Literature DB >> 22351120

American Society of Cytopathology workload recommendations for automated Pap test screening: developed by the productivity and quality assurance in the era of automated screening task force.

Tarik M Elsheikh1, R Marshall Austin, David F Chhieng, Fern S Miller, Ann T Moriarty, Andrew A Renshaw.   

Abstract

Based on current literature and the best available research to date, the current FDA workload limits for automated image-assisted screening, including the ThinPrep Imaging System and the FocalPoint GS, of 100 slides/day (imaged only slides counted as 0.5) are extremely high and may be associated with significant reduction in sensitivity. This task force has proposed six recommendations relating to cytotechnologist (CT) workload in automated image-guided Pap test screening, which have already been endorsed by major pathology professional societies. These evidence-based recommendations, however, pertain only to gynecologic specimens with image-assisted screening, as there is no current available data to justify modifying screening practices regarding non-gynecologic specimens. The proposed recommendations are as follow: 1) CT workday should not include more than 7 hours of Pap test screening in a 24-hr period, and an 8-hr shift day must include at least 2 paid mini-breaks of 15 minutes each and a 30-minute lunch break. 2) Future Studies examining CT workload should use actual hours of screening rather than lesser number of hours extrapolated to 8-hour days. 3) Average laboratory CT workload should NOT exceed 70 slides/day (slides counted per 2010 FDA bulletin). 4) Proportion of imaged slides that undergo full manual review should be at least either 15%, or twice (2×) the epithelial cell abnormality (ECA) rate, whichever is greater. 5) ECA-adjusted workload measure is a promising method for calculating and monitoring CT workload, but further studies of this method are necessary before full endorsement. 6) CT productivity and workload limits are just one aspect of a good quality assurance program in a cytology laboratory, so other quality indicators to assess CT performance are essential.
Copyright © 2012 Wiley Periodicals, Inc.

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Year:  2012        PMID: 22351120     DOI: 10.1002/dc.22817

Source DB:  PubMed          Journal:  Diagn Cytopathol        ISSN: 1097-0339            Impact factor:   1.582


  7 in total

1.  Nanoscale refractive index fluctuations detected via sparse spectral microscopy.

Authors:  John E Chandler; Lusik Cherkezyan; Hariharan Subramanian; Vadim Backman
Journal:  Biomed Opt Express       Date:  2016-02-19       Impact factor: 3.732

2.  High-speed spectral nanocytology for early cancer screening.

Authors:  John E Chandler; Hariharan Subramanian; Charles D Maneval; Craig A White; Richard M Levenson; Vadim Backman
Journal:  J Biomed Opt       Date:  2013-11       Impact factor: 3.170

3.  Point-of-Care Digital Cytology With Artificial Intelligence for Cervical Cancer Screening in a Resource-Limited Setting.

Authors:  Oscar Holmström; Nina Linder; Harrison Kaingu; Ngali Mbuuko; Jumaa Mbete; Felix Kinyua; Sara Törnquist; Martin Muinde; Leena Krogerus; Mikael Lundin; Vinod Diwan; Johan Lundin
Journal:  JAMA Netw Open       Date:  2021-03-01

4.  Performance of A Convolutional Neural Network in Screening Liquid Based Cervical Cytology Smears.

Authors:  Parikshit Sanyal; Sanghita Barui; Prabal Deb; Harish Chander Sharma
Journal:  J Cytol       Date:  2019 Jul-Sep       Impact factor: 1.000

5.  A Deep Learning Model for Cervical Cancer Screening on Liquid-Based Cytology Specimens in Whole Slide Images.

Authors:  Fahdi Kanavati; Naoki Hirose; Takahiro Ishii; Ayaka Fukuda; Shin Ichihara; Masayuki Tsuneki
Journal:  Cancers (Basel)       Date:  2022-02-24       Impact factor: 6.639

Review 6.  A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development.

Authors:  Shiliang Ai; Chen Li; Xiaoyan Li; Tao Jiang; Marcin Grzegorzek; Changhao Sun; Md Mamunur Rahaman; Jinghua Zhang; Yudong Yao; Hong Li
Journal:  Biomed Res Int       Date:  2021-06-26       Impact factor: 3.411

Review 7.  Screening for cervical cancer using automated analysis of PAP-smears.

Authors:  Ewert Bengtsson; Patrik Malm
Journal:  Comput Math Methods Med       Date:  2014-03-20       Impact factor: 2.238

  7 in total

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