Evaluation of CDRAD and TO20 test objects and associated software in digital radiography

Abstract

Adequate reproduction of low contrast image detail is essential for accurate diagnosis in diagnostic radiology. Artinis CDRAD and Leeds Test Object TO20 are commercially available test objects that can be used to test this aspect of imaging performance in digital radiography. Automated analysis software is available for both test objects (CDRAD Analyser and AutoPIA (TO20)). This study evaluated and compared both test objects and software, including their sensitivity to changes in exposure parameters and image processing. Images of the test objects were acquired in scatter and scatter-free environments and analysed using a range of metrics derived from automated analysis, visual assessment and manual contrast-to-noise ratio measurements. The CNR (TO20) and correctly identified holes (%) (CDRAD) were found to be the most sensitive to changes in exposure conditions. The total number of detected discs (TO20) was the least sensitive. None of the image quality metrics was sensitive to a change in image processing. Other methods, such as anthropomorphic phantoms, would therefore be required to evaluate changes in clinical image processing. The results of this investigation help to inform best use of these test objects in routine quality control and image quality benchmarking for optimisation.

Evaluation of Non-Uniform Image Quality Caused by Anode Heel Effect in Digital Radiography Using Mutual Information

“…On the contrary, the nMI metrics were calculated from the image of CSW phantom made of acrylic material and with a suitable size that fits the flat panel detector. A previous study showed that the image quality reflected by the correctly identified holes (%) of the CDRAD phantom was more sensitive to changes in exposure parameters than the number of detected details in a CDR phantom [ 12 ], suggesting that the acrylic material of the CDRAD phantom was sensitive to changes in signal intensity. Similarly, our results demonstrated that the nMI metrics (CSW phantom) were more sensitive to changes in exposure parameters and orientations than the VR metrics (CDR phantom).…”

“…Detective quantum efficiency (DQE), which is a function of MTF, NPS, and system gain, is the most commonly used metric to quantify the overall performance of X-ray imaging systems [ 4 , 5 , 6 ]; however, DQE cannot reflect entire imaging chains, such as image processing and correction [ 7 ]. In contrast, a more practical approach to quantifying overall image quality of a radiograph is to use contrast-detail phantoms [ 8 , 9 , 10 , 11 , 12 ]. Previously, an emerging metric, termed as mutual information (MI), was shown to successfully quantify the overall image quality of a digital radiograph with the use of a linear step-wedge phantom [ 13 , 14 ].…”

Comparison of Non-Uniform Image Quality Caused by Anode Heel Effect between Two Digital Radiographic Systems Using a Circular Step-Wedge Phantom and Mutual Information

“…In contrast, the symmetrically circular fashion of the CSW phantom allowed us to evaluate directional image quality in one acquisition, and thus it can be used to efficiently compare non-uniform image quality between many radiographic systems. Moreover, the acrylic material used in the CSW phantom could more sensitively detect changes in image quality than the CDR phantom [ 12 ].…”

“…However, DQE cannot reflect the entire imaging pipeline, such as image post-processing and corrections [ 7 ]. Although many studies have utilized contrast-detail resolution (CDR) phantoms to quantitatively evaluate the overall image quality of radiographic images [ 8 , 9 , 10 , 11 , 12 ], the asymmetric designs of these phantoms could not evaluate non-uniform image quality caused by the anode heel effect.…”