Digital cytology part 2: artificial intelligence in cytology: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force

David Kim, Kaitlin E. Sundling, Renu Virk, Michael J. Thrall, Susan Alperstein, Marilyn M. Bui, Heather Chen-Yost, Amber D. Donnelly, Oscar Lin, Xiaoying Liu, Emilio Madrigal, Pamela Michelow, Fernando C. Schmitt, Philippe R. Vielh, Maureen F. Zakowski, Anil V. Parwani, Elizabeth Jenkins, Momin T. Siddiqui, Liron Pantanowitz, Zaibo Li

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations

Abstract

Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported.

Original languageEnglish (US)
Pages (from-to)97-110
Number of pages14
JournalJournal of the American Society of Cytopathology
Volume13
Issue number2
DOIs
StatePublished - Mar 2024

Keywords

  • Artificial intelligence
  • Cytopathology
  • Digital cytology
  • Recommendation
  • Validation
  • Whole slide image

ASJC Scopus subject areas

  • Pathology and Forensic Medicine

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