The impact of temporal inaccuracies on 4DCT image quality.
Accurate delineation of target volumes is one of the critical components contributing to the success of image-guided radiotherapy treatments and several imaging modalities are employed to increase the accuracy in target identification. Four-dimensional (4D) techniques are incorporated into existing radiation imaging techniques like computed tomography (CT) to account for the mobility of the target volumes. However, these methods in some cases introduce further inaccuracies in the target delineation when further quality assurance measures are not implemented. A source of commonly observed inaccuracy is the misidentification of the respiration cycles and resulting respiration phase assignments used in the construction of the 4D patient model. The aim of this work is to emphasize the importance of optimal respiration phase assignment during the 4DCT image acquisition process and to perform a quantitative assessment of the effect of inaccurate phase assignments on the overall image quality. The accuracy of the phase assignment was assessed by comparison with an independent calculation of the respiration phases. Misplaced phase assignments manifest themselves as deformations and artifacts in reconstructed images. These effects are quantified as volumetric discrepancies in the localization of target objects represented by spherical phantoms. Measurements are performed using a fully programmable motion phantom designed and built at Mayo Clinic (Rochester, MN). Implementation of a case based independent check and correction procedure is also demonstrated with emphasis on the use of this procedure in the clinical environment. Review of clinical 4D scans performed in this institution showed discrepancies in the phase assignments in about 40% of the cases when compared to our independent calculations. It is concluded that for improved image reconstruction, an independent check of the sorting procedure should be performed for each clinical 4DCT case.
Mutaf
Y D
YD
Radiation Oncology Department, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905, USA.
Antolak
J A
JA
Brinkmann
D H
DH
D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012119:Respiration; D014057:Tomography, X-Ray Computed