Quantification of the impact of MLC modeling and tissue heterogeneities on dynamic IMRT dose calculations

I. B. Mihaylov, F. A. Lerma, M. Fatyga, J. V. Siebers

Research output: Contribution to journalArticle

13 Scopus citations


This study quantifies the dose prediction errors (DPEs) in dynamic IMRT dose calculations resulting from (a) use of an intensity matrix to estimate the multi-leaf collimator (MLC) modulated photon fluence (DPEIGfluence) instead of an explicit MLC particle transport, and (b) handling of tissue heterogeneities (DPEhetero) by superposition/convolution (SC) and pencil beam (PB) dose calculation algorithms. Monte Carlo (MC) computed doses are used as reference standards. Eighteen head-and-neck dynamic MLC IMRT treatment plans are investigated. DPEs are evaluated via comparing the dose received by 98% of the GTV (GTV D98%), the CTV D95%, the nodal D90%, the cord and the brainstem D02%, the parotid D50%, the parotid mean dose (DMean), and generalized equivalent uniform doses (gEUDs) for the above structures. For the MC-generated intensity grids, DPEIGfluence is within ±2.1% for all targets and critical structures. The SC algorithm DPEhetero is within ±3% for 98.3% of the indices tallied, and within ±3.4% for all of the tallied indices. The PB algorithm DPEhetero is within ±3% for 92% of the tallied indices. Statistical equivalence tests indicate that PB DPEhetero requires a ±3.6% interval to state equivalence with the MC standard, while the intervals are <1.5% for SC DPEhetero and DPEIGfluence. Overall, these results indicate that SC and MC IMRT dose calculations which use MC-derived intensity matrices for fluence prediction do not introduce significant dose errors compared with full Monte Carlo dose computations; however, PB algorithms may result in clinically significant dose deviations.

Original languageEnglish (US)
Pages (from-to)1244-1252
Number of pages9
JournalMedical physics
Issue number4
StatePublished - Jan 1 2007
Externally publishedYes


  • Dose computation
  • Fluence
  • IMRT
  • MLC
  • Monte Carlo
  • Tissue heterogeneities

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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