Can advanced edge enhancement software improve image quality to visualise tubes, catheters and wires in digital chest radiographs?

INTRODUCTION: This study aimed to test whether Advanced Edge Enhancement (AEE) software could improve the localisation of tubes, catheters or wires, while also affecting the overall image quality in chest x-rays (CXR). METHODS: In total, 50 retrospective CXRs were included. All images were obtained utilising the Canon X-ray system (CANON/Arcoma Precision T3 DR System, Canon Europe, Amsterdam, NL) with a CXDI-810C wireless detector. A clinical image, plus three additional AEE algorithms were applied using post processing (two intensity variations 1 and 4) on all CXRs totalling 350 different images. Three radiologists evaluated the images using a subjective Absolute Visual Grading Analysis (VGA). The clinical images used in post processing were not applied as reference in the analysis. Each radiologist graded the images separately in a randomized order, with a score of three indicating suitability for diagnostic assessment. RESULTS: The three AEE algorithms contributed to an overall improvement (average 16-49%) in visualisation of tube, catheter or wire on CXR images. The Mann-Whitney U tests showed a statistically significant (p < 0.05) improvement in contrast resolution and sharpness, indicating an increased ability to differentiate tubes, wires or catheters tips from surrounding tissues. For the noise criterion, not applying any AEE algorithm showed a significantly higher homogeneity in soft tissue (p < 0.001), reducing the ability to visualise soft tissue. The high-intensity catheter algorithm was the only algorithm to achieve a statistically significant (p = 0.017) increase in the ability to differentiate pulmonary tissues of similar density. CONCLUSION: An overall improvement in the visualisation of tube, catheter and wire placement was obtained using the three AEE-algorithms. The bone and catheter algorithms showed the highest consistency, with the small structure algorithm underperforming in resolution and low contrast resolution. In general, image noise increased regardless of algorithm type or applied intensity. The AEE-algorithms should therefore be seen as a supplementary tool to the clinical image protocol, while having the potential to improve image quality to specific clinical situations. IMPLICATIONS FOR PRACTICE: AEE filtered images appear to be a supplement to the current practice of using CXRs in the diagnosis in placement of catheters, tubes and wires in the chest region. The use of AEE-algorithms has the potential to improve the daily work in clinical practice, which serves the basis for further investigation of its effect on radiographic practices.

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.

Radiographers' perspectives' on Visual Grading Analysis as a scientific method to evaluate image quality.

INTRODUCTION: Radiographers routinely undertake many initiatives to balance image quality with radiation dose (optimisation). For optimisation studies to be successful image quality needs to be carefully evaluated. Purpose was to 1) discuss the strengths and limitations of a Visual Grading Analysis (VGA) method for image quality evaluation and 2) to outline the method from a radiographer's perspective. METHODS: A possible method for investigating and discussing the relationship between radiographic image quality parameters and the interpretation and perception of X-ray images is the VGA method. VGA has a number of advantages such as being low cost and a detailed image quality assessment, although it is limited to ensure the images convey the relevant clinical information and relate the task based radiography. RESULTS: Comparing the experience of using VGA and Receiver Operating Characteristic (ROC) it is obviously that less papers are published on VGA (Pubmed n=1.384) compared to ROC (Pubmed n=122.686). Hereby the scientific experience of the VGA method is limited compared to the use of ROC. VGA is, however, a much newer method and it is slowly gaining more and more attention. CONCLUSION: The success of VGA requires a number of steps to be completed, such as defining the VGA criteria, choosing the VGA method (absolute or relative), including observers, finding the best image display platforms, training observers and selecting the best statistical method for the study purpose should be thoroughly considered. IMPLICATION FOR PRACTICE: Detailed evaluation of image quality for optimisation studies related to technical definition of image quality.

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.