Summary
Intensity-modulated radiation therapy (IMRT) is a state-of-the-art technique for administering radiation to cancer patients. The goal of a treatment is to deliver a prescribed amount of radiation to the tumor, while limiting the amount absorbed by the surrounding healthy and critical organs. Planning an IMRT treatment requires determining fluence maps, each consisting of hundreds or more beamlet intensities. Since it is difficult or impossible to deliver a sufficient dose to a tumor without irradiating nearby critical organs, radiation oncologists have developed guidelines to allow tradeoffs by introducing so-called dose-volume constraints (DVCs), which specify a given percentage of volume for each critical organ that can be sacrificed if necessary. Such constraints, however, are of combinatorial nature and pose significant challenges to the fluence map optimization problem.
The purpose of this paper is two-fold. We try to introduce the IMRT fluence map optimization problem to a broad optimization audience, with the hope of attracting more interests in this promising application area. We also propose a geometric approach to the fluence map optimization problem. Contrary to the traditional view, we treat dose distributions as primary independent variables and beamlet intensities as secondary. We present theoretical and preliminary computational results for the proposed approach, while omitting excessive technical details to maintain an expository nature of the paper.
This author’s work was supported in part by DOE/LANL Contract 03891-99-23 and NSF Grant No. DMS-0240058.
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Zhang, Y., Merritt, M. (2006). Fluence Map Optimization in IMRT Cancer Treatment Planning and A Geometric Approach. In: Hager, W.W., Huang, SJ., Pardalos, P.M., Prokopyev, O.A. (eds) Multiscale Optimization Methods and Applications. Nonconvex Optimization and Its Applications, vol 82. Springer, Boston, MA. https://doi.org/10.1007/0-387-29550-X_8
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