Differences in the Known Cellular Composition of Benign Pigmented Skin Lesions Reflected in Computer-Aided Image Analysis

BACKGROUND: Computer-aided image analysis (CAIA) has been suggested as an effective diagnostic tool for pigmented skin lesions (PSLs), especially melanoma. However, few studies on benign PSLs have been reported. OBJECTIVE: The purpose of this study was to evaluate benign PSLs with our CAIA software and analyze the differences between the parameters of those lesions. METHODS: By using homegrown CAIA software, we analyzed 3 kinds of PSLs-nevus, lentigo, and seborrheic keratosis. The group of seborrheic keratosis was divided into pigmented seborrheic keratosis, sebolentigine, and hyperkeratotic seborrheic keratosis. The CAIA was used to extract the color, as well as the morphological, textural, and topological features from each image. RESULTS: In line with clinical observations, the objective parameters indicated that nevus was dark and round, lentigo was small and bright, and seborrheic keratosis was large and spiky. The surface of nevus showed the highest contrast and correlation. In topological analysis, the concentricity clearly separated melanocytic lesions from seborrheic keratosis. The parameters of pigmented seborrheic keratosis were between those of typical nevus and seborrheic keratosis. CONCLUSION: We confirmed that definite correlations exist between the subjective differentiation by experts' examination and the objective evaluation by using CAIA. We also found that the morphological differences observed in CAIA were greatly influenced by the composition ratios of keratinocytes and melanocytes, which are already known histopathological characteristics of each PSL.

Differentiation of Benign Pigmented Skin Lesions with the Aid of Computer Image Analysis: A Novel Approach

BACKGROUND: The differential diagnosis of common pigmented skin lesions is important in cosmetic dermatology. The computer aided image analysis would be a potent ancillary diagnostic tool when patients are hesitant to undergo a skin biopsy. OBJECTIVE: We investigated the numerical parameters discriminating each pigmented skin lesion from another with statistical significance. METHODS: For each of the five magnified digital images containing clinically diagnosed nevus, lentigo and seborrheic keratosis, a total of 23 parameters describing the morphological, color, texture and topological features were calculated with the aid of a self-developed image analysis software. A novel concept of concentricity was proposed, which represents how closely the color segmentation resembles a concentric circle. RESULTS: Morphologically, seborrheic keratosis was bigger and spikier than nevus and lentigo. The color histogram revealed that nevus was the darkest and had the widest variation in tone. In the aspect of texture, the surface of the nevus showed the highest contrast and correlation. Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis. CONCLUSION: We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.

Differentiation of Benign Pigmented Skin Lesions with the Aid of Computer Image Analysis: A Novel Approach

BACKGROUND: The differential diagnosis of common pigmented skin lesions is important in cosmetic dermatology. The computer aided image analysis would be a potent ancillary diagnostic tool when patients are hesitant to undergo a skin biopsy. OBJECTIVE: We investigated the numerical parameters discriminating each pigmented skin lesion from another with statistical significance. METHODS: For each of the five magnified digital images containing clinically diagnosed nevus, lentigo and seborrheic keratosis, a total of 23 parameters describing the morphological, color, texture and topological features were calculated with the aid of a self-developed image analysis software. A novel concept of concentricity was proposed, which represents how closely the color segmentation resembles a concentric circle. RESULTS: Morphologically, seborrheic keratosis was bigger and spikier than nevus and lentigo. The color histogram revealed that nevus was the darkest and had the widest variation in tone. In the aspect of texture, the surface of the nevus showed the highest contrast and correlation. Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis. CONCLUSION: We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.

A Case of Dowling-Degos Disease on the Vulva

Dowling-Degos disease (DDD) is an autosomal dominant genodermatosis and this disease is a genetically determined disturbance of epidermal proliferation. It is characterized by acquired, slowly progressive pigmented lesions that primarily involve the great skin folds and flexural areas such as the axilla, neck, limb flexures, the inframammary area and the inguinal folds. The vulva is an unusual location for DDD. A 41-year-old woman presented with a 10-year history of multiple, small, reticulated and brownish macules distributed symmetrically on the bilateral external genital regions. We found no other similarly pigmented skin lesions on her body, including the flexural areas. There was no known family history of similar eruptions or pigmentary changes. The histologic examination showed irregular rete ridge elongation with a filiform or antler-like pattern and basilar hyperpigmentation on the tips. Fontana-Masson staining showed increased pigmentation of the rete ridges and the S100 protein staining did not reveal an increased number of melanocytes in the epidermis. From these findings, we diagnosed this lesion as DDD.