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Artificial Intelligence-driven Digital Cytology-based Cervical Cancer Screening: Is the Time Ripe to Adopt This
Ruchika Gupta1, Neeta Kumar2, Shivani Bansal1
1Division of Cytopathology, ICMR-National Institute of Cancer Prevention and Research, I-7, Sector-39, Noida, 201301, India.
Journal of Digital Imaging
|April 7, 2023
Summary
Artificial intelligence (AI) enhances cervical cancer screening objectivity using whole slide imaging (WSI). This review summarizes AI
Area of Science:
- Gynecology
- Pathology
- Medical Imaging
Background:
- Cervical cancer remains a significant public health issue in developing nations, often due to inadequate screening programs.
- Liquid-based cytology (LBC) has improved cervical cytology, but interpretation remains subjective.
- Artificial intelligence (AI) offers objectivity, potentially improving sensitivity and specificity in cervical cancer screening.
Purpose of the Study:
- To review the current progress of AI applications in cervical cytology using whole slide imaging (WSI).
- To identify research gaps and suggest future directions for AI-based cervical cancer screening.
Main Methods:
- Review of recent studies utilizing AI algorithms on WSI images of conventional and LBC cervical smears.
- Analysis of AI performance metrics such as sensitivity, specificity, and accuracy in detecting cervical abnormalities.
Main Results:
- AI algorithms applied to WSI images show varying degrees of success in detecting cervical abnormalities.
- Studies demonstrate AI's potential to introduce objectivity into cervical cytology interpretation.
Conclusions:
- AI, particularly with WSI, presents a promising avenue for more objective and potentially more accurate cervical cancer screening.
- Further research is needed to address current limitations and optimize AI algorithms for widespread clinical adoption.
