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An algorithm for thoracic re-irradiation using biologically effective dose: a common language on how to treat in a “no-treat zone”

Authors
  • Brooks, Eric D.1, 2
  • Wang, Xiaochun3
  • De, Brian1
  • Verma, Vivek4
  • Williamson, Tyler D.3
  • Hunter, Rachel3
  • Mohamed, Abdallah S. R.3
  • Ning, Matthew S.1
  • Zhang, Xiaodong3
  • Chang, Joe Y.1
  • 1 University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, USA , Houston (United States)
  • 2 University of Florida Health Proton Therapy Institute, Jacksonville, FL, USA , Jacksonville (United States)
  • 3 University of Texas MD Anderson Cancer Center, Houston, TX, USA , Houston (United States)
  • 4 Allegheny General Hospital, Pittsburgh, PA, USA , Pittsburgh (United States)
Type
Published Article
Journal
Radiation Oncology
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Jan 06, 2022
Volume
17
Issue
1
Identifiers
DOI: 10.1186/s13014-021-01977-1
Source
Springer Nature
Keywords
Disciplines
  • Clinical Radiation Oncology
License
Green

Abstract

BackgroundRe-irradiation (re-RT) is a technically challenging task for which few standardized approaches exist. This is in part due to the lack of a common platform to assess dose tolerance in relation to toxicity in the re-RT setting. To better address this knowledge gap and provide new tools for studying and developing thresholds for re-RT, we developed a novel algorithm that allows for anatomically accurate three-dimensional mapping of composite biological effective dose (BED) distributions from nominal doses (Gy).MethodsThe algorithm was designed to automatically convert nominal dose from prior treatment plans to corresponding BED value maps (voxel size 2.5 mm3 and α/β of 3 for normal tissue, BED3). Following the conversion of each plan to a BED3 dose distribution, deformable registration was used to create a summed composite re-irradiation BED3 plan for each patient who received two treatments. A proof-of-principle analysis was performed on 38 re-irradiation cases of initial stereotactic ablative radiotherapy (SABR) followed by either re-SABR or chemoradiation for isolated locoregional recurrence of early-stage non-small cell lung cancer.ResultsEvaluation of the algorithm-generated maps revealed appropriate conversion of physical dose to BED at each voxel. Of 14 patients receiving repeat SABR, there was one case each of grade 3 chest wall pain (7%), pneumonitis (7%), and dyspnea (7%). Of 24 patients undergoing repeat fractionated radiotherapy, grade 3 events were limited to two cases each of pneumonitis and dyspnea (8%). Composite BED3 dosimetry for each patient who experienced grade 2–3 events is provided and may help guide development of precise cumulative dose thresholds for organs at risk in the re-RT setting.ConclusionsThis novel algorithm successfully created a voxel-by-voxel composite treatment plan using BED values. This approach may be used to more precisely examine dosimetric predictors of toxicities and to establish more accurate normal tissue constraints for re-irradiation.

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