Journal
MEDICAL PHYSICS
Volume 33, Issue 9, Pages 3399-3407Publisher
WILEY
DOI: 10.1118/1.2335486
Keywords
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Funding
- NCI NIH HHS [1 R01 CA103904-01A1] Funding Source: Medline
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Radiotherapy planning involves inherent tradeoffs: the primary mission, to treat the tumor with a high, uniform dose, is in conflict with normal tissue sparing. We seek to understand these tradeoffs on a case-to-case basis, by computing for each patient a database of Pareto optimal plans. A treatment plan is Pareto optimal if there does not exist another plan which is better in every measurable dimension. The set of all such plans is called the Pareto optimal surface. This article presents an algorithm for computing well distributed points on the (convex) Pareto optimal surface of a multiobjective programming problem. The algorithm is applied to intensity-modulated radiation therapy inverse planning problems, and results of a prostate case and a skull base case are presented, in three and four dimensions, investigating tradeoffs between tumor coverage and critical organ sparing. (c) 2006 American Association of Physicists in Medicine.
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