title: Correlation between the signal-to-noise ratio improvement factor (KSNR) and clinical image quality for chest imaging with a computed radiography system.
abstract: This work assessed the appropriateness of the signal-to-noise ratio improvement factor (KSNR) as a metric for the optimisation of computed radiography (CR) of the chest. The results of a previous study in which four experienced image evaluators graded computer simulated chest images using a visual grading analysis scoring (VGAS) scheme to quantify the benefit of using an anti-scatter grid were used for the clinical image quality measurement (number of simulated patients  =  80). The KSNR was used to calculate the improvement in physical image quality measured in a physical chest phantom. KSNR correlation with VGAS was assessed as a function of chest region (lung, spine and diaphragm/retrodiaphragm), and as a function of x-ray tube voltage in a given chest region. The correlation of the latter was determined by the Pearson correlation coefficient. VGAS and KSNR image quality metrics demonstrated no correlation in the lung region but did show correlation in the spine and diaphragm/retrodiaphragmatic regions. However, there was no correlation as a function of tube voltage in any region; a Pearson correlation coefficient (R) of  -0.93 (p  =  0.015) was found for lung, a coefficient (R) of  -0.95 (p  =  0.46) was found for spine, and a coefficient (R) of  -0.85 (p  =  0.015) was found for diaphragm. All demonstrate strong negative correlations indicating conflicting results, i.e. KSNR increases with tube voltage but VGAS decreases. Medical physicists should use the KSNR metric with caution when assessing any potential improvement in clinical chest image quality when introducing an anti-scatter grid for CR imaging, especially in the lung region. This metric may also be a limited descriptor of clinical chest image quality as a function of tube voltage when a grid is used routinely.
authors.affiliation: Radiation Physics Department, Queen's Centre for Oncology and Haematology, Castle Hill Hospital, Hull & East Yorkshire Hospitals NHS Trust, Castle Road, Hull, HU16 5JQ, UK. Faculty of Science and Engineering, University of Hull, Cottingham Road, Hull, HU6 7RX, UK.
authors.forename: C S
authors.initials: CS
authors.lastname: Moore
authors.forename: T J
authors.initials: TJ
authors.lastname: Wood
authors.forename: J R
authors.initials: JR
authors.lastname: Saunderson
authors.forename: A W
authors.initials: AW
authors.lastname: Beavis
mesh_terms: D000328:Adult; D000465:Algorithms; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods / Q000592:standards*; D013902:Radiography, Thoracic / Q000379:methods / Q000592:standards*; D059629:Signal-To-Noise Ratio; D013131:Spine / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods / Q000592:standards*; D014963:X-Ray Intensifying Screens