Pilot study of an automated method to determine Melasma Area and Severity Index. (12th May 2015)

• Record Type: Journal Article
• Authors: Tay, E.Y.; Gan, E.Y.; Tan, V.W.D.; Lin, Z.; Liang, Y.; Lin, F.; Wee, S.; Thng, T.G.
• Is Part Of: British journal of dermatology. Volume 172:Number 6(2015:Jun.)
• Page Start: 1535
• Page End: 1540
• Publication Date: 2015-05-12
• Subjects: Dermatology -- Periodicals; Skin -- Diseases -- Periodicals; 616.5
• DOI: 10.1111/bjd.13699
• Languages: English
• ISSNs: 0007-0963

Abstract

Summary: Background: Objective outcome measures for melasma severity are essential for the evaluation of severity as well as results of treatment. The modified Melasma Area and Severity Index (mMASI) score is a validated tool for assessing melasma severity but is often subject to inter‐observer variability. Objectives: To develop and validate a novel image analysis software designed to automatically calculate the area and degree of hyperpigmentation in melasma from computer image analysis of whole‐face digital photographs, thereby deriving an automated mMASI score (aMASI). Methods: The algorithm was developed in collaboration between dermatologists and image analysis experts. Firstly, using an adaptive threshold method, the algorithm identifies, segments and calculates the areas involved. It then calculates the darkness. Finally, the derived area and darkness are then used to calculate mMASI. The scores derived from the algorithm are validated prospectively. Twenty‐nine patients with melasma using depigmenting agents were recruited for validation. Three dermatologists scored mMASI at baseline and post‐treatment using standardized photographs. These scores were compared with aMASI scores derived from computer analysis. Results: aMASI scores correlated well with clinical mMASI pre‐treatment ( r = 0·735, P < 0·001) and post‐treatment ( r = 0·608, P < 0·001). aMASI was reliable in detecting changes with treatment. These changes in aMASI scores correlated well with changes in clinician‐assessed mMASI ( r = 0·622, P < 0·001). Conclusions: This study proposes a novel approach in melasma scoring using digital image analysis. It holds promise as a tool that would enable clinicians worldwide to standardize melasma severity scoring and outcome measures in an easy and reproducible manner, enabling different treatment options to be compared accurately. Abstract : What's already known about this topic? The Melasma Area and Severity Index (MASI) and modified MASI (mMASI) are the only two validated scores for assessing melasma severity. They are essential to the evaluation of treatment response in trials and in the clinical setting. However, MASI and mMASI scoring is subject to much inter‐observer variability and training is necessary to ensure consistent scoring. What does this study add? A novel image analysis software has been developed to derive automated a MASI scores. Automated mMASI scores correlate well with clinician‐scored mMASI scores.