A tumor irreversible electroporation ablation procedure parameter optimization system

By optimizing the parameters of irreversible electroporation ablation surgery for tumors using the NSGA-II algorithm, the problem of preoperative parameter setting relying on physician experience was solved, achieving precision and safety in tumor ablation, and reducing damage to normal tissues and the number of pulses.

CN119623281BActive Publication Date: 2025-12-09NORTHWEST UNIV
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Patent Information

Application Number
CN202411713822.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-11-27
Publication Date
2025-12-09
Estimated Expiration
2044-11-27

AI Technical Summary

Technical Problem

In current tumor ablation surgeries, the preoperative surgical parameters are set based on the doctor's subjective experience, which makes it difficult to achieve the goal of maximizing tumor tissue killing and minimizing damage to normal tissue, and there is a risk of incomplete ablation or damage to normal tissue.

Method used

The NSGA-II algorithm in the genetic algorithm is used to optimize surgical parameters. Combined with threshold setting, the surgical parameters of irreversible electroporation ablation of tumor, including electrode parameters and pulse parameters, are optimized. The optimal combination of surgical parameters is generated through non-dominated sorting, crossover and mutation operations.

Benefits of technology

It assists doctors in developing optimal surgical parameter plans to maximize tumor tissue killing, minimize damage to normal tissue, reduce the number of pulses, and improve surgical outcomes and safety.

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Abstract

The application discloses a tumor irreversible electroporation ablation operation parameter optimization system, comprising an initialization population module, an individual grade division module, a first generation sub-population generation module, a new population determination module, a new parent population establishment module, a new parent population update module, a merging module and a result selection module. The NSGA-II algorithm in the genetic algorithm is adopted to optimize the operation parameters, and a threshold setting is added. The system can assist doctors in formulating the best operation parameter scheme, so as to achieve the operation target of maximizing killing of tumor tissues, minimizing damage to normal tissues and minimizing the number of pulses.
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