Digital analyses of nuclear features can help discriminate among non‐invasive follicular thyroid neoplasm with papillary‐like nuclear features, papillary thyroid carcinoma follicular subtype, and follicular carcinoma in cytological specimens

Background As it stands, the diagnosis of non‐invasive follicular thyroid neoplasm with papillary‐like nuclear features (NIFTP) is primarily based on histological analysis. We hypothesised that computerised analysis of nuclear images of cytological specimens could be used to differentiate NIFTP from papillary thyroid carcinoma follicular subtype (PTCFS) and follicular carcinoma (FC), influencing patient management. Methods We employed a retrospective analytical observational study based on nuclear morphometric variables of cytological material from thyroid nodules classified as PTCFS, NIFTP, or FC. Five cases of each entity were analysed. Cytological slides were photographed, and 1170 cells for each entity were analysed digitally. The captured images were evaluated (blindly) using the ImageJ software package. The morphometric evaluation included area, perimeter, width, height, and circularity. Numerical variables were expressed as mean, median, minimum, and maximum (min; max) values. Kruskal‐Wallis and Dunn's tests were used with a 5% significance level. Results Regarding nuclear analysis, all variables differed among the three groups (p