title: Reconstruction of 3D lung models from 2D planning data sets for Hodgkin's lymphoma patients using combined deformable image registration and navigator channels.
abstract: OBJECTIVE
  Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose-risk models could potentially be used to estimate radiotherapy-related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects.
  
  
  METHODS
  Three-dimensional planning CT images of 52 current HL patients were acquired. 12 image sets were used to construct a male and a female population lung model. 23 "Reference" images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient-specific lung geometry using a biomechanical-based DIR algorithm, MORFEUS. 17 "Test" patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges. Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference-adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient.
  
  
  RESULTS
  The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be 89.2 +/- 3.9% (Right lung = 88.8%; Left lung = 89.6%) and 89.3 +/- 2.7% (Right = 88.5%; Left = 90.2%), respectively. Paired T-tests demonstrated that the volumetric reconstruction method made a statistically significant improvement to the population lung model shape (p < 0.05). The error in the results were also comparable to the volume overlap difference observed between inhale and exhale lung volumes during free-breathing respiratory motion (POL: p = 0.43; Dice: p = 0.20), which implies that the accuracies of the reconstruction method are within breathing constraints and would not be the confining factor in estimating normal tissue dose exposure.
  
  
  CONCLUSIONS
  The result findings show that the DIR-NC technique can achieve a high degree of reconstruction accuracy, and could be useful in approximating 3D dosimetric representations of historical 2D treatment. In turn, this could provide a better understanding of the biophysical relationship between dose-volume exposure and late term radiotherapy effects.
authors.affiliation: Radiation Medicine Program, Princess Margaret Hospital, University Health Network, Toronto, Ontario M5G 2M9, Canada.
authors.forename: Angela
authors.initials: A
authors.lastname: Ng
authors.forename: Thao-Nguyen
authors.initials: TN
authors.lastname: Nguyen
authors.forename: Joanne L
authors.initials: JL
authors.lastname: Moseley
authors.forename: David C
authors.initials: DC
authors.lastname: Hodgson
authors.forename: Michael B
authors.initials: MB
authors.lastname: Sharpe
authors.forename: Kristy K
authors.initials: KK
authors.lastname: Brock
mesh_terms: D003198:Computer Simulation; D006689:Hodgkin Disease / Q000000981:diagnostic imaging* / Q000503:physiopathology / Q000532:radiotherapy*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging / Q000503:physiopathology*; D008954:Models, Biological; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods*