Comparison of Cost Function of IMRT Optimization with RTP Research Tool Box (RTB)

  • Ko, Young-Eun (Department of Radiation Oncology, Asan Medical Center, College of Medicine, University of Ulsan) ;
  • Yi, Byong-Yong (Department of Radiation Oncology, Asan Medical Center, College of Medicine, University of Ulsan) ;
  • Lee, Sang-Wook (Department of Radiation Oncology, Asan Medical Center, College of Medicine, University of Ulsan) ;
  • Ahn, Seung-Do (Department of Radiation Oncology, Asan Medical Center, College of Medicine, University of Ulsan) ;
  • Kim, Jong-Hoon (Department of Radiation Oncology, Asan Medical Center, College of Medicine, University of Ulsan) ;
  • Park, Eun-Kyung (Department of Radiation Oncology, Asan Medical Center, College of Medicine, University of Ulsan)
  • Published : 2002.09.01

Abstract

A PC based software, the RTP Research Tool Box (RTB), was developed for IMRT optimization research. The software was consisted of an image module, a beam registration module, a dose calculation module, a dose optimization module and a dose display module. The modules and the Graphical User Interface (GUI) were designed to easily amendable by negotiating the speed of performing tasks. Each module can be easily replaced to new functions for research purpose. IDL 5.5 (RSI, USA) language was used for this software. Five major modules enable one to perform the research on the dose calculation, on the dose optimization and on the objective function. The comparison of three cost functions, such as the uncomplicated tumor control probability (UTCP), the physical objective function and the pseudo-biological objective function, which was designed in this study, were performed with the RTB. The optimizations were compared to the simulated annealing and the gradient search optimization technique for all of the optimization objective functions. No significant differences were found among the objective functions with the dose gradient search technique. But the DVH analysis showed that the pseudo-biological objective function is superior to the physical objective function when with the simulated annealing for the optimization.

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