Literature DB >> 29634435

LI-RADS for MR Imaging Diagnosis of Hepatocellular Carcinoma: Performance of Major and Ancillary Features.

Milena Cerny1, Catherine Bergeron1, Jean-Sébastien Billiard1, Jessica Murphy-Lavallée1, Damien Olivié1, Joshua Bérubé1, Boyan Fan1, Hélène Castel1, Simon Turcotte1, Pierre Perreault1, Miguel Chagnon1, An Tang1.   

Abstract

Purpose To evaluate the performance of major features, ancillary features, and categories of Liver Imaging Reporting and Data System (LI-RADS) version 2014 at magnetic resonance (MR) imaging for the diagnosis of hepatocellular carcinoma (HCC). Materials and Methods This retrospective institutional review board-approved study included patients with liver MR imaging and at least one pathologically proved lesion. Between 2004 and 2016, 102 patients (275 observations including 113 HCCs) met inclusion criteria. Two radiologists independently assessed major and ancillary imaging features for each liver observation and assigned a LI-RADS category. Per-lesion estimates of diagnostic performance of major features, ancillary features, and LI-RADS categories were assessed by using generalized estimating equation models. Results Major features (arterial phase hyperenhancement, washout, capsule, and threshold growth) had a sensitivity of 88.5%, 60.6%, 32.9%, and 41.6%, and a specificity of 18.6%, 84.8%, 98.8%, and 83.2% for HCC, respectively. Ancillary features (mild-moderate T2 hyperintensity, restricted diffusion, mosaic architecture, intralesional fat, lesional fat sparing, blood products, and subthreshold growth) had a sensitivity of 62.2%, 54.8%, 9.9%, 30.9%, 23.1%, 2.8%, and 48.3%, and a specificity of 79.4%, 90.6%, 99.4%, 94.2%, 83.1%, 99.3%, and 91.4% for HCC, respectively. The LR-5 or LR-5 V categories had a per-lesion sensitivity of 50.8% and a specificity of 95.8% for HCC, respectively. The LR-4, LR-5, or LR-5 V categories (determined by using major features only vs combination of major and ancillary features) had a per-lesion sensitivity of 75.9% and 87.9% and a per-lesion specificity of 87.5% and 86.2%, respectively. Conclusion The use of ancillary features in combination with major features increases the sensitivity while preserving a high specificity for the diagnosis of HCC. © RSNA, 2018 Online supplemental material is available for this article.

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Year:  2018        PMID: 29634435     DOI: 10.1148/radiol.2018171678

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  20 in total

1.  Increasing the sensitivity of LI-RADS v2018 for diagnosis of small (10-19 mm) HCC on extracellular contrast-enhanced MRI.

Authors:  Jingbiao Chen; Sichi Kuang; Yao Zhang; Wenjie Tang; Sidong Xie; Linqi Zhang; Dailin Rong; Bingjun He; Ying Deng; Yuanqiang Xiao; Wenqi Shi; Kathryn Fowler; Jin Wang; Claude B Sirlin
Journal:  Abdom Radiol (NY)       Date:  2020-10-11

2.  Retrospective validation of a new diagnostic criterion for hepatocellular carcinoma on gadoxetic acid-enhanced MRI: can hypointensity on the hepatobiliary phase be used as an alternative to washout with the aid of ancillary features?

Authors:  Ijin Joo; Jeong Min Lee; Dong Ho Lee; Ju Hyeon Jeon; Joon Koo Han
Journal:  Eur Radiol       Date:  2018-09-25       Impact factor: 5.315

Review 3.  Joint Consensus Statement of the Indian National Association for Study of the Liver and Indian Radiological and Imaging Association for the Diagnosis and Imaging of Hepatocellular Carcinoma Incorporating Liver Imaging Reporting and Data System.

Authors:  Sonal Krishan; Radha K Dhiman; Navin Kalra; Raju Sharma; Sanjay S Baijal; Anil Arora; Ajay Gulati; Anu Eapan; Ashish Verma; Shyam Keshava; Amar Mukund; S Deva; Ravi Chaudhary; Karthick Ganesan; Sunil Taneja; Ujjwal Gorsi; Shivanand Gamanagatti; Kumble S Madhusudan; Pankaj Puri; Shallini Govil; Manav Wadhavan; Sanjiv Saigal; Ashish Kumar; Shallini Thapar; Ajay Duseja; Neeraj Saraf; Anubhav Khandelwal; Sumit Mukhopadyay; Ajay Gulati; Nitin Shetty; Nipun Verma
Journal:  J Clin Exp Hepatol       Date:  2019-08-06

Review 4.  Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma.

Authors:  Guilherme Moura Cunha; Victoria Chernyak; Kathryn J Fowler; Claude B Sirlin
Journal:  J Hepatocell Carcinoma       Date:  2021-05-31

5.  LI-RADS ancillary features favoring benignity: is there a role in LR-5 observations?

Authors:  Roberto Cannella; Federica Vernuccio; Michela Antonucci; Domenico Salvatore Gagliano; Francesco Matteini; Massimo Midiri; Giuseppe Brancatelli
Journal:  Eur Radiol       Date:  2021-09-20       Impact factor: 7.034

6.  Tumor size-based validation of contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS) 2017 for hepatocellular carcinoma characterizing.

Authors:  Jia-Min Pan; Wei Chen; Yan-Ling Zheng; Mei-Qing Cheng; Dan Zeng; Hui Huang; Yang Huang; Xiao-Yan Xie; Ming-De Lu; Ming Kuang; Hang-Tong Hu; Li-Da Chen; Wei Wang
Journal:  Br J Radiol       Date:  2021-10-01       Impact factor: 3.629

7.  Fat-only Dixon: how to use it in body MRI.

Authors:  Reza Salari; David H Ballard; Mark J Hoegger; Daniel Young; Anup S Shetty
Journal:  Abdom Radiol (NY)       Date:  2022-05-18

Review 8.  Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients.

Authors:  Victoria Chernyak; Kathryn J Fowler; Aya Kamaya; Ania Z Kielar; Khaled M Elsayes; Mustafa R Bashir; Yuko Kono; Richard K Do; Donald G Mitchell; Amit G Singal; An Tang; Claude B Sirlin
Journal:  Radiology       Date:  2018-09-25       Impact factor: 11.105

9.  Can Risk Stratification Based on Ultrasound Elastography of Background Liver Assist CEUS LI-RADS in the Diagnosis of HCC?

Authors:  Jiawu Li; Wenwu Ling; Shuang Chen; Lulu Yang; Lin Ma; Qiang Lu; Yan Luo
Journal:  Front Oncol       Date:  2021-04-30       Impact factor: 6.244

Review 10.  CT/MRI LI-RADS v2018 vs. CEUS LI-RADS v2017-Can Things Be Put Together?

Authors:  Cosmin Caraiani; Bianca Boca; Vlad Bura; Zeno Sparchez; Yi Dong; Christoph Dietrich
Journal:  Biology (Basel)       Date:  2021-05-06
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