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

Image processing setting adaptions according to image dose and radiologist preference can improve image quality in computed radiography of the equine distal limb: A cadaveric study

Image processing (IP) in digital radiography has been steadily refined to improve image quality. Adaptable settings enable users to adjust systems to their specific requirements. This prospective, analytical study aimed to investigate the influence of different IP settings and dose reductions on image quality. Included were 20 cadaveric equine limb specimens distal to the metacarpophalangeal and metatarsophalangeal joints. Images were processed with the Dynamic Visualization II system (Fujifilm) using five different IP settings including multiobjective frequency processing, flexible noise control (FNC), and virtual grid processing (VGP). Seven criteria were assessed by three veterinary radiology Diplomates and one veterinary radiology resident in a blinded study using a scoring system. Algorithm comparison was performed using an absolute visual grading analysis. The rating of bone structures was improved by VGP at full dose (P < .05; AUCVGC  = 0.45). Überschwinger artifact perception was enhanced by VGP (P < .001; AUCVGC  = 0.66), whereas image noise perception was suppressed by FNC (P < .001; AUCVGC  = 0.29). The ratings of bone structures were improved by FNC at 50% dose (P < .05; AUCVGC  = 0.44), and 25% dose (P < .001; AUCVGC  = 0.32), and clinically acceptable image quality was maintained at 50% dose (mean rating 2.16; 95.8% ratings sufficient or better). The favored IP setting varied among observers, with higher agreement at lower dose levels. These findings supported using individualized IP settings based on the radiologist's preferences and situational image requirements, rather than using default settings.

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.

REDUCING PELVIS RADIOGRAPH EXPOSURE IN CHILDREN USING A DOSE SIMULATION X-RAY RESEARCH SOFTWARE

Pelvis radiography is a frequent X-ray examination. The objective of our study was to determine the minimum dose to be delivered without reducing the quality. We included 60 children having a pelvis X-ray in four groups that were equally represented by weight ranges. A software simulated, for each radiograph, six additional simulated photonic noise images corresponding to 100, 80, 64, 50, 40 and 32% of the initial dose. The 360 radiographs were blindly scored by two radiologists using a semi-quantitative Likert scale. There was no significant difference in scoring between the reference radiograph and simulated radiographs at 80% of the dose in children between 0 and 15 kg and over 35 kg. Inter-observer reproducibility was moderate to very good. Pelvis X-ray doses might be reduced by 20% in children in our institution. Software that produces simulated X-ray with decreasing dose might be a useful tool for an optimization process.

COMPARISON OF CONVENTIONAL HAND EXAMINATION ON SIX OPTIMISED DR SYSTEMS

The purpose of this study was to investigate the challenges in comparing digital radiography (DR) systems from different vendors for various combinations of exposure factors in posterior-anterior hand radiographs. Image quality was evaluated for a range of tube voltages and tube current-time products using a technical contrast-detail (CDRAD) phantom and an anthropomorphic hand phantom. 900 technical CDRAD images were analysed providing quality figures of merit (IQFinv) and two experienced reporting radiographers using visual grading analysis (VGA) scored 108 anthropomorphic images. This study demonstrates the differences between the DR systems included. When compensating for variations in dose, Canon showed superior results for technical image quality and Fuji for visual image quality for a standard dose point at DR hand examination (ln(DAP) 1.1, 50 kV and 2.5 mAs).

Evaluation of the image quality and dose reduction in digital radiography with an advanced spatial noise reduction algorithm in pediatric patients

OBJECTIVES

To evaluate whether the advanced spatial noise reduction (ASNR) algorithm installed in a digital radiography system generates acceptable images at a lower dose than a conventional denoising algorithm in pediatric patients.

METHODS

Nine sets of 30 images of pediatric patients, classified under three protocols and three age groups, were retrospectively selected. Different levels of low-dose image sets of these 270 images were generated by a noise simulation tool after validation testing using phantoms. Each image set was obtained with both the ASNR and conventional algorithm, and grouped randomly and blinded. Three experienced pediatric radiologists were asked to pick the "image with optimum dose" among images of different dose levels with an ALARA (as low as reasonably achievable) perspective. Dose reduction rates for each protocol and age group were calculated, and entrance skin exposure (ESE) was calculated using the values of kVp and mAs, assuming a standard body depth for each age group.

RESULTS

With the ASNR algorithm, estimated dose reduction rates were highest for abdominal radiographs (45.0%, 27.3%, and 24.3% in infants, children, and adolescents, respectively, p < 0.001). The mean dose reductions for all age groups in the abdominal, chest, and skull radiographs were 32.8%, 12.9%, and 23.2%, respectively (p < 0.001). Average of the calculated ESE was lower with the ASNR algorithm than with the conventional algorithm group (p < 0.001).

CONCLUSIONS

The ASNR algorithm facilitated optimization of image quality with a higher reduction in radiation dose than the conventional algorithm, making it more acceptable for use in pediatric patients.

KEY POINTS

•ASNR algorithm in DR system improves image quality via enhanced contrast and noise removal by estimating actual noise distribution based on a multi-scale noise covariance and frequency processing. •Noise simulation tool (NST) generating images of different dose levels can be used for evaluation of the optimum dose without unnecessary additional radiation exposure to pediatric patients. •Retrospective clinical study using NST showed that the ASNR algorithm enabled a higher reduction in radiation dose than the conventional algorithm in pediatric patients.

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.

A Dose Simulation X-Ray Software: An Innovating Tool to Reduce Chest Radiograph Exposure in Children

PURPOSE

Chest radiography is one of the most frequent x-ray examinations performed on children. Reducing the delivered dose is always a major task. The objective of our study was to determine the minimum dose to be delivered while maintaining the image quality of chest radiographs, using dose reduction simulation software.

MATERIALS AND METHODS

We included 60 children who had had a chest radiography in 5 groups established according to the diagnostic reference levels equitably represented by weight ranges. The software simulated for each radiograph 6 additional simulated photonic noise images corresponding to 100%, 80%, 64%, 50%, 40%, and 32% of the initial dose. The 360 radiographs were blindly scored by 2 radiologists, according to the 7 European quality criteria and a subjective criterion of interpretability, using a semiquantitative visual Lickert scale.

RESULTS

There was no significant difference in scoring between the reference radiograph (100%) and simulated radiographs at 80% of the dose in children between 5 and 20 kg, 50% of the dose in children between 20 and 30 kg, and between simulated radiographs at 40% of the dose in children over 30 kg. Interobserver reproducibility was moderate to excellent.

CONCLUSION

Chest radiography dose might be reduced by 20% in children between 5 and 20 kg, 50% in children between 20 and 30 kg, and 60% in children over 30 kg, without any difference in the image quality appreciation. Software that produced simulated x-ray with decreasing delivered dose is an innovating tool for an optimization process.

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.