Impact of image analysis and artificial intelligence in thyroid pathology, with particular reference to cytological aspects

Abstract

Objective Thyroid pathology has great potential for automated/artificial intelligence algorithm application as the incidence of thyroid nodules is increasing and the indeterminate interpretation rate of fine‐needle aspiration remains relatively high. The aim of the study is to review the published literature on automated image analysis and artificial intelligence applications to thyroid pathology with whole‐slide imaging. Methods Systematic search was carried out in electronic databases. Studies dealing with thyroid pathology and use of automated algorithms applied to whole‐slide imaging were included. Quality of studies was assessed with a modified QUADAS‐2 tool. Results Of 919 retrieved articles, 19 were included. The main themes addressed were the comparison of automated assessment of immunohistochemical staining with manual pathologist's assessment, quantification of differences in cellular and nuclear parameters among tumour entities, and discrimination between benign and malignant nodules. Correlation coefficients with manual assessment were higher than 0.76 and diagnostic performance of automated models was comparable with an expert pathologist diagnosis. Computational difficulties were related to the large size of whole‐slide images. Conclusions Overall, the results are promising and it is likely that, with the resolution of technical issues, the application of automated algorithms in thyroid pathology will increase and be adopted following suitable validation studies.

Deep Learning-Based Recognition of Different Thyroid Cancer Categories Using Whole Frozen-Slide Images

“…and mild nuclear atypia (chromatin margins, nuclear membrane irregularities, etc. ), which are confused with malignant lesions; cell enlargement can also be seen locally in benign thyroid tissue ( Girolami et al, 2020 ; Böhland et al, 2021 ). Benign thyroid tissue may also have a background of fibrosis and calcification at the background level, which is common in thyroid cancer.…”

Artificial intelligence and thyroid disease management

“…A third observation is the application of AI for the automation of image analysis with whole-slide imaging ( 14 ). A recent study reported that the coefficients of correlation with manual evaluation were higher than 0.76 and that the diagnosis performance of the AI based robotized models was similar to a specialist pathologist analysis ( 14 ).…”

Thyroid FNA terminology: The case for a single unified international system for thyroid FNA reporting

“…This will be particularly important in the context of clinical trials, evaluations of peer‐reviewed literature, or commercial studies. Examples include development or introduction of new molecular methods, validation of artificial intelligence routines for thyroid nodule assessment using ultrasound and histopathology, eg for assessment of ultrasound characteristics, 36 or morphometry of papillary carcinoma‐type nuclei to ascertain whether a particular lesion is benign or malignant 37 . It will therefore be essential that molecular pathology methods, histopathology terminologies, and cytopathology terminologies are very much aligned so that the clinical results obtained in one part of the world can be extrapolated with ease and utilised in other parts of the world.…”

“…Examples include development or introduction of new molecular methods, validation of artificial intelligence routines for thyroid nodule assessment using ultrasound and histopathology, eg for assessment of ultrasound characteristics, 36 or morphometry of papillary carcinoma-type nuclei to ascertain whether a particular lesion is benign or malignant. 37 It will therefore be essential that molecular pathology methods, histopathology terminologies, and cytopathology terminologies are very much aligned so that the clinical results obtained in one part of the world can be extrapolated with ease and utilised in other parts of the world. In the authors' opinion the recently highlighted issue of the variation in cytopathology results obtained between Eastern and Western cytological practice 6 can be attributed to multidisciplinary treatment differences and diagnostic threshold differences, at least some of which are based on differing care pathways for the management of nodules.…”