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Precision of a Commercial Automated Quality Control Program for Digital Radiography

C MacLellan*, T Nishino , S Fahrenholtz , H Monsivais , C Willis , UT MD Anderson Cancer Center, Houston, TX


(Wednesday, 8/1/2018) 10:00 AM - 10:30 AM

Room: Exhibit Hall | Forum 8

Purpose: to determine the precision of values reported by an automated quality control product for digital radiography (DR) and assess some sources of uncertainty in the measurements.

Methods: The Quality Assurance Process (QAP) is a commercial product consisting of a 20 cm aluminum flat field phantom, an Image Quality Signature Test (IQST) phantom and software that reports 17 parameters for the GE XQi Revolution DR system. A custom software program retrieved the QAP results remotely from each machine, parsed the files, and stored the data in an SQL database. Data were exported from the SQL database into a csv file for analysis. Parameter values from repetitions of the QAP on each of 8 individual XQi DRs, including configurations with an alternate flat field or IQST phantom, were analyzed using SSPS software to calculate measures of central tendency for each of the 17 parameters. Tukey Post Hoc tests were used to search for homogeneous subsets among the multiple configurations. Confidence intervals for measurement of each parameter were established based on these observations. A ninth XQi system where service had replaced the flat field phantom was included for comparison.

Results: Parameter values for individual units were normally distributed about the mean. The range of parameter values among different units was much greater than that observed for any individual unit even configured with substitute phantoms. The average Coefficient of Variation (COV) ranged from 1.8 to 8% for non-uniformity parameters, 0.2 to 2.9% for MTF, and 3.3 and 9.5% for noise parameters. The magnitude of errors introduced by substituting phantoms was on the order of the COV.

Conclusion: The precision of the QAP parameters is sufficient for clinical quality control purposes. Recognizing the magnitude and differences in COV for each parameter will improve our ability to assess the operational status of DR systems.

Funding Support, Disclosures, and Conflict of Interest: C.W. is a member of the GEMS Medical Advisory Board for X-Ray Products


Quality Control, Radiography, Digital Imaging


IM- X-ray: Quality Control

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