Computer-assisted image analysis of cytological specimens clarify the correlation between nuclear size and intranuclear cytoplasmic inclusions regardless of BRAFV600E mutation in papillary thyroid carcinoma.

ABSTRACT

OBJECTIVE: The morphological features of nuclei in cytological and histological specimens were compared and examined for the presence of BRAFV600E mutation and the appearance rate of intranuclear cytoplasmic inclusions (NI). METHODS: BRAFV600E mutation was identified using a mutation-specific antibody (clone; VE1) in 103 thyroid papillary carcinoma cases at Gunma University Hospital. The nuclear area, perimeter, and roundness of the corresponding cytological specimens and haematoxylin and eosin-stained specimens were analysed using image analysis software, and the appearance rate of NI was calculated and compared. RESULTS: BRAFV600E mutation was detected in 71 (69%) cases. The appearance rate of NI was significantly higher in the BRAFV600E mutation-positive group in cytological and histological specimens (P = .0070 and .0184, respectively). Significant differences were observed between the BRAFV600E mutation-negative and -positive groups in the average nuclear area and average nuclear perimeter in cytological specimens (P = .0137 and .0152, respectively). In addition, nuclear enlargement was correlated with the appearance rate of NI regardless of the presence of BRAFV600E mutation in cytological specimens. In the BRAFV600E mutation-negative group, the nuclear area and perimeter were significantly smaller in the lymph node metastasis-positive cases (P = .0182 and .0260, respectively). CONCLUSION: This study found that the appearance rate of NI was positively correlated with the nuclear area and perimeter and negatively correlated with nuclear roundness in cytological specimens. Furthermore, these results were observed regardless of the existence of BRAFV600E mutation. These results have never been previously reported and clearly demonstrate the usefulness of cytological specimens in computer-assisted image analysis.