Telecytology for rapid on-site evaluation Journal Article


Authors: Hanna, M. G.; Lin, O.; Sirintrapun, S. J.; Pantanowitz, L.
Article Title: Telecytology for rapid on-site evaluation
Abstract: Telecytology is the method of interpreting cytology material from a distance using digital representation for cytology evaluation. Pioneering efforts have been underway for over a decade to introduce telecytology into clinical practice. The field of telecytology has been evolving and many of the prior technologies are rapidly becoming outdated. With such expansion, the current applications of telecytology are increasing for clinical practice, quality assurance, education, and research. Although the literature for digital telecytology is relatively scant, this highlights the unique challenges in relation to telecytology platforms, use cases, implementation, and validation. Several modes of telecytology exist, including static (store-And-forward), dynamic (live video streaming), robotic microscopy, whole-slide imaging, or hybrid technology. Considerations for telecytology include understanding the people, processes, and technology in considering and deploying a telecytology system. Challenges when implementing telecytology specific for rapid on-site evaluations (ROSE) may include cost analysis and administrative buy-in, workflow assessment, training, and staffing (i.e., cytotechnologists, trainees, cytopathologists), as well as technical difficulties. Each implementation will be dependent on the intended use case and need for adoption. This chapter covers all of the aforementioned aspects of telecytology for ROSE. © 2020 S. Karger AG, Basel.
Journal Title: Monographs in Clinical Cytology
Volume: 25
ISSN: 0077-0809
Publisher: S. Karger AG  
Date Published: 2020-01-01
Start Page: 75
End Page: 83
Language: English
DOI: 10.1159/000496525
PROVIDER: scopus
DOI/URL:
Notes: Chapter 7 in "Modern Techniques in Cytopathology" (ISBN: 978-3-318-06575-6) -- Export Date: 2 March 2020 -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Oscar Lin
    307 Lin
  2. Matthew George Hanna
    101 Hanna