Role of fine-needle aspiration cytology in the diagnosis of thyroid diseases

作者
Radwa Attia,Fatma M Kotb,Omnia M. Rabie
出处
期刊:the egyptian journal of surgery [Medknow]
卷期号:38 (3): 439- 被引量:5
标识
DOI:10.4103/ejs.ejs_32_19
摘要

Background Fine-needle aspiration cytology (FNAC) is a gold standard investigation in the diagnosis of thyroid diseases. It is a simple, safe, cost-effective, and quick-to-perform procedure, with excellent patient compliance. It has high sensitivity, specificity, and accuracy as a preoperative investigation of thyroid gland diseases. Aim To determine the accuracy of FNAC in the diagnosis of thyroid diseases and to correlate the relationship between FNAC findings and histopathology of excised specimen. Patients and methods This was a prospective study conducted on 80 patients between September 2015 and September 2017. All patients with thyroid lesions were subjected to FNAC at Al Zahraa University Hospital. All patients with a clinically diagnosed solitary thyroid nodule, euthyroid multinodular goiter, and hypothyroid or hyperthyroid were excluded from this study. Results The study population was female predominant, represented by 73 (91.25%) patients, with age ranging from 18 to 65 years. Most cases were non-neoplastic, representing 42 (52.5%) cases, whereas 12 (15%) cases were neoplastic. The commonest lesion in thyroid gland was colloid goiter, and papillary carcinoma was the commonest among malignant lesion. On statistical analysis of our study, data showed the diagnostic accuracy of FNAC to be 80%, sensitivity to be 80%, and specificity to be 87.5% in neoplastic lesions, but results in carcinomatous lesions had accuracy of 92.5%, sensitivity of 80%, and specificity of 95.38%. Conclusion FNAC is an excellent first-line method as a preoperative investigation of thyroid swelling showing the nature of the lesion. It is a safe, minimally invasive, cost-effective diagnostic tool and correlates with the findings of tissue biopsy.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
烟花应助qinggui127采纳,获得50
1秒前
zcc完成签到,获得积分10
1秒前
CipherSage应助锦鲤附体采纳,获得10
1秒前
psj123发布了新的文献求助10
1秒前
1秒前
zxf发布了新的文献求助10
1秒前
聪明汉堡完成签到,获得积分20
2秒前
大个应助Wjk采纳,获得10
2秒前
朱成豪发布了新的文献求助10
2秒前
2秒前
sh完成签到,获得积分0
3秒前
李爱国应助BPATIENT采纳,获得10
3秒前
香菜碗里来完成签到,获得积分10
3秒前
鸡蛋酱完成签到 ,获得积分10
4秒前
Orange应助拜拜拜仁采纳,获得10
5秒前
FashionBoy应助fan采纳,获得10
6秒前
梓树完成签到,获得积分10
6秒前
6秒前
inclubs发布了新的文献求助10
6秒前
7秒前
董123完成签到 ,获得积分20
7秒前
团子发布了新的文献求助10
7秒前
8秒前
8秒前
sxw完成签到,获得积分10
8秒前
8秒前
8秒前
8秒前
科研通AI2S应助小孙同学采纳,获得10
9秒前
jia7完成签到,获得积分10
9秒前
充电宝应助常温可乐采纳,获得10
9秒前
哪位发布了新的文献求助10
10秒前
songcheng发布了新的文献求助10
10秒前
史行天完成签到 ,获得积分10
10秒前
1.0完成签到,获得积分10
11秒前
11秒前
11秒前
月牙儿发布了新的文献求助10
11秒前
不吃汉堡完成签到 ,获得积分10
12秒前
告元完成签到,获得积分10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7622498
求助须知:如何正确求助?哪些是违规求助? 9197768
关于积分的说明 19716205
捐赠科研通 7193961
什么是DOI,文献DOI怎么找? 3272988
关于科研通互助平台的介绍 2435377
邀请新用户注册赠送积分活动 2268358