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Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system

BACKGROUND: Hepatocellular carcinoma (HCC) can be diagnosed non-invasively, provided certain imaging criteria are met. However, the recent Liver Imaging Reporting and Data System (LI-RADS) version 2018 has not been widely validated. OBJECTIVES: This study aimed to evaluate the diagnostic accuracy an...

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Autores principales: Singh, Ranjit, Wilson, Mitchell P., Manolea, Florin, Ahmed, Bilal, Fung, Christopher, Receveur, Darryn, Low, Gavin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AOSIS 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210145/
https://www.ncbi.nlm.nih.gov/pubmed/35747784
http://dx.doi.org/10.4102/sajr.v26i1.2386
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author Singh, Ranjit
Wilson, Mitchell P.
Manolea, Florin
Ahmed, Bilal
Fung, Christopher
Receveur, Darryn
Low, Gavin
author_facet Singh, Ranjit
Wilson, Mitchell P.
Manolea, Florin
Ahmed, Bilal
Fung, Christopher
Receveur, Darryn
Low, Gavin
author_sort Singh, Ranjit
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) can be diagnosed non-invasively, provided certain imaging criteria are met. However, the recent Liver Imaging Reporting and Data System (LI-RADS) version 2018 has not been widely validated. OBJECTIVES: This study aimed to evaluate the diagnostic accuracy and reader reliability of the LI-RADS version 2018 lexicon amongst fellowship trained radiologists compared with an expert consensus reference standard. METHOD: This retrospective study was conducted between 2018 and 2020. A total of 50 contrast enhanced liver magnetic resonance imaging (MRI) studies evaluating focal liver observations in patients with cirrhosis, hepatitis B virus (HBV) or prior HCC were acquired. The standard of reference was a consensus review by three fellowship-trained radiologists. Diagnostic accuracy including sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV) and area under the curve (AUC) values were calculated per LI-RADS category for each reader. Kappa statistics were used to measure reader agreement. RESULTS: Readers demonstrated excellent specificities (88% – 100%) and NPVs (85% – 100%) across all LI-RADS categories. Sensitivities were variable, ranging from 67% to 83% for LI-RADS 1, 29% to 43% for LI-RADS 2, 100% for LI-RADS 3, 70% to 80% for LI-RADS 4 and 80% to 84% for LI-RADS 5. Readers showed excellent accuracy for differentiating benign and malignant liver lesions with AUC values > 0.90. Overall inter-reader agreement was ‘good’ (kappa = 0.76, p < 0.001). Pairwise inter-reader agreement was ‘very good’ (kappa ≥ 0.90, p < 0.001). CONCLUSION: The LI-RADS version 2018 demonstrates excellent specificity, NPV and AUC values for risk stratification of liver observations by radiologists. Liver Imaging Reporting and Data System can reliably differentiate benign from malignant lesions when used in conjunction with corresponding LI-RADS management recommendations.
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spelling pubmed-92101452022-06-22 Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system Singh, Ranjit Wilson, Mitchell P. Manolea, Florin Ahmed, Bilal Fung, Christopher Receveur, Darryn Low, Gavin SA J Radiol Original Research BACKGROUND: Hepatocellular carcinoma (HCC) can be diagnosed non-invasively, provided certain imaging criteria are met. However, the recent Liver Imaging Reporting and Data System (LI-RADS) version 2018 has not been widely validated. OBJECTIVES: This study aimed to evaluate the diagnostic accuracy and reader reliability of the LI-RADS version 2018 lexicon amongst fellowship trained radiologists compared with an expert consensus reference standard. METHOD: This retrospective study was conducted between 2018 and 2020. A total of 50 contrast enhanced liver magnetic resonance imaging (MRI) studies evaluating focal liver observations in patients with cirrhosis, hepatitis B virus (HBV) or prior HCC were acquired. The standard of reference was a consensus review by three fellowship-trained radiologists. Diagnostic accuracy including sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV) and area under the curve (AUC) values were calculated per LI-RADS category for each reader. Kappa statistics were used to measure reader agreement. RESULTS: Readers demonstrated excellent specificities (88% – 100%) and NPVs (85% – 100%) across all LI-RADS categories. Sensitivities were variable, ranging from 67% to 83% for LI-RADS 1, 29% to 43% for LI-RADS 2, 100% for LI-RADS 3, 70% to 80% for LI-RADS 4 and 80% to 84% for LI-RADS 5. Readers showed excellent accuracy for differentiating benign and malignant liver lesions with AUC values > 0.90. Overall inter-reader agreement was ‘good’ (kappa = 0.76, p < 0.001). Pairwise inter-reader agreement was ‘very good’ (kappa ≥ 0.90, p < 0.001). CONCLUSION: The LI-RADS version 2018 demonstrates excellent specificity, NPV and AUC values for risk stratification of liver observations by radiologists. Liver Imaging Reporting and Data System can reliably differentiate benign from malignant lesions when used in conjunction with corresponding LI-RADS management recommendations. AOSIS 2022-05-19 /pmc/articles/PMC9210145/ /pubmed/35747784 http://dx.doi.org/10.4102/sajr.v26i1.2386 Text en © 2022. The Authors https://creativecommons.org/licenses/by/4.0/Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License.
spellingShingle Original Research
Singh, Ranjit
Wilson, Mitchell P.
Manolea, Florin
Ahmed, Bilal
Fung, Christopher
Receveur, Darryn
Low, Gavin
Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system
title Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system
title_full Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system
title_fullStr Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system
title_full_unstemmed Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system
title_short Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system
title_sort diagnostic accuracy and inter-reader reliability of the mri liver imaging reporting and data system (version 2018) risk stratification and management system
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210145/
https://www.ncbi.nlm.nih.gov/pubmed/35747784
http://dx.doi.org/10.4102/sajr.v26i1.2386
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