Department of Radiology, First Central Clinical College, Tianjin Medical University, No. 24 Fu Kang Road, Nan Kai District, Tianjin 300192, China; Department of Radiology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, No. 314 Anshan West Road, Nan Kai District, Tianjin 300193, China; Department of Radiology, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, No. 314 Anshan West Road, Nan Kai District, Tianjin 300193, China.
Department of Radiology, First Central Clinical College, Tianjin Medical University, No. 24 Fu Kang Road, Nan Kai District, Tianjin 300192, China; Department of Radiology, JiLin Cancer Hospital, No.1066 JinHu Road, ChaoYang District, ChangChun 130000, China.
Eur J Radiol. 2021 Dec;145:110060. doi: 10.1016/j.ejrad.2021.110060. Epub 2021 Nov 22.
The current study aimed to develop and validate a prediction model to estimate the independent risk factors for lateral cervical lymph node metastasis (LLNM) in papillary thyroid carcinoma (PTC) patients based on dual-energy computed tomography (DECT).
This study retrospectively conducted 406 consecutive patients from July 2015 to June 2019 to form the derivation cohorts and performed internal validation. 101 consecutive patients from July 2019 to June 2020 were included to create the external validation cohort. Univariable and multivariable logistic regression analyses were used to evaluate independent risk factors for LLNM. A prediction model based on DECT parameters was built and presented on a nomogram. The internal and external validations were performed.
Iodine concentration (IC) in the arterial phase (OR 2.761, 95% CI 1.028-7.415, P 0.044), IC in venous phase (OR 3.820, 95% CI 1.430-10.209, P 0.008), located in the superior pole (OR 4.181, 95% CI 2.645-6.609, P 0.000), and extrathyroidal extension (OR 4.392, 95% CI 2.142-9.004, P 0.000) were independently associated with LLNM in the derivation cohort. These four predictors were incorporated into the nomogram. The model showed good discrimination in the derivation (AUC, 0.899), internal (AUC, 0.905), and external validation (AUC, 0.912) cohorts. The decision curve revealed that more advantages would be added using the nomogram to estimate LLNM, which implied that the lateral lymph node dissection was recommended.
DECT parameters could provide independent indicators of LLNM in PTC patients, and the nomogram based on them may be helpful in treatment decision-making.
本研究旨在基于双能 CT（DECT）建立并验证一个预测模型，以评估甲状腺乳头状癌（PTC）患者颈侧区淋巴结转移（LLNM）的独立危险因素。
本研究回顾性纳入了 2015 年 7 月至 2019 年 6 月期间的 406 例连续患者作为推导队列，并进行内部验证。2019 年 7 月至 2020 年 6 月期间纳入 101 例连续患者作为外部验证队列。采用单变量和多变量逻辑回归分析评估与 LLNM 相关的独立危险因素。建立基于 DECT 参数的预测模型，并以列线图呈现。进行内部和外部验证。
在推导队列中，动脉期碘浓度（IC）（OR 2.761，95%CI 1.028-7.415，P=0.044）、静脉期 IC（OR 3.820，95%CI 1.430-10.209，P=0.008）、位于上极（OR 4.181，95%CI 2.645-6.609，P=0.000）和甲状腺外侵犯（OR 4.392，95%CI 2.142-9.004，P=0.000）与 LLNM 独立相关。这四个预测因子被纳入到列线图中。该模型在推导队列（AUC，0.899）、内部（AUC，0.905）和外部验证队列（AUC，0.912）中均具有良好的区分度。决策曲线分析显示，使用列线图来估计 LLNM 会带来更多的优势，这意味着建议进行侧颈部淋巴结清扫。
DECT 参数可提供 PTC 患者 LLNM 的独立指标，基于这些参数的列线图可能有助于治疗决策。
