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LIRADS分类≥3的肝硬化结节栓塞后的数字减影血管造影及碘油沉积

Digital subtract angiography and lipiodol deposits following embolization in cirrhotic nodules of LIRADS category ≥3.

作者信息

Kang Zhen, Wang Nan, Xu Anhui, Wang Liang

机构信息

Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Hubei, Wuhan, 430030, PR China.

出版信息

Eur J Radiol Open. 2019 Feb 23;6:106-112. doi: 10.1016/j.ejro.2019.02.005. eCollection 2019.

DOI:10.1016/j.ejro.2019.02.005
PMID:30899770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6405901/
Abstract

PURPOSE

To assess the correlation between Liver Imaging Reporting and Data System (LIRADS) and digital substract angiography (DSA) and lipiodol deposits in cirrhotic nodules of LIRADS category ≥3 receiving interventional treatment.

METHODS

From June 2014 to June 2016, patients with cirrhotic nodules were identified retrospectively and MR images were reviewed by sub-specialty radiologists according to modified LIRADS v2014. Correlation between nodules of LIRADS category ≥3 and DSA findings and lipiodol deposits were analyzed.

RESULTS

71 cirrhotic nodules were evaluated in 33 patients. 39/71 nodules were classified as LR-3, 9/71 nodules were categorized as LR-4, 23/71 nodules were grouped into LR-5. 43 nodules presented positive DSA, 37 nodules showed presence of lipiodol deposits during follow up. With the upgrade of LIRADS category of cirrhotic nodules, DSA and lipiodol deposits became more conspicuous. Spearman analysis demonstrated positive correlations between LIRADS and DSA (r = 0.567, P = 0.000) as well as LIRADS and lipiodol deposits (r = 0.616, P = 0.000). ROC analysis revealed a cut-off value of LR ≥ 4 resulted in a sensitivity of 67.4% and specificity of 89.3% in predicting positive DSA (RUC = 0.799, P < 0.0001), and a sensitivity of 75.7% and specificity of 88.2% in predicting lipiodol deposits (RUC = 0.818, P < 0.0001). Of 39 lesions of LR-3, 64.1% (25/39) showed negative DSA, and 76.9% (30/39) showed absence of lipiodol deposits during follow up. Logistic regression analysis identified arterial enhancement (OR = 26.837, P = 0.002) and lesion size (OR = 1.325, P = 0.022) were independently associated with positive DSA in nodule of LIRADS category ≥3, while no factors were associated with lipiodol deposits.

CONCLUSION

The LIRADS can be used to predict DSA findings and lipiodol deposits in nodules with LIRADS score 3 and above. LIRADS 3 nodules tend to be DSA-negative and have less lipiodol deposits. DSA and lipiodol deposits become more conspicuous in nodules from LIRADS 3 to 5.

摘要

目的

评估肝脏影像报告和数据系统(LIRADS)与数字减影血管造影(DSA)以及接受介入治疗的LIRADS分类≥3级肝硬化结节中碘油沉积之间的相关性。

方法

回顾性纳入2014年6月至2016年6月的肝硬化结节患者,由专科放射科医生根据改良的2014版LIRADS对磁共振图像进行评估。分析LIRADS分类≥3级结节与DSA表现及碘油沉积之间的相关性。

结果

对33例患者的71个肝硬化结节进行了评估。71个结节中,39个被分类为LR-3,9个被分类为LR-4,23个被分类为LR-5。43个结节DSA表现为阳性,37个结节在随访期间显示有碘油沉积。随着肝硬化结节LIRADS分类的升级,DSA表现及碘油沉积变得更加明显。Spearman分析显示LIRADS与DSA之间呈正相关(r = 0.567,P = 0.000),LIRADS与碘油沉积之间也呈正相关(r = 0.616,P = 0.000)。ROC分析显示,LR≥4的截断值在预测DSA阳性时的敏感度为67.4%,特异度为89.3%(RUC = 0.799,P<0.0001),在预测碘油沉积时的敏感度为75.7%,特异度为88.2%(RUC = 0.818,P<0.0001)。在39个LR-3级病变中,64.1%(25/39)的DSA表现为阴性,76.9%(30/39)在随访期间未显示碘油沉积。Logistic回归分析显示,动脉强化(OR = 26.837,P = 0.002)和病变大小(OR = 1.325,P = 0.022)与LIRADS分类≥3级结节的DSA阳性独立相关,而没有因素与碘油沉积相关。

结论

LIRADS可用于预测LIRADS评分3及以上结节的DSA表现和碘油沉积。LIRADS 3级结节倾向于DSA阴性且碘油沉积较少。从LIRADS 3级到5级,结节的DSA表现及碘油沉积变得更加明显。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/5de478d40722/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/6c3a841077c2/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/8866e56a57cb/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/dc8db58149fe/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/fb4e8856c562/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/7e0b04ed2586/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/0844624b7959/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/5de478d40722/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/6c3a841077c2/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/8866e56a57cb/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/dc8db58149fe/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/fb4e8856c562/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/7e0b04ed2586/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/0844624b7959/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d46d/6405901/5de478d40722/gr6.jpg

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