Use of dermoscopy by trained users, but not novices, improves diagnostic accuracy for cutaneous melanoma compared with naked eye examination alone.
1 Experts of dermoscopy tend to review a dermoscopic image and reach a diagnosis without use of structured analytical criteria, a diagnostic process that can be referred to as pattern analysis. Multiple simplified dermoscopic algorithms, such as the ABCD rule, the Menzies method, the 7-point checklist, the 3-point checklist, chaos and clues, and CASH (color, architecture, symmetry, and homogeneity), were developed to facilitate a novice’s ability to distinguish melanomas from nevi with high diagnostic accuracy.
2-7 A comparison of these algorithms reveals 2 diverging approaches to simplified melanoma detection (Table 1). The ABCD rule and CASH principally quantify the overall organization of a lesion by assessing features such as symmetry, architectural disorder, border sharpness, and heterogeneity in colors and structures. However, the 7-point checklist relies on the identification of atypical appearances of dermoscopic structures (eg, atypical network) in distinction from otherwise normal counterparts or on identifying unique structures strongly associated with melanoma (eg, regression). Chaos and clues, the Menzies method, and the 3-point checklist include elements of both approaches.