Does software optimization influence the radiologists' perception in low dose paediatric pelvic examinations?. Issue 2 (May 2019)

• Record Type: Journal Article
• Authors: Precht, H.; Waaler, D.; Outzen, C.B.; Brock Thorsen, J.B.; Steen, T.; Hellfritzsch, M.B.; Aagesen, H.; Holst, A.K.; Le, P.; Lindequist, S.; Rasmussen, L.; Tingberg, A.
• Is Part Of: Radiography. Volume 25:Issue 2(2019)
• Page Start: 143
• Page End: 147
• Publication Date: 2019-05
• Subjects: Image quality -- Software optimisation -- Paediatric femur -- Visual Grading Analysis; Diagnostic imaging -- Periodicals; Radiotherapy -- Periodicals; Cancer -- Radiotherapy -- Periodicals; Diagnostic Imaging -- Periodicals; Neoplasms -- Periodicals; Radiotherapy -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Radiothérapie -- Périodiques; Cancer -- Radiothérapie -- Périodiques; Electronic journals; 616.0757
• DOI: 10.1016/j.radi.2018.12.013
• Languages: English
• ISSNs: 1078-8174

Abstract

Abstract: 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. Highlights: Multi-frequency image processing can influence an observer's perception of image quality. Noise reduction was found to be the only processing parameter that could improve image quality. Low dose femur DR examinations can be used diagnostically when software optimization is applied.