Patient position verification using CT images.
The use of ions in the radiotherapy of cancer patients requires an accurate patient positioning in order to exploit its potential benefits. Using CT images as the basis for the setup verification offers the advantage of a high in-plane resolution in combination with a geometrically accurate, volumetric information. Before each fraction a single CT slice is acquired at the isocenter level after the positioning procedure. This single slice is registered to the planning CT cube using automated image registration algorithms. Thus any erreonous translation or rotation can be detected and quantified. The registration process involves the interpolation of the volumetric data, the calculation of an energy function, and the minimization of this energy function. Several data interpolation functions as well as minimization algorithms were compared. CT studies with a head phantom were performed in which defined translations and rotations were simulated by moving a motor-driven treatment chair. Different slice thicknesses and anatomical sites were studied to investigate their potential influence on the registration accuracy. The accuracy of the registration was found to be a fraction of a voxel size for suitable combinations of algorithms (typically better than 0.16 mm/deg). A significant dependancy of the registration accuracy on the CT slice thickness and the anatomical site was found (the accuracy ranges from 0.05 mm/deg to 0.16 mm/deg depending on the site). The calculation time is dependant on the used algorithms and the magnitude of the setup error. For the standard combination of algorithms as proposed by the authors (Downhill Simplex minimization with Trilinear interpolation) the typical calculation time is about 20 s for a Sun UltraSPARC processor. Taking into account the mechanical accuracy of the setup device (motor-driven chair) the registration of CT images is thus a useful tool for detecting and quantifying any significant error in the patient position.
Kress
J
J
Department of Radiation Oncology, Deutsches Krebsforschungszentrum, Heidelberg, Germany.
Minohara
S
S
Endo
M
M
Debus
J
J
Kanai
T
T
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D006801:Humans; D009369:Neoplasms / Q000532:radiotherapy; D019047:Phantoms, Imaging; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed