Estimation of CT cone-beam geometry using a novel method insensitive to phantom fabrication inaccuracy: Implications for isocenter localization accuracy

J. Chetley Ford, Dandan Zheng, Jeffrey F. Williamson

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


Purpose: Mechanical instabilities that occur during gantry rotation of on-board cone-beam computed tomography (CBCT) imaging systems limit the efficacy of image-guided radiotherapy. Various methods for calibrating the CBCT geometry and correcting errors have been proposed, including some that utilize dedicated fiducial phantoms. The purpose of this work was to investigate the role of phantom fabrication imprecision on the accuracy of a particular CT cone-beam geometry estimate and to test a new method to mitigate errors in beam geometry arising from imperfectly fabricated phantoms. Methods: The authors implemented a fiducial phantom-based beam geometry estimation following the one described by Cho Med Phys 32(4), 968-983 (2005). The algorithm utilizes as input projection images of the phantom at various gantry angles and provides a full nine parameter beam geometry characterization of the source and detector position and detector orientation versus gantry angle. A method was developed for recalculating the beam geometry in a coordinate system with origin at the source trajectory center and aligned with the axis of gantry rotation, thus making the beam geometry estimation independent of the placement of the phantom. A second CBCT scan with the phantom rotated 180 about its long axis was averaged with the first scan to mitigate errors from phantom imprecision. Computer simulations were performed to assess the effect of 2D fiducial marker positional error on the projections due to image discretization, as well as 3D fiducial marker position error due to phantom fabrication imprecision. Experimental CBCT images of a fiducial phantom were obtained and the algorithm used to measure beam geometry for a Varian Trilogy with an on-board CBCT. Results: Both simulations and experimental results reveal large sinusoidal oscillations in the calculated beam geometry parameters with gantry angle due to displacement of the phantom from CBCT isocenter and misalignment with the gantry axis, which are eliminated by recalculating the beam geometry in the source coordinate system. Simulations and experiments also reveal an additional source of oscillations arising from fiducial marker position error due to phantom fabrication imprecision that are mitigated by averaging the results with those of a second CBCT scan with phantom rotated. With a typical fiducial marker position error of 0.020 mm (0.001 in.), source and detector position are found in simulations to be within 250 m of the true values, and detector and gantry angles less than 0.2. Detector offsets are within 100 m of the known value. Experimental results verify the efficacy of the second scan in mitigating beam geometry errors, as well as large apparent source/detector isocenter offsets arising from phantom fabrication imprecision. Conclusions: The authors have developed and validated a novel fiducial phantom-based CBCT beam geometry estimation algorithm that does not require precise positioning of the phantom at machine isocenter and is insensitive to positional imprecision of fiducial markers within the phantom due to fabrication errors. The method can accurately locate source and detector isocenters even when using an imprecise phantom, which is very important for measurement of isocenter coincidence of the therapy and on-board imaging systems.

Original languageEnglish
Pages (from-to)2829-2840
Number of pages12
JournalMedical physics
Issue number6
StatePublished - Jun 2011


  • cone-beam computed tomography
  • fiducial phantom
  • geometric calibration
  • image-guidance
  • isocenter
  • radiation therapy


Dive into the research topics of 'Estimation of CT cone-beam geometry using a novel method insensitive to phantom fabrication inaccuracy: Implications for isocenter localization accuracy'. Together they form a unique fingerprint.

Cite this