Computerized nuclear morphometry in the diagnosis of thyroid lesions with predominant follicular pattern

Background: Differential diagnosis of thyroid lesions with predominantly follicular pattern is one of the most common problems in thyroid pathology. Development of more objective and reproducible tools for diagnosis is needed. This work is aimed at studying the role of nuclear morphometry in differential diagnosis of different thyroid lesions having predominant follicular pattern. Material and methods: Semiautomatic image analysis system was used to measure a total of 8 nuclear parameters in 48 thyroid lesions including seven nodular goiter (NG), 14 follicular adenoma (FA), 14 follicular carcinoma (FC) and 13 follicular variant papillary carcinoma (FVPC). Results: The parameters related to nuclear size (area, perimeter, MaxD, MinD, nuclear size) and shape (L/S ratio, Form_AR) were significantly higher in neoplastic group (FA, FC, FVPC) when compared to non-neoplastic group (NG) P<0.05. The perimeter was the most reliable parameter (area under the cure (AUC)=97%) followed by area, MaxD, and size (all have AUC=96%) then form-AR (90%), LS ratio (86%) and the least reliable was Min D (79%). Within the neoplastic group, most parameters related to size and shape of the nuclei was significantly higher in FVPC than in FA and FC (p <= 0.05). Nuclear area and size (AUC 77%) were the most reliable parameters for differentiation between FVPC and FA. The best cut off values for diagnosing FVPC are nuclear area >= 39.9 mu m(2) and nuclear size >= 27.7 mu m(2). However, there was no quantitative difference between FC and FA. Conclusion: Nuclear morphometric parameters may help in the differentiation between neoplastic and non-neoplastic thyroid lesions and between FVPC and follicular neoplasms (FC and FA) but they have no value in the differentiation between FC and FA.