Khatri Pallavi, Choudhury Monisha, Jain Manjula, Thomas Shaji
Department of Pathology, Lady Hardinge Medical College, New Delhi, India.
Department of Surgery, Lady Hardinge Medical College, New Delhi, India.
J Cytol. 2017 Jan-Mar;34(1):1-4. doi: 10.4103/0970-9371.197579.
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.
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.
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.
Normally distributed continuous variables were compared using the unpaired -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.
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 ( < 0.05). Cut-off values were derived to differentiate between benign and malignant cases.
甲状腺结节是一个常见问题，估计患病率为4%-7%。尽管细针穿刺细胞学检查（FNAC）已被公认为一线诊断测试，但恶性肿瘤的假阴性报告率仍然很高。核形态计量学是通过图像分析测量核参数。图像分析可以将形态学解释的优点与定量数据的优点结合起来。
评估甲状腺病变细针穿刺抽吸物中的核形态计量学参数，并研究其在鉴别甲状腺良性和恶性病变中的作用。
该研究包括19例良性和16例恶性甲状腺病变。通过尼康NIS-Elements高级研究软件（版本4.00）对吉姆萨染色的FNAC玻片进行图像分析。分析的核形态计量学参数包括核大小、形状、纹理和密度参数。
对于正态分布的连续变量，两组之间使用不成对t检验进行比较，三组或更多组使用方差分析。使用Tukey或Tamhane's T2多重比较检验评估各个组之间的差异。分类变量使用卡方检验进行分析。
所研究的六个核大小参数中的五个以及所有纹理和密度参数在区分甲状腺良性和恶性病变方面具有显著性（P<0.05）。得出了区分良性和恶性病例的临界值。
