Evaluation of Erythema Severity in Dermatoscopic Images of Canine Skin: Erythema Index Assessment and Image Sampling Reliability.

Affiliation

Cugmas B(1), Viškere D(1)(2), Štruc E(3), Olivry T(4)(5).
Author information:
(1)Biophotonics laboratory, Institute of Atomic Physics and Spectroscopy, University of Latvia, 19 Raiņa Blvd., LV-1586 Rīga, Latvia.
(2)Faculty of Veterinary Medicine, Latvia University of Life Sciences and Technologies, 8 Kristapa Helmaņa Str., LV-3004 Jelgava, Latvia.
(3)Vetamplify SIA, veterinary services, 57/59-32 Krišjāņa Valdemāra Str., LV-1010 Rīga, Latvia.
(4)Department of Clinical Sciences, College of Veterinary Medicine, NC State University, 1060 William Moore Dr., Raleigh, NC 27607, USA.
(5)Comparative Medicine Institute, NC State University, Raleigh, NC 27606, USA.

Abstract

The regular monitoring of erythema, one of the most important skin lesions in atopic (allergic) dogs, is essential for successful anti-allergic therapy. The smartphone-based dermatoscopy enables a convenient way to acquire quality images of erythematous skin. However, the image sampling to evaluate erythema severity is still done manually, introducing result variability. In this study, we investigated the correlation between the most popular erythema indices (EIs) and dermatologists' erythema perception, and we measured intra- and inter-rater variability of the currently-used manual image-sampling methods (ISMs). We showed that the EIBRG, based on all three RGB (red, green, and blue) channels, performed the best with an average Spearman coefficient of 0.75 and a typical absolute disagreement of less than 14% with the erythema assessed by clinicians. On the other hand, two image-sampling methods, based on either selecting specific pixels or small skin areas, performed similarly well. They achieved high intra- and inter-rater reliability with the intraclass correlation coefficient (ICC) and Krippendorff's alpha well above 0.90. These results indicated that smartphone-based dermatoscopy could be a convenient and precise way to evaluate skin erythema severity. However, better outlined, or even automated ISMs, are likely to improve the intra- and inter-rater reliability in severe erythematous cases.