The effect of different lung densities on the accuracy of various radiotherapy dose calculation methods: Implications for tumour coverage

Research output: Contribution to journalArticle


Purpose: To evaluate against Monte-Carlo the performance of various dose calculations algorithms regarding lung turnout coverage in stereotactic body radiotherapy (SBRT) conditions. Materials and methods: Dose distributions in virtual lung phantoms have been calculated using four commercial Treatment Planning System (TPS) algorithms and one Monte Carlo (MC) system (EGSnrc). We compared the performance of the algorithms in calculating the target dose for different degrees of lung inflation. The phantoms had a cubic 'body' and 'lung' and a central 2-cm diameter spherical 'tumour' (the body and turnout have unit density). The lung tissue was assigned five densities (rho(lung)): 0.01, 0.1, 0.2, 0.4 and 1 g/cm(3). Four-field treatment plans were calculated with 6- and 18 MV narrow beams for each value of rho(lung). We considered the Pencil Beam Convolution (PBCEl) and the Analytical Anisotropic Algorithm (AAA(ECl)) from Varian Eclipse and the Pencil Beam Convolution (PBCOMP) and the Collapsed Cone Convolution (CCCOMP) algorithms from Oncentra MasterPlan. Results: When changing rho(lung) from 0.4 to 0.1 g/cm(3), the MC median target dose decreased from 89.2% to 74.9% for 6 MV and from 83.3% to 61.6% for 18 MV (of dose maximum in the homogenous case at both energies), while for both PB algorithms the median target dose was virtually independent of lung density. Conclusions: Both PB algorithms overestimated the target dose, the overestimation increasing as rho(lung) decreased. Concerning target dose, the AAA(ECl) and CCCOMP algorithms appear to be adequate alternatives to MC. (C) 2009 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and oncology 91 (2009) 405-414


  • Lasse Rye Aarup
  • Alan E. Nahum
  • Christina Zacharatou
  • Trine Juhler-Nottrup
  • Tommy Knöös
  • Hakan Nystrom
  • Lena Specht
  • Elinore Wieslander
  • Stine S. Korreman
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging


  • Density variations, PBC, Gating, 4D-CT, CCC, AAA, Monte Carlo, Lung cancer, Radiotherapy
Original languageEnglish
Pages (from-to)405-414
JournalRadiotherapy and Oncology
Issue number3
Publication statusPublished - 2009
Publication categoryResearch