Computational enhancements to fluence map optimization for total marrow irradiation using IMRT

The fluence map optimization (FMO) problem is a core problem in intensity modulated radiation therapy (IMRT) treatment planning. Although it has been studied extensively for site‐specific treatment planning, few studies have examined efficient computational methods for solving it for intensity modulated total marrow irradiation (IM‐TMI) planning; few studies have also looked at exploiting prior beamlet information to solve the FMO problem in a beam orientation optimization context. In this study, we consider different types of line search strategies and different types of warm‐start techniques to improve the speed with which the FMO problem for IM‐TMI is solved and the quality of the end solution. We also consider a parallelism‐enhanced algorithm to solve the FMO problem for IM‐TMI treatment planning with a large number of beams (36 equispaced beams at each of 11 isocenters, for a total of 396 beams). We show that the backtracking line search strategy with step reduction exhibits the best performance and that using either of the two types of warm‐start techniques which we consider leads to significant improvements in both solution time and quality. We also provide results for the aforementioned 396‐beam plan and show that 30‐beam solutions obtained using beam orientation optimization attain a comparable level of quality as this larger solution.