Irreversible electroporation: maximizing treatment efficacy through optimization strategies and robotic assitance

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Irreversible electroporation (IRE) is a non-thermal ablation technique that uses an electric field to destroy tumor cells. The distribution of the electric field within the targeted tissue is critical for successful treatment. Achieving complete ablation requires full coverage of the tumor area by the electric field, which depends on the appropriate configuration of treatment parameters. However, determining the optimal configuration for IRE treatment is challenging due to variations in target tissues.Another significant challenge for clinicians in IRE treatment is electrode placement. Accurate positioning and insertion of needles into the tumor are crucial to ensure complete tumor removal. Multiple needles are required, and they need to be placed in parallel and at equal depth to achieve effective tumor ablation.This thesis proposes the integration of computational models and robotic systems to enhance the effectiveness of IRE treatment. The computational models analyze the effects of pulse parameters and electrode configurations on ablation and thermal damage, aiming to identify the optimal treatment parameters. Model validation has been conducted on animal and vegetable tissue, with detailed discussions provided in Chapters 2 and 3. To improve the accuracy of the models, the actual shape of the tissue should be considered during the simulation process. In Chapter 4, an automatic segmentation method utilizing deep learning is introduced to accurately segment liver and tumors from CT images, offering higher accuracy and faster processing compared to manual segmentation.The thesis also presents two 3D-printed robotic designs actuated by a pneumatic system, suitable for use in MRI scanners. Detailed descriptions and evaluations of the robot performances are provided in Chapters 5 and 6. Both designs demonstrate limited deviation within acceptable ranges for irreversible electroporation procedures. These robotic systems have significant potential to assist clinicians in achieving precise electrode placement in target tissues, ultimately leading to improved treatment outcomes.