Evaluation of three types of reference image data for external beam radiotherapy target localization using digital tomosynthesis (DTS).
Digital tomosynthesis (DTS) is a fast, low-dose three-dimensional (3D) imaging approach which yields slice images with excellent in-plane resolution, though low plane-to-plane resolution. A stack of DTS slices can be reconstructed from a single limited-angle scan, with typical scan angles ranging from 10 degrees to 40 degrees and acquisition times of less than 10 s. The resulting DTS slices show soft tissue contrast approaching that of full cone-beam CT. External beam radiotherapy target localization using DTS requires the registration of on-board DTS images with corresponding reference image data. This study evaluates three types of reference volume: original reference CT, exact reference DTS (RDTS), and a more computationally efficient approximate reference DTS (RDTSapprox), as well as three different DTS scan angles (22 degrees, 44 degrees, and 65 degrees) for the DTS target localization task. Three-dimensional mutual information (MI) shared between reference and onboard DTS volumes was computed in a region surrounding the spine of a chest phantom, as translations spanning +/-5 mm and rotations spanning +/-5 degrees were simulated along each dimension in the reference volumes. The locations of the MI maxima were used as surrogates for registration accuracy, and the width of the MI peaks were used to characterize the registration robustness. The results show that conventional treatment planning CT volumes are inadequate reference volumes for direct registration with on-board DTS data. The efficient RDTSapprox method also appears insufficient for MI-based registration without further refinement of the technique, though it may be suitable for manual registration performed by a human observer. The exact RDTS volumes, on the other hand, delivered a 3D DTS localization accuracy of 0.5 mm and 0.50 along each axis, using only a single 44 degrees coronal on-board DTS scan of the chest phantom.
Godfrey, DJ; Ren, L; Yan, H; Wu, Q; Yoo, S; Oldham, M; Yin, FF
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