Treatment planning optimization based on response-surface modeling of cost function versus multiple constraints

H. H. Liu, Rosen, N. A. Janjan, A. Pollack

Research output: Contribution to journalConference article

Abstract

In treatment planning optimization and inverse planning, a solution is governed by operator-specified objectives and constraints, which are usually in conflict with each other. Currently, the planning process involves manual iterations of testing different combinations of constraints and/or objectives, and evaluating the resulting solutions. In this we are developing a more efficient paradigm to automate this process. The key component of our approach is to model the cost to be optimized as a function of all the competing constraints. Initially we evaluated this technique for optimizing angles and weights of coplanar beams in conformal therapy of pancreas prostate cancer. The minimum tumor dose was maximized with multiple dose-volume constraints for other critical structures. An initial set of constraints was established such that the tumor dose fell within desired limits. Subsequently, each active constraint was changed by a small step and the optimization was rerun to obtain a new solution. Effectively, we sampled the solution space and obtained a database of the optimized solutions for a variety of different constraint values. We then modeled the tumor dose as a multi-variable function of doses to critical structures using a response-surface method. This allowed us to visualize how the constraints competed and affected the tumor dose. Using this information, one can interactively navigate through the solution space and quickly balance among the tumor dose and doses to other structures. This new paradigm focuses on clinical considerations during optimization and improves the efficiency of the treatment planning process.

Original languageEnglish (US)
Pages (from-to)119-122
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
StatePublished - Dec 1 2000
Externally publishedYes
Event22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States
Duration: Jul 23 2000Jul 28 2000

Keywords

  • Inverse planning
  • Response-surface method
  • Treatment plan optimization

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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