Diagnostic imaging of melanocytic skin tumors

In tissue counter analysis, digital images are dissected into subregions (elements), and the digital information in each element is used for statistical analysis. The aim of this study was to test the applicability of tissue counter analysis and CART (Classification and Regression Tree) to the diagnostic discrimination of benign common nevi and malignant melanoma in dermatopathology.

Two hundred cases each of benign nevi and malignant melanoma were consecutively sampled. CART analyses of background versus tissue elements, cellular versus 'other' tissue elements and benign versus malignant cellular elements were performed. For diagnostic assessment, only the percentage of cellular elements suggestive for malignancy in each case was used.

CART analysis led to a correct classification of 99% of background versus tissue elements, 96% of cellular versus 'other' tissue elements and 79.1% of benign versus malignant cellular elements. When the percentage of cellular elements suggestive for malignancy in each case was evaluated, 29.5 +/- 14% (range 4.1-62.4) 'malignant' elements were found in benign nevi (n = 200), in contrast to 75.9 +/- 13.9% (range 32.8-97.3) in melanoma (n = 200; z =-16.72, p < 0.001). It turned out that a threshold level of 52.51% provides a correct classification of 192 nevi and 186 melanoma out of 200 each (specificity 96%, sensitivity 93%, positive predictive value 95.9%).

Tissue counter analysis combined with CART may be a useful method for diagnostic purposes in histopathology.