Algorithm to detect in situ melanomas. (1st July 2018)

• Record Type: Journal Article
• Authors: Borsari, S.; Pampena, R.; Benati, E.; Bombonato, C.; Athanassios, K.; Moscarella, E.; Lallas, A.; Argenziano, G.; Pellacani, G.; Longo, C.
• Is Part Of: British journal of dermatology. Volume 179:Number 1(2018)
• Page Start: e63
• Page End: e63
• Publication Date: 2018-07-01
• Subjects: Dermatology -- Periodicals; Skin -- Diseases -- Periodicals; 616.5
• DOI: 10.1111/bjd.16854
• Languages: English
• ISSNs: 0007-0963

Abstract

Summary: In situ melanoma (MIS) is the very early stage of a skin tumour called melanoma. In recent decades, the incidence rate for melanoma has increased by 2.6% per year and MIS is the main diagnosis responsible for this increase. It is important to recognize MIS, since in this phase (called the intraepidermal phase) cancer cells don't have the opportunity to spread anywhere in the body. Since MIS can be challenging to distinguish from benign (harmless) pigmented lesions, such as normal moles, this study, from Reggio Emilia, Italy, looked at two ways of diagnosing skin cancers that are non‐invasive (meaning they don't require any surgery), called reflectance confocal microscopy (RCM) and dermoscopy, to see if their use can help detect intraepidermal melanomas. Dermoscopy is a cheap, 20‐year‐old method used worldwide, in which doctors use a handheld device called a dermatoscope to look at the skin magnified by about ten times, allowing them to see things that would not be visible to the naked eye. RCM is a more recent technique, but not so readily available, that creates a grey‐scale image of a section of the skin, allowing doctors to see abnormalities, magnified by about 500 times. The authors analysed images of 120 MIS and 213 nevi (moles) using dermoscopy and RCM, which allowed them to identify several features related to MIS diagnosis (RCM aspects of intraepidermal melanoma were not yet well‐known). These features were then combined in a multi‐step diagnostic algorithm which is able to aid the physician to decide if a given pigmented lesion is an early melanoma or not (a score ≥2 signifies melanoma) with a very low margin of error. This new diagnostic algorithm, which is easy to apply, could become helpful in doctors' clinics.