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LI-RADS 治疗反应算法:性能和诊断准确性。

LI-RADS Treatment Response Algorithm: Performance and Diagnostic Accuracy.

机构信息

From the Department of Radiology (E.L.S., M.C., C.M.M., B.C.A., E.B., G.L.J., C.Y.K., J.R., M.R.B.), Department of Pathology (D.M.C.), Division of Gastroenterology, Department of Medicine (L.Y.K., M.R.B.), and Center for Advanced Magnetic Resonance Development (G.L.J., M.R.B.), Duke University Medical Center, Box 3808, Durham, NC; and Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (R.K.D.).

出版信息

Radiology. 2019 Jul;292(1):226-234. doi: 10.1148/radiol.2019182135. Epub 2019 Apr 30.

Abstract

Background In 2017, the Liver Imaging Reporting and Data System (LI-RADS) included an algorithm for the assessment of hepatocellular carcinoma (HCC) treated with local-regional therapy. The aim of the algorithm was to enable standardized evaluation of treatment response to guide subsequent therapy. However, the performance of the algorithm has not yet been validated in the literature. Purpose To evaluate the performance of the LI-RADS 2017 Treatment Response algorithm for assessing the histopathologic viability of HCC treated with bland arterial embolization. Materials and Methods This retrospective study included patients who underwent bland arterial embolization for HCC between 2006 and 2016 and subsequent liver transplantation. Three radiologists independently assessed all treated lesions by using the CT/MRI LI-RADS 2017 Treatment Response algorithm. Radiology and posttransplant histopathology reports were then compared. Lesions were categorized on the basis of explant pathologic findings as either completely (100%) or incompletely (<100%) necrotic, and performance characteristics and predictive values for the LI-RADS Treatment Response (LR-TR) Viable and Nonviable categories were calculated for each reader. Interreader association was calculated by using the Fleiss κ. Results A total of 45 adults (mean age, 57.1 years ± 8.2; 13 women) with 63 total lesions were included. For predicting incomplete histopathologic tumor necrosis, the accuracy of the LR-TR Viable category for the three readers was 60%-65%, and the positive predictive value was 86%-96%. For predicting complete histopathologic tumor necrosis, the accuracy of the LR-TR Nonviable category was 67%-71%, and the negative predictive value was 81%-87%. By consensus, 17 (27%) of 63 lesions were categorized as LR-TR Equivocal, and 12 of these lesions were incompletely necrotic. Interreader association for the LR-TR category was moderate (κ = 0.55; 95% confidence interval: 0.47, 0.67). Conclusion The Liver Imaging Reporting and Data System 2017 Treatment Response algorithm had high predictive value and moderate interreader association for the histopathologic viability of hepatocellular carcinoma treated with bland arterial embolization when lesions were assessed as Viable or Nonviable. © RSNA, 2019 See also the editorial by Gervais in this issue.

摘要

背景 2017 年,肝脏成像报告和数据系统(LI-RADS)纳入了用于评估局部区域治疗的肝细胞癌(HCC)的算法。该算法的目的是实现对治疗反应的标准化评估,以指导后续治疗。然而,该算法在文献中的性能尚未得到验证。目的 评估 LI-RADS 2017 版治疗反应算法在评估单纯动脉栓塞治疗 HCC 的组织病理学活力方面的性能。材料与方法 本回顾性研究纳入了 2006 年至 2016 年期间接受单纯动脉栓塞治疗 HCC 并随后接受肝移植的患者。3 名放射科医生独立使用 CT/MRI LI-RADS 2017 版治疗反应算法评估所有治疗后的病灶。然后比较放射学和移植后组织病理学报告。根据肝移植标本的病理结果,将病灶分为完全(100%)和不完全(<100%)坏死,并为每位读者计算 LI-RADS 治疗反应(LR-TR)有活力和无活力类别的性能特征和预测值。采用 Fleiss κ 计算读者间的关联。结果 共纳入 45 例成人(平均年龄,57.1 岁±8.2;13 例女性)共 63 个病灶。对于预测不完全的组织病理学肿瘤坏死,3 位读者的 LR-TR 有活力类别的准确性为 60%65%,阳性预测值为 86%96%。对于预测完全的组织病理学肿瘤坏死,LR-TR 无活力类别的准确性为 67%71%,阴性预测值为 81%87%。通过共识,63 个病灶中的 17 个(27%)被归类为 LR-TR 不确定,其中 12 个病灶为不完全坏死。LR-TR 类别的读者间关联为中度(κ=0.55;95%置信区间:0.47,0.67)。结论 当病灶被评估为有活力或无活力时,LI-RADS 2017 版治疗反应算法对于接受单纯动脉栓塞治疗的 HCC 的组织病理学活力具有较高的预测值和中度的读者间关联。©2019 RSNA. 本期杂志中的 Gervais 社论亦有相关内容。

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