title: Laboratory test of an automated cell analysis system for cervical screening.
abstract: An automated cell analysis system (Autoplan-MIAC) for the early detection of precancerous lesions of the cervix was tested under semi-routine conditions in a clinical cytology laboratory. A set of 1500 specimens, highly enriched with abnormal cases, was analysed. Cervical scrapings were collected in suspension and processed by cytocentrifugation for microscopy. Two slides were prepared from each sample: one for staining according to Papanicolaou for the visual reference diagnosis and one for Feulgen staining for automated analysis. The specimens were evaluated in two ways: the first one, which is referred to as the automated machine classification system (AMC), classifies the specimens according to the number and ratio of selected objects (alarms) and is a fully automated system. The second system classifies the specimens after visual evaluation of the stored alarms as they are displayed on a TV monitor, and is designated the interactive machine classification system (IMC). The AMC results showed a false positive rate of 16.5% when the cut-off threshold was selected so that all 117 positively diagnosed specimens were classified 'positive' by the system. In that case 87.4% of the CIN I and 96.9% of the CIN II cases were AMC-positive. The IMC results showed a false positive rate of 2.5%, when 86.3% of the CIN I cases, 96.9% of the CIN II cases and all CIN III and invasive carcinoma cases were positively classified.
authors.affiliation: Department of Obstetrics and Gynaecology, University of Frankfurt/Main, Germany.
authors.forename: R
authors.initials: R
authors.lastname: Strohmeier
authors.forename: H
authors.initials: H
authors.lastname: Naujoks
authors.forename: A M
authors.initials: AM
authors.lastname: van Driel-Kulker
authors.forename: J S
authors.initials: JS
authors.lastname: Ploem
mesh_terms: D002584:Cervix Uteri / Q000166:cytology*; D003581:Cytodiagnosis / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D013194:Staining and Labeling; D002583:Uterine Cervical Neoplasms / Q000517:prevention & control