title: Voxel-based dose reconstruction for total body irradiation with helical tomotherapy.
abstract: OBJECTIVE
  We have developed a megavoltage CT (MVCT)-based dose reconstruction strategy for total body irradiation (TBI) with helical TomoTherapy (HT) using a deformable registration model to account for the patient's interfraction changes. The proposed technique serves as an efficient tool for delivered dose verification and, potentially, plan adaptation.
  
  
  METHODS
  Four patients with acute myelogenous leukemia treated with TBI using HT were selected for this study. The prescription was 12 Gy, 2 Gy/fraction, twice per day, given at least 6 h apart. The original plan achieved coverage of 80% of the clinical target volume (CTV) by the 12 Gy isodose surface. MVCTs were acquired prior to each treatment. Regions of interest were contoured on each MVCT. The dose for each fraction was calculated based on the MVCT using the HT planned adaptive station. B-spline deformable registration was conducted to establish voxel-to-voxel correspondence between the MVCT and the planning CT. The resultant deformation vector was employed to map the reconstructed dose from each fraction to the same point as the plan dose, and a voxel-to-voxel summed dose from all six fractions was obtained. The reconstructed dose distribution and its dosimetric parameters were compared with those of the original treatment plan.
  
  
  RESULTS
  While changes in CTV contours occurred in all patients, the reconstructed dose distribution showed that the dose-volume histogram for CTV coverage was close (<1.5%) to that of the original plan. For sensitive structures, the differences between the reconstructed and the planned doses were less than 3.0%.
  
  
  CONCLUSIONS
  Voxel-based dose reconstruction strategy that takes into account interfraction anatomical changes using MVCTs is a powerful tool for treatment verification of the delivered doses. This proposed technique can also be applied to adaptive TBI therapy using HT.
authors.affiliation: Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205-7199, USA. mchao@uams.edu
authors.forename: Ming
authors.initials: M
authors.lastname: Chao
authors.forename: Jose
authors.initials: J
authors.lastname: Penagaricano
authors.forename: Yulong
authors.initials: Y
authors.lastname: Yan
authors.forename: Eduardo G
authors.initials: EG
authors.lastname: Moros
authors.forename: Peter
authors.initials: P
authors.lastname: Corry
authors.forename: Vaneerat
authors.initials: V
authors.lastname: Ratanatharathorn
mesh_terms: D000465:Algorithms; D019583:Dose Fractionation, Radiation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007668:Kidney / Q000000981:diagnostic imaging; D015470:Leukemia, Myeloid, Acute / Q000000981:diagnostic imaging / Q000532:radiotherapy; D008168:Lung / Q000000981:diagnostic imaging; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies; D036542:Tomography, Spiral Computed / Q000379:methods*; D014916:Whole-Body Irradiation / Q000379:methods*