Role of morphometry in the cytological differentiation of benign and malignant thyroid lesions.
BACKGROUND
Thyroid nodules represent a common problem, with an estimated prevalence of 4-7%. Although fine needle aspiration cytology (FNAC) has been accepted as a first line diagnostic test, the rate of false negative reports of malignancy is still high. Nuclear morphometry is the measurement of nuclear parameters by image analysis. Image analysis can merge the advantages of morphologic interpretation with those of quantitative data.


OBJECTIVE
To evaluate the nuclear morphometric parameters in fine needle aspirates of thyroid lesions and to study its role in differentiating benign from malignant thyroid lesions.


METHODS
The study included 19 benign and 16 malignant thyroid lesions. Image analysis was performed on Giemsa-stained FNAC slides by Nikon NIS-Elements Advanced Research software (Version 4.00). Nuclear morphometric parameters analyzed included nuclear size, shape, texture, and density parameters.


METHODS
Normally distributed continuous variables were compared using the unpairedt-test for two groups and analysis of variance was used for three or more groups. Tukey or Tamhane's T2 multiple comparison test was used to assess the differences between the individual groups. Categorical variables were analyzed using the chi square test.


CONCLUSIONS
Five out of the six nuclear size parameters as well as all the texture and density parameters studied were significant in distinguishing between benign and malignant thyroid lesions (P< 0.05). Cut-off values were derived to differentiate between benign and malignant cases.
Department of Pathology, Lady Hardinge Medical College, New Delhi, India.
Pallavi
P
Khatri
Department of Pathology, Lady Hardinge Medical College, New Delhi, India.
Monisha
M
Choudhury
Department of Pathology, Lady Hardinge Medical College, New Delhi, India.
Manjula
M
Jain
Department of Surgery, Lady Hardinge Medical College, New Delhi, India.
Shaji
S
Thomas
Fine needle aspiration cytology (FNAC); image analysis; nuclear morphometry; thyroid lesions