The LI-RADS Version 2018 MRI Treatment Response Algorithm: Evaluation of Ablated Hepatocellular Carcinoma.


Background The Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is used to assess presumed hepatocellular carcinoma (HCC) after local-regional therapy, but its performance has not been extensively assessed. Purpose To assess the performance of LI-RADS version 2018 TRA in the evaluation of HCC after ablation. Materials and Methods In this retrospective study, patients who underwent ablation therapy for presumed HCC followed by liver transplantation between January 2011 and December 2015 at a single tertiary care center were identified. Lesions were categorized as completely (100%) or incompletely (≤99%) necrotic based on transplant histology. Three radiologists assessed pre- and posttreatment MRI findings using LI-RADS version 2018 and the TRA, respectively. Interreader agreement was assessed by using the Fleiss κ test. Performance characteristics for predicting necrosis category based on LI-RADS treatment response (LR-TR) category (viable or nonviable) were calculated by using generalized mixed-effects models to account for clustering by subject. Results A total of 36 patients (mean age, 58 years ± 5 [standard deviation]; 32 men) with 53 lesions was included. Interreader agreement for pretreatment LI-RADS category was 0.40 (95% confidence interval [CI]: 0.15, 0.67; P < .01) and was lower than the interreader agreement for TRA category (κ = 0.71; 95% CI: 0.59, 0.84; P < .01). After accounting for clustering by subject, sensitivity of tumor necrosis across readers ranged from 40% to 77%, and specificity ranged from 85% to 97% when LR-TR equivocal assessments were treated as nonviable. When LR-TR equivocal assessments were treated as viable, sensitivity of tumor necrosis across readers ranged from 81% to 87%, and specificity ranged from 81% to 85% across readers. Six (11%) of 53 treated lesions were LR-TR equivocal by consensus, with most (five of six) incompletely necrotic at histopathology. Conclusion The Liver Imaging Reporting and Data System treatment response algorithm can be used to predict viable or nonviable hepatocellular carcinoma after ablation. Most ablated lesions rated as treatment response equivocal were incompletely necrotic at histopathology. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Do and Mendiratta-Lala in this issue.






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Publication Info

Chaudhry, Mohammad, Katrina A McGinty, Benjamin Mervak, Reginald Lerebours, Cai Li, Erin Shropshire, James Ronald, Leah Commander, et al. (2019). The LI-RADS Version 2018 MRI Treatment Response Algorithm: Evaluation of Ablated Hepatocellular Carcinoma. Radiology. p. 191581. 10.1148/radiol.2019191581 Retrieved from

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Reginald (Gino) Lerebours

Biostatistician II

Education: Masters Degree, Biostatistics. Harvard University. 2017
Bachelors Degree, Statistics. North Carolina State University. 2015

Overview:  Gino currently collaborates with researchers, residents, and clinicians in the Departments of Surgery, Radiology and Infectious Diseases. His main research interests and experience are in statistical programming, data management, statistical modeling, statistical consulting and statistical education.


James Spencer Ronald

Associate Professor of Radiology

Sheng Luo

Professor of Biostatistics & Bioinformatics

Mustafa Shadi Rifaat Bashir

Professor of Radiology

Hepatobiliary and pancreatic imaging
Liver cancer (hepatocellular carcinoma)
Fatty liver, NAFLD, and NASH
Chronic liver disease and cirrhosis
Pancreatic cancer
Technical development in MRI
Quantitative imaging

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