IAGA Based Spot Scanning Path Optimization for Intensity Modulated Proton Therapy

The objective of this research is to study and develop a proton spot scanning path optimization method using an improved genetic algorithm for proton therapy and to evaluate the scanning time under clinical conditions. An Improved Adaptive Genetic Algorithm (IAGA) based scanning path optimization module was developed and integrated into the home-grown treatment planning system. Four cases, including two AAPM TG-119 standard cases and two clinical cases, were selected to compare their scanning path length before and after scanning path optimization. For the two AAPM TG-119 cases, the optimized scanning path length dropped by 27.17% and 18.72%, and for the corresponding clinical cases, the optimized scanning path length dropped by 25.36% and 32.95% respectively. The performance of scanning path optimization was affected by the number of zero-weight spots and connected regions in the scanning map. IAGA based scanning path optimization can reduce the total scanning path length in intensity modulated proton therapy and, therefore, can be used in spot rescanning to accommodate organ motion.