Targetoid hepatic observations on gadoxetic acid-enhanced MRI using LI-RADS version 2018: emphasis on hepatocellular carcinomas assigned to the LR-M category

被引:20
作者
Park, H. J. [1 ]
Kim, Y. K. [2 ,3 ]
Cha, D., I [2 ,3 ]
Ko, S. E. [2 ,3 ]
Kim, S. [2 ,3 ]
Lee, E. S. [1 ]
Ahn, S. [4 ]
机构
[1] Chung Ang Univ, Chung Ang Univ Hosp, Dept Radiol, Coll Med, Seoul, South Korea
[2] Sungkyunkwan Univ, Samsung Med Ctr, Dept Radiol, Sch Med, 50 Ilwon Dong, Seoul 135710, South Korea
[3] Sungkyunkwan Univ, Samsung Med Ctr, Ctr Imaging Sci, Sch Med, 50 Ilwon Dong, Seoul 135710, South Korea
[4] Ajou Univ, Dept Math, Suwon, South Korea
关键词
DIFFUSION-WEIGHTED IMAGES; INTRAHEPATIC CHOLANGIOCARCINOMA; HEPATOBILIARY PHASE; LIVER; CAPSULE; CT; DIFFERENTIATION; CONTRAST; FEATURES; SEPTUM;
D O I
10.1016/j.crad.2020.01.002
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
AIM: To determine useful imaging features for differentiating hepatocellular carcinoma (HCC) categorised as LR-M from non-HCC malignancies in using the Liver Imaging-Reporting and Data System (LI-RADS) version 2018 on gadoxetic acid-enhanced magnetic resonance imaging (MRI). MATERIALS AND METHODS: Patients at high-risk for HCC with surgically confirmed HCCs (n=131) and non-HCC malignancies (n=90) and who had undergone gadoxetic acid-enhanced MRI were included. LI-RADS categories were assigned to identify hepatic observations defined as LR-M by two radiologists. Major and ancillary imaging features of hepatic observation with targetoid appearance including intratumoural septa were compared between HCCs and non-HCC malignancies. A classification tree analysis (CTA) was applied to differentiate high-risk HCCs from non-HCC malignancies in the LR-M category. RESULTS: A total of 36 HCCs (27.5%) and 70 non-HCC malignancies (77.8%) were assigned as LR-M. An enhancing capsule (p=0.0293), blood products in the mass (p=0.0393), non-targetoid restriction (p=0.018), and a septum (p=0.0053) were significantly predictive of HCC. On CTA, the presence of a septum was an initial predictor for a high probability of HCC followed by non-targetoid restriction. The CTA model has a sensitivity of 63.9%, specificity of 90%, and accuracy of 81.1% for differentiating HCC assigned LR-M from non-HCC malignancy. CONCLUSION: A considerable proportion of HCCs could have been categorised as LR-M as they had a targetoid appearance on gadoxetic acid-enhanced MRI. An intratumoural septum and non-targetoid restriction as well as enhancing capsule and blood products in the mass may be useful for differentiating HCC assigned to LR-M from non-HCC malignancy on gadoxetic acid-enhanced MRI. (C) 2020 Published by Elsevier Ltd on behalf of The Royal College of Radiologists.
引用
收藏
页码:478.e13 / 478.e23
页数:11
相关论文
共 46 条
  • [31] A gadoxetic acid-enhanced MRI-based multivariable model using LI-RADS v2018 and other imaging features for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma
    Liang, Yingying
    Xu, Fan
    Wang, Zihua
    Tan, Caihong
    Zhang, Nianru
    Wei, Xinhua
    Jiang, Xinqing
    Wu, Hongzhen
    EUROPEAN JOURNAL OF RADIOLOGY, 2022, 153
  • [32] A Semi-Automatic Step-by-Step Expert-Guided LI-RADS Grading System Based on Gadoxetic Acid-Enhanced MRI
    Sheng, Ruofan
    Huang, Jing
    Zhang, Weiguo
    Jin, Kaipu
    Yang, Li
    Chong, Huanhuan
    Fan, Jia
    Zhou, Jian
    Wu, Dijia
    Zeng, Mengsu
    JOURNAL OF HEPATOCELLULAR CARCINOMA, 2021, 8 : 671 - 683
  • [33] Comparison of Gadobenate-Enhanced MRI and Gadoxetate-Enhanced MRI for Hepatocellular Carcinoma Detection Using LI-RADS Version 2018: A Prospective Intraindividual Randomized Study
    Rong, Dailin
    He, Bingjun
    Tang, Wenjie
    Xie, Sidong
    Kuang, Sichi
    Grazioli, Luigi
    Hussain, Shahid M.
    Yang, Yang
    Wang, Jin
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2022, 218 (04) : 687 - 698
  • [34] LI-RADS v2018: utilizing ancillary features on gadoxetic acid-enhanced MRI to improve the diagnostic performance of small hapatocellular carcinoma (≤ 20 mm)
    Rong Lyu
    Weijuan Hu
    Di Wang
    Jiao Wang
    Zhongsong Gao
    Kefeng Jia
    Abdominal Radiology, 2023, 48 : 1987 - 1994
  • [35] LI-RADS v2018: utilizing ancillary features on gadoxetic acid-enhanced MRI to improve the diagnostic performance of small hapatocellular carcinoma (=20 mm)
    Lyu, Rong
    Hu, Weijuan
    Wang, Di
    Wang, Jiao
    Gao, Zhongsong
    Jia, Kefeng
    ABDOMINAL RADIOLOGY, 2023, 48 (06) : 1987 - 1994
  • [36] LI-RADS treatment response categorization on gadoxetic acid-enhanced MRI: diagnostic performance compared to mRECIST and added value of ancillary features
    Se Woo Kim
    Ijin Joo
    Hyo-Cheol Kim
    Su Joa Ahn
    Hyo-Jin Kang
    Sun Kyung Jeon
    Jeong Min Lee
    European Radiology, 2020, 30 : 2861 - 2870
  • [37] Intra-individual comparison of gadolinium-enhanced MRI using pseudo-golden-angle radial acquisition with gadoxetic acid-enhanced MRI for diagnosis of HCCs using LI-RADS
    Yoon-Chul Kim
    Ji Hye Min
    Young Kon Kim
    Soon Jin Lee
    Soohyun Ahn
    Eunju Kim
    Hans Peeters
    European Radiology, 2019, 29 : 2058 - 2068
  • [38] Application of Liver Imaging Reporting and Data System version 2018 ancillary features to upgrade from LR-4 to LR-5 on gadoxetic acid-enhanced MRI
    Lee, Sunyoung
    Kim, Seung-seob
    Bae, Heejin
    Shin, Jaeseung
    Yoon, Ja Kyung
    Kim, Myeong-Jin
    EUROPEAN RADIOLOGY, 2021, 31 (02) : 855 - 863
  • [39] Liver imaging reporting and data system (LI-RADS) v2018: comparison between computed tomography and gadoxetic acid-enhanced magnetic resonance imaging
    Sei Nakao
    Masahiro Tanabe
    Munemasa Okada
    Matakazu Furukawa
    Etsushi Iida
    Keisuke Miyoshi
    Naofumi Matsunaga
    Katsuyoshi Ito
    Japanese Journal of Radiology, 2019, 37 : 651 - 659
  • [40] Liver imaging reporting and data system (LI-RADS) v2018: comparison between computed tomography and gadoxetic acid-enhanced magnetic resonance imaging
    Nakao, Sei
    Tanabe, Masahiro
    Okada, Munemasa
    Furukawa, Matakazu
    Iida, Etsushi
    Miyoshi, Keisuke
    Matsunaga, Naofumi
    Ito, Katsuyoshi
    JAPANESE JOURNAL OF RADIOLOGY, 2019, 37 (09) : 651 - 659