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Sci‐Thurs PM: Delivery‐10: Marker trajectory reconstruction using cone‐beam CT projection images
Author(s) -
Becker N,
Kay I
Publication year - 2008
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2965917
Subject(s) - cone beam computed tomography , cone beam ct , projection (relational algebra) , trajectory , iterative reconstruction , medical imaging , nuclear medicine , physics , optics , computed tomography , medicine , computer vision , computer science , radiology , algorithm , astronomy
Image guidance and daily verification is becoming increasingly important in radiotherapy today, especially when dealing with moving targets. Cone‐beam CT (CBCT) is a 3D imaging modality available in the treatment room, but it is difficult to assess motion from this integrated image. If a fiducial marker is placed in a moving target, it can easily be identified in the raw projection images that are captured during the CBCT. Normally, this projection data is discarded after reconstruction, but we show a method that can be used to extract trajectory information from this data. A CBCT was acquired of a moveable phantom with a known motion and an implanted gold seed. During the scan, the phantom underwent 14 cycles of motion. The fiducial marker location was determined from each raw projection image, and the data was separated into individual breathing cycles. Each point in each cycle was then assigned a ‘breath phase’ based temporal position in the cycle. To reconstruct a single 3D position in room coordinates, two nearly orthogonal images at the same ‘breath phase’ but in two different breaths were used. Multiple reconstructions from 14 nearly orthogonal pairs produced points which on average should represent the 4D trajectory. When compared to the true motion, the reconstructed average trajectory had an accuracy of less than 1mm. We have shown that in the ideal case of identical motion in each cycle we can accurately measure the 4D trajectory. Future work will use this tool to collect and estimate the trajectories for more realistic motions which differ from cycle to cycle.