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.