Applications of Computational Pathology in Head and Neck Cytopathology-Reference-Cited by-同舟云学术

Applications of Computational Pathology in Head and Neck Cytopathology

Published:2021 Issue:4 Volume:65 Page:330-334
ISSN:0001-5547
Container-title:Acta Cytologica
language:en
Short-container-title:Acta Cytologica

Author:

Lollie Trang K.,Krane Jeffrey F.^ORCID

Abstract

Background: The application of computational technology to head and neck cytology material has been explored experimentally in several areas with a variety of potential applications. Summary: This review summarizes the application of these techniques to the diagnosis of thyroid, salivary gland, and other head and neck fine-needle aspiration specimens. Current limitations and potential future applications in diagnosis are discussed along with the possibilities for therapeutic applications of computational methodology. Key Message: Particularly promising applications include resolving diagnostic uncertainty in indeterminate thyroid aspirates and assessing the tumor microenvironment in response to immunotherapy for squamous cell carcinoma.

Publisher

S. Karger AG

Subject

General Medicine,Histology,Pathology and Forensic Medicine

Reference18 articles.

1. Pouliakis A, Karakitsou E, Margari N, Bountris P, Haritou M, Panayiotides J, et al. Artificial neural networks as decision support tools in cytopathology: past, present, and future. Biomed Eng Comput Biol. 2016 Feb 18;7:1–18.

2. Chain K, Legesse T, Heath JE, Staats PN. Digital image-assisted quantitative nuclear analysis improves diagnostic accuracy of thyroid fine-needle aspiration cytology. Cancer Cytopathol. 2019;127(8):501–13.

3. Cochand-Priollet B, Koutroumbas K, Megalopoulou TM, Pouliakis A, Sivolapenko G, Karakitsos P. Discriminating benign from malignant thyroid lesions using artificial intelligence and statistical selection of morphometric features. Oncol Rep. 2006;15(4):1023–6.

4. Sanyal P, Mukherjee T, Barui S, Das A, Gangopadhyay P. Artificial intelligence in cytopathology: a neural network to identify papillary carcinoma on thyroid fine-needle aspiration cytology smears. J Pathol Inform. 2018;9(1):43.

5. Murata S, Mochizuki K, Nakazawa T, Kondo T, Nakamura N, Yamashita H, et al. Morphological abstraction of thyroid tumor cell nuclei using morphometry with factor analysis. Microsc Res Tech. 2003;61(5):457–62.

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