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肝细胞癌(HCC)与非 HCC:肝脏影像报告和数据系统 v2018 的准确性和可靠性。

Hepatocellular carcinoma (HCC) versus non-HCC: accuracy and reliability of Liver Imaging Reporting and Data System v2018.

机构信息

Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.

University of Pittsburgh Medical Center, Pittsburgh, PA, USA.

出版信息

Abdom Radiol (NY). 2019 Jun;44(6):2116-2132. doi: 10.1007/s00261-019-01948-x.

Abstract

PURPOSE

The Liver Imaging Reporting and Data System (LI-RADS) was created to standardize the diagnostic criteria for hepatocellular carcinoma (HCC) and has undergone multiple revisions including a recent update in 2018 (v2018). The primary aim of this study was to determine the diagnostic performance and interrater reliability (IRR) of LI-RADS v2018 for distinguishing HCC from non-HCC primary hepatic malignancy in patients 'at-risk' for HCC. A secondary aim was to assess the impact of changes introduced in the v2018 diagnostic algorithm.

METHODS

This retrospective study combined a 10-year experience of pathologically proven primary liver malignancies from two large liver transplant centers. Two blinded readers independently evaluated each lesion and assigned a LI-RADS diagnostic category, additionally scoring all relevant imaging features. Changes in category based on the reader-provided features and the new v2018 criteria were assessed by a study coordinator.

RESULTS

The final study cohort comprised 105 HCCs and 73 non-HCC primarily liver malignancies. LI-RADS had a high specificity for distinguishing HCC from non-HCC (89% and 90% for reader 1 and reader 2, respectively), and IRR was moderate to substantial for final LI-RADS category and most features. Revision of the LI-RADS v2018 diagnostic algorithm resulted in very few changes [5 (2.8%) and 3 (1.7%) for reader 1 and reader 2, respectively] in overall lesion classification.

CONCLUSION

LI-RADS diagnostic categories and features had moderate to substantial IRR and high specificity for distinguishing HCC from non-HCC primary liver malignancy. Revision of LI-RADS v2018 diagnostic algorithm resulted in reclassification of very few lesions.

摘要

目的

肝脏影像报告和数据系统(LI-RADS)旨在规范肝细胞癌(HCC)的诊断标准,并经历了多次修订,包括最近在 2018 年的更新(v2018)。本研究的主要目的是确定 LI-RADS v2018 用于区分 HCC 和非 HCC 原发性肝脏恶性肿瘤在 HCC 高危患者中的诊断性能和组内一致性(IRR)。次要目的是评估 v2018 诊断算法中引入的变化的影响。

方法

这项回顾性研究结合了来自两个大型肝移植中心的 10 年经病理证实的原发性肝脏恶性肿瘤经验。两名盲法读者独立评估每个病变并分配 LI-RADS 诊断类别,另外还对所有相关的影像学特征进行评分。根据读者提供的特征和新的 v2018 标准,由研究协调员评估类别变化。

结果

最终的研究队列包括 105 例 HCC 和 73 例非 HCC 原发性肝脏恶性肿瘤。LI-RADS 对区分 HCC 和非 HCC 具有很高的特异性(读者 1 和读者 2 的特异性分别为 89%和 90%),并且对最终的 LI-RADS 类别和大多数特征的 IRR 为中度至高度。LI-RADS v2018 诊断算法的修订导致整体病变分类的变化很少[读者 1 和读者 2 分别为 5(2.8%)和 3(1.7%)]。

结论

LI-RADS 诊断类别和特征对区分 HCC 和非 HCC 原发性肝脏恶性肿瘤具有中度至高度的 IRR 和高度特异性。LI-RADS v2018 诊断算法的修订导致很少有病变被重新分类。

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