A Reverse Optimization Algorithm for the Thermoseed Mediated Magnetic Induction Hyperthermia Preoperative Treatment Plan

With a lot of researches focusing on hyperthermia treatment technology, thermoseed mediated magnetic induction hyperthermia (MIH) has the potential to become a clinical intervention for tumor. While, quantitative thermoseed distribution in tumor is a key technical problem for thermoseed mediated MIH treatment plans. In order to solve this problem, a reverse optimization algorithm (ROA) is proposed to use a minimum number of thermoseeds to achieve the desired temperature distribution which meets the treatment needs. An improved simulated annealing algorithm is applied to generate conformal thermoseed distribution with that the tumor achieves irreversible thermal damage and the temperature distribution in normal tissues is controlled in a safe range. Because of the specialty of the thermoseed distribution problem, initial temperature, stop condition, evaluation function, annealing strategy, and specific calculation steps are redefined. Finally, computer simulation was used to model the tumor region and generate the thermoseed implant model as well as the temperature distribution. According to the application in MIH planning system, the feasibility of ROA to solve the problem of thermoseed distribution was verified. This research can promote the application of the magnetic induction hyperthermia computation method to clinical trials, which will improve the safety, efficacy, and accuracy of clinical trials in the future.