TU-G-BRB-02: A New Mathematical Framework for IMRT Inverse Planning with Voxel-Dependent Optimization Parameters

Medical Physics
Masoud ZarepishehS Jiang

Abstract

To establish a new mathematical framework for IMRT treatment optimization with voxel-dependent optimization parameters. In IMRT inverse treatment planning, a physician seeks for a plan to deliver a prescribed dose to the target while sparing the nearby healthy tissues. The conflict between these objectives makes the multi-criteria optimization an appropriate tool. Traditionally, a clinically acceptable plan can be generated by fine-tuning organ-based parameters. We establish a new mathematical framework by using voxel-based parameters for optimization. We introduce three different Pareto surfaces, prove the relationship between those surfaces, and compare voxel-based and organ-based methods. We prove some new theorems providing conditions under which the Pareto optimality is guaranteed. The new mathematical framework has shown that: 1) Using an increasing voxel penalty function with an increasing derivative, in particular the popular power function, it is possible to explore the entire Pareto surface by changing voxel-based weighting factors, which increases the chances of getting more desirable plan. 2) The Pareto optimality is always guaranteed by adjusting voxel-based weighting factors. 3) If the plan is initially produced b...Continue Reading

Citations

Feb 28, 2013·Physics in Medicine and Biology·M ZarepishehY Zinchenko

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