Optimization of Transpedicular Electrode Insertion for Electroporation-Based Treatments of Vertebral Tumors

SIMPLE SUMMARY: Electroporation has sparked great interest regarding its use in medicine. When planning electroporation-based treatments, the main goal is to determine the best possible electrode position and voltage amplitude that will ensure treatment of the entire target tissue’s volume. However, this process is still mainly performed manually or using computationally intensive genetic algorithms. This study presents an algorithm for optimizing electrode positions based on spatial information of the electric field distribution in the target tissue. The algorithm is currently designed for the electrochemotherapy of vertebral tumors via a transpedicular approach but could be adapted to other anatomic sites in the future. The algorithm performs successfully for different spinal segments, tumor sizes, and locations within the vertebra. Application of the algorithm significantly reduces the time and expertise required to create a treatment plan for the electrochemotherapy of vertebral tumors. ABSTRACT: Electroporation-based treatments such as electrochemotherapy and irreversible electroporation ablation have sparked interest with respect to their use in medicine. Treatment planning involves determining the best possible electrode positions and voltage amplitudes to ensure treatment of the entire clinical target volume (CTV). This process is mainly performed manually or with computationally intensive genetic algorithms. In this study, an algorithm was developed to optimize electrode positions for the electrochemotherapy of vertebral tumors without using computationally intensive methods. The algorithm considers the electric field distribution in the CTV, identifies undertreated areas, and uses this information to iteratively shift the electrodes from their initial positions to cover the entire CTV. The algorithm performs successfully for different spinal segments, tumor sizes, and positions within the vertebra. The average optimization time was 71 s with an average of 4.9 iterations performed. The algorithm significantly reduces the time and expertise required to create a treatment plan for vertebral tumors. This study serves as a proof of concept that electrode positions can be determined (semi-)automatically based on the spatial information of the electric field distribution in the target tissue. The algorithm is currently designed for the electrochemotherapy of vertebral tumors via a transpedicular approach but could be adapted for other anatomic sites in the future.