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

Abstract

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.