Evaluation of a simple image-based tool to quantify facial erythema in rosacea during treatment
- PMID: 32537843
- PMCID: PMC7754330
- DOI: 10.1111/srt.12878
Evaluation of a simple image-based tool to quantify facial erythema in rosacea during treatment
Abstract
Background: Facial erythema is a common symptom in rosacea. To overcome subjectivity in scoring erythema severity, objective redness quantification is desirable. This study evaluated an image-based erythema quantification tool to monitor facial erythema in rosacea patients during treatment and compared these values to clinical scores.
Materials and methods: Twenty-one rosacea patients were treated with topical ivermectin for 16 weeks. Clinical erythema scores and clinical photographs were taken at week 0, 6, 16 and 28. Using ImageJ, RGB images were split into red, green and blue channels to measure the green/red ratio of lesional skin compared with a green sticker. With CIELAB colour space, a* (indicating colour from green to red) of a lesional and non-lesional facial site was measured, calculating ∆a*. Interobserver concordance and correlation between quantitative and clinical erythema values were determined.
Results: Treatment resulted in reduction of clinical erythema scores. No significant changes in red/green ratios were measured. Lesional a* and ∆a* significantly decreased from baseline to week 16 and 28 (P < .05). A weak correlation existed between clinical scores and lesional a* (Rs = 0.37), and between clinical scores and ∆a* (Rs = 0.30), with a clear trend towards higher a* and ∆a* for higher clinical scores. Interobserver correlation was high (R2 = 0.82).
Conclusion: ImageJ is a simple, rapid, objective and reproducible tool to monitor erythema in rosacea patients during treatment. The photographs allow retrospective analysis, evaluation of large and small lesions, and discrimination of subtle redness differences. We recommend using lesional a* to monitor erythema of inflammatory dermatoses in clinical practice.
Keywords: ImageJ; clinical photography; computer-aided image analysis; erythema; rosacea.
© 2020 The Authors. Skin Research and Technology published by John Wiley & Sons Ltd.
Figures
References
-
- Gallo RL, Granstein RD, Kang S, et al. Standard classification and pathophysiology of rosacea: the 2017 update by the National Rosacea Society Expert Committee. J Am Acad Dermatol. 2018;78:148‐155. - PubMed
-
- Xu DT, Yan JN, Cui Y, et al. Quantifying facial skin erythema more precisely by analyzing color channels of the VISIA red images. J Cosmet Laser Ther. 2016;18:296‐300. - PubMed
-
- Hopkinson D, Moradi Tuchayi S, Alinia H, et al. Assessment of rosacea severity: a review of evaluation methods used in clinical trials. J Am Acad Dermatol. 2015;73(1):138–143.e4. - PubMed
-
- Bamford JT, Gessert CE, Renier CM. Measurement of the severity of rosacea. J Am Acad Dermatol. 2004;51:697‐703. - PubMed
-
- Tan J, Liu H, Leyden JJ, et al. Reliability of clinician erythema assessment grading scale. J Am Acad Dermatol. 2014;71:760‐763. - PubMed
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical
