Lung IMRT planning with automatic determination of beam angle configurations.

Published online

Journal Article

Beam angle configuration is a major planning decision in intensity modulated radiation treatment (IMRT) that has a significant impact on dose distributions and thus quality of treatment, especially in complex planning cases such as those for lung cancer treatment. We propose a novel method to automatically determine beam configurations that incorporates noncoplanar beams. We then present a completely automated IMRT planning algorithm that combines the proposed method with a previously reported OAR DVH prediction model. Finally, we validate this completely automatic planning algorithm using a set of challenging lung IMRT cases. A beam efficiency index map is constructed to guide the selection of beam angles. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams by introducing a beam-spread term. The effect of the beam-spread term on plan quality was studied systematically and the weight of the term to balance PTV dose conformity against OAR avoidance was determined. For validation, complex lung cases with clinical IMRT plans that required the use of one or more noncoplanar beams were re-planned with the proposed automatic planning algorithm. Important dose metrics for the PTV and OARs in the automatic plans were compared with those of the clinical plans. The results are very encouraging. The PTV dose conformity and homogeneity in the automatic plans improved significantly. And all the dose metrics of the automatic plans, except the lung V5 Gy, were statistically better than or comparable with those of the clinical plans. In conclusion, the automatic planning algorithm can incorporate non-coplanar beam configurations in challenging lung cases and can generate plans efficiently with quality closely approximating that of clinical plans.

Full Text

Duke Authors

Cited Authors

  • Yuan, L; Zhu, W; Ge, Y; Jiang, Y; Sheng, Y; Yin, F-F; Wu, QJ

Published Date

  • July 6, 2018

Published In

Volume / Issue

  • 63 / 13

Start / End Page

  • 135024 -

PubMed ID

  • 29846178

Pubmed Central ID

  • 29846178

Electronic International Standard Serial Number (EISSN)

  • 1361-6560

Digital Object Identifier (DOI)

  • 10.1088/1361-6560/aac8b4

Language

  • eng

Conference Location

  • England