Department of Radiology, Affiliated Hospital, Jiangnan University, Wuxi, China.
Department of Radiology, Affiliated Renmin Hospital, Jiangsu University, Zhenjiang, China.
Front Endocrinol (Lausanne). 2020 Jun 12;11:326. doi: 10.3389/fendo.2020.00326. eCollection 2020.
To investigate whether diffusion-weighted imaging (DWI) with multi b values can be used as a quantitative assessment tool to predict central lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC). A total of 214 PTC patients were enrolled from January 2015 to April 2018. Each patient underwent multi b value DWI (300, 500, and 800 s/mm) preoperatively and then clinical treatment of central LN dissection at the Thyroid Surgery Department. These patients were divided as two groups based on with and without CLNM. The corresponding apparent diffusion coefficients (ADCs) were evaluated with separated b value, i.e., 300, 500, or 800 s/mm. Clinicopathological variables and ADC values were analyzed retrospectively by using univariate and binary logistic regression. The corresponding obtained variables with statistical significance were further applied to create a nomogram in which the bootstrap resampling method was used for correction. PTCs with CLNM had significantly lower ADC, ADC, and ADC values compared with PTCs without CLNM. Using receiver operating characteristic (ROC) analysis, the ADC value (0.817) showed a higher area under the curve (AUC) than those of the ADC and ADC values (0.610 and 0.641, respectively) in differentiating patients with CLNM and without CLNM. The corresponding cutoff value for ADC was also determined (1.444 × 10 mm/s), with respective sensitivity and specificity of 88.6 and 66%. The nomogram was generated by binary logistic regression results, incorporating four variables: gender, primary tumor size, extrathyroidal extension (ETE), and ADC value. The AUC of the nomogram was 0.894 in predicting CLNM. Moreover, as shown in the calibration curve between nomogram and clinical findings, a strong agreement was observed in the prediction of CLNM. In summary, the ADC value is a valuable noninvasive imaging biomarker for evaluating CLNM in PTCs. The nomogram, as a clinical predictive model, is able to provide an effective evaluation of CLNM risk in PTC patients preoperatively.
为了研究多 b 值扩散加权成像（DWI）是否可作为预测甲状腺乳头状癌（PTC）中央淋巴结转移（CLNM）的定量评估工具。本研究共纳入了 214 例于 2015 年 1 月至 2018 年 4 月期间在甲状腺外科接受治疗的 PTC 患者。每位患者术前均进行了多 b 值 DWI（300、500 和 800 s/mm）检查，然后根据临床情况选择性地进行中央区淋巴结清扫术。这些患者根据是否存在 CLNM 被分为两组。采用分离的 b 值（300、500 或 800 s/mm）评估相应的表观扩散系数（ADC）。采用单变量和二元逻辑回归对临床病理变量和 ADC 值进行回顾性分析。将有统计学意义的相关变量进一步应用于创建列线图，其中使用自举重采样方法进行校正。与无 CLNM 的 PTC 相比，有 CLNM 的 PTC 的 ADC 值、ADC 值和 ADC 值均显著降低。使用受试者工作特征（ROC）分析，ADC 值（0.817）在区分 CLNM 患者和无 CLNM 患者方面的曲线下面积（AUC）高于 ADC 值（0.610）和 ADC 值（0.641）。ADC 值的相应截断值也被确定（1.444×10mm/s），其敏感性和特异性分别为 88.6%和 66%。列线图是根据二元逻辑回归结果生成的，纳入了四个变量：性别、原发肿瘤大小、甲状腺外侵犯（ETE）和 ADC 值。该列线图预测 CLNM 的 AUC 为 0.894。此外，如图中所示，在列线图与临床发现之间的校准曲线中，CLNM 的预测显示出很强的一致性。总之，ADC 值是评估 PTC 中 CLNM 的有价值的无创成像生物标志物。该列线图作为一种临床预测模型，能够在术前对 PTC 患者的 CLNM 风险进行有效评估。
