Comparison of IMRT optimization based on a pencil beam and a superposition algorithm

Med Phys. 2003 Jul;30(7):1909-13. doi: 10.1118/1.1586452.

Abstract

To investigate the role of sophisticated dose calculation methods for treatment planning, we compared conventional pencil beam optimized 6 and 15 MV intensity-modulated treatment plans with optimizations based on the superposition technique. Five lung and five head and neck IMRT cases with spatial resolutions of bixels and dose voxels usually employed in clinical practice were considered for tumor volumes between 15 and 500 cm3. We investigated the systematic error of the pencil beam algorithm and the pencil beam induced error to the optimal solution of bixel weights. For the lung cases, the pencil beam overestimated the mean dose deposited inside the planning target volume (PTV) by about 8%, for small lung tumors even up to 20.6%. In the head and neck cases only a slight overestimation in mean PTV dose of 1.5% was observed. The optimization with the superposition method substantially improved the dose coverage of the considered radiation targets. Additionally, for the head and neck cases, the brainstem was significantly spared by about 4% mean PTV dose through the use of the superposition technique. Our studies showed that, in target regions with intricate tissue inhomogeneities, superposition or Monte Carlo techniques have to be used for the optimization and the final dose calculation of intensity-modulated treatment plans.

Publication types

  • Comparative Study
  • Evaluation Study
  • Validation Study

MeSH terms

  • Algorithms*
  • Head and Neck Neoplasms / diagnostic imaging*
  • Head and Neck Neoplasms / radiotherapy*
  • Lung Neoplasms / diagnostic imaging*
  • Lung Neoplasms / radiotherapy*
  • Quality Control
  • Radiography
  • Radiometry / methods*
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted / methods*
  • Radiotherapy, Conformal / methods*
  • Reproducibility of Results
  • Scattering, Radiation
  • Sensitivity and Specificity