On dose distribution comparison

Phys Med Biol. 2006 Feb 21;51(4):759-76. doi: 10.1088/0031-9155/51/4/001. Epub 2006 Jan 25.

Abstract

In radiotherapy practice, one often needs to compare two dose distributions. Especially with the wide clinical implementation of intensity-modulated radiation therapy, software tools for quantitative dose (or fluence) distribution comparison are required for patient-specific quality assurance. Dose distribution comparison is not a trivial task since it has to be performed in both dose and spatial domains in order to be clinically relevant. Each of the existing comparison methods has its own strengths and weaknesses and there is room for improvement. In this work, we developed a general framework for comparing dose distributions. Using a new concept called maximum allowed dose difference (MADD), the comparison in both dose and spatial domains can be performed entirely in the dose domain. Formulae for calculating MADD values for various comparison methods, such as composite analysis and gamma index, have been derived. For convenience in clinical practice, a new measure called normalized dose difference (NDD) has also been proposed, which is the dose difference at a point scaled by the ratio of MADD to the predetermined dose acceptance tolerance. Unlike the simple dose difference test, NDD works in both low and high dose gradient regions because it considers both dose and spatial acceptance tolerances through MADD. The new method has been applied to a test case and a clinical example. It was found that the new method combines the merits of the existing methods (accurate, simple, clinically intuitive and insensitive to dose grid size) and can easily be implemented into any dose/intensity comparison tool.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Algorithms*
  • Body Burden
  • Computer Simulation
  • Models, Biological*
  • Radiometry / methods*
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted / methods*
  • Radiotherapy, Conformal / methods*
  • Relative Biological Effectiveness
  • Reproducibility of Results
  • Sensitivity and Specificity