title: A two-dimensional deformable phantom for quantitatively verifying deformation algorithms.
abstract: OBJECTIVE
  The incorporation of deformable image registration into the treatment planning process is rapidly advancing. For this reason, the methods used to verify the underlying deformation algorithms must evolve equally fast. This manuscript proposes a two-dimensional deformable phantom, which can objectively verify the accuracy of deformation algorithms, as the next step for improving these techniques.
  
  
  METHODS
  The phantom represents a single plane of the anatomy for a head and neck patient. Inflation of a balloon catheter inside the phantom simulates tumor growth. CT and camera images of the phantom are acquired before and after its deformation. Nonradiopaque markers reside on the surface of the deformable anatomy and are visible through an acrylic plate, which enables an optical camera to measure their positions; thus, establishing the ground-truth deformation. This measured deformation is directly compared to the predictions of deformation algorithms, using several similarity metrics. The ratio of the number of points with more than a 3 mm deformation error over the number that are deformed by more than 3 mm is used for an error metric to evaluate algorithm accuracy.
  
  
  RESULTS
  An optical method of characterizing deformation has been successfully demonstrated. For the tests of this method, the balloon catheter deforms 32 out of the 54 surface markers by more than 3 mm. Different deformation errors result from the different similarity metrics. The most accurate deformation predictions had an error of 75%.
  
  
  CONCLUSIONS
  The results presented here demonstrate the utility of the phantom for objectively verifying deformation algorithms and determining which is the most accurate. They also indicate that the phantom would benefit from more electron density heterogeneity. The reduction of the deformable anatomy to a two-dimensional system allows for the use of nonradiopaque markers, which do not influence deformation algorithms. This is the fundamental advantage of this verification technique.
authors.affiliation: Department of Radiation Oncology, University of California San Francisco, San Francisco, California 94143-1708, USA.
authors.forename: Neil
authors.initials: N
authors.lastname: Kirby
authors.forename: Cynthia
authors.initials: C
authors.lastname: Chuang
authors.forename: Jean
authors.initials: J
authors.lastname: Pouliot
mesh_terms: D000465:Algorithms; D006258:Head and Neck Neoplasms / Q000532:radiotherapy; D006801:Humans; D019047:Phantoms, Imaging; D011786:Quality Control; D011857:Radiographic Image Interpretation, Computer-Assisted; D011880:Radiotherapy Planning, Computer-Assisted / Q000592:standards / Q000706:statistics & numerical data*; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data