablation treatment.
  • FIG. 1 shows a functional block diagram of a pulsed electric field ablation parameter optimization system according to an embodiment of the present invention.
  • a pulsed electric field ablation parameter optimization system proposed by an embodiment of the present invention includes:
  • the estimation module is used for estimating the basic data of the current patient based on the basic data of the historical patient; the basic data is used to characterize the electrical characteristics and muscle shaking characteristics of the patient's tissue under the pre-pulse field strength;
  • An optimization module configured to use an optimization strategy to select an optimal ablation parameter combination for the current patient from multiple sets of ablation parameter combinations based on the basic data of the current patient.
  • the historical patients here mainly refer to patients who have received pulsed electric field ablation and have collected data related to the treatment.
  • the current patient refers to patients who are ready to receive pulsed electric field ablation. It is understood that the current patient is undergoing pulsed electric field ablation.
  • Post-ablation therapy can also be a history patient.
  • the basic data of the historical patient is used to characterize the electrical properties (such as electrical conductivity properties) and muscle shaking properties of the tissue of the historical patient under the pre-pulse field strength; the basic data of the current patient is used to characterize the tissue of the current patient in the pre-pulse field. Electrical properties and muscle shaking properties under pulsed field strengths. It can be seen that the basic data of the patient used in the embodiments of the present application can reflect the biological condition of the individual patient. Moreover, by estimating the basic data of the current patient based on the basic data of the historical patient, the existing data can be used to provide scientific and reasonable basic data for the current patient.
  • the embodiment of the present invention is based on the basic data of historical patients, and uses an optimization strategy to automatically optimize the ablation parameters, which can fully consider the biological condition of the individual patient, help to formulate a personalized treatment plan, and improve the accuracy of the treatment plan. , improve the accuracy of tumor ablation, reduce the experience requirements for medical personnel, and can effectively reduce excessive treatment, so that it can more conveniently provide scientific medical solutions for medical personnel before treatment.
  • the basic data includes: the conductivity ratio and the muscle shaking constant; the conductivity The rate ratio is used to characterize the electrical properties of the patient's tissue under the pre-pulse field strength, and the muscle shake constant is used to characterize the muscle shake characteristic of the patient's tissue under the pre-pulse field strength.
  • the estimating the muscle shaking constant of the current patient based on the basic data of the historical patient includes:
  • the historical patient database From the historical patient database, find out a first number of basal muscle shaking accelerations that have the same physical parameters of needle administration as the current patient and are closest to the basal muscle shaking acceleration of the current patient; the historical patient database includes at least a third number of basic data of the historical patient, the first number being less than the third number and greater than or equal to 2; and,
  • the average value of the muscle shaking constants corresponding to the first number of basic muscle shaking accelerations is calculated as the muscle shaking constant of the current patient.
  • the pre-pulse field strength here can be selected as 500V/cm, of course, the field strength value such as 1000V/cm can also be selected according to the actual situation.
  • the current patient's basal muscle shaking acceleration can be measured by existing means.
  • the historical patient database may include all or part of the pulse width, electrode needle spacing, electrode needle exposed length, electric field strength, conductivity ratio, simulated current ratio, muscle shaking acceleration, muscle shaking constant, Data such as pulse voltage can also be included as needed.
  • the estimating the conductivity ratio of the current patient based on the basic data of the historical patient includes:
  • the average value of the electrical conductivity ratios corresponding to the second number of basal current ratios is calculated as the electrical conductivity ratio of the current patient.
  • the current basal current ratio of the patient is calculated by using the current ratio before and after current stabilization.
  • the method for obtaining the current ratio before and after the current is stabilized includes: applying an electrical pulse to the organ or tissue through a pair of electrodes on the tissue that has not been ablated by the pulsed electric field, and the current of the electrical pulse slowly rises to the current with the treatment time. Stable, the schematic diagrams of the curves are shown in Figures 3 and 4. In the example of Figure 3, the schematic diagram of the initial current and the stable current when the same pre-pulse field strength is applied, and the example of Figure 4 shows the application of two different Schematic diagram of the stable current corresponding to the pre-pulse field strength. In the example of FIG.
  • Is /I 0 is the current ratio before and after the current is stabilized
  • the two different pre-pulse field strengths are 500V/cm and 1000V/cm respectively, and the stable current corresponding to the two different pre-pulse field strengths is recorded, and the corresponding stable current when the pre-pulse field strength is larger
  • the ratio of the stable current to the corresponding stable current when the pre-pulse field strength is small, that is, I s1000 /I s500 is the current ratio before and after the current is stabilized.
  • the current can also be replaced by resistance.
  • the corresponding stable resistance is the same as the pre-pulse field strength.
  • the ratio of the corresponding stable resistance when the pulse field strength is large, that is, R s5000 /R s1000 is the current ratio before and after the current is stabilized.
  • the electric field strength of the electric pulse (hereinafter referred to as the pre-pulse field strength for the convenience of distinction) generally adopts a low value.
  • electric pulse signals with low electric field strength are used to test the effects of different organs or tissues on tissues with different pulse widths. properties, thereby additionally performing parameter optimization based on the tested tissue properties to improve the effectiveness of personalized therapy.
  • the main purpose of finding the first number of basic muscle shaking accelerations instead of only finding one basic muscle shaking acceleration is to follow the mean value of the muscle shaking constants corresponding to each of the plurality of basic muscle shaking accelerations, to estimate the mechanism jitter constant of the current patient to reduce estimation bias.
  • the specific values of the first quantity and the second quantity can be selected according to the actual situation, for example, 3, 4, 5, 6, etc. are selected, and the first quantity and the second quantity can be equal or unequal. Generally speaking, the larger the value of the first quantity and the second quantity, the more accurate the estimation result may be.
  • the third number is mainly determined by the number of historical patients. It can be understood that the larger the third number, the more samples of historical patients, the more accurate the estimated result, and the better the effect of ablation parameter optimization. For example, the third number may be 500.
  • the ablation parameters in the ablation parameter combination at least include electric field strength (“field strength” for short), pulse width (“pulse width” for short), and physical parameters of needle application, etc. of the electrical pulse.
  • the physical parameters of the needle application may include, for example, the electrode needle spacing and the exposed length of the electrode needles.
  • a wrap-around needle placement scheme can be used. Specifically, an electrode needle is placed in the center of the lesion, which can be called a central electrode needle, and then multiple electrode needles are arranged around the central electrode needle. Multiple electrode needles need to be located within the edge of the lesion. The multiple electrode needles can be called peripheral electrode needles from the perspective of their arrangement position.
  • the number of peripheral electrode needles depends on the size of the lesion. Generally, 3-5 electrode needles can be used to surround the lesion.
  • Figure 2a shows the distribution of central electrode needles and peripheral electrode needles in the type cloth needle scheme. Figure 2a shows the situation where there is one central electrode needle and four peripheral electrode needles. It can be understood that the surrounding cloth needle
  • the number of peripheral electrode needles in the scheme is not limited to this; for small lesions or strip-shaped lesions, the filling needle distribution scheme can be used.
  • the difference between the filled-type needle-distribution scheme is that the filled-type needle-distribution scheme has no central electrode needle.
  • the distribution of the peripheral electrode needles in the filled-type needle-distribution scheme can be referred to as shown in Figure 2b.
  • Figure 2b shows that there are three peripheral electrode needles. It can be understood that the number of peripheral electrode needles in the filled needle distribution scheme is not limited to this.
  • the needle distribution scheme can be determined according to the actual situation of the lesion, and is not limited to the enumerated wrap-around needle distribution scheme and filling needle distribution scheme.
  • the number of electrode needles can also be flexibly selected according to the actual situation.
  • the peripheral electrode needles can also be 2 and so on.
  • multiple sets of ablation parameter combinations may be determined for the current patient-selected needle placement protocol.
  • each set of ablation parameter combinations includes the electric field strength of the electrical pulse, the pulse width, and the physical parameters of the needle application. It is foreseeable that the less the number of ablation parameter combinations or the less the number of ablation parameters in each ablation parameter combination, the less time and computation required for optimization, but the corresponding treatment effect may be relatively low. Therefore, scientifically and reasonably selecting the ablation parameters in the multiple sets of ablation parameter combinations can not only reduce the time and calculation amount, but also effectively ensure the treatment effect. According to the actual experience of treatment, the inventor finds that, when the needle placement plan is determined, the main optimized ablation parameters can be limited to the electric field strength and pulse width of the electric pulse.
  • the system further includes a preset module for determining multiple sets of initial ablation parameter combinations based on a needle placement plan for a patient, as shown by the dotted line in FIG. 1 .
  • the number of electrode needles required by the needle-distribution scheme also needs to be determined.
  • the electrode needles required in response to the needle placement scheme are a pair of electrode needles (also referred to as a single group of electrode needles), and the formed ablation area is the ablation area formed by the single group of electrode needles; in response to the needle placement scheme
  • the required electrode needles are multiple electrode needles, and the formed ablation area is the superposition of the ablation areas formed by each pair of electrode needles (also referred to as multiple groups of electrode needles) formed by sequentially combining the multiple electrode needles. area behind.
  • the lesion area can be acquired with the help of imaging equipment before the ablation parameters are designed.
  • the optimization strategy includes: reducing muscle shaking of the current patient, and reducing the ablated normal tissue area of the current patient on the premise that the ablation area covers the lesion area.
  • the muscle shaking of the current patient can be characterized by the muscle shaking data of the current patient, for example: the muscle shaking acceleration; the muscle shaking acceleration F( ⁇ ) of the current patient is determined by the basic muscle shaking of the current patient. Acceleration f( ⁇ ) and muscle shaking constant C 1 ⁇ of the current patient are calculated.
  • reducing the ablated normal tissue area of the current patient under the premise that the ablation area covers the lesion area is also one of the optimization strategies, which not only ensures the treatment effect, but also reduces the trauma to the patient.
  • the ablated normal tissue region of the current patient is characterized by a difference between the ablation region of the current patient and the lesion region of the current patient.
  • Focus on F( ⁇ ), or focus more on A e ( ⁇ , ⁇ ), its value range is 0 ⁇ w ⁇ 1, when w is 1/2, it indicates that F( ⁇ ) and A e ( ⁇ , ⁇ ) ) have the same weight, when the value of w is less than 1/2, it indicates that A e ( ⁇ , ⁇ ) has a higher weight, and when the value of w is greater than 1/2, it indicates that F( ⁇ ) has a higher weight ;
  • F( ⁇ ) represents the muscle shaking acceleration of the current patient, which is a function of the relative pulse width ⁇ ;
  • a e ( ⁇ , ⁇ ) represents the difference between the ablation area of the current patient and the lesion area of the current patient, is a function of relative pulse width ⁇ and relative field strength ⁇ .
  • the ablation parameter combination corresponding to the minimum cost function value is used as the optimal ablation parameter combination.
  • the optimization strategy includes: under constraints, the area of the ablation region of the current patient is minimized.
  • the constraints include that the ablation area of the current patient covers the lesion area of the current patient, and the muscle shaking of the current patient is within a threshold.
  • the threshold is determined based on the patient's tolerance.
  • the system further includes a database building module, as shown by the dotted line in FIG. 1 .
  • Fig. 1 shows a functional block diagram of a pulsed electric field ablation parameter optimization system according to another embodiment of the present invention in conjunction with the structure diagram shown by the dotted line.
  • the database building module is used to build the historical patient database.
  • the database building module constructs the historical patient database comprising:
  • the historical patient database is constructed based on the constructed simulation database, the calculated conductivity ratios, and the calculated muscle shaking constants.
  • the simulation database is used to establish the corresponding relationship between the preselected parameter combination and the simulation current ratio.
  • the preselected parameters in the preselected parameter combination include a preselected ablation parameter combination and a preselected conductivity ratio.
  • the simulated current ratio can be obtained by software modeling and simulation, or by physical measurement (for example, to a biological tissue with a preselected conductivity ratio, apply electrical pulses with a preselected combination of ablation parameters, and measure the current ratio. ).
  • the preselected values of each preselected parameter have a fixed selection range, that is, the number of preselected values of each preselected parameter is fixed, and the number of preselected parameter combinations is also fixed, which is the preselected value of each preselected parameter.
  • each preselected parameter combination corresponds to a simulated current ratio.
  • the distance between the two electrode needles is generally selected, that is, the distance between the preselected electrode needles is between 0.5cm and 2cm (including the end value), and the range of the preselected treatment field strength is generally 500V/cm to 1500V/ Between cm (including the end value), the preselected pulse width is generally selected from 2 ⁇ s, 5 ⁇ s, 10 ⁇ s, 20 ⁇ s, 50 ⁇ s, and 100 ⁇ s.
  • the upper limit of the range of the preselected treatment field strength can also reach 3000V/cm or other values, and the 1500V/cm and 3000V/cm here are just examples.
  • the preselected parameters include the preselected pulse voltage
  • the preselected treatment field can be calculated when the preselected pulse voltage and the preselected electrode needle spacing are known. powerful.
  • the inventors have found that the conductivity ratio and muscle jitter constant remain substantially unchanged under different field strengths, therefore, in an alternative embodiment, the simulation database is constructed only for a preselected treatment field strength of 500V/cm to reduce simulation The storage space occupied by the database can improve the efficiency of data processing. It can be understood that those skilled in the art can also know the construction method of the simulation database under the preselected treatment field strength with reference to the construction method of the simulation database under the preselected treatment field strength of 500V/cm.
  • the historical patient database is used to establish a corresponding relationship between the ablation parameter combination of the historical patient and the basic data of the historical patient. For a certain historical patient, when the ablation parameter combination is determined, the corresponding basic data can be obtained through the historical patient database.
  • calculating the conductivity ratio of the historical patient under the pre-pulse field strength based on the simulation database and the base current ratio includes:
  • n is a natural number greater than or equal to 2;
  • the electrical conductivity ratio at the pre-pulse field strength for the historical patient is calculated using the functional relationship and the basal current ratio.
  • calculating the muscle shaking constant of the historical patient based on the basic muscle shaking acceleration of the historical patient including:
  • ⁇ is the relative pulse width
  • ⁇ is the relative field strength
  • F( ⁇ )' is the muscle shaking acceleration of the historical patient, which can be obtained by measurement
  • f( ⁇ )' is the basic muscle shaking acceleration of the historical patient, can be obtained by measurement.
  • This embodiment takes a specific application scenario as an example, and provides an implementation manner in which the database building module constructs the historical patient database, so as to more clearly describe the technical solutions proposed by the embodiments of the present invention, but not for the embodiments of the present invention. limit.
  • the database building module constructs the historical patient database, which may include:
  • the simulation database may use the COMSOL multiphysics simulation platform or other simulation tools to establish a numerical simulation model of pulsed electric field ablation.
  • examples of preselected ablation parameters and their preselected values for building a simulation database are as follows:
  • Preselected pulse width T the preselected value of preselected pulse width T is: 2 ⁇ s, 5 ⁇ s, 10 ⁇ s, 20 ⁇ s, 50 ⁇ s, 100 ⁇ s, a total of 6 data points;
  • the preselected electrode needle spacing D the preselected value of the preselected electrode needle spacing D: 0.5cm, 1.0cm, 1.5cm, 2.0cm, 2.5cm, 3.0cm, 3.5cm, 4.0cm, a total of 8 data points;
  • the exposed length L of the electrode needle is preselected, and the preselected values of the exposed length L of the preselected electrode needle are: 1cm, 1.5cm, 2cm, 2.5cm, 3cm, 3.5cm, 4cm, with a total of 7 data points;
  • the preselected electric field intensity E is: 500V/cm ⁇ 1500V/cm, wherein, a data point is established every 50V/cm, a total of 21 data points; in an optional embodiment, the preselected electric field The preselected value of intensity E is fixed to select 500V/cm as a data point;
  • the preselected conductivity ratio R the preselected value of the preselected conductivity ratio R: 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, a total of 7 data points.
  • a simulation database is established according to the preselected values of the above preselected parameters and the corresponding simulated current ratios.
  • the simulation database can be represented in the form of a table.
  • the row of the simulation database can be the parameter combination composed of the preselected value of each preselected parameter and the corresponding simulation current ratio, and the number of columns is the number of preselected value combinations of each preselected parameter, that is, the preselected value of each preselected parameter.
  • the product of the number of preselected values of the parameters; each preselected parameter combination corresponds to a simulated current ratio, and the following Table 2 gives an example of the simulated database of a historical patient when the preselected electric field strength is 500V/cm.
  • the simulation database proposed by the present invention not only reflects the combination relationship between the preselected values of each preselected parameter, but also records the simulated current ratio corresponding to each preselected parameter combination.
  • the number of preselected values of the preselected pulse width T is 6
  • the number of preselected values of the preselected electrode needle spacing D is 8
  • the number of preselected values of the preselected exposed length L is 7,
  • the number of preselected values of the preselected electric field strength E is 7.
  • the number of preselected values is 21, and the number of preselected values of the preselected conductivity ratio R is 7.
  • the preselected value of the preselected electric field intensity E is fixed at 500V/cm
  • the needles were placed according to the actual lesion shape, and the pre-pulse field strength was 500V/cm, and the pre-pulse width was 2 ⁇ s and 5 ⁇ s. , 10 ⁇ s, 20 ⁇ s, 50 ⁇ s, 100 ⁇ s pulse waves to test tissue characteristics, determine the basal current ratio is measured from the pulse train of narrow pulses, because the tissue area of narrow pulse ablation is small; record the pre-pulse field strength of each historical patient
  • the basal current ratios of different pulse widths T are shown in Table 1. Table 1 only intercepts the basal current ratios corresponding to the i-th historical patient.
  • the application process of pulse wave with pre-pulse field strength (eg 500V/cm) and pre-pulse width T sequentially from low to high is used, which is called the pre-pulse stage.
  • Table 1 the electrode needle spacing D corresponding to the i -th historical patient is represented by Di, and the exposed length L of the electrode needle is represented by Li . This embodiment is described by taking the i-th historical patient as an example, so that those skilled in the art can clearly and completely understand the design idea of the present invention.
  • Table 1 The basal current ratio record of the i-th historical patient corresponding to the pre-pulse with a field strength of 500V/cm
  • S 1 represents the base current ratio of the i -th historical patient when the pre-pulse field strength is 500 V/cm
  • the relative pulse width ⁇ is 1 ⁇ s
  • the electrode needle spacing is Di
  • the electrode needle exposed length is Li
  • S 2 represents the base current ratio corresponding to the i -th historical patient when the pre-pulse field strength is 500 V/cm
  • the relative pulse width ⁇ is 2.5 ⁇ s
  • the electrode needle spacing is Di
  • the electrode needle exposed length is Li
  • the basic current ratio record table can also be expressed in other forms, not limited to the form shown in Table 1, and it is subject to clearly expressing the corresponding relationship between the basic current ratio and each relevant parameter.
  • Table 2 The conductivity ratio record table for the i-th historical patient when the preselected field strength is 500V/cm
  • an nth-order polynomial can be used to fit the functional relationship between the current ratio and the conductivity ratio. It can be understood that the larger the value of n is, the more accurate the fitted functional relationship is, but the larger the amount of computation required.
  • the value of n is preferably 4, 5 or 6 after comprehensively considering the accuracy and the amount of calculation.
  • the fitting method may adopt the least squares method, or may also use other fitting methods, such as a neural network method.
  • the fitting technique belongs to a mature technique in the field, and will not be repeated here.
  • the coefficients a, b, c, d, e, and f can be determined according to the least squares method based on the values of the preselected conductivity ratios and the simulated current ratios in Table 2.
  • Table 3 The basal current ratio and the corresponding conductivity ratio record table for the i-th historical patient with a field strength of 500V/cm
  • the meanings of f 3 , . . . , f 6 in the table can be known. It can be understood that the record forms shown in Table 4 are only examples, and those skilled in the art may use other record forms to clearly record the correspondence between the parameters.
  • the muscle shaking acceleration F( ⁇ ) during the ablation treatment is used (for example, formula (2)) and the functional relationship between the muscle shaking influence factor g ⁇ ( ⁇ ) and the relative field strength ⁇ (eg formula (3)), the muscle shaking constant in the expression can be obtained.
  • the field strength is 2000V/cm
  • its muscle shaking acceleration F( ⁇ ) can be measured, so F( ⁇ ) is known, denoted as f 4_2000 , combined with formula (2) and (3), we can get: From this it can be calculated
  • the following historical data can be obtained, with a total of 6 rows. If there are N historical patients in total in the historical patient database, the number of rows of the historical patient pre-pulse database regarding historical data is 6N.
  • Table 5 Historical patient database of the i-th historical patient when the field strength is 500V/cm
  • the needle scheme adopted by a single group of electrode needles is generally a filled needle cloth scheme.
  • the size and shape of the lesion are determined from medical imaging data such as MRI or ultrasound, and the area of the lesion area is assumed to be AL . Arrange the needles reasonably in the lesion area.
  • This embodiment mainly describes the layout of a single group of electrode needles. Therefore, exemplarily, two electrode needles are arranged in the lesion area to complete the ablation.
  • Figure 5 is a schematic diagram of a single group of electrode clothing needles, from which the electrode needle spacing can be determined.
  • the parameter optimization of the ablation parameters of a single group of electrode needles by the pulsed electric field ablation parameter optimization system includes:
  • step 10 a cost function of a single group of electrode needle ablation parameters is established, and the cost function under the pulse width and treatment field strength of each optional parameter combination is traversed and calculated, and the parameter combination corresponding to the minimum cost function is the optimal ablation parameter combination .
  • the cost function C is established as:
  • ⁇ is the relative pulse width
  • ⁇ is the relative field strength
  • F( ⁇ ) represents the muscle shaking acceleration of the current patient, which is a function of the relative pulse width ⁇
  • a e ( ⁇ , ⁇ ) represents the ablation of the current patient
  • F( ⁇ ) represents the acceleration of muscle shaking during a single group of ablation treatment, and its value is mainly related to the relative pulse width ⁇ .
  • a e ( ⁇ , ⁇ ) is the difference between the ablation area A alb and the lesion area AL, which can represent the normal tissue area to be ablated in some cases .
  • the value of A e ( ⁇ , ⁇ ) is related to the relative pulse width ⁇ and
  • the relative field strength ⁇ is related, which is proportional to the electric field strength E of the electrical pulse.
  • step 20 before the formal treatment, a pre-pulse with a field strength of 500 V/cm and a relative pulse width of ⁇ is released to the current patient, and the measured acceleration of the basic muscle shaking at this time is f ⁇ c_500 .
  • step 30 before the formal treatment, a pre-pulse train with a field strength of 500 V/cm and a relative pulse width of ⁇ is released to the current patient until the treatment current is stabilized to obtain the current patient's basal current ratio S c .
  • the historical patient pre-pulse database select multiple historical patients whose pulse width T c , needle spacing D c , and exposed length L c are consistent, and whose basal current ratio is closest to the current patient's basal current ratio S c , such as For 5 historical patients, the average value of the conductivity ratios corresponding to these 5 historical patients is calculated as the conductivity ratio Rc of the current patient (that is, the conductivity ratio corresponding to the current patient at 500V/cm).
  • the relative pulse width ⁇ and the relative field strength ⁇ are determined, according to the conductivity ratio R c calculated as above, combined with the needle spacing D and the exposed length L, use the estimated model provided by the application number CN202010302357.0, or other With the technology, the ablation area corresponding to the relative pulse width ⁇ and the relative field strength ⁇ can be obtained.
  • the ablation area of the ablation parameter combination (relative pulse width ⁇ and relative field strength ⁇ ) cannot cover all the lesions, this group of ablation parameters is discarded; when the ablation area of the ablation parameter combination completely covers the lesions, as shown by the solid line in Figure 5 Illustratively, the difference A e ( ⁇ , ⁇ ) between the area A alb of the ablation area of the current patient and the area A L of the lesion area of the current patient is calculated.
  • step 40 the F c ( ⁇ ) and A e ( ⁇ , ⁇ ) are substituted into the cost function formula to obtain the value of the cost function C.
  • step 20 and step 30 Use the method in step 20 and step 30 to traverse all possible parameter combinations (T: 2 ⁇ s, 5 ⁇ s, 10 ⁇ s, 20 ⁇ s, 50 ⁇ s, 100 ⁇ s; E: 500V/cm ⁇ 1500V/cm, take a number every 50V) or use ant colony Wait for the optimization algorithm to calculate the cost function C corresponding to all possible parameter combinations.
  • the ablation parameter combination is the optimal ablation parameter combination
  • the parameter value is the optimal value of the ablation parameters of a single group of electrode needles.
  • the pulse width and electric field strength in the optimal ablation parameter combination are the optimal pulse width and electric field strength.
  • the optimization strategy includes: under a constraint condition, the area of the ablation area of the current patient is the smallest; the constraint condition includes that the ablation area of the current patient covers the current patient. of the lesion area, and the muscle shake of the current patient is within the threshold.
  • constraints include:
  • f( ⁇ ) represents the peak value of muscle shaking acceleration during pre-pulse
  • the pulse width T c , the electrode needle spacing D c , and the electrode needle exposed length L c are selected from the historical patient database, which are consistent with the current treatment data, and whose basic muscle shaking acceleration f is ( ⁇ ) A specific number of rows closest to the current patient's basal muscle shaking acceleration f ⁇ c_500 , and average the corresponding muscle shaking constants in these rows as the current patient's muscle shaking constant
  • Fmax represents the muscle shaking acceleration threshold; this value can be set based on the patient's tolerance.
  • a L represents the area of the lesion area of the current patient
  • a alb ( ⁇ , ⁇ ) represents the area of the ablation region corresponding to the relative pulse width ⁇ and the relative field strength ⁇ .
  • the minimum area of the ablation region can be obtained.
  • parameter optimization of multiple groups of electrode needle ablation parameters is exemplified to illustrate the main aspects of the embodiments of the present invention more clearly, and should not be construed as limitations of the embodiments of the present invention.
  • a single group of electrode needles cannot be used to complete the treatment, multiple groups of electrode needles need to be used for treatment.
  • the multi-group electrode needle treatment process it is necessary to first determine the ablation area treated by each group of electrode needles, and finally superimpose the ablation areas treated by each group of electrode needles to obtain the final ablation area.
  • Electrode needle therapy (1, 2), (2, 3), (3, 4).
  • Each group of electrode needles can be treated in the same manner as the single group of electrode needles in Embodiment 2, and details are not described in this embodiment.
  • the cost function value of each ablation parameter combination is calculated, and the specific parameter combination is as follows.
  • the optional value of T is: 2 ⁇ s, 5 ⁇ s, 10 ⁇ s, 20 ⁇ s, 50 ⁇ s, 100 ⁇ s, a total of 6 optional values;
  • E 500V/cm ⁇ 1500V/cm, take a number every 50V, a total of 21 optional values;
  • the optimal value of , the pulse width and electric field intensity in the optimal ablation parameter combination are the optimized pulse width and electric field intensity.
  • the number of electrode needles is different depending on the patient's lesion area. For example, 3, 5, 6 or more electrode needles need to be arranged for ablation.
  • the treatment plan can also be any combination of needle groups, and the parameter optimization method is similar to the processing method in Example 3, and will not be repeated here.
  • a "computer-readable medium” can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or apparatus.
  • computer readable media include the following: electrical connections with one or more wiring (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), Read Only Memory (ROM), Erasable Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM).
  • the computer readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, followed by editing, interpretation, or other suitable medium as necessary process to obtain the program electronically and then store it in computer memory.
  • each part or each module of the present invention may be implemented by hardware, software, firmware or a combination thereof.
  • various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or a combination of the following techniques known in the art: Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.

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Abstract

一种脉冲电场消融参数优化系统，包括：估算模块，用于基于历史患者的基础数据估算当前患者的基础数据；所述基础数据用于表征患者的组织在预脉冲场强下的电学特性和肌肉抖动特性；以及，优化模块，基于所述当前患者的基础数据，使用优化策略从多组消融参数组合中选取针对所述当前患者的最优的消融参数组合。该系统以历史患者的基础数据为依据，使用优化策略，可以针对不同的个体病患，充分考虑患者个体的生物情况，给出个性化的治疗计划，提高肿瘤消融的精准度，减少对医疗人员的经验要求，有助于医疗人员快速形成临床治疗经验，并且能够有效减少过度治疗。

Description

一种脉冲电场消融参数优化系统 技术领域
本发明属于医疗器械技术领域，具体涉及一种脉冲电场消融参数优化系统。
背景技术
癌症是危害人类健康的主要疾病。肿瘤的生长过程经过多次分裂增殖，其子细胞在肿瘤生长速度、侵袭能力、对药物敏感性等方面又存在明显的差异，而且患者不同，肿瘤的形态各异，因此采用传统的治疗方法，其疗效较弱。当前，个性化精准治疗成为现代医学的发展方向，然而肿瘤的异质性严重降低了肿瘤治疗的精准度。
为了提高肿瘤治疗的精准度，目前的电场消融治疗计划制定方法已经取得了可喜的发展，但还存在一定的局限性。一方面，在实际的治疗过程中需要根据患者的个体特性进行调整，这就需要医疗技术人员进行大量的动物实验和在有经验的医生指导下进行临床治疗以实现技术积累，很显然这一过程耗时费力，同时还存在一定的医疗风险；另一方面，为了保证治疗的有效性，治疗过程中难以避免地会出现过度治疗。
发明内容
为了解决上述肿瘤消融的精准度较低的技术问题，本发明实施例提出了一种脉冲电场消融参数优化系统，针对不同的个体病患，充分考虑患者个体的生物情况，给出个性化的治疗计划，提高肿瘤消融的精准度，减少对医疗人员的经验要求，并且能够有效减少过度治疗。
本发明提出的一种脉冲电场消融参数优化系统，包括：
估算模块，用于基于历史患者的基础数据估算当前患者的基础数据；所述基础数据用于表征患者的组织在预脉冲场强下的电学特性和肌肉抖动特性；以及，
优化模块，用于基于所述当前患者的基础数据，使用优化策略从多组消融参数组合中选取针对所述当前患者的最优的消融参数组合。
在某些实施例中，所述基础数据包括：电导率比率和肌肉抖动常数；所述电导率比率用于表征患者的组织在预脉冲场强下的电学特性，所述肌肉抖动常数用于表征患者的组织在预脉冲场强下的肌肉抖动特性；以及，
所述消融参数组合中的消融参数至少包括：电场强度、脉冲宽度和施针物理参数。
在某些实施例中，所述基于历史患者的基础数据估算当前患者的基础数据包括：
基于历史患者的肌肉抖动常数估算当前患者的肌肉抖动常数，其包括：
在预脉冲场强下，测试所述当前患者的基础肌肉抖动加速度；
从历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础肌肉抖动加速度的第一数量的基础肌肉抖动加速度；以及，
计算所述第一数量的基础肌肉抖动加速度所对应的肌肉抖动常数的均值，作为所述当前患者的肌肉抖动常数；
基于历史患者的电导率比率估算当前患者的电导率比率，其包括：
在预脉冲场强下，测试所述当前患者的基础电流比；
从所述历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础电流比的第二数量的基础电流比；以及，
计算所述第二数量的基础电流比所对应的电导率比率的均值，作为所述当前患者的电导率比率。
在某些实施例中，所述历史患者数据库中包括至少第三数量的所述历史患者的基础数据，第一数量小于第三数量，且大于等于2。
在某些实施例中，第二数量小于第三数量，且大于等于2。
在某些实施例中，所述优化策略包括：减小所述当前患者的肌肉抖动，并且在消融区域覆盖病灶区域的前提下减小所述当前患者的被消融的正常组织区域。
在某些实施例中，所述当前患者的肌肉抖动采用所述当前患者的肌肉抖动加速度表征；所述当前患者的肌肉抖动加速度通过所述当前患者的基础肌肉抖动加速度和所述当前患者的肌肉抖动常数计算获得；
所述当前患者的被消融的正常组织区域通过所述当前患者的消融区域和所述当前患者的病灶区域的差值表征。
在某些实施例中，所述优化策略通过代价函数表征，所述代价函数用C表示，代价函数的表达式为：
C＝w*F(τ)+(1-w)*A e(τ,ε)
其中，τ为相对脉冲宽度，ε为相对场强；w为权重系数，其取值范围为0<w<1；F(τ)代表所述当前患者的肌肉抖动加速度，为相对脉冲宽度τ的函数；A e(τ,ε)代表所述当前患者的消融区域和所述当前患者的病灶区域的差值，为相对脉冲宽度τ和相对场强ε的函数。
在某些实施例中，对应于最小代价函数值的消融参数组合作为所述最优的消融参数组合。
在某些实施例中，所述优化策略包括：在约束条件下，所述当前患者的消融区域的面积最小；
所述约束条件包括所述当前患者的消融区域覆盖所述当前患者的病灶区域，以及所述当前患者的肌肉抖动在阈值内。
在某些实施例中，所述系统还包括：
预设模块，用于基于针对当前患者的布针方案，预设所述多组消融参数组合。
在某些实施例中，所述系统还包括：数据库构建模块，用于构建所述历史患者数据库。
在某些实施例中，所述数据库构建模块构建所述历史患者数据库包括：
获取在预脉冲场强下并使用预选的消融参数组合时预选电导率比率所对应的仿真电流比，并构建仿真数据库；
测试所述历史患者在预脉冲场强下并使用所述预选的消融参数组合时的基础电流比；
基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率；
在预脉冲场强下，获取所述历史患者的基础肌肉抖动加速度；
基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数；以及，
基于所述构建的仿真数据库、所述计算的电导率比率和所述计算的肌肉抖动常数，构建所述历史患者数据库。
在某些实施例中，所述基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率，包括：
利用n阶多项式以及所述仿真数据库中的所述仿真电流比和所述预选电导率比率，建立电流比与电导率比率之间的函数关系，n为大于等于2的自然数；
利用所述函数关系和所述历史患者的基础电流比计算所述历史患者在预脉冲场强下的电导率比率。
在某些实施例中，所述基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数，包括：
利用公式
Figure PCTCN2021090042-appb-000001
计算所述历史患者的肌肉抖动常数
Figure PCTCN2021090042-appb-000002
其中，τ为相对脉冲宽度，ε为相对场强，F(τ)’为所述历史患者的肌肉抖动加速度，f(τ)’为所述历史患者的基础肌肉抖动加速度。
本发明的有益效果：本发明实施例提出的脉冲电场消融参数优化系统，以历史患者的基础数据为依据，使用优化策略，可以针对不同的个体病患，给出个性化的治疗计划，提高肿瘤消融的精准度，减少对医疗人员的经验要求，有助于医疗人员快速形成临床治疗经验，并且能够有效减少过度治疗。
附图说明
图1示出本发明实施例提出的脉冲电场消融参数优化系统的功能框图；
图2a示出本发明实施例提出的脉冲电场消融参数优化系统中环绕式布针方案的示意图；
图2b示出本发明实施例提出的脉冲电场消融参数优化系统中填充式布针方案的示意图；
图3示出本发明实施例提出的脉冲电场消融参数优化系统中一次预脉冲时脉冲串个数与电流之间的关系；
图4示出本发明实施例提出的脉冲电场消融参数优化系统中两次预脉冲时脉冲串个数与电流之间的关系；
图5示出本发明实施例提出的脉冲电场消融参数优化系统中单组电极针的布针示意图；
图6示出本发明实施例提出的脉冲电场消融参数优化系统中多组电极针的布针示意图。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚明白，以下结合具体实施例，并参照附图，对本发明进一步详细说明。但本领域技术人员知晓，本发明并不局限于附图和以下实施例。
如本文中所述，术语“包括”及其各种变体可以被理解为开放式术语，其意味着“包括但不限于”。术语“基于”可以被理解为“至少部分地基于”。术语“一个实施例”可以被理解为“至少一个实施例”。术语“另一实施例”可以被理解为“至少一个其它实施例”。文中的“第一”、“第二”等术语仅是为了区分技术特征，并无实质含义。
如前所述，在提高肿瘤治疗的精确度方面，目前电场消融治疗计划的制定方法在一定程度上正朝着个性化精准治疗的方向发展，而患者的生物情况不同，这对医疗人员的经验依赖较大，并且在治疗有效性和过度治疗之间存在难以平衡的关系。基于此，本发明实施例提出了一种脉冲电场消融参数优化系统，以历史患者的基础数据为依据，使用优化策略，对消融参数进行自动优化，充分考虑患者个体的生物情况，提高肿瘤消融的精准度，减少对医疗人员的经验要求，并且能够有效减少过度治疗，可以在消融治疗前较为便利地为医疗人员提供科学的医疗方案。
下面结合附图对本发明实施例作进一步描述。图1示出了根据本发明的一个实施例的脉冲电场消融参数优化系统的功能框图。参考图1所示，本发明实施例提出的一种脉冲电场消融参数优化系统，包括：
估算模块，用于基于历史患者的基础数据估算当前患者的基础数据；所述基础数据用于表征患者的组织在预脉冲场强下的电学特性和肌肉抖动特性；
优化模块，用于基于所述当前患者的基础数据，使用优化策略从多组消融参数组合中选 取针对所述当前患者的最优的消融参数组合。
这里的历史患者主要指已经接受过脉冲电场消融治疗并被采集了与治疗相关的数据的患者，所述当前患者是指准备接受脉冲电场消融治疗的患者，可以理解，当前患者在接受过脉冲电场消融治疗后也可以成为历史患者。所述历史患者的基础数据用于表征历史患者的组织在预脉冲场强下的电学特性(例如电导率特性)和肌肉抖动特性；所述当前患者的基础数据用于表征当前患者的组织在预脉冲场强下的电学特性和肌肉抖动特性。可见，本申请实施例使用的患者的基础数据可以体现患者个体的生物情况。而且通过基于历史患者的基础数据估算当前患者的基础数据，可以利用已有的数据为当前患者提供科学合理的基础数据。
本发明实施例以历史患者的基础数据为依据，使用优化策略，对消融参数进行自动优化，可以充分考虑患者个体的生物情况，有助于制定出个性化的治疗方案，提高治疗方案的准确性，提高肿瘤消融的精准度，减少对医疗人员的经验要求，并且能够有效减少过度治疗，从而可以在治疗前较为便利地为医疗人员提供科学的医疗方案。
在一个实施例中，为了体现不同器官或组织的特异性，有利于制定出个性化的治疗方案，提高个性化治疗的效果，所述基础数据包括：电导率比率和肌肉抖动常数；所述电导率比率用于表征患者的组织在预脉冲场强下的电学特性，所述肌肉抖动常数用于表征患者的组织在预脉冲场强下的肌肉抖动特性。
发明人发现，电导率比率的值和肌肉抖动常数的值均无法通过测量的方式直接获得，基于此，在一个实施例中，肌肉抖动常数通过可以测量的基础肌肉抖动加速度来获取，电导率比率通过可以测量的基础电流比来获取。
在一可选实施例中，所述基于历史患者的基础数据估算当前患者的肌肉抖动常数包括：
在预脉冲场强下，测试所述当前患者的基础肌肉抖动加速度；
从历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础肌肉抖动加速度的第一数量的基础肌肉抖动加速度；所述历史患者数据库中包括至少第三数量的所述历史患者的基础数据，第一数量小于第三数量，且大于等于2；以及，
计算所述第一数量的基础肌肉抖动加速度所对应的肌肉抖动常数的均值，作为所述当前患者的肌肉抖动常数。
为了操作方便等原因，这里的预脉冲场强可以选用500V/cm，当然，也可以根据实际情况选用1000V/cm等场强值。当前患者的基础肌肉抖动加速度可以通过现有的手段测量得到。
在一实施例中，所述历史患者数据库可以包括脉冲宽度、电极针间距、电极针裸露长度、电场强度、电导率比率、仿真电流比、肌肉抖动加速度、肌肉抖动常数中的全部或部分数据，还可以根据需要包括脉冲电压等数据。
在一可选实施例中，所述基于历史患者的基础数据估算当前患者的电导率比率包括：
在预脉冲场强下，测试所述当前患者的基础电流比；
从所述历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础电流比的第二数量的基础电流比，第二数量小于第三数量，且大于等于2；以及，
计算所述第二数量的基础电流比所对应的电导率比率的均值，作为所述当前患者的电导率比率。
其中，在一个实施例中，所述当前患者的基础电流比利用电流稳定前后电流比来计算。在一可选实施例中，电流稳定前后电流比的获取方法包括：在未经脉冲电场消融的组织上通过一对电极针对器官或组织施加电脉冲，电脉冲的电流随治疗时间缓慢上升至电流稳定，曲线示意图如图3和图4所示，在图3的示例中示出了施加同一预脉冲场强时初始电流和稳定电流的示意图，在图4的示例中示出了施加两次不同预脉冲场强时对应的稳定电流示意图。在图3的示例中，记录下初始电流I 0和稳定电流I s，则I s/I 0即为电流稳定前后电流比，电流稳定前后电流比用S表示，S＝I s/I 0；或者，电流用电阻替代，即I 0、I s分别由R 0、R s代替，则电流稳定前后电流比S＝R 0/R s。在图4的示例中，两次不同预脉冲场强分别为500V/cm和1000V/cm，记录下两次不同预脉冲场强时对应的稳定电流，预脉冲场强较大时对应的稳定电流与预脉冲场强较小时对应的稳定电流之比，即I s1000/I s500为电流稳定前后电流比，同样，电流也可以用电阻替代，此时预脉冲场强较小时对应的稳定电阻与预脉冲场强较大时对应的稳定电阻之比，即R s5000/R s1000为电流稳定前后电流比。电脉冲的电场强度(为便于区分，后续称为预脉冲场强)一般采用低值，例如，在进行参数优化前，采用低电场强度的电脉冲信号测试不同器官或组织对不同脉冲宽度的组织特性，从而附加地基于测试的组织特性进行参数优化，以提高个性化治疗的效果。
在本实施例中，找出第一数量的基础肌肉抖动加速度而不是仅找出一个基础肌肉抖动加速度，其主要目的是为了后续可以根据多个基础肌肉抖动加速度各自对应的肌肉抖动常数的均值，来估算当前患者的机构抖动常数，以减小估算偏差。找出第二数量的基础电流比的主要作用亦如此。第一数量和第二数量的具体数值可以根据实际情况进行选择，例如选择3、4、5、6等，第一数量与第二数量可以相等，也可以不相等。一般来说，第一数量和第二数量的数值越大，估算的结果可能越准确。例如，从历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础肌肉抖动加速度的5个基础肌肉抖动加速度，将这5个基础肌肉抖动加速度各自对应的肌肉抖动常数进行平均后，作为当前患者的肌肉抖动常数。第三数量主要由历史患者的数量决定，可以理解，第三数量越大，意味着历史 患者的样本数越多，估算的结果可能越准确，相应地，消融参数优化的效果可能也越优异。例如第三数量可以为500个。
在一个实施例中，所述消融参数组合中的消融参数至少包含电脉冲的电场强度(简称“场强”)、脉冲宽度(简称“脉宽”)和施针物理参数等。施针物理参数例如可以包括电极针间距和电极针裸露长度。
本领域技术人员知晓，患者的病灶会存在个体差异，其病灶的大小和形状可能各不相同。因此需要根据病灶的具体形态合理布针，并在合理的布针方案下选择合适的消融参数组合。在具体实施时，可以根据病灶的大小采用不同的布针方案。例如，对于较大病灶，可以采用环绕式布针方案，具体而言，在病灶中心布一根电极针，这根电极针可以称为中心电极针，然后围绕中心电极针布置多根电极针，多根电极针需要位于病灶边缘内，所述多根电极针从布置位置的角度可以称为外围电极针，外围电极针的数量依病灶大小而定，一般可以采用3-5根电极针，环绕式布针方案中中心电极针和外围电极针的分布情况可以参考图2a所示，图2a示出了中心电极针为一根，外围电极针为4根的情形，可以理解，环绕式布针方案中外围电极针的数量不局限于此；对于较小病灶或者条形病灶，可以采用填充式布针方案，具体而言，多根电极针紧贴病灶并且均布在病灶边缘内，与环绕式布针方案不同的是，所述填充式布针方案没有中心电极针，填充式布针方案中外围电极针的分布情况可以参考图2b所示，图2b示出了外围电极针为3根的情形，可以理解，填充式布针方案中外围电极针的数量不局限于此。布针方案可以根据病灶的实际情况确定，不仅仅局限于所例举的环绕式布针方案和填充式布针方案，电极针的数量也可以根据实际情况灵活选择，例如外围电极针还可以为2根等。
在一个实施例中，针对当前患者选择的布针方案，可以确定多组消融参数组合。例如，每组消融参数组合包括电脉冲的电场强度、脉冲宽度和施针物理参数。可以预见的是，消融参数组合的数量越少或每组消融参数组合中的消融参数的取值个数越少，优化所需的时间和计算量也会越少，但对应的治疗效果可能相对较差，因此，科学合理地选择多组消融参数组合中的消融参数，不仅可以减少时间和计算量，而且能够有效保证治疗效果。发明人根据治疗实际经验发现，在布针方案确定的情况下，主要优化的消融参数可以局限为电脉冲的电场强度和脉冲宽度。可以理解，消融参数组合中的消融参数也可以扩展到包含其他或所有消融参数，采用的优化方案可以与电脉冲的电场强度和脉冲宽度的优化方案相同或者思路相类似。在一个实施例中，所述系统还包括预设模块，用于基于针对患者的布针方案，确定多组初始消融参数组合，可参考图1的虚线所示。
在一个实施例中，对应于布针方案，还需要确定布针方案所需的电极针的数量。响应于 布针方案所需的电极针为一对电极针(也可称为单组电极针)，所述形成的消融区域为所述单组电极针所形成的消融区域；响应于布针方案所需的电极针为多根电极针，所述形成的消融区域为所述多根电极针依序组合而成的每对电极针(也可称为多组电极针)所形成的消融区域叠加后的区域。病灶区域可以借助影像设备在消融参数设计前获取。
在一实施例中，所述优化策略包括：减小所述当前患者的肌肉抖动，并且在消融区域覆盖病灶区域的前提下减小所述当前患者的被消融的正常组织区域。
通过在制定消融治疗方案前，将减小当前患者的肌肉抖动作为优化策略之一，不仅可以充分考虑不同患者的个体差异，而且可以减轻患者的痛苦，因此有助于制定出个性化的消融治疗优化方案。
在一可选实施例中，当前患者的肌肉抖动可以采用当前患者的肌肉抖动数据表征，例如：肌肉抖动加速度；所述当前患者的肌肉抖动加速度F(τ)通过所述当前患者的基础肌肉抖动加速度f(τ)和所述当前患者的肌肉抖动常数C 1 τ计算获得。另外，通过将在消融区域覆盖病灶区域的前提下减小所述当前患者的被消融的正常组织区域也作为优化策略之一，不仅可以保证治疗效果，也可以减少对患者的创伤。消融区域的获取方式可以采用现有的技术方案，或者可以参考申请人在先申请(申请号为CN202010302357.0)中所公开的技术方案，即在获得当前患者的电导率比率R之后，代入到上述在先申请中的拟合函数Eth＝a1*E+b1*N+c1*R+d1*E*N+e1*E*R+f1*N*R+g1*E*N*R+h1或者拟合函数Eth＝a2*U+b2*N+c2*D+d2*R+e2*U*N+f2*U*D+g2*U*R+h2*N*D+i2*N*R+j2*D*R+k2*N*D*R+l2*U*N*D+m2*U*N*R+n2*U*D*R+o2*U*N*D*R+p2中，以求出当前患者的电场强度消融阈值Eth，然后基于Eth确定当前患者的消融区域。具体内容可参考在先申请。在一个可选实施例中，所述当前患者的被消融的正常组织区域通过所述当前患者的消融区域和所述当前患者的病灶区域的差值表征。在一可选实施例中，所述优化策略通过代价函数表征，所述代价函数用C表示，代价函数的表达式为：C＝w*F(τ)+(1-w)*A e(τ,ε)，其中，τ为相对脉冲宽度，ε为相对场强；w为权重系数，用以调整F(τ)和A e(τ,ε)的权重从而影响优化策略，体现优化策略更侧重F(τ)，还是更侧重A e(τ,ε)，其取值范围为0<w<1，当w取值为1/2时，表明F(τ)和A e(τ,ε)具有相同的权重，当w取值小于1/2时，表明A e(τ,ε)具有更高的权重，当w取值大于1/2时，表明F(τ)具有更高的权重；F(τ)代表所述当前患者的肌肉抖动加速度，为相对脉冲宽度τ的函数；A e(τ,ε)代表所述当前患者的消融区域和所述当前患者的病灶区域的差值，为相对脉冲宽度τ和相对场强ε的函数。优选地，对应于最小代价函数值的消融参数组合作为所述最优的消融参数组合。
在另一实施例中，所述优化策略包括：在约束条件下，所述当前患者的消融区域的面积 最小。所述约束条件包括所述当前患者的消融区域覆盖所述当前患者的病灶区域，以及所述当前患者的肌肉抖动在阈值内。所述阈值基于患者的可承受范围来确定。
在一个实施例中，为了进一步提高治疗方案的准确性，提高肿瘤消融的精准度，有助于医疗人员快速形成临床治疗经验，所述系统还包括数据库构建模块，如图1中虚线所示。图1中结合虚线所示的结构图示出了根据本发明的另一个实施例的脉冲电场消融参数优化系统的功能框图。在本实施例中，所述数据库构建模块用于构建所述历史患者数据库。
在一个可选实施例中，所述数据库构建模块构建所述历史患者数据库包括：
获取在预脉冲场强下并使用预选的消融参数组合时预选电导率比率所对应的仿真电流比，并构建仿真数据库；
测试所述历史患者在预脉冲场强下并使用所述预选的消融参数组合时的基础电流比；
基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率；
在预脉冲场强下，获取所述历史患者的基础肌肉抖动加速度；
基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数；以及，
基于所述构建的仿真数据库、所述计算的电导率比率和所述计算的肌肉抖动常数，构建所述历史患者数据库。
所述仿真数据库用于建立预选参数组合与仿真电流比之间的对应关系。预选参数组合中的预选参数包括预选的消融参数组合和预选电导率比率。仿真电流比可以通过软件建模仿真的方式获取，也可以通过实物测量的方式获取(例如，对一个具有预选电导率比率的生物组织，施加预选的消融参数组合的电脉冲，并测量其电流比)。对于同一治疗设备，各个预选参数的预选值具有固定的选择范围，也就是说，各个预选参数的预选值的数量是固定的，那么预选参数组合的个数也是固定的，为各个预选参数的预选值的数量的乘积。每个预选参数组合都对应着一个仿真电流比。根据发明人的实际治疗经验，一般选择两根电极针的布针间距即预选电极针间距在0.5cm至2cm之间(含端值)，预选治疗场强的范围一般在500V/cm至1500V/cm之间(含端值)，预选脉冲宽度一般在2μs、5μs、10μs、20μs、50μs、100μs中选择。预选治疗场强的范围的上限也可以达到3000V/cm或者其他数值，这里的1500V/cm、3000V/cm仅是示例。某些场景中，预选参数包括预选脉冲电压，那么根据电场强度＝脉冲电压/电极针间距的函数关系，可以在预选脉冲电压和预选电极针间距已知的情况下，由此计算出预选治疗场强。发明人发现，在不同场强下，电导率比率和肌肉抖动常数基本保持不变，因此，在一个可选实施例中，仿真数据库只针对500V/cm的预选治疗场强进行构建，以减少仿真数据库占用的存储空间，并且可以提高数据处理效率。可以理解，本领域技术人员参照 500V/cm的预选治疗场强下的仿真数据库的构建方法，也可以知晓其他预选治疗场强下的仿真数据库的构建方法。
所述历史患者数据库用于建立历史患者的消融参数组合与历史患者的基础数据之间的对应关系。针对某位历史患者，在消融参数组合确定的情况下，可以通过历史患者数据库获取对应的基础数据。
在一可选实施例中，所述基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率，包括：
利用n阶多项式以及所述仿真数据库中的所述仿真电流比和所述预选电导率比率，建立电流比与电导率比率之间的函数关系，n为大于等于2的自然数；
利用所述函数关系和所述基础电流比计算所述历史患者在预脉冲场强下的的电导率比率。
可选地，所述基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数，包括：
利用公式
Figure PCTCN2021090042-appb-000003
计算所述历史患者的肌肉抖动常数
Figure PCTCN2021090042-appb-000004
其中，τ为相对脉冲宽度，ε为相对场强，F(τ)’为所述历史患者的肌肉抖动加速度，可以通过测量得到，f(τ)’为所述历史患者的基础肌肉抖动加速度，可以通过测量得到。
下面以具体实施例为例，以期更清楚地说明本发明实施例的主要方面，而不应理解为是对本发明实施例的限制。
实施例1
本实施例以具体的应用场景为例，提供了所述数据库构建模块构建所述历史患者数据库的实施方式，以便于更清楚地说明本发明实施例提出的技术方案，并非是对本发明实施例的限制。
所述数据库构建模块构建所述历史患者数据库，可以包括：
100、获取在预脉冲场强下并使用预选的消融参数组合时预选电导率比率所对应的仿真电流比，并构建仿真数据库；
在一实施例中，所述仿真数据库可以采用COMSOL多物理场仿真平台或其他仿真工具建立脉冲电场消融的数值仿真模型。例如，构建仿真数据库的预选的消融参数及其预选值示例如下：
预选脉冲宽度T，预选脉冲宽度T的预选值为：2μs、5μs、10μs、20μs、50μs、100μs，共6个数据点；
预选电极针间距D，预选电极针间距D的预选值为：0.5cm、1.0cm、1.5cm、2.0cm、2.5cm、 3.0cm、3.5cm、4.0cm，共8个数据点；
预选电极针裸露长度L，预选电极针裸露长度L的预选值为：1cm、1.5cm、2cm、2.5cm、3cm、3.5cm、4cm，共7个数据点；
预选电场强度E，预选电场强度E的预选值为：500V/cm～1500V/cm，其中，每间隔50V/cm设立一个数据点，共21个数据点；在一可选实施例中，预选电场强度E的预选值固定选择500V/cm这一个数据点；
预选电导率比率R，预选电导率比率R的预选值为：1.0、1.5、2.0、2.5、3.0、3.5、4.0，共7个数据点。
根据上述预选参数的预选值及对应的仿真电流比建立仿真数据库。例如可以以表格的形式表示仿真数据库，仿真数据库的行可以为各预选参数的预选值和对应的仿真电流比构成的参数组合，列数为各预选参数的预选值组合的数量，即为各预选参数的预选值个数的乘积；每个预选参数组合都对应着一个仿真电流比，后续的表2给出了预选电场强度为500V/cm时某位历史患者的仿真数据库的示例。因此，本发明提出的仿真数据库不仅体现了各预选参数的预选值之间的组合关系，而且记录了各预选参数组合所对应的仿真电流比。对于所述示例，预选脉冲宽度T的预选值个数为6个，预选电极针间距D的预选值个数为8个，预选裸露长度L的预选值个数为7个，预选电场强度E的预选值个数为21个，预选电导率比率R的预选值个数为7个，因此，共有预选值组合的个数为6×8×7×21×7＝49392个，每个预选值组合都可以对应一个仿真电流比。在预选电场强度E的预选值固定选择500V/cm这一个数据点时，预选值组合的个数为6×8×7×7＝2352个，每个预选值组合都可以对应一个仿真电流比。
200、测试所述历史患者在预脉冲场强下并使用所述预选的消融参数组合时的基础电流比。
为了满足个性化消融治疗的需求，并且提高个性化消融治疗的效果，在每位历史患者治疗之前，根据实际病灶形态完成布针，并使用预脉冲场强500V/cm、预脉冲宽度2μs、5μs、10μs、20μs、50μs、100μs的脉冲波进行组织特性测试，确定基础电流比是从窄脉冲的脉冲串开始测定，因为窄脉冲消融的组织区域较小；记录每位历史患者在预脉冲场强下不同脉宽T的基础电流比，记录形式见表1，表1仅截取了对应于第i位历史患者的基础电流比。其中，针对历史患者，采用预脉冲场强(例如500V/cm)、预脉冲宽度T依次从低到高的脉冲波的施加过程，称为预脉冲阶段。定义表中的τ为相对脉冲宽度，相对脉冲宽度τ与脉冲宽度存在正比例关系，例如τ＝T/2。表1中，对应第i位历史患者的电极针间距D用D i表示，电极针裸露长度L用L i表示。本实施例以第i位历史患者为例进行说明，本领域技术人员由此可清楚完整地了解本发明的设计思路。
Figure PCTCN2021090042-appb-000005
表1 场强为500V/cm的预脉冲对应第i位历史患者的基础电流比记录表
表1中，S 1表示对应第i位历史患者的在预脉冲场强为500V/cm、相对脉冲宽度τ为1μs、电极针间距为D i、电极针裸露长度为L i时的基础电流比，S 2表示对应第i位历史患者的在预脉冲场强为500V/cm、相对脉冲宽度τ为2.5μs、电极针间距为D i、电极针裸露长度为L i时的基础电流比，同理，可以知晓S 3、…、S 6表示的含义。
在表1所示的预脉冲场强为500V/cm时基础电流比记录表中，每增加一位历史患者的组织特性测试病例，表1所示的记录表增加一行，每行中的变化参数可能包括：电极针间距D和电极针裸露长度L，每一列中的相对脉冲宽度τ仍然保持从小到大的顺序，对应的结果为每位历史患者对应的基础电流比。可以理解，基础电流比记录表还可以采用其他形式表示，而不局限于表1所示的形式，以清楚表达基础电流比与各相关参数之间的对应关系为准。
300、基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率。
针对第i位历史患者，预选脉冲宽度T＝2μs、5μs、10μs、20μs、50μs或100μs，预选电极针间距D i、预选电极针裸露长度L i和预选电场强度E i已知，首先从所述仿真数据库中挑选出符合上述预选参数组合的行，构成电导率记录表，其结构形式可以如表2所示，由于预选脉冲宽度T的预选值为6个，预选电极针间距D、预选电极针裸露长度L和预选电场强度E为确定值，预选电导率比率的预选值为7个，因此，针对第i位历史患者的电导率记录表按照表2所示的总行数为6×1×1×1×7＝42行，可参见表2的示例。
脉冲宽度T 电极针间距D 电极针裸露长度L 电场强度E 电导率比率R 仿真电流比
2μs D i L i 500V/cm 1.0 S 1.0s_1
2μs D i L i 500V/cm 1.5 S 1.5s_1
2μs D i L i 500V/cm 2.0 S 2.0s_1
2μs D i L i 500V/cm 2.5 S 2.5s_1
2μs D i L i 500V/cm 3.0 S 3.0s_1
2μs D i L i 500V/cm 3.5 S 3.5s_1
2μs D i L i 500V/cm 4.0 S 4.0s_1
…… …… …… …… …… ……
100μs D i L i 500V/cm 1.0 S 1.0s_6
100μs D i L i 500V/cm 1.5 S 1.5s_6
100μs D i L i 500V/cm 2.0 S 2.0s_6
100μs D i L i 500V/cm 2.5 S 2.5s_6
100μs D i L i 500V/cm 3.0 S 3.0s_6
100μs D i L i 500V/cm 3.5 S 3.5s_6
100μs D i L i 500V/cm 4.0 S 4.0s_6
表2 预选场强为500V/cm时针对第i位历史患者的电导率比率记录表
根据所述挑选出的上述预选参数组合，可以采用n阶多项式拟合电流比与电导率比率之间的函数关系。可以理解，n的取值越大，拟合出的函数关系越准确，但所需的计算量越大。在综合考虑精确性和计算量后，n的取值优选为4、5或6。拟合方法可以采用最小二乘方法，或者也可以其他拟合方法，例如神经网络方法，拟合技术属于本领域的成熟技术，在此不再赘述。
例如，当脉冲宽度T＝2μs，根据最小二乘方法，采用n阶多项式建立电流比与电导率比率之间的函数关系。
当n＝5时，其函数关系S s为：S s＝a×R 5+b×R 4+c×R 3+d×R 2+e×R+f     (1)
其中的系数a、b、c、d、e、f可基于表2中的预选电导率比率和仿真电流比的数值根据最小二乘方法确定。
当上述函数关系确定后，将表1中第i位历史患者在脉冲宽度T＝2μs(即τ＝1μs)对应的基础电流比的数据S 1带入，即可计算出第i位历史患者在500V/cm场强下对应的电导率比率R 1。
同理，当脉冲宽度T＝5、10、20、50或100μs时，可采用相同方法，分别利用各脉冲宽度对应的基础电流比S 2、S 3、S 4、S 5、S 6，求出第i位历史患者对应的电导率比率R 2、R 3、R 4、R 5、R 6。记录形式可参见表3所示，可以理解，表3所示的记录形式仅是示例，本领域技术人员可以采用其他记录形式，来清楚记录各参数之间的对应关系。
Figure PCTCN2021090042-appb-000006
表3 场强为500V/cm的针对第i位历史患者的基础电流比以及对应的电导率比率记录表
400、在预脉冲场强下，获取所述历史患者的基础肌肉抖动加速度；基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数。
在所述预脉冲阶段，获取和记录每位历史患者在预脉冲场强的不同脉宽T的基础肌肉抖动加速度，记录形式可以参见表4所示，f 1表示第i位历史患者在τ＝1μs时的基础肌肉抖动 加速度，f 2表示第i位历史患者在τ＝2.5μs时的基础肌肉抖动加速度，同理，可以知晓表中f 3、…、f 6表示的含义。可以理解，表4所示的记录形式仅是示例，本领域技术人员可以采用其他记录形式，来清楚记录各参数之间的对应关系。
Figure PCTCN2021090042-appb-000007
表4 场强为500V/cm时的第i位历史患者的基础肌肉抖动加速度记录表
假定该历史患者在正式消融治疗过程中，采用相对脉冲宽度τ、治疗场强为2000V/cm的脉冲进行消融治疗，记录消融治疗过程中肌肉抖动加速度F(τ)的值。如果针对该历史患者还采用其他场强值进行消融，也一并记录对应的肌肉抖动加速度的值，同样可采用表4的形式进行记录。
从历史数据来看，在脉宽T一定的情况下，肌肉抖动加速度大致与相对场强ε成正比，其中，ε＝E/500。因此，定义消融治疗过程中肌肉抖动加速度F(τ)的函数表达式如下：
F(τ)＝f(τ)*g τ(ε)      (2)
其中，f(τ)表示预脉冲(相对脉冲宽度τ＝T/2、场强为500V/cm)时的基础肌肉抖动加速度。g τ(ε)表示肌肉抖动影响因子，g τ(ε)为一阶多项式；当E＝500V/cm(即ε＝1)时，F(τ)＝f(τ)，g τ(ε)＝1。所述消融治疗过程中肌肉抖动加速度F(τ)的函数表达式基于动物实验数据及技术人员的经验获取。根据动物实验研究，肌肉抖动加速度与相对场强ε呈线性关系，其中ε＝E/500，将肌肉抖动影响因子与相对场强ε的函数关系表示为：
Figure PCTCN2021090042-appb-000008
其中，
Figure PCTCN2021090042-appb-000009
为肌肉抖动常数。正式消融时场强E为已知，基础肌肉抖动加速度可以通过现有设备测量得到，因此根据正式消融时的基础肌肉抖动加速度，利用消融治疗过程中肌肉抖动加速度F(τ)的函数表达式(例如公式(2))以及肌肉抖动影响因子g τ(ε)与相对场强ε的函数关系(例如公式(3))，即可求出该表达式中的肌肉抖动常数
Figure PCTCN2021090042-appb-000010
例如，以第i位历史患者为例，在脉冲宽度T＝20μs，即相对脉冲宽度τ＝10μs时，其预脉冲时的基础肌肉抖动加速度为f(τ)＝f 4，假设正式消融时的场强为2000V/cm，相对场强ε＝E/500＝4，其肌肉抖动加速度F(τ)可以测量得到，因此F(τ)为已知，记为f 4_2000，结合公式(2)和(3)中，可以得到：
Figure PCTCN2021090042-appb-000011
由此可以计算出
Figure PCTCN2021090042-appb-000012
如果针对该历史患者还采用其他相对脉冲宽度进行了消融，也可将
Figure PCTCN2021090042-appb-000013
Figure PCTCN2021090042-appb-000014
等对应参数补齐。
500、基于所述构建的仿真数据库、所述计算的电导率比率和所述计算的肌肉抖动常数，构建所述历史患者数据库。
针对第i位历史患者，即可得到如下历史数据，共6行。如果历史患者数据库中总计有N位历史患者，则历史患者预脉冲数据库关于历史数据的行数为6N。
Figure PCTCN2021090042-appb-000015
表5 场强为500V/cm时第i位历史患者的历史患者数据库
实施例2
在本实施例中，对单组电极针消融参数组合的优化进行示例性说明，以更加清楚地说明本发明实施例的主要方面，而不应理解为是对本发明实施例的限制。单组电极针采用的针方案一般为填充式布针方案。
根据MRI或超声等医学影像数据确定病灶的大小和形状，假定病灶区域的面积为A L。在病灶区域合理布针，本实施例主要说明单组电极针布局情况，因此示例性地在病灶区域布2根电极针来完成消融。图5为单组电极针布针示意图，从该图中即可确定电极针间距。本实施例中，脉冲电场消融参数优化系统对单组电极针消融参数的参数优化，包括：
在步骤10中，建立单组电极针消融参数的代价函数，遍历计算各个可选的参数组合的脉冲宽度和治疗场强下的代价函数，代价函数最小时对应的参数组合为最优消融参数组合。
具体来说，对于单组电极针治疗而言，消融参数优化的主要参数为：脉冲宽度T(或者相对脉冲宽度τ＝T/2)和治疗场强E(或者相对场强ε＝E/500)；所述优化策略包括：减小所述当前患者的肌肉抖动，并且在消融区域覆盖病灶区域的前提下减小所述当前患者的被消融的正常组织区域。在步骤10中，将代价函数C建立为：
C＝w*F(τ)+(1-w)*A e(τ,ε)     (4)
其中，τ为相对脉冲宽度，ε为相对场强；F(τ)代表所述当前患者的肌肉抖动加速度， 为相对脉冲宽度τ的函数；A e(τ,ε)代表所述当前患者的消融区域和所述当前患者的病灶区域的差值，为相对脉冲宽度τ和相对场强ε的函数；w为权重系数，其取值范围为0<w<1，w的具体取值可以根据需要设定，如果肌肉抖动权重高，多余消融区域权重低，则w>1/2；如果两者权重接近,则W＝1/2；如果肌肉抖动权重低，多余消融区域权重高，则w＜1/2。F(τ)表示单组消融治疗过程中肌肉抖动加速度，其值主要与相对脉冲宽度τ相关。A e(τ,ε)为消融区域A alb和病灶区域A L的差值，在某些情况下可以表示被消融的正常组织区域，A e(τ,ε)的值与相对脉冲宽度τ和相对场强ε相关，所述相对场强ε与电脉冲的电场强度E成正比。
在步骤20中，正式治疗之前，给当前患者释放场强500V/cm、相对脉冲宽度为τ的预脉冲，此时实测的基础肌肉抖动加速度为f τc_500。
当相对脉冲宽度τ和相对场强ε确定时，结合肌肉抖动加速度的函数表达式，例如前述的公式(2)，计算相对场强ε对应的肌肉抖动加速度：F c(τ)＝f τc_500*g τ(ε)。
实际计算时，从历史患者数据库中，挑选脉冲宽度T c、电极针间距D c、电极针裸露长度L c与本次治疗数据相吻合的，且其基础肌肉抖动加速度f(τ)最接近所述当前患者的基础肌肉抖动加速度f τc_500的特定数量的行，并将这些行中对应的肌肉抖动常数求平均作为当前患者的肌肉抖动常数
Figure PCTCN2021090042-appb-000016
将当前患者的肌肉抖动常数
Figure PCTCN2021090042-appb-000017
的估计值代入公式(3)中，得到g τ(ε)，代入公式F c(τ)＝f τc_500*g τ(ε)中，即可获得相对脉冲宽度τ和相对场强ε对应的肌肉抖动加速度F c(τ)。可能在数据库建立初期，会存在某些参数组合对应的肌肉抖动常数缺失的情况，使得计算出的值存在误差，待历史患者数据库成长到一定规模后可以避免出现上述问题。每位当前患者在消融治疗结束后也可以成为历史患者。
在步骤30中，正式治疗之前，给当前患者释放场强500V/cm、相对脉冲宽度为τ的预脉冲串直至治疗电流稳定，获得当前患者的基础电流比S c。从历史患者预脉冲数据库中，挑选脉冲宽度T c、针间距D c、裸露长度L c相吻合的，且其基础电流比与当前患者的基础电流比S c最接近的多位历史患者，例如5位历史患者，计算这5位历史患者所对应的电导率比率均值作为当前患者的电导率比率R c(即当前患者在500V/cm下对应的电导率比率)。
当相对脉冲宽度τ和相对场强ε确定时，根据如上计算得到的电导率比率R c，结合布针间距D和裸露长度L，利用申请号为CN202010302357.0提供的预估模型，或者其他已有技术，即可得到相对脉冲宽度τ和相对场强ε对应的消融区域。若该消融参数组合(相对脉冲宽度τ和相对场强ε)的消融区域不能覆盖所有病灶时，该组消融参数舍弃；当该消融参数组合的消融区域完全覆盖病灶时，如图5中实线示意，计算当前患者的消融区域的面积A alb和当前患者的病灶区域的面积A L的差值A e(τ,ε)。
在步骤40中，将所述F c(τ)和A e(τ,ε)代入代价函数公式中，得到代价函数C的值。
采用步骤20和步骤30中的方法遍历所有可能参数组合(T：2μs，5μs，10μs，20μs，50μs，100μs；E：500V/cm～1500V/cm，每间隔50V取一个数)或采用蚁群等寻优算法，计算得到所有可能参数组合对应的代价函数C。
选取在满足优化策略的前提下代价函数C最小时所对应的消融参数组合，该消融参数组合为最优的消融参数组合，其中的参数值即为单组电极针消融参数的最优值，最优消融参数组合中的脉冲宽度和电场强度即为最优的脉冲宽度和电场强度。
可替代地或者进一步地，在一个实施例中，所述优化策略包括：在约束条件下，当前患者的消融区域的面积最小；所述约束条件包括所述当前患者的消融区域覆盖所述当前患者的病灶区域，以及所述当前患者的肌肉抖动在阈值内。
具体的,所述约束条件包括：
Figure PCTCN2021090042-appb-000018
A L∈A alb(τ,ε)，ε∈{1,2,…,21}，τ∈{1,2.5,5,10,25,50}；
其中，ε表示相对场强，其中，ε＝E/500，E表示电场强度；
τ表示相对脉冲宽度，其中，τ＝T/2，T表示脉冲宽度；
f(τ)表示预脉冲时的肌肉抖动加速度峰值；
Figure PCTCN2021090042-appb-000019
为当前患者的肌肉抖动常数。在一个实施例中，实际计算时，从历史患者数据库中，挑选脉冲宽度T c、电极针间距D c、电极针裸露长度L c与本次治疗数据相吻合的，且其基础肌肉抖动加速度f(τ)最接近所述当前患者的基础肌肉抖动加速度f τc_500的特定数量的行，并将这些行中对应的肌肉抖动常数求平均作为当前患者的肌肉抖动常数
Figure PCTCN2021090042-appb-000020
F max表示肌肉抖动加速度阈值；该值可以基于患者的承受能力来设定。
A L表示当前患者的病灶区域的面积；
A alb(τ,ε)表示对应于相对脉冲宽度τ和相对场强ε的消融区域的面积。
基于上述约束条件，可以获取所述消融区域的面积最小。
实施例3
在本实施例中，对多组电极针消融参数的参数优化进行示例性说明，以更加清楚地说明本发明实施例的主要方面，而不应理解为是对本发明实施例的限制。针对不能采用单组电极针完成治疗的情况，需要采用多组电极针来进行治疗。在多组电极针治疗过程中，需要先确定每组电极针治疗的消融区域，最后将每组电极针治疗的消融区域叠加得到最终的消融区域。
假定某患者的病灶如图6所示，由于病灶区域较小，可以选用填充式布针方案，在病灶区域内均匀布置了4根电极针用于消融，这种情况下，假设需要进行三组电极针治疗：(1、2)， (2、3)，(3、4)。每组电极针可分别按照实施例2中单组电极针的方式处理，在本实施例中不再赘述。
针对每组治疗的每种消融参数组合，计算每种消融参数组合的代价函数值，具体参数组合如下。
Figure PCTCN2021090042-appb-000021
Figure PCTCN2021090042-appb-000022
Figure PCTCN2021090042-appb-000023
……
Figure PCTCN2021090042-appb-000024
其中，T的可选值为：2μs、5μs、10μs、20μs、50μs、100μs，共6个可选值；
E的可选值为：500V/cm～1500V/cm，每间隔50V取一个数，共21个可选值；
因此，消融参数组合一共为6*21＝126个组合。
分别计算每个参数组合中步骤1、2、3的肌肉抖动，取三个步骤中肌肉抖动的最大值即为F(τ)。同理，分别计算每个参数组合中步骤1、2、3的消融区域，三个消融区域叠加之后的面积即为最终消融区域的面积A alb；如果叠加的消融区域不能完全覆盖实际病灶区域，则该组消融参数舍弃，如果叠加的消融区域能够完全覆盖实际病灶区域时，计算最终消融区域的面积A alb和病灶区域的面积A L的差值A e(τ,ε)。最后，将F(τ)和A e(τ,ε)代入代价函数公式中，得到代价函数C。
遍历所有参数组合(T：2μs，5μs，10μs，20μs，50μs，100μs；E：500V/cm～1500V/cm，每间隔50V取一个数)或采用蚁群等寻优算法，计算得到所有可能消融参数组合对应的代价函数C。
选取在满足优化策略的前提下代价函数C最小时所对应的消融参数组合，该消融参数组合即为最优消融参数组合，其中的参数值(例如T和E)即为多组电极针消融参数的最优值，最优消融参数组合中的脉冲宽度和电场强度即为优化的脉冲宽度和电场强度。
在实际应用中，根据患者的病灶区域不同，布置电极针数量的情况也不同，比如：需要布置3根、5根、6根或更多的电极针进行消融。其治疗方案也可以是任意的针组组合，其参数优化的方式与实施例3中的处理方式类似，在此不再赘述。
本领域技术人员可以理解，在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，“计算机可读介质”可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。
计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本发明的各部分或各模块可以用硬件、软件、固件或它们的组合来实现。在 上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或它们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
以上，对本发明的实施方式进行了说明。但是，本发明不限定于上述实施方式。凡在本发明的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (13)

  1. 一种脉冲电场消融参数优化系统，其特征在于，包括：
    估算模块，用于基于历史患者的基础数据估算当前患者的基础数据；所述基础数据用于表征患者的组织在预脉冲场强下的电学特性和肌肉抖动特性；以及，
    优化模块，用于基于所述当前患者的基础数据，使用优化策略从多组消融参数组合中选取针对所述当前患者的最优的消融参数组合。
  2. 根据权利要求1所述的系统，其特征在于，
    所述基础数据包括：电导率比率和肌肉抖动常数；所述电导率比率用于表征患者的组织在预脉冲场强下的电学特性，所述肌肉抖动常数用于表征患者的组织在预脉冲场强下的肌肉抖动特性；以及，
    所述消融参数组合中的消融参数至少包括：电场强度、脉冲宽度和施针物理参数。
  3. 根据权利要求2所述的系统，其特征在于，所述基于历史患者的基础数据估算当前患者的基础数据包括：
    基于历史患者的肌肉抖动常数估算当前患者的肌肉抖动常数，其包括：
    在预脉冲场强下，测试所述当前患者的基础肌肉抖动加速度；
    从历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础肌肉抖动加速度的第一数量的基础肌肉抖动加速度；以及，
    计算所述第一数量的基础肌肉抖动加速度所对应的肌肉抖动常数的均值，作为所述当前患者的肌肉抖动常数；
    基于历史患者的电导率比率估算当前患者的电导率比率，其包括：
    在预脉冲场强下，测试所述当前患者的基础电流比；
    从所述历史患者数据库中，找出具有与所述当前患者相同的施针物理参数且最接近所述当前患者的基础电流比的第二数量的基础电流比；以及，
    计算所述第二数量的基础电流比所对应的电导率比率的均值，作为所述当前患者的电导率比率。
  4. 根据权利要求3所述的系统，其特征在于，所述优化策略包括：减小所述当前患者的肌肉抖动，并且在消融区域覆盖病灶区域的前提下减小所述当前患者的被消融的正常组织区域。
  5. 根据权利要求4所述的系统，其特征在于，
    所述当前患者的肌肉抖动采用所述当前患者的肌肉抖动加速度表征；所述当前患者的肌肉抖动加速度通过所述当前患者的基础肌肉抖动加速度和所述当前患者的肌肉抖动常数计算获得；
    所述当前患者的被消融的正常组织区域通过所述当前患者的消融区域和所述当前患者的病灶区域的差值表征。
  6. 根据权利要求5所述的系统，其特征在于，所述优化策略通过代价函数表征，所述代价函数用C表示，代价函数的表达式为：
    C＝w*F(τ)+(1-w)*A e(τ,ε)
    其中，τ为相对脉冲宽度，ε为相对场强；w为权重系数，其取值范围为0<w<1；F(τ)代表所述当前患者的肌肉抖动加速度，为相对脉冲宽度τ的函数；A e(τ,ε)代表所述当前患者的消融区域和所述当前患者的病灶区域的差值，为相对脉冲宽度τ和相对场强ε的函数。
  7. 根据权利要求6所述的系统，其特征在于，对应于最小代价函数值的消融参数组合作为所述最优的消融参数组合。
  8. 根据权利要求3所述的系统，其特征在于，所述优化策略包括：在约束条件下，所述当前患者的消融区域的面积最小；
    所述约束条件包括所述当前患者的消融区域覆盖所述当前患者的病灶区域，以及所述当前患者的肌肉抖动在阈值内。
  9. 根据权利要求1所述的系统，其特征在于，还包括：
    预设模块，用于基于针对当前患者的布针方案，预设所述多组消融参数组合。
  10. 根据权利要求3所述的系统，其特征在于，还包括：数据库构建模块，用于构建所述历史患者数据库。
  11. 根据权利要求10所述的系统，其特征在于，所述数据库构建模块构建所述历史患者数据库包括：
    获取在预脉冲场强下并使用预选的消融参数组合时预选电导率比率所对应的仿真电流比，并构建仿真数据库；
    测试所述历史患者在预脉冲场强下并使用所述预选的消融参数组合时的基础电流比；
    基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率；
    在预脉冲场强下，获取所述历史患者的基础肌肉抖动加速度；
    基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数；以及，
    基于所述构建的仿真数据库、所述计算的电导率比率和所述计算的肌肉抖动常数，构建所述历史患者数据库。
  12. 根据权利要求11所述的系统，其特征在于，所述基于所述仿真数据库和所述基础电流比，计算所述历史患者在预脉冲场强下的电导率比率，包括：
    利用n阶多项式以及所述仿真数据库中的所述仿真电流比和所述预选电导率比率，建立电流比与电导率比率之间的函数关系，n为大于等于2的自然数；
    利用所述函数关系和所述历史患者的基础电流比计算所述历史患者在预脉冲场强下的电导率比率。
  13. 根据权利要求11所述的系统，其特征在于，所述基于所述历史患者的基础肌肉抖动加速度，计算所述历史患者的肌肉抖动常数，包括：
    利用公式
    Figure PCTCN2021090042-appb-100001
    计算所述历史患者的肌肉抖动常数
    Figure PCTCN2021090042-appb-100002
    其中，τ为相对脉冲宽度，ε为相对场强，F(τ)’为所述历史患者的肌肉抖动加速度，f(τ)’为所述历史患者的基础肌肉抖动加速度。
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