Ultrastructural discrimination between malignant melanomas and benign nevocytic nevi using high-resolution image and multivariate analyses.

Prompted by the well-known difficulties of reliable and objective histologic differentiation between initial malignant melanoma (MM) and benign nevocytic nevi (NN), ultrastructural high-resolution image and multivariate analyses were evaluated for their diagnostic efficiency. Thirty-seven different features describing morphometry (area, circumference, and shape factor), amount of heterochromatin and euchromatin, chromatin homogeneity, and presence of smaller dark chromatin aggregations were determined by a MICROVAX 3500 computer in each of 1840 intraepidermal melanocytic nuclei of 17 MM and 20 NN. A strategy for the classification of cases based on the identification of markedly atypical melanocytic cells (MACS) was developed. MACS, selected in multivariate analysis with a linear combination of the eight most important features for cell classification, were found in 39.4% of the melanoma cells, but only in 0.3% of nevocytic nevus cells. The presence of MACS allowed a clear differentiation between MM and NN. All cases of MM had more than four MACS, whereas 17 cases of nevocytic nevi were MACS negative, and in each of the remaining three cases only one MAC was present. The percentage of MACS detected within intraepidermal parts of MM by using computerized high-resolution image analysis was found to be a highly efficient diagnostic marker. The new classification strategy has the potential of saving considerable time in subsequent studies, because preselected sampling and the calculation of only a few criteria have proven sufficient for correct classification of malignant melanomas.