TY - JOUR
T1 - The current state of digital cytology and artificial intelligence (AI)
T2 - global survey results from the American Society of Cytopathology Digital Cytology Task Force
AU - Kim, David
AU - Thrall, Michael J.
AU - Michelow, Pamela
AU - Schmitt, Fernando C.
AU - Vielh, Philippe R.
AU - Siddiqui, Momin T.
AU - Sundling, Kaitlin E.
AU - Virk, Renu
AU - Alperstein, Susan
AU - Bui, Marilyn M.
AU - Chen-Yost, Heather
AU - Donnelly, Amber D.
AU - Lin, Oscar
AU - Liu, Xiaoying
AU - Madrigal, Emilio
AU - Zakowski, Maureen F.
AU - Parwani, Anil V.
AU - Jenkins, Elizabeth
AU - Pantanowitz, Liron
AU - Li, Zaibo
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/9/1
Y1 - 2024/9/1
N2 - Introduction: The integration of whole slide imaging (WSI) and artificial intelligence (AI) with digital cytology has been growing gradually. Therefore, there is a need to evaluate the current state of digital cytology. This study aimed to determine the current landscape of digital cytology via a survey conducted as part of the American Society of Cytopathology (ASC) Digital Cytology White Paper Task Force. Materials and methods: A survey with 43 questions pertaining to the current practices and experiences of WSI and AI in both surgical pathology and cytology was created. The survey was sent to members of the ASC, the International Academy of Cytology (IAC), and the Papanicolaou Society of Cytopathology (PSC). Responses were recorded and analyzed. Results: In total, 327 individuals participated in the survey, spanning a diverse array of practice settings, roles, and experiences around the globe. The majority of responses indicated there was routine scanning of surgical pathology slides (n = 134; 61%) with fewer respondents scanning cytology slides (n = 150; 46%). The primary challenge for surgical WSI is the need for faster scanning and cost minimization, whereas image quality is the top issue for cytology WSI. AI tools are not widely utilized, with only 16% of participants using AI for surgical pathology samples and 13% for cytology practice. Conclusions: Utilization of digital pathology is limited in cytology laboratories as compared to surgical pathology. However, as more laboratories are willing to implement digital cytology in the near future, the establishment of practical clinical guidelines is needed.
AB - Introduction: The integration of whole slide imaging (WSI) and artificial intelligence (AI) with digital cytology has been growing gradually. Therefore, there is a need to evaluate the current state of digital cytology. This study aimed to determine the current landscape of digital cytology via a survey conducted as part of the American Society of Cytopathology (ASC) Digital Cytology White Paper Task Force. Materials and methods: A survey with 43 questions pertaining to the current practices and experiences of WSI and AI in both surgical pathology and cytology was created. The survey was sent to members of the ASC, the International Academy of Cytology (IAC), and the Papanicolaou Society of Cytopathology (PSC). Responses were recorded and analyzed. Results: In total, 327 individuals participated in the survey, spanning a diverse array of practice settings, roles, and experiences around the globe. The majority of responses indicated there was routine scanning of surgical pathology slides (n = 134; 61%) with fewer respondents scanning cytology slides (n = 150; 46%). The primary challenge for surgical WSI is the need for faster scanning and cost minimization, whereas image quality is the top issue for cytology WSI. AI tools are not widely utilized, with only 16% of participants using AI for surgical pathology samples and 13% for cytology practice. Conclusions: Utilization of digital pathology is limited in cytology laboratories as compared to surgical pathology. However, as more laboratories are willing to implement digital cytology in the near future, the establishment of practical clinical guidelines is needed.
KW - Artificial intelligence
KW - Cytology
KW - Digital cytology
KW - Digital pathology
KW - Survey
KW - Whole slide imaging
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U2 - 10.1016/j.jasc.2024.04.003
DO - 10.1016/j.jasc.2024.04.003
M3 - Article
C2 - 38744615
AN - SCOPUS:85192770216
SN - 2213-2945
VL - 13
SP - 319
EP - 328
JO - Journal of the American Society of Cytopathology
JF - Journal of the American Society of Cytopathology
IS - 5
ER -