title: Image cytometry and chemoprevention in cervical cancer.
abstract: Of the approximately 60 million Pap smears performed in the United States in 1995, about 8% or 5 million will show cytology that is "not negative" (ASCUS, AGCUS, LSIL, HSIL, etc.). Possibly 15% or about 0.7 million of these cases will have positive follow-up by repeated Pap smears, colposcopy or biopsy. More than 4 million will be false-positive smears based on the reference standard of biopsy or repeated smears. If no treatment or medical intervention was offered to the 0.7 million cytologically and histologically positive cases, perhaps 20,000 (3%) would develop into invasive cancer. Of the original 5 million cytologically "not negative" cases, fewer than 0.5% have the potential to develop into invasive cancer. While considerable attention has been paid to false-negatives in Pap screening, the above considerations indicate that the cytological and histological criteria for assessing the malignant potential of "not negative" samples might benefit from some refinement. Until such refinement occurs, any chemoprevention studies in cervix face a formidable signal-to-noise problem--worse than 1:30. This paper presents data from quantitative image cytometry of cervical smears for assessing the malignant potential of various "not negative" cases. We have approached this in two ways--by analyzing dysplastic cell nuclei and by analyzing the nuclei of cytologically normal cells growing in the vicinity of the neoplastic lesion. In both cases, nuclear features describing the distribution of the DNA in the cell nuclei (especially texture features) are the discriminating factors. Future research into the objective assessment of malignant potential of "not negative" cases is outlined.
authors: Cancer Imaging Department, British Columbia Cancer Agency, Vancouver, Canada.
authors: B
authors: B
authors: Palcic
authors: D M
authors: DM
authors: Garner
authors: C E
authors: CE
authors: MacAulay
mesh_terms: D018890:Chemoprevention; D002986:Clinical Trials as Topic; D018450:Disease Progression; D005260:Female; D006801:Humans; D019044:Image Cytometry; D065006:Papanicolaou Test; D011237:Predictive Value of Tests; D011336:Probability; D012107:Research Design; D002583:Uterine Cervical Neoplasms / Q000473:pathology* / Q000517:prevention & control*; D014626:Vaginal Smears