He Lin, Chen Xiao, Hu Jiayin, Meng Yun, Zhang Yan, Chen Wei, Fan Yuhong, Li Tao, Fang Jingqin
Department of Ultrasound, Daping Hospital, Army Medical University, Chongqing, China.
Front Endocrinol (Lausanne). 2024 Apr 18;15:1336787. doi: 10.3389/fendo.2024.1336787. eCollection 2024.
To investigate the association between contrast-enhanced ultrasound (CEUS) features of PTC and central lymph node metastasis (CLNM) and to develop a predictive model for the preoperative identification of CLNM.
This retrospective study evaluated 750 consecutive patients with PTC from August 2020 to April 2023. Conventional ultrasound and qualitative CEUS features were analyzed for the PTC with or without CLNM using univariate and multivariate logistic regression analysis. A nomogram integrating the predictors was constructed to identify CLNM in PTC. The predictive nomogram was validated using a validation cohort.
A total of 684 patients were enrolled. The 495 patients in training cohort were divided into two groups according to whether they had CLNM (pCLNM, n= 191) or not (nCLNM, n= 304). There were significant differences in terms of tumor size, shape, echogenic foci, enhancement direction, peak intensity, and score based on CEUS TI-RADS between the two groups. Independent predictive US features included irregular shape, larger tumor size (≥ 1.0cm), and score. Nomogram integrating these predictive features showed good discrimination and calibration in both training and validation cohort with an AUC of 0.72 (95% CI: 0.68, 0.77) and 0.79 (95% CI: 0.72, 0.85), respectively. In the subgroup with larger tumor size, age ≤ 35 years, irregular shape, and score > 6 were independent risk factors for CLNM.
The score based on preoperative CEUS features of PTC may help to identify CLNM. The nomogram developed in this study provides a convenient and effective tool for clinicians to determine an optimal treatment regimen for patients with PTC.
探讨甲状腺乳头状癌(PTC)的超声造影(CEUS)特征与中央区淋巴结转移(CLNM)之间的关联,并建立术前识别CLNM的预测模型。
本回顾性研究评估了2020年8月至2023年4月期间连续收治的750例PTC患者。采用单因素和多因素逻辑回归分析,对有或无CLNM的PTC进行常规超声和定性CEUS特征分析。构建整合预测因子的列线图以识别PTC中的CLNM。使用验证队列对预测列线图进行验证。
共纳入684例患者。训练队列中的495例患者根据是否发生CLNM分为两组(pCLNM,n = 191;nCLNM,n = 304)。两组在肿瘤大小、形态、回声灶、增强方向、峰值强度以及基于CEUS TI-RADS的评分方面存在显著差异。独立的预测性超声特征包括形态不规则、肿瘤较大(≥1.0cm)和评分。整合这些预测特征的列线图在训练队列和验证队列中均显示出良好的区分度和校准度,AUC分别为0.72(95%CI:0.68,0.77)和0.79(95%CI:0.72,0.85)。在肿瘤较大的亚组中,年龄≤35岁、形态不规则和评分>6是CLNM的独立危险因素。
基于PTC术前CEUS特征的评分可能有助于识别CLNM。本研究开发的列线图为临床医生确定PTC患者的最佳治疗方案提供了一种方便有效的工具。