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双源双能量薄层CT联合小视野技术用于甲状腺癌微小淋巴结的回顾性诊断研究

Dual-source dual-energy thin-section CT combined with small field of view technique for small lymph node in thyroid cancer: a retrospective diagnostic study.

作者信息

Zhuo Shuiqing, Sun Jiayuan, Chang Jinyong, Liu Longzhong, Li Sheng

机构信息

Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

出版信息

Gland Surg. 2021 Apr;10(4):1347-1358. doi: 10.21037/gs-20-822.

Abstract

BACKGROUND

To evaluate the diagnostic performance of quantitative spectral parameters derived from dual-source dual-energy CT at small field of view (FOV) for small lymph node metastasis in thyroid cancer.

METHODS

This was a retrospective diagnostic study. From 2016 to 2019, 280 patients with thyroid disease underwent thin-section dual-source dual-energy thyroid CT and thyroid surgery. The data of patients with lymph nodes having a short diameter of 2-6 mm was analyzed. The quantitative dual-energy CT parameters of targeted lymph nodes were measured, and all parameters between metastatic and non-metastatic lymph nodes were compared. These parameters were then fitted to univariable and multivariable binary logistic regression models. The diagnostic role of spectral parameters was analyzed by receiver operating characteristic (ROC) curves and compared with the McNemar test. Small FOV CT images and a mathematical model were used to judge the status of lymph nodes respectively, and then compared with the golden criterion-pathological diagnosis. The cut-off value of the model was 0.4419, with a sensitivity of 90.2% and a specificity of 92.7%.

RESULTS

Of the 216 lymph nodes investigated in this study, 52.3% and 23.6% had a short diameter of 2-3 and 4 mm, respectively. Multiple quantitative CT parameters were significantly different between benign and malignant lymph nodes, and binary regression analysis was performed. The mathematical model was: p=ey/(1+ ey), y=-23.119+0.033× precontrast electron cloud density +0.076× arterial phase normalized iodine concentration +2.156× arterial phase normalized effective atomic number -0.540× venous phase slope of the spectral Hounsfield unit curve +1.676× venous phase iodine concentration. This parameter model had an AUC of 92%, with good discrimination and consistency, and the diagnostic accuracy was 90.3%. The diagnostic accuracy of the CT image model was 43.1%, and for lymph nodes with a short-diameter of 2-3 mm, the diagnostic accuracy was 22.1%.

CONCLUSIONS

The parameter model showed higher diagnostic accuracy than the CT image model for diagnosing small lymph node metastasis in thyroid cancer, and quantitative dual-energy CT parameters were very useful for small lymph nodes that were difficult to be diagnosed only on conventional CT images.

TRIAL REGISTRATION

This study is retrospectively registered, and we have registered a prospective study (Registration number: ChiCTR2000035195; http://www.chictr.org.cn).

摘要

背景

评估小视野(FOV)双源双能CT获得的定量光谱参数对甲状腺癌小淋巴结转移的诊断性能。

方法

这是一项回顾性诊断研究。2016年至2019年,280例甲状腺疾病患者接受了薄层双源双能甲状腺CT检查及甲状腺手术。分析短径为2 - 6mm淋巴结患者的数据。测量目标淋巴结的双能CT定量参数,比较转移和非转移淋巴结之间的所有参数。然后将这些参数拟合到单变量和多变量二元逻辑回归模型中。通过受试者工作特征(ROC)曲线分析光谱参数的诊断作用,并与McNemar检验进行比较。分别使用小视野CT图像和数学模型判断淋巴结状态,然后与金标准——病理诊断进行比较。该模型的截断值为0.4419,灵敏度为90.2%,特异度为92.7%。

结果

本研究共调查216个淋巴结,短径2 - 3mm和4mm的分别占52.3%和23.6%。良性和恶性淋巴结之间多个CT定量参数存在显著差异,并进行了二元回归分析。数学模型为:p = ey /(1 + ey),y = -23.119 + 0.033×平扫电子云密度 + 0.076×动脉期归一化碘浓度 + 2.156×动脉期归一化有效原子序数 - 0.540×光谱Hounsfield单位曲线静脉期斜率 + 1.676×静脉期碘浓度。该参数模型的曲线下面积(AUC)为92%,具有良好的区分度和一致性,诊断准确性为90.3%。CT图像模型的诊断准确性为43.1%,对于短径2 - 3mm的淋巴结,诊断准确性为22.1%。

结论

在诊断甲状腺癌小淋巴结转移方面,参数模型比CT图像模型具有更高的诊断准确性;双能CT定量参数对于仅通过传统CT图像难以诊断的小淋巴结非常有用。

试验注册

本研究为回顾性注册,我们已注册一项前瞻性研究(注册号:ChiCTR2000035195;http://www.chictr.org.cn)。

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