Lngegowda Jyothi B, Muddegowda Prakash H, Rajesh Kumar N, Ramkumar Kurpad R
Department of Pathology, VMKV Medical College, Salem, India.
J Cytol. 2010 Jan;27(1):1-7. doi: 10.4103/0970-9371.66688.
Various methods are used to arrive at a conclusive diagnosis of thyroid lesions on fine needle aspiration cytology (FNAC). Systemic pattern analysis is one such that can be used to analyze the lesions and divide them into individual categories.
To study the application of pattern analysis in the interpretation of solitary thyroid nodule (STN).
Two hundred and nineteen cases of fine needle aspiration cytology of STN were reviewed along with histopathological correlation. Smears were classified based on primary and secondary patterns. Predominant pattern (primary) was identified and lesion categorized. This was followed by identifying the next dominant pattern (secondary) and recategorization. Cytological diagnosis based on primary and secondary patterns was correlated with the histopathological diagnosis.
Based on pattern analysis, the study had a sensitivity of 66.7% and specificity of 98.9%. The positive predictive value and negative predictive value were 88.9% and 96% respectively and the overall diagnostic accuracy was 95.4%.
The present study demonstrates the feasibility and applicability of pattern analysis in diagnosing thyroid lesions by FNAC, which could be easily reproducible.
在细针穿刺细胞学检查(FNAC)中,有多种方法可用于对甲状腺病变做出确定性诊断。系统模式分析就是其中一种可用于分析病变并将其分为不同类别的方法。
研究模式分析在孤立性甲状腺结节(STN)诊断中的应用。
回顾了219例STN的细针穿刺细胞学检查病例,并与组织病理学结果进行对照。涂片根据主要和次要模式进行分类。确定主要模式(主要)并对病变进行分类。随后确定下一个主导模式(次要)并重新分类。基于主要和次要模式的细胞学诊断与组织病理学诊断进行对照。
基于模式分析,该研究的敏感性为66.7%,特异性为98.9%。阳性预测值和阴性预测值分别为88.9%和96%,总体诊断准确性为95.4%。
本研究证明了模式分析在通过FNAC诊断甲状腺病变中的可行性和适用性,该方法易于重复。