Open AccessCBCT image quality QA: Establishing a quantitative program
Author(s) -
Taneja Sameer,
Barbee David L.,
Rea Anthony J.,
Malin Martha
Publication year - 2020
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.13062
Subject(s) - medical physics , computer science , image quality , quality (philosophy) , quality assurance , medicine , computer vision , image (mathematics) , external quality assessment , pathology , philosophy , epistemology
Purpose Routine quality assurance (QA) of cone‐beam computed tomography (CBCT) scans used for image‐guided radiotherapy is prescribed by the American Association of Physicists in Medicine Task Group (TG)‐142 report. For CBCT image quality, TG‐142 recommends using clinically established baseline values as QA tolerances. This work examined how image quality parameters vary both across machines of the same model and across different CBCT techniques. Additionally, this work investigated how image quality values are affected by imager recalibration and repeated exposures during routine QA. Methods Cone‐beam computed tomography scans of the Catphan 604 phantom were taken on four TrueBeam® and one Edge™ linear accelerator using four manufacturer‐provided techniques. TG‐142 image quality parameters were calculated for each CBCT scan using SunCHECK Machine™. The variability of each parameter with machine and technique was evaluated using a two‐way ANOVA test on a dataset consisting of 200 CBCT scans. The impact of imager calibration on image quality parameters was examined for a subset of three machines using an unpaired Student’s t ‐test. The effect of artifacts appearing on CBCTs taken in rapid succession was characterized and an approach to reduce their appearance was evaluated. Additionally, a set of baselines and tolerances for all image quality metrics was presented. Results All imaging parameters except geometric distortion varied with technique ( P < 0.05) and all imaging parameters except slice thickness varied with machine ( P < 0.05). Imager calibration can change the expected value of all imaging parameters, though it does not consistently do so. While changes are statistically significant, they may not be clinically significant. Finally, rapid acquisition of CBCT scans can introduce image artifacts that degrade CBCT uniformity. Conclusions This work characterized the variability of acquired CBCT data across machines and CBCT techniques along with the impact of imager calibration and rapid CBCT acquisition on image quality.