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Neural network-based screening of atypical squamous cells of undetermined significance
C J Dunton1, K van Hoeven, L James
1*Department of Obstetrics and Gynecology and †Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University, Philadelphia, PA.
Objectives:
To determine the usefulness of computerized rescreening for detecting high-grade cervical intraepithelial neoplasia (CIN) in patients with cytological evidence of atypical squamous cells of undertermined significance (ASCUS).
Methods:
One hundred and eight patients with ASCUS cytology who had undergone colposcopy had their Papanicolaou smears reviewed using PAPNET, a neural network-based instrument.
Results:
Twenty (18.5%) of the 108 slides were reclassified to a higher-grade lesion. Analysis showed sensitivity (77.8%), specificity (86.9%), and positive (35%) and negative (97.7%) predictive values for detection of high-grade CIN.
Conclusions:
PAPNET neural network-based rescreening of ASCUS smears identifies patients with high-grade cancer precursors. It may be a triage test for ASCUS cytology.
