ArticleAbdominal radiology (New York)2022
Inter-observer agreement using the LI-RADS version 2018 CT treatment response algorithm in patients with hepatocellular carcinoma treated with conventional transarterial chemoembolization.
Article in Abdominal radiology (New York), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The 2024 LI-RADS treatment response update: practical reporting after non-radiation and radiation locoregional therapies for hepatocellular carcinoma.Insights into imaging · 2026Review
- LI-RADS CT/MRI Treatment Response Assessment Update in 2024.Journal of the Korean Society of Radiology · 2025Review
- Article
- CT/MRI LI-RADS 2024 Update: Treatment Response Assessment.Radiology · 2024Review
- Updates on LI-RADS Treatment Response Criteria for Hepatocellular Carcinoma: Focusing on MRI.Journal of magnetic resonance imaging : JMRI · 2023Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo determine inter-reader agreement in categorization of imaging features using the Liver Imaging Reporting and Data System (LI-RADS) treatment response (LR-TR) algorithm in patients with hepatocellular carcinoma (HCC) treated with conventional transarterial chemoembolization (cTACE).
methodsTwo radiologists used the LR-TR algorithm to assess 112 computed tomography (CT) examinations of 102 patients treated with cTACE. The inter-observer agreement in categorization of LR-TR features was assessed using kappa (κ) statistics.
resultsThere was substantial inter-observer agreement between the two reviewers using the LR-TR algorithm (κ = 0.70; 95% CI 0.58-0.81). The two reviewers categorized tumors as non-viable in 37 (33.0%) and 39 (34.8%) of 112 examinations, viable in 58 (51.8%) and 62 (55.4%) examinations, and equivocal in 18 (16.1%) and 11 (9.8%) examinations, respectively. There was almost perfect inter-observer agreement for the LR-TR non-viable category (κ = 0.80; 95% CI 0.68-0.92), substantial agreement for the viable category (κ = 0.78 95% CI 0.67-0.90), and fair agreement for the equivocal category (κ = 0.25; 95% CI 0.02-0.49).
conclusionThe LR-TR algorithm conveys high degrees of inter-observer agreement for the assessment of CT imaging features in the viable and non-viable categories. Further refinement of indeterminate features may be necessary to improve the correct categorization of equivocal lesions.
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