A Multi Objective Genetic Algorithm (MOGA) for Optimizing Thermal and Electrical Distribution in Tumor Ablation by Irreversible Electroporation

Background: Irreversible electroporation (IRE) is a novel tumor ablation technique. IRE is associated with high electrical fields and is often reported in conjunction with thermal damage caused by Joule heating. For good response to surgery it is crucial to produce minimum thermal damage in both tumoral and healthy tissues named Non-Thermal Irreversible Electroporation(NTIRE). Non-thermal irreversible electroporation attempts have concentrated on tumor ablation with strong electric field with producing minimum thermal damage.Objective: To establish a Multi Objective Genetic Algorithm (MOGA) for IRE treatment planning.Methods: Numerical modeling and genetic programming were coupled to optimize thermal and electrical distribution in tissue. A 3D MRI based model was established and treatment parameters such as electrode thickness, electrode insertion, distance between electrode and applied voltage were optimized.Results: Prefect tumor ablation with IRE surgery with relatively little electrical and thermal damage on healthy tissue can be achieved by using genetic algorithm optimization. Such optimization can trade off between perfect tumor coverage and damage to healthy tissue. Concerning the thermal aspect of IRE surgery.Conclusion: The established multi-objective genetic algorithm based treatment planning system, can optimize both geometric and electric parameters in IRE surgery. Such optimization result in prefect tumor ablation as well as minimum thermal damage to both normal and tumoral tissue.