Semiautomatic PAPNET analysis of proliferating (MiB-1-positive) cells in cervical cytology and histology.
With the event of microwave-antigen retrieval it has become possible to detect proliferating cells (staining positive for MiB-1) in cervical smears containing epithelial fragments and in paraffin sections containing cancerous cervical epithelium. The PAPNET system, using neural network computing, is able to collect from the slides epithelial fragments with positive-staining nuclei. The nuclei in epithelial fragments are semiautomatically quantitated using the PAPNET-digitized images. The parameter PPN (proportion-positive nuclei), in which the nuclear area of the positive nuclei is taken into account, prove to be superior to the proliferation index for distinguishing moderate dysplasia from carcinoma in situ. In repair cells, all four quantitative parameters are close to those of moderate dysplasias, indicating that this method is unfit for distinguishing these two entities. However, we show that MiB-1 staining is valuable for the analysis of "false-negative" and "false-positive" smears, and for quantifying proliferation in sections of carcinoma in situ.
Boon
M E
ME
Leiden Cytology and Pathology Laboratory, Netherlands.
Beck
S
S
Kok
L P
LP
D034961:Antigens, Nuclear; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019394:Ki-67 Antigen; D016571:Neural Networks, Computer; D009687:Nuclear Proteins / Q000032:analysis*; D013194:Staining and Labeling / Q000379:methods*; D014626:Vaginal Smears
D034961:Antigens, Nuclear; D019394:Ki-67 Antigen; D009687:Nuclear Proteins