Division of Cytopathology, ICMR-National Institute of Cancer Prevention and Research, I-7, Sector-39, Noida, 201301, India.
Department of General Pathology, Faculty of Dentistry, Jamia Millia Islamia Central University, New Delhi, India.
J Digit Imaging. 2023 Aug;36(4):1643-1652. doi: 10.1007/s10278-023-00821-0. Epub 2023 Apr 7.
Cervical cancer is still a public health scourge in the developing countries due to the lack of organized screening programs. Though liquid-based cytology methods improved the performance of cervical cytology, the interpretation still suffers from subjectivity. Artificial intelligence (AI) algorithms have offered objectivity leading to better sensitivity and specificity of cervical cancer screening. Whole slide imaging (WSI) that converts a glass slide to a virtual slide provides a new perspective to the application of AI, especially for cervical cytology. In the recent years, there have been a few studies employing various AI algorithms on WSI images of conventional or LBC smears and demonstrating differing sensitivity/specificity or accuracy at detection of abnormalities in cervical smears. Considering the interest in AI-based screening modalities, this well-timed review intends to summarize the progress in this field while highlighting the research gaps and providing future research directions.
宫颈癌仍然是发展中国家的公共卫生灾难,这是由于缺乏有组织的筛查计划。虽然基于液基的细胞学方法提高了宫颈细胞学的性能,但解释仍然存在主观性。人工智能(AI)算法提供了客观性,从而提高了宫颈癌筛查的灵敏度和特异性。全玻片成像(WSI)将玻璃载玻片转换为虚拟载玻片,为 AI 的应用提供了新的视角,特别是在宫颈细胞学方面。近年来,已经有一些研究在传统或 LBC 涂片的 WSI 图像上使用各种 AI 算法,并证明在检测宫颈涂片异常方面具有不同的灵敏度/特异性或准确性。考虑到对基于人工智能的筛查方式的兴趣,这篇适时的综述旨在总结该领域的进展,同时突出研究差距并提供未来的研究方向。