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高危患者肝内胆管细胞癌与肝细胞癌的鉴别诊断:应用超声造影的预测模型。

Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound.

机构信息

Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, Guangdong Province, China.

Department of Pathology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, Guangdong Province, China.

出版信息

World J Gastroenterol. 2018 Sep 7;24(33):3786-3798. doi: 10.3748/wjg.v24.i33.3786.

Abstract

AIM

To develop a contrast-enhanced ultrasound (CEUS) predictive model for distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) in high-risk patients.

METHODS

This retrospective study consisted of 88 consecutive high-risk patients with ICC and 88 high-risk patients with HCC selected by propensity score matching between May 2004 and July 2016. Patients were assigned to two groups, namely, a training set and validation set, at a 1:1 ratio. A CEUS score for diagnosing ICC was generated based on significant CEUS features. Then, a nomogram based on the CEUS score was developed, integrating the clinical data. The performance of the nomogram was then validated and compared with that of the LR-M of the CEUS Liver Imaging Reporting and Data System (LI-RADS).

RESULTS

The most useful CEUS features for ICC were as follows: rim enhancement (64.5%), early washout (91.9%), intratumoral vein (58.1%), obscure boundary of intratumoral non-enhanced area (64.5%), and marked washout (61.3%, all < 0.05). In the validation set, the area under the curve (AUC) of the CEUS score (AUC = 0.953) for differentiation between ICC and HCC was improved compared to the LI-RADS (AUC = 0.742) ( < 0.001). When clinical data were added, the CEUS score nomogram was superior to the LI-RADS nomogram (AUC: 0.973 0.916, = 0.036, Net Reclassification Improvement: 0.077, Integrated Discrimination Index: 0.152). Subgroup analysis demonstrated that the CEUS score model was notably improved compared to the LI-RADS in tumors smaller than 5.0 cm ( < 0.05) but not improved in tumors smaller than 3.0 cm ( > 0.05).

CONCLUSION

The CEUS predictive model for differentiation between ICC and HCC in high-risk patients had improved discrimination and clinical usefulness compared to the CEUS LI-RADS.

摘要

目的

建立一种对比增强超声(CEUS)预测模型,以区分高危患者的肝内胆管细胞癌(ICC)和肝细胞癌(HCC)。

方法

本回顾性研究纳入了 2004 年 5 月至 2016 年 7 月间通过倾向评分匹配选择的 88 例连续高危 ICC 患者和 88 例高危 HCC 患者。将患者按 1:1 比例分为训练集和验证集。基于显著的 CEUS 特征生成 ICC 诊断的 CEUS 评分。然后,基于 CEUS 评分并整合临床数据,建立一个列线图。随后验证并比较了该列线图与 CEUS 肝脏成像报告和数据系统(LI-RADS)的 LR-M 的性能。

结果

ICC 最有用的 CEUS 特征如下:边缘增强(64.5%)、早期廓清(91.9%)、肿瘤内静脉(58.1%)、肿瘤内非增强区边界模糊(64.5%)和明显廓清(61.3%,均 < 0.05)。在验证集中,CEUS 评分(AUC = 0.953)对 ICC 和 HCC 的区分优于 LI-RADS(AUC = 0.742)( < 0.001)。当添加临床数据时,CEUS 评分列线图优于 LI-RADS 列线图(AUC:0.973 0.916, = 0.036,净重新分类改善:0.077,综合鉴别指数:0.152)。亚组分析表明,CEUS 评分模型在小于 5.0 cm 的肿瘤中明显优于 LI-RADS( < 0.05),但在小于 3.0 cm 的肿瘤中没有改善( > 0.05)。

结论

与 CEUS LI-RADS 相比,用于区分高危患者 ICC 和 HCC 的 CEUS 预测模型具有更好的区分度和临床实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6592/6127655/0c0d34162f13/WJG-24-3786-g001.jpg

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