Digital/Computational Technology for Molecular Cytology Testing: A Short Technical Note with Literature Review

Author:

Osamura Robert Y.,Matsui Naruaki,Kawashima Masato,Saiga Hiroyasu,Ogura Maki,Kiyuna Tomoharu

Abstract

This short article describes the method of digital cytopathology using Z-stack scanning with or without extended focusing. This technology is suitable to observe such thick clusters as adenocarcinoma on cytologic specimens. Artificial intelligence (AI) has been applied to histological images, but its application on cytologic images is still limited. This article describes our attempt to apply AI technology to cytologic digital images. For molecular analysis, cytologic materials, such as smear, LBC, and cell blocks, have been successfully used for targeted single gene detection and multiplex gene analysis with next-generation sequencing. As a future perspective, the system can be connected to full automation by combining digital cytopathology with AI application to detect target cancer cells and to perform molecular analysis. The literature review is updated according to the subjects.

Publisher

S. Karger AG

Subject

General Medicine,Histology,Pathology and Forensic Medicine

Reference23 articles.

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2. Zarella MD, Bowman D, Aeffner F, Farahani N, Xthona A, Absar SF, et al. A practical guide to whole slide imaging: a white paper from the digital pathology association. Arch Pathol Lab Med. 2019 Feb;143(2):222–34.

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4. Aeffner F, Zarella MD, Buchbinder N, Bui MM, Goodman MR, Hartman DJ, et al. Introduction to digital image analysis in whole-slide imaging: a white paper from the digital pathology association. J Pathol Inform. 2019;10:9.

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