Zhang Luyao, Li Yize, Chen Ziqi, Dai Xinpeng, Gao Huimin, Chen Yingmin
Department of Radiology, Hebei General Hospital, 348 Heping West Road, Shijiazhuang 050051, Hebei, China.
Department of Urinary Surgery, Hebei General Hospital, 348 Heping West Road, Shijiazhuang 050051, Hebei, China.
Eur J Radiol. 2025 Feb;183:111917. doi: 10.1016/j.ejrad.2025.111917. Epub 2025 Jan 3.
This study systematically evaluated the diagnostic performance of dual-energy computed tomography (DECT) quantitative parameters in detecting cervical lymph node metastasis in patients with papillary thyroid cancer (PTC).
We searched PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data databases for relevant original studies from database inception to March 2024. The quality of the included studies was evaluated using the QUADAS-2 tool. A bivariate random-effects model was used to calculate the pooled sensitivity and specificity of DECT. The threshold effect was determined by calculating Spearman correlation coefficients, meta-regression and subgroup analysis were performed to evaluate the sources of variability. Publication bias was assessed using the asymmetry of Deek's funnel plot.
Thirteen studies involving 951 patients (2,782 lymph nodes) were included in this meta-analysis. We analyzed four quantitative parameters of DECT, among which the normalized iodine concentration (NIC) in the arterial phase had the highest area under the receiver operating characteristic curve (AUC). The combined sensitivity, specificity, and AUC were 83 % (95 % confidence interval [CI]: 76 % - 89 %), 90 % (95 % CI: 82 % - 95 %), and 0.92 (95 % CI: 0.90 - 0.94), respectively. The Spearman correlation coefficient was - 0.244 (p = 0.4). Meta-regression and subgroup analysis revealed that use of blinding, mean patients' age, female proportion, presence of Hashimoto's thyroiditis, number of lymph nodes included in the study, and slice thickness were sources of heterogeneity for the NIC in the arterial phase. No significant publication bias was observed among the studies.
DECT, a noninvasive technique, can be used to distinguish metastatic from nonmetastatic cervical lymph nodes in patients with PTC by measuring quantitative lymph node parameters.
本研究系统评价了双能计算机断层扫描（DECT）定量参数在检测甲状腺乳头状癌（PTC）患者颈部淋巴结转移中的诊断性能。
我们检索了PubMed、Embase、Web of Science、Cochrane图书馆、中国知网和万方数据数据库，以获取从数据库建立至2024年3月的相关原始研究。使用QUADAS-2工具评估纳入研究的质量。采用双变量随机效应模型计算DECT的合并敏感性和特异性。通过计算Spearman相关系数确定阈值效应，进行Meta回归和亚组分析以评估异质性来源。使用Deek漏斗图的不对称性评估发表偏倚。
本Meta分析纳入了13项研究，共951例患者（2782个淋巴结）。我们分析了DECT的四个定量参数，其中动脉期归一化碘浓度（NIC）的受试者工作特征曲线下面积（AUC）最高。合并敏感性、特异性和AUC分别为83%（95%置信区间[CI]：76% - 89%）、90%（95%CI：82% - 95%）和0.92（95%CI：0.90 - 0.94）。Spearman相关系数为 - 0.244（p = 0.4）。Meta回归和亚组分析显示，使用盲法、患者平均年龄、女性比例、桥本甲状腺炎的存在、研究中纳入的淋巴结数量以及层厚是动脉期NIC异质性的来源。研究中未观察到显著的发表偏倚。
DECT作为一种非侵入性技术，可通过测量淋巴结定量参数来区分PTC患者颈部转移与非转移淋巴结。
