Image Enhancement Effect on Inter and Intra-Observer Reliability of Nailfold Capillary Assessment Publisher Pubmed



Karbalaie A¹ ; Etehadtavakol M² ; Abtahi F³ ; Fatemi A⁴ ; Emrani Z² ; Erlandsson BE¹ Show Affiliations
Source: Microvascular Research Published:2018

Abstract

Background: Nailfold capillaroscopy (NC) is a diagnostic imaging technique that is used to assess the blood capillary network in the nailfold area. NC is routinely used for patients with microcirculation problems, such as systemic sclerosis and other connective tissue diseases. Experts commonly use subjective evaluation as a reference point in images of nailfold video capillaroscopy, so it is important to reduce the inherent ambiguities in human judgment and diagnosis. Image quality is an important factor that affects measurement error and assessment time of NC images. Objective: In this study, a new image enhancement technique was introduced and evaluated subjectively. Methods: In total, 475 nailfold video capillaroscopy images from 18 healthy subjects and 41 systemic lupus erythematosus patients were used. The images were randomly divided into two sets, one each with 275 and 200. Eight independent observers who were familiar with the capillaroscopy technique participated in this study. The set of 275 images was evaluated by three observers with the forced–choice pairwise comparison method. Elliptic broken line (EBL) was used to count the number of capillaries. The intra- and inter-observer reliability of the original and enhanced images was evaluated on 200 images by five observers. Result: Except for eight images, all observers preferred the enhanced images in the visual quality comparison method. The intra-class correlation coefficient (ICC) of intra- and inter-observer reliability increased from 0.76–0.84 to 0.82–0.89, respectively, when using the enhancement method. Conclusion: By improving the image quality, more capillary details will be visible, and an observer can document more details that may not be visible in the original image and can do so more efficiently. © 2018 Elsevier Inc.