WO2021128890A1 - Système de prédiction de zone d'ablation par impulsions électriques - Google Patents
Système de prédiction de zone d'ablation par impulsions électriques Download PDFInfo
- Publication number
- WO2021128890A1 WO2021128890A1 PCT/CN2020/110558 CN2020110558W WO2021128890A1 WO 2021128890 A1 WO2021128890 A1 WO 2021128890A1 CN 2020110558 W CN2020110558 W CN 2020110558W WO 2021128890 A1 WO2021128890 A1 WO 2021128890A1
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- WIPO (PCT)
- Prior art keywords
- electric field
- field intensity
- pulse
- ablation
- ablation area
- Prior art date
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- 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
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- 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
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- 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
- A61B2018/00827—Current
-
- 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
- A61B2018/00892—Voltage
-
- 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
- A61B2018/00898—Alarms or notifications created in response to an abnormal condition
Definitions
- the target acquisition module is configured to acquire the target electric field intensity contour from the acquired electric field intensity contour set based on the second constraint condition, and the area within the acquired target electric field intensity contour is used as the predicted electric pulse ablation area.
- the variables of the fitting function include fitting variables used to represent the expression of the fitting function, and the fitting variables appear in the expression of the fitting function.
- the variables of the fitting function include conditional variables for selecting the expression of the corresponding fitting function, and the conditional variables do not appear in the expression of the fitting function.
- condition variables of the fitting function include the sub-pulse width and the exposed length of the electrode needle.
- it further includes:
- Fig. 1 shows a functional block diagram of a system for predicting an electric pulse ablation area proposed by an embodiment of the present invention
- 4a and 4b show schematic diagrams of Cassini curves matching electric field intensity contours in the system for predicting the electric pulse ablation area proposed by an embodiment of the present invention
- 5a and 5b show schematic diagrams of the connection of the electric field intensity contours in the system for predicting the electric pulse ablation area proposed by the embodiment of the present invention
- FIG. 10 shows a schematic diagram of the superimposition of predicted electrical pulse ablation areas of multiple treatments in the system for predicting electrical pulse ablation areas proposed by an embodiment of the present invention
- the set acquisition module is configured to acquire a set of electric field intensity contour lines from the electric field intensity database based on the first constraint condition;
- the target acquisition module is configured to acquire the target electric field intensity contour from the acquired electric field intensity contour set based on the second constraint condition, and the area within the acquired target electric field intensity contour is used as the predicted electric pulse ablation area.
- the preset values of each construction parameter in different parameter combinations are not completely the same, and the number of parameter combinations is determined by the number of construction parameters and the number of preset values of each construction parameter. For example, assuming that the number of construction parameters is three, and the number of preset values of the three construction parameters are respectively 2, 3, and 4, then the number of parameter combinations does not exceed 24.
- the field strength distribution parameter set corresponding to the parameter combination is obtained.
- Each field strength distribution parameter in the field strength distribution parameter set represents a field strength contour.
- the field intensity distribution parameter groups corresponding to all parameter combinations in the parameter combination model together constitute the electric field intensity database.
- ⁇ 0 is the tissue conductivity without electrical breakdown (also called initial conductivity)
- ⁇ max is the tissue conductivity at which biological tissue cells undergo complete permeabilization (also called complete electrical breakdown, permeabilization).
- a and B are the coefficients that determine the position and growth rate of the tissue conductivity curve.
- the shape of the field strength contours takes many forms, as shown in Figure 3, so it is necessary to reconstruct the field strength contours.
- the electric field intensity isoline in the electric field intensity isoline set is represented by a Cassini curve or a spline fitting curve.
- the field strength distribution parameter can be represented by (M, N).
- the condition included in the second constraint condition may be a single condition or a combination of multiple conditions.
- the conditions for inclusion may be specific numerical values, or numerical ranges and the like.
- the second constraint condition is related to a treatment plan.
- the second constraint condition includes: the second pulse voltage, the second conductivity ratio of the ablation area, the exposed length of the second electrode needle, and the electrode needle coordinates.
- the preset electric field strength 500V/cm
- the current ratio S can be calculated by using the ratio of the stable resistance when different preset electric field strengths are applied, and the current ratio S is greater than one. For example, if electric pulses with preset electric field strengths of 500V/cm and 1000V/cm are respectively applied, and their respective stable resistances are denoted as R s500 and R s1000 respectively , the current ratio S can be expressed by R s1000 /R s500 .
- the first case the two electrode needles are on the same horizontal line, at this time, the target electric field intensity contour can be drawn according to the target field intensity distribution parameter.
- a "computer-readable medium” can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, device, or device or in combination with these instruction execution systems, devices, or devices.
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- Health & Medical Sciences (AREA)
- Surgery (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biomedical Technology (AREA)
- Otolaryngology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Plasma & Fusion (AREA)
- Physics & Mathematics (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
L'invention concerne un système de prédiction d'une zone d'ablation par impulsions électriques, comprenant : un module d'acquisition défini, utilisé pour acquérir une ligne de contour d'intensité de champ électrique définie à partir d'une base de données d'intensités de champ électrique sur la base d'une première condition de contrainte ; un module d'acquisition de cible, utilisé pour acquérir une ligne de contour d'intensité de champ électrique cible à partir de la ligne de contour d'intensité de champ électrique acquise définie sur la base d'une seconde condition de contrainte, une zone dans la ligne de contour d'intensité de champ électrique cible acquise servant de zone d'ablation par impulsions électriques prédite. Le système de prédiction d'une zone d'ablation par impulsions électriques peut s'adapter à des différences individuelles chez différents patients, et peut prédire rapidement et efficacement une zone d'ablation par impulsions électriques avant le traitement, ce qui est bénéfique pour une répartition avantageuse et efficace des aiguilles pendant le traitement, assure le bon déroulement d'un plan de traitement, assure au maximum un effet de traitement, et réduit l'ablation et l'endommagement du tissu normal.
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CN202010302357.0A CN111529052B (zh) | 2020-04-16 | 2020-04-16 | 一种预测电脉冲消融区域的系统 |
CN202010302357.0 | 2020-04-16 |
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WO2021128890A1 true WO2021128890A1 (fr) | 2021-07-01 |
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PCT/CN2020/110558 WO2021128890A1 (fr) | 2020-04-16 | 2020-08-21 | Système de prédiction de zone d'ablation par impulsions électriques |
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CN (1) | CN111529052B (fr) |
WO (1) | WO2021128890A1 (fr) |
Families Citing this family (10)
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CN111529052B (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 |
CN112489741B (zh) * | 2020-11-13 | 2021-11-05 | 上海睿刀医疗科技有限公司 | 一种脉冲电场消融参数优化系统 |
CN112315579B (zh) * | 2020-11-25 | 2021-07-02 | 上海睿刀医疗科技有限公司 | 一种基于病灶区域的电极针布针装置及方法 |
CN114869455A (zh) * | 2021-05-27 | 2022-08-09 | 上海商阳医疗科技有限公司 | 脉冲消融参数的获取方法、系统、电子设备和存储介质 |
CN113380394B (zh) * | 2021-06-18 | 2022-04-12 | 上海睿刀医疗科技有限公司 | 确定电极针消融边界的方法、装置、电子设备及存储介质 |
CN113436744B (zh) * | 2021-07-01 | 2024-05-14 | 上海诺生医疗科技有限公司 | 用于预测消融电压值的方法及装置 |
CN113506633B (zh) * | 2021-07-01 | 2024-05-14 | 上海诺生医疗科技有限公司 | 用于预测消融电压值的方法及装置 |
CN113705807B (zh) * | 2021-08-26 | 2022-06-10 | 上海睿刀医疗科技有限公司 | 神经网络的训练装置及方法,消融布针规划装置及方法 |
CN114469309B (zh) * | 2022-02-16 | 2022-10-21 | 上海睿刀医疗科技有限公司 | 一种消融装置、电极针布设策略获得方法、电子设备和存储介质 |
CN115385423B (zh) * | 2022-08-22 | 2023-09-29 | 华中科技大学 | 一种利用脉冲电场防治固着生物污损的系统设计方法 |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102421386A (zh) * | 2009-03-31 | 2012-04-18 | 安吉戴尼克公司 | 用于估计医疗装置的治疗区和互动式地计划患者治疗的系统和方法 |
US20130345697A1 (en) * | 2008-04-29 | 2013-12-26 | Virginia Tech Intellectual Properties, Inc. | System and method for estimating a treatment volume for administering electrical-energy based therapies |
US20180140832A1 (en) * | 2016-11-21 | 2018-05-24 | Covidien Lp | Electroporation catheter |
CN110464454A (zh) * | 2019-07-12 | 2019-11-19 | 华科精准(北京)医疗科技有限公司 | 磁共振引导的激光热疗系统 |
CN111529052A (zh) * | 2020-04-16 | 2020-08-14 | 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 |
CN111529051A (zh) * | 2020-04-16 | 2020-08-14 | 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 |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11272979B2 (en) * | 2008-04-29 | 2022-03-15 | Virginia Tech Intellectual Properties, Inc. | System and method for estimating tissue heating of a target ablation zone for electrical-energy based therapies |
CN112807074A (zh) * | 2014-05-12 | 2021-05-18 | 弗吉尼亚暨州立大学知识产权公司 | 电穿孔系统 |
WO2018092071A1 (fr) * | 2016-11-16 | 2018-05-24 | Navix International Limited | Estimateurs d'efficacité d'ablation |
EP3378426A1 (fr) * | 2017-03-20 | 2018-09-26 | Koninklijke Philips N.V. | Localisation de tissus enlevés à l'aide de la tomographie de propriétés électriques |
JP6853145B2 (ja) * | 2017-08-29 | 2021-03-31 | 日本ライフライン株式会社 | アブレーションシステム |
CN109157280A (zh) * | 2018-08-10 | 2019-01-08 | 重庆大学 | 不可逆电穿孔组织消融效果动态实时评估设备 |
CN110432977A (zh) * | 2019-08-07 | 2019-11-12 | 杭州睿笛生物科技有限公司 | 一种电脉冲消融设备以及适用其仿真方法 |
-
2020
- 2020-04-16 CN CN202010302357.0A patent/CN111529052B/zh active Active
- 2020-08-21 WO PCT/CN2020/110558 patent/WO2021128890A1/fr active Application Filing
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130345697A1 (en) * | 2008-04-29 | 2013-12-26 | Virginia Tech Intellectual Properties, Inc. | System and method for estimating a treatment volume for administering electrical-energy based therapies |
CN102421386A (zh) * | 2009-03-31 | 2012-04-18 | 安吉戴尼克公司 | 用于估计医疗装置的治疗区和互动式地计划患者治疗的系统和方法 |
US20180140832A1 (en) * | 2016-11-21 | 2018-05-24 | Covidien Lp | Electroporation catheter |
CN110464454A (zh) * | 2019-07-12 | 2019-11-19 | 华科精准(北京)医疗科技有限公司 | 磁共振引导的激光热疗系统 |
CN111529052A (zh) * | 2020-04-16 | 2020-08-14 | 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 |
CN111529051A (zh) * | 2020-04-16 | 2020-08-14 | 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 |
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