The influence of a novel edge enhancement software on image quality of DR hand images of patients with rheumatoid arthritis.

INTRODUCTION: This study aimed to evaluate the effects of a newly developed Advanced Edge Enhancement software (AEE) (Canon Europe, Amsterdam, NL) on image quality (IQ) of Digital Radiography (DR) hand images focusing on rheumatoid arthritis (RA). METHODS AND MATERIALS: Fifty posterior-anterior hand images with or suspected for RA were collected. For each of the 50 images, six copies were made with each their AEE algorithm settings. A total of 330 images (30 images iterated) were evaluated using relative Visual Grading Analysis (VGA) by three observers and combined into a VGA Score (VGAS). Second, 50 images of a technical Contrast Detail Radiography Phantom (CDRAD) was produced with three different AEE software settings, each at level 1,5 and without the AEE software yielding 350 CDRAD images. All images was analysed by the CDRAD Analyser and included for an objective analysis of the AEE software. RESULTS: The VGA study showed a significant difference in image quality between a standard image and images with AEE software applied. The average VGA score of the AEE software was better than the standard images (interval between 0.2 and 0.9). The AEE algorithms at level 5 scored significantly lower for noise but significantly higher for spatial resolution, sharpness and contrast in the VGA. The CDRAD images showed that all AEE algorithms had a statistically significant improvement for level 1 and deterioration for level 5 compared to the standard image. CONCLUSION: Overall the AEE algorithm: small structure level 1 showed an improvement of all IQ criteria in the VGA and a better technical IQ. IMPLICATIONS FOR PRACTICE: The AEE software ought to be considered as a useful addition to the current software, possibly enabling visualisation of structures currently visible.

Does software optimization influence the radiologists' perception in low dose paediatric pelvic examinations?

PURPOSE: To investigate whether software optimisation can improve an observers' perception of image quality in low dose paediatric pelvic examinations. METHODS: Twenty-five consecutive patients (3-7 years old) were referred for a pelvic digital radiography (DR) examination. They were prospectively enrolled in the study over a 3-month period. Images were taken at 80 kV and 2-4 mAs depending on pelvic thickness (9-15 cm). A small focal spot, 130 cm SID: 10 cm air gap and 1 mm Al and 0.2 mm Cu additional filtration were also utilised. Images were acquired on a Canon DR detector and optimised using five different combinations of the multi-frequency processing software (Canon DR system version NE, Version 7.1 with SPECTRA) to comply with the ALARA principle. Image quality was blindly evaluated using the subjective Visual Grading Analysis (VGA) by five experienced musculoskeletal radiologists, including the evaluation of six anatomical image quality criteria (scored from 1 to 5). RESULTS: Consistently, the VGA results indicated that by using software optimised parameters, image quality was suitable for diagnosis in 48-71% of all images. Based on a VGC analysis all software optimised images did have significant better image quality then the one with just the clinical settings. Noise reduction was the software setting which influenced the image quality the most, area under the curve (AUC) of 0.8172 95%CI 0.7953-0.8375. CONCLUSION: Software optimisation improve the radiologists' perception of image quality and should thus be thoroughly considered within clinical practise. Noise reduction is the software parameter which has the greatest influence.