ArticleEuropean radiology2020
LI-RADS treatment response categorization on gadoxetic acid-enhanced MRI: diagnostic performance compared to mRECIST and added value of ancillary features.
Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- LI-RADS treatment response algorithm for detecting incomplete necrosis in hepatocellular carcinoma after locoregional treatment: a systematic review and meta-analysis using individual patient data.Abdominal radiology (New York) · 2021Pooled it
- Diagnostic performance of Liver Imaging Reporting and Data System treatment response algorithm: a systematic review and meta-analysis.European radiology · 2021Pooled it
- Hepatobiliary phase imaging in HCC: revisiting diagnostic algorithms and clinical utility of gadoxetic acid-enhanced MRI across international guidelines.Insights into imaging · 2026Review
- Diagnostic performance of liver imaging reporting and data system ancillary features for hepatocellular carcinoma: a systematic review and evidence synthesis.Abdominal radiology (New York) · 2026Review
- LI-RADS nonradiation treatment response assessment version 2024: diagnostic performance in HCC treated with transarterial chemoembolization.European radiology · 2026Article
- Hepatocellular carcinoma treatment response: Imaging findings and criteria.World journal of radiology · 2025Review
- Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.Abdominal radiology (New York) · 2025Article
- Assessment of viable tumours by [European journal of nuclear medicine and molecular imaging · 2025Article
- 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
- LI-RADS version 2018 treatment response algorithm on extracellular contrast-enhanced MRI in patients treated with transarterial chemoembolization for hepatocellular carcinoma: diagnostic performance and the added value of ancillary features.Abdominal radiology (New York) · 2024Article
- Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.Abdominal radiology (New York) · 2024Article
- Updates on LI-RADS Treatment Response Criteria for Hepatocellular Carcinoma: Focusing on MRI.Journal of magnetic resonance imaging : JMRI · 2023Review
- Evaluation and Prediction of Treatment Response for Hepatocellular Carcinoma.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2023Article
- Gadoxetic acid-enhanced MRI with a focus on LI-RADS v2018 imaging features predicts the prognosis after radiofrequency ablation in small hepatocellular carcinoma.Frontiers in oncology · 2023Article
- [CT/MRI Liver Imaging Reporting and Data System (LI-RADS): Standardization, Evidence, and Future Direction].Journal of the Korean Society of Radiology · 2023Review
- Application of Intravoxel Incoherent Motion in the Evaluation of Hepatocellular Carcinoma after Transarterial Chemoembolization.Current oncology (Toronto, Ont.) · 2022Article
- Role of gadoxetic acid-enhanced liver magnetic resonance imaging in the evaluation of hepatocellular carcinoma after locoregional treatment.World journal of gastroenterology · 2022Review
- Characterization and Prediction of Signal Intensity Changes in Normal Liver Parenchyma on Gadoxetic Acid-enhanced MRI Scans after Liver-directed Radiation Therapy.Radiology. Imaging cancer · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
objectivesThis study was conducted in order to assess the performance of the Liver Imaging Reporting and Data System (LI-RADS) treatment response (TR) (LR-TR) categorization on gadoxetic acid-enhanced MRI (Gd-EOB-MRI) for detecting viable tumors in hepatocellular carcinoma (HCC) treated with locoregional treatment (LRT) and to investigate the added value of ancillary features (AFs) to conventional enhancement-based criteria.
methodsThis retrospective study included 183 patients with Gd-EOB-MRI after LRT for HCC and appropriate reference standards for tumor viability (84 viable and 99 nonviable). Two independent radiologists assigned per-lesion mRECIST and TR categories (TR-nonviable, TR-equivocal, or TR-viable) according to the LR-TR algorithm and modified LR-TR algorithms including mLR-TR(TP) allowing transitional phase (TP) washout and mLR-TR(AF) allowing category adjustment by applying AFs. Diagnostic performances of imaging criteria were compared using the Cochran's Q test with post hoc analysis.
resultsFor detecting viable tumors, LR-TR-viable resulted in sensitivities of 64.5%/39.3% and specificities of 98.0%/98.0% in reviewers 1/2. In comparison to LR-TR-viable, mRECIST-viable, mLR-TR(TP)-viable, and mLR-TR(AF)-viable showed significantly higher sensitivities (92.9%/94.0%, 77.4%/56.6%, and 86.9%/83.3% in reviewers 1/2) (ps < 0.001). The specificity of mRECIST-viable (73.7%/62.6%) was significantly lower than that of LR-TR-viable (ps < 0.001), while those of mLR-TR(TP)-viable and mLR-TR(AF)-viable were greater than 95% (98.0%/96.0% and 97.0%/96.0%), statistically equivalent to LR-TR-viable (ps > 0.05). TR-equivocal was least assigned on mLR-TR(AF) (1.1%/7.7%) than LR-TR (15.8%/32.2%) or mLR-TR(TP) (6.6%/23.5%) in both reviewers.
conclusionThe LR-TR algorithm on Gd-EOB-MRI provides a specific diagnosis of viable tumor but with limited sensitivity. By applying AFs in the category adjustment, more sensitive and confident diagnosis can be achieved without significant loss of specificity. KEY POINTS: • The LI-RADS treatment response (LR-TR) algorithm on Gd-EOB-MRI provides a highly specific diagnosis of viable HCC but with limited sensitivity. • The inferior sensitivity of LR-TR-viable category to that of mRECIST can be improved by applying ancillary features in the category adjustment.
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