Terminology inaccuracies in the interpretation of imaging results in detection of cervical lymph node metastases in papillary thyroid cancer

乳头状甲状腺癌颈部淋巴结转移检测中影像学结果解读的术语不准确

阅读:1

Abstract

Cervical lymph nodes (CLNs) are the most common site of metastases in papillary thyroid cancer (PTC). Ultrasound scan (US) is the most commonly used imaging modality in the evaluation of CLNs in PTC. Computerised tomography (CT) and (18)fluorodeoxyglucose positron emission tomography ((18)FDG PET-CT) are used less commonly. It is widely believed that the above imaging techniques should guide the surgical approach to the patient with PTC. METHODS: We performed a systematic review of imaging studies from the literature assessing the usefulness for the detection of metastatic CLNs in PTC. We evaluated the author's interpretation of their numeric findings specifically with regard to 'sensitivity' and 'negative predictive value' (NPV) by comparing their use against standard definitions of these terms in probabilistic statistics. RESULTS: A total of 16 studies used probabilistic terms to describe the value of US for the detection of LN metastases. Only 6 (37.5%) calculated sensitivity and NPV correctly. For CT, out of the eight studies, only 1 (12.5%) used correct terms to describe analytical results. One study looked at magnetic resonance imaging, while three assessed (18)FDG PET-CT, none of which provided correct calculations for sensitivity and NPV. CONCLUSION: Imaging provides high specificity for the detection of cervical metastases of PTC. However, sensitivity and NPV are low. The majority of studies reporting on a high sensitivity have not used key terms according to standard definitions of probabilistic statistics. Against common opinion, there is no current evidence that failure to find LN metastases on ultrasound or cross-sectional imaging can be used to guide surgical decision making.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。