Radiotherapy of lung cancers: FFF beams improve dose coverage at tumor periphery compromised by electronic disequilibrium

Phys Med Biol. 2018 Sep 28;63(19):195007. doi: 10.1088/1361-6560/aadf7d.

Abstract

The purpose of this work was to investigate radiotherapy underdosing at the periphery of lung tumors, and differences in dose for treatments delivered with flattening filter-free (FFF) beams and with conventional flattened (FF) beams. The true differences between these delivery approaches, as assessed with Monte Carlo simulations, were compared to the apparent differences seen with clinical treatment planning algorithms AAA and Acuros XB. Dose was calculated in a phantom comprised of a chest wall, lung parenchyma, and a spherical tumor (tested diameters: 1, 3, and 5 cm). Three lung densities were considered: 0.26, 0.2, and 0.1 g cm-3, representing normal lung, lung at full inspiration, and emphysematous lung, respectively. The dose was normalized to 50 Gy to the tumor center and delivered with 7 coplanar, unmodulated 6 MV FFF or FF beams. Monte Carlo calculations used EGSnrc and phase space files for the TrueBeam accelerator provided by Varian Medical Systems. Voxel sizes were 0.5 mm for the 1 cm tumor and 1 mm for the larger tumors. AAA and Acuros XB dose calculations were performed in Eclipse with a 2.5 mm dose grid, the resolution normally used clinically. Monte Carlo dose distributions showed that traditional FF beams underdosed the periphery of the tumor by up to ~2 Gy as compared to FFF beams; the latter provided a more uniform dose throughout the tumor. In all cases, the underdosed region was a spherical shell about 5 mm thick around the tumor and extending into the tumor by 2-3 mm. The effect was most pronounced for smaller tumors and lower lung densities. The underdosing observed with conventional FF beams was not captured by the clinical treatment planning systems. We concluded that FFF beams mitigate dose loss at tumor periphery and current clinical practice fails to capture tumor periphery underdosing and possible ways to mitigate it.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Electrons*
  • Humans
  • Lung Neoplasms / radiotherapy*
  • Monte Carlo Method
  • Phantoms, Imaging
  • Radiation Dosage*
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted / methods*