Cervical cancer: Automation of Pap test screening.

BACKGROUND: Cervical cancer progresses slowly, increasing the chance of early detection of pre-neoplastic lesions via Pap exam test and subsequently preventing deaths. However, the exam presents both false-negatives and false-positives results. Therefore, automatic methods (AMs) of reading the Pap test have been used to improve the quality control of the exam. We performed a literature review to evaluate the feasibility of implementing AMs in laboratories. METHODS: This work reviewed scientific publications regarding automated cytology from the last 15 years. The terms used were "Papanicolaou test" and "Automated cytology screening" in Portuguese, English, and Spanish, in the three scientific databases (SCIELO, PUBMED, MEDLINE). RESULTS: Of the resulting 787 articles, 34 were selected for a complete review, including three AMs: ThinPrep Imaging System, FocalPoint GS Imaging System and CytoProcessor. In total, 1 317 148 cytopathological slides were evaluated automatically, with 1 308 028 (99.3%) liquid-based cytology slides and 9120 (0.7%) conventional cytology smears. The AM diagnostic performances were statistically equal to or better than those of the manual method. AM use increased the detection of cellular abnormalities and reduced false-negatives. The average sample rejection rate was ≤3.5%. CONCLUSION: AMs are relevant in quality control during the analytical phase of cervical cancer screening. This technology eliminates slide-handling steps and reduces the sample space, allowing professionals to focus on diagnostic interpretation while maintaining high-level care, which can reduce false-negatives. Further studies with conventional cytology are needed. The use of AM is still not so widespread in cytopathology laboratories.

Comparison of ThinPrep Integrated Imager-Assisted Screening versus Manual Screening of ThinPrep Liquid-Based Cytology Specimens.

OBJECTIVE: The aim of this study was to find out whether ThinPrep Integrated Imager (Hologic Inc.) screening is non-inferior to manual screening in the detection of cervical lesion. STUDY DESIGN: For a total of 4,011 ThinPrep Pap test specimens stained by ThinPrep staining, manual screening (Manual arm) and ThinPrep Integrated Imager screening (Imager arm) were performed so as not to be screened by the same cytotechnologist, and the sensitivity and specificity in the detection of cervical lesion were compared using McNemar's test. RESULTS: The sensitivity to detect CIN1 or more squamous cell abnormalities or glandular abnormalities was 91.67% (= 374/408, 95% confidence interval [CI]: 88.44-94.08%) for the Manual arm and 92.40% (= 377/408, 95% CI: 89.28-94.70%) for the Imager arm, and the specificity was 88.87% (= 3,113/3,503, 95% CI: 87.77-89.88%) for the Manual arm and 89.55% (= 3,137/3,503, 95% CI: 88.48-90.54%) for the Imager arm. The differences in sensitivity and in specificity, respectively, were 0.74% (95% CI: -3.14-4.61%, McNemar's test, p = 0.8041) and 0.69% (95% CI: -0.13-1.50%, McNemar's test, p = 0.1125). About the equality of sensitivity and specificity between the 2 methods, 95% CIs of the difference between sensitivity and specificity are in the clinical equivalence range of ±5%, so the Imager arm is non-inferior to the Manual arm. CONCLUSION: The Imager arm was confirmed to have an equivalent and non-inferior capacity in the detection of cervical lesions compared with the Manual arm, suggesting that its practical application in cervical cytology tests is highly possible.

Automated screening of Papanicolaou tests: A review of the literature.

Automated Papanicolaou test screening systems have now been available for over 25 years. Currently two automated screening systems are in widespread clinical use. These are the ThinPrep Imaging System and the FocalPoint GS Imaging System. In their current configurations, both facilitate faster screening by showing a limited number of fields of view (FOV) to cytotechnologists. The FOV are based on the use of proprietary algorithms applied to computerized images of the slide that determine the cells and cell groups with the highest likelihood of abnormality. If all of the FOV are deemed to be negative, the case can be signed out with no additional review; if one or more fields appear possibly abnormal, the entire slide must be manually screened. The United States Food and Drug Administration has ruled that for workload calculation purposes, looking at only the FOV review counts as one-half slide, potentially greatly increasing the number of slides that can be screened. However, follow-up studies of this technology have shown that screening accuracy declines when very large numbers of cases are reviewed per day. Recommendations designed to limit screening volumes to levels that do not jeopardize patient care have therefore been created. The development of fully automated screening that does not rely on human judgment remains an unrealized aspiration. This review covers the history of the development and clinical implementation of automated screening technology with descriptions of the various automated screening systems and their performance as reported in published literature.