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钆塞酸增强 MRI 上 LI-RADS M 病变的诊断:通过血清标志物和影像学特征识别含胆管癌的肿瘤。

Diagnosis of LI-RADS M lesions on gadoxetate-enhanced MRI: identifying cholangiocarcinoma-containing tumor with serum markers and imaging features.

机构信息

Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.

Department of Radiology and Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Box 3808, Durham, NC, 27710, USA.

出版信息

Eur Radiol. 2021 Jun;31(6):3638-3648. doi: 10.1007/s00330-020-07488-z. Epub 2020 Nov 27.

Abstract

OBJECTIVES

The LI-RADS M (LR-M) category describes hepatic lesions probably or definitely malignant, but not specific for hepatocellular carcinoma in at-risk patients. Differentiation among LR-M entities, particularly detecting cholangiocarcinoma-containing tumors (M-CCs), is essential for treatment and prognosis. Thus, we aimed to develop diagnostic models on gadoxetate disodium-enhanced MRI comprising serum tumor markers and LI-RADS imaging features for M-CC.

METHODS

Consecutive at-risk patients with LR-M lesions exclusively (no co-existing LR-4 and/or LR-5 lesions) were retrieved retrospectively from a prospectively collected database spanning 3 years. Intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (c-HCC-CCA) were classified together as M-CC. LI-RADS features determined by three independent radiologists and clinically relevant serum tumor markers were used to generate M-CC diagnostic models through logistic regression analysis against histology. Per-patient performance was evaluated using area under the receiver operating curve (AUC), sensitivity, and specificity.

RESULTS

Forty-five patients were included, 42.2% (19/45) with hepatocellular carcinoma, 33.3% (15/45) with ICC, 13.3% (6/45) with c-HCC-CCA, and 11.1% (5/45) with other hepatic lesions. Carbohydrate antigen (CA)19-9 > 38 U/mL, α-fetoprotein (AFP) > 4.8 ng/mL, and absence of the LI-RADS feature "blood products in mass" were significant predictors of M-CC. Combining three predictors demonstrated AUC of 0.862, sensitivity of 76%, and specificity of 88%. The risk of M-CC with all three criteria fulfilled was 98% (AUC, 0.690; sensitivity, 38%; specificity, 100%).

CONCLUSIONS

In at-risk patients with LR-M lesions, integrating CA19-9, AFP, and the LI-RADS feature "blood products in mass" achieved high diagnostic performance for M-CC. When all three criteria were fulfilled, the specificity for M-CC was 100%.

KEY POINTS

• In at-risk patients who had LR-M lesions exclusively (no concomitant LR-4/5 lesions), a model with carbohydrate antigen > 38 U/mL, α-fetoprotein > 4.8 ng/mL, and absence of the LI-RADS feature "blood products in mass" achieved high accuracy for diagnosing cholangiocarcinoma-containing tumors. • In patients of whom all three criteria were fulfilled, the specificity for M-CC was 100%, which might reduce or eliminate the need for biopsy confirmation.

摘要

目的

LI-RADS M(LR-M)类别描述了在高危患者中可能或肯定为恶性的肝脏病变,但不能特异性诊断为肝细胞癌。区分 LR-M 实体,特别是检测包含胆管癌的肿瘤(M-CCs),对于治疗和预后至关重要。因此,我们旨在开发基于钆塞酸二钠增强 MRI 的诊断模型,该模型包含血清肿瘤标志物和 LI-RADS 成像特征,用于诊断 M-CC。

方法

我们回顾性地从一个前瞻性收集的数据库中检索了连续的仅具有 LR-M 病变的高危患者(无共存的 LR-4 和/或 LR-5 病变),该数据库跨越了 3 年。肝内胆管癌(ICC)和肝细胞癌-胆管细胞癌(c-HCC-CCA)合并为 M-CC。由三位独立的放射科医生确定的 LI-RADS 特征和临床相关的血清肿瘤标志物被用于通过逻辑回归分析针对组织学生成 M-CC 诊断模型。使用接受者操作特征曲线(AUC)下的面积、敏感性和特异性来评估每个患者的表现。

结果

共纳入 45 例患者,其中 42.2%(19/45)为肝细胞癌,33.3%(15/45)为 ICC,13.3%(6/45)为 c-HCC-CCA,11.1%(5/45)为其他肝脏病变。CA19-9>38 U/mL、AFP>4.8ng/mL 和缺乏 LI-RADS 特征“肿块内血液制品”是 M-CC 的显著预测因素。结合三个预测因子,AUC 为 0.862,敏感性为 76%,特异性为 88%。三个标准均满足时,M-CC 的风险为 98%(AUC,0.690;敏感性,38%;特异性,100%)。

结论

在仅具有 LR-M 病变的高危患者中,整合 CA19-9、AFP 和 LI-RADS 特征“肿块内血液制品”可实现对 M-CC 的高诊断性能。当所有三个标准均满足时,M-CC 的特异性为 100%。

重点

• 在仅具有 LR-M 病变(无同时存在的 LR-4/5 病变)的高危患者中,模型中包含 CA>38 U/mL、AFP>4.8ng/mL 和缺乏 LI-RADS 特征“肿块内血液制品”,对诊断包含胆管癌的肿瘤具有较高的准确性。• 在三个标准均满足的患者中,M-CC 的特异性为 100%,这可能减少或消除对活检确认的需求。

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