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LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma

OBJECTIVE: To assess the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 treatment response algorithm (TRA) for the evaluation of hepatocellular carcinoma (HCC) treated with transarterial radioembolization. MATERIALS AND METHODS: This retrospective study...

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Autores principales: Yoon, Jongjin, Lee, Sunyoung, Shin, Jaeseung, Kim, Seung-seob, Kim, Gyoung Min, Won, Jong Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316770/
https://www.ncbi.nlm.nih.gov/pubmed/33987991
http://dx.doi.org/10.3348/kjr.2020.1159
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author Yoon, Jongjin
Lee, Sunyoung
Shin, Jaeseung
Kim, Seung-seob
Kim, Gyoung Min
Won, Jong Yun
author_facet Yoon, Jongjin
Lee, Sunyoung
Shin, Jaeseung
Kim, Seung-seob
Kim, Gyoung Min
Won, Jong Yun
author_sort Yoon, Jongjin
collection PubMed
description OBJECTIVE: To assess the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 treatment response algorithm (TRA) for the evaluation of hepatocellular carcinoma (HCC) treated with transarterial radioembolization. MATERIALS AND METHODS: This retrospective study included patients who underwent transarterial radioembolization for HCC followed by hepatic surgery between January 2011 and December 2019. The resected lesions were determined to have either complete (100%) or incomplete (< 100%) necrosis based on histopathology. Three radiologists independently reviewed the CT or MR images of pre- and post-treatment lesions and assigned categories based on the LI-RADS version 2018 and the TRA, respectively. Diagnostic performances of LI-RADS treatment response (LR-TR) viable and nonviable categories were assessed for each reader, using histopathology from hepatic surgeries as a reference standard. Inter-reader agreements were evaluated using Fleiss κ. RESULTS: A total of 27 patients (mean age ± standard deviation, 55.9 ± 9.1 years; 24 male) with 34 lesions (15 with complete necrosis and 19 with incomplete necrosis on histopathology) were included. To predict complete necrosis, the LR-TR nonviable category had a sensitivity of 73.3–80.0% and a specificity of 78.9–89.5%. For predicting incomplete necrosis, the LR-TR viable category had a sensitivity of 73.7–79.0% and a specificity of 93.3–100%. Five (14.7%) of 34 treated lesions were categorized as LR-TR equivocal by consensus, with two of the five lesions demonstrating incomplete necrosis. Inter-reader agreement for the LR-TR category was 0.81 (95% confidence interval: 0.66–0.96). CONCLUSION: The LI-RADS version 2018 TRA can be used to predict the histopathologic viability of HCCs treated with transarterial radioembolization.
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spelling pubmed-83167702021-08-03 LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma Yoon, Jongjin Lee, Sunyoung Shin, Jaeseung Kim, Seung-seob Kim, Gyoung Min Won, Jong Yun Korean J Radiol Gastrointestinal Imaging OBJECTIVE: To assess the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 treatment response algorithm (TRA) for the evaluation of hepatocellular carcinoma (HCC) treated with transarterial radioembolization. MATERIALS AND METHODS: This retrospective study included patients who underwent transarterial radioembolization for HCC followed by hepatic surgery between January 2011 and December 2019. The resected lesions were determined to have either complete (100%) or incomplete (< 100%) necrosis based on histopathology. Three radiologists independently reviewed the CT or MR images of pre- and post-treatment lesions and assigned categories based on the LI-RADS version 2018 and the TRA, respectively. Diagnostic performances of LI-RADS treatment response (LR-TR) viable and nonviable categories were assessed for each reader, using histopathology from hepatic surgeries as a reference standard. Inter-reader agreements were evaluated using Fleiss κ. RESULTS: A total of 27 patients (mean age ± standard deviation, 55.9 ± 9.1 years; 24 male) with 34 lesions (15 with complete necrosis and 19 with incomplete necrosis on histopathology) were included. To predict complete necrosis, the LR-TR nonviable category had a sensitivity of 73.3–80.0% and a specificity of 78.9–89.5%. For predicting incomplete necrosis, the LR-TR viable category had a sensitivity of 73.7–79.0% and a specificity of 93.3–100%. Five (14.7%) of 34 treated lesions were categorized as LR-TR equivocal by consensus, with two of the five lesions demonstrating incomplete necrosis. Inter-reader agreement for the LR-TR category was 0.81 (95% confidence interval: 0.66–0.96). CONCLUSION: The LI-RADS version 2018 TRA can be used to predict the histopathologic viability of HCCs treated with transarterial radioembolization. The Korean Society of Radiology 2021-08 2021-05-04 /pmc/articles/PMC8316770/ /pubmed/33987991 http://dx.doi.org/10.3348/kjr.2020.1159 Text en Copyright © 2021 The Korean Society of Radiology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Gastrointestinal Imaging
Yoon, Jongjin
Lee, Sunyoung
Shin, Jaeseung
Kim, Seung-seob
Kim, Gyoung Min
Won, Jong Yun
LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma
title LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma
title_full LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma
title_fullStr LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma
title_full_unstemmed LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma
title_short LI-RADS Version 2018 Treatment Response Algorithm: Diagnostic Performance after Transarterial Radioembolization for Hepatocellular Carcinoma
title_sort li-rads version 2018 treatment response algorithm: diagnostic performance after transarterial radioembolization for hepatocellular carcinoma
topic Gastrointestinal Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316770/
https://www.ncbi.nlm.nih.gov/pubmed/33987991
http://dx.doi.org/10.3348/kjr.2020.1159
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