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基于CT增强扫描的低风险胸腺瘤与高密度胸腺囊肿鉴别简化评分模型:一篇遵循STARD规范的文章

CECT-based simplified scoring model for differentiating low-risk thymomas from hyper-attenuating thymic cysts: A STARD compliant article.

作者信息

Zhao Lin, Li Jingwu, Liu Yongliang, Zhao Wenzhe, Cai Haifeng, Cao Lixiu

机构信息

Department of Computed Tomography, Tangshan People's Hospital, Tangshan, Hebei Province, China.

Hebei Key Laboratory of Molecular Oncology, Tangshan, Hebei Province, China.

出版信息

Medicine (Baltimore). 2025 Sep 5;104(36):e44453. doi: 10.1097/MD.0000000000044453.

Abstract

This retrospective study aims to evaluate the effectiveness of a simplified scoring model utilizing contrast-enhanced computed tomography (CECT) in distinguishing low-risk thymomas (LRTs) from thymic cysts in patients with anterior mediastinal hyper-attenuating nodules. A total of 32 patients of LRTs and 40 patients of hyper-attenuating thymic cysts who underwent chest biphasic CECT preoperatively from January 2015 to December 2022 were included. The traditional CT imaging features and clinical features of each patient were analyzed. A predictive model was built by multivariable logistic regression, and subsequently, a simplified scoring model was developed according to the regression coefficients of each risk factor of LRTs. The performance of risk factors and models were assessed by receiver operating characteristic curve, decision curve analysis, and DeLong test. Compared to hyper-attenuating thymic cysts, LRTs tended to be located off-midline, higher CT values in the venous phase, and moderate to severe enhancement (all P < .001). Based on the above risk factors of LTRs, the predictive model achieved an area under the receiver operating characteristic curve of 0.938. While the simplified scoring model demonstrated comparable diagnostic ability (area under the receiver operating characteristic curve = 0.936, P = .42), with ideal sensitivity (0.719), accuracy (0.861), and specificity (0.975). Decision curve analysis indicated this scoring model provided a higher clinical net benefit. Biphasic CECT had a strong diagnostic capability in differentiating LRTs from hyper-attenuating thymic cysts. The diagnostic scoring model is straightforward and convenient, making it easy to popularize.

摘要

本回顾性研究旨在评估一种利用对比增强计算机断层扫描(CECT)的简化评分模型在区分前纵隔高密度结节患者的低风险胸腺瘤(LRT)与胸腺囊肿方面的有效性。纳入了2015年1月至2022年12月期间术前接受胸部双期CECT检查的32例LRT患者和40例高密度胸腺囊肿患者。分析了每位患者的传统CT影像特征和临床特征。通过多变量逻辑回归建立预测模型,随后根据LRT各风险因素的回归系数开发简化评分模型。通过受试者工作特征曲线、决策曲线分析和德龙检验评估风险因素和模型的性能。与高密度胸腺囊肿相比,LRT往往位于中线以外,静脉期CT值较高,且有中度至重度强化(均P < 0.001)。基于上述LTR的风险因素,预测模型的受试者工作特征曲线下面积为0.938。而简化评分模型显示出相当的诊断能力(受试者工作特征曲线下面积 = 0.936,P = 0.42),具有理想的敏感性(0.719)、准确性(0.861)和特异性(0.975)。决策曲线分析表明该评分模型提供了更高的临床净效益。双期CECT在区分LRT与高密度胸腺囊肿方面具有很强的诊断能力。该诊断评分模型简单方便,易于推广。

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