GRADING CERVICAL DYSPLASIA WITH AGNORS USING A SEMIAUTOMATED IMAGE-ANALYSIS SYSTEM

Colposcopic biopsies were classified according to previously establish ed criteria by a group of three pathologists interested in cervical pa thology. Ten cases were identified in each of the following five group s: normal, koilocytosis, low grade squamous intraepithelial lesions (C IN 1), high grade squamous intraepithelial lesions (CIN 2) and high gr ade squamous intraepithelial lesions (CIN 3). The Crocker technique wa s used to stain the sections cut 3 mum thick. With this silver stain t he nucleolar organizer regions (NORs) are stained black and referred t o as AgNORs. It has been shown that malignant and premalignant changes in cells produce an increase in AgNORs. In each case eight images wer e captured using a 100x oil-immersion objective and stored in a Datacu be Maxvideo system as 512 x 480 pixels in an 8-bit gray-scale per imag e. The images were processed using the NeoPath field-of-view computer to detect the AgNORs and nuclei by using grayscale mathematical morpho logy algorithms. Color overlays of the AgNORs and nuclei were created using segmentation algorithms. The results show that it is possible to differentiate between low grade squamous intraepithelial lesions (CIN 1) and high grade squamous intraepithelial lesions (CIN 2 and CIN 3) taken together; however, there is no difference between low grade squa mous intraepithelial lesions (CIN 1) and koilocytosis. The results sup port the concept that dysplasia cannot be classified effectively into three grades and that low grade squamous intraepithelial lesions (mild dysplasia [CIN 1]) is indistinguishable from koilocytosis.