Trial reportEuropean radiology2023
Radiomics nomograms based on R2* mapping and clinical biomarkers for staging of liver fibrosis in patients with chronic hepatitis B: a single-center retrospective study.
Trial report in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Role of radiomics in staging liver fibrosis: a meta-analysis.BMC medical imaging · 2024Pooled it
- Multimodal artificial intelligence models for liver fibrosis staging: a scoping review.Abdominal radiology (New York) · 2026Review
- Exploring Transcriptomic and MRI-Derived Parameters Correlations in NAFLD Fibrosis: Insights from a Rat Model.Digestive diseases and sciences · 2026Article
- Radiomics analysis based on T2-weighed imaging and T2 mapping for staging endometrial fibrosis.Scientific reports · 2025Article
- Radiomic analysis using T1 mapping in gadoxetic acid disodium-enhanced MRI for liver function assessment.BMC medical imaging · 2025Article
- A combination model of CT-based radiomics and clinical biomarkers for staging liver fibrosis in the patients with chronic liver disease.Scientific reports · 2024Article
- Quantitative measurements of M2BPGi depend on liver fibrosis and inflammation.Journal of gastroenterology · 2024Article
- Staging liver fibrosis: comparison of radiomics model and fusion model based on multiparametric MRI in patients with chronic liver disease.Abdominal radiology (New York) · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate the value of R2* mapping-based radiomics nomograms in staging liver fibrosis in patients with chronic hepatitis B.
methodsBetween January 2020 and December 2020, 151 patients with chronic hepatitis B were randomly divided into training (n = 103) and validation (n = 48) cohorts. From January to February 2021, 58 patients were included in a test cohort. Radiomics features were selected using the interclass correlation coefficient and least absolute shrinkage and selection operator method. Three radiomics nomograms, combining the radiomics score (Radscore) derived from R2* mapping and clinical variables, were used for staging significant and advanced fibrosis, and cirrhosis. Performance of the model was evaluated using the AUC. The utility and clinical benefits were evaluated using the continuous net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).
resultsThe Radscore calculated by 12 radiomics features and independent factors (laminin and platelet) of advanced fibrosis were used to construct the radiomics nomograms. In the test cohort, the AUCs of the radiomics nomograms for staging significant fibrosis, advanced fibrosis, and cirrhosis were 0.738 (95% confidence interval [CI]: 0.604-0.872), 0.879 (95% CI: 0.779-0.98), and 0.952 (95% CI: 0.878-1), respectively. NRI, IDI, and DCA confirmed that radiomics nomograms demonstrated varying degrees of clinical benefit and improvement for advanced fibrosis and cirrhosis, but not for significant fibrosis.
conclusionsRadiomics nomograms combined with R2* mapping-based Radscore, laminin, and platelet have value in staging advanced fibrosis and cirrhosis but limited value for staging significant fibrosis. KEY POINTS: • Laminin and platelets were independent predictors of advanced fibrosis. • Radiomics analysis based on R2* mapping was beneficial for evaluating advanced fibrosis and cirrhosis. • It was difficult to distinguish significant fibrosis using a radiomics nomogram, which is possibly due to the complex pathological microenvironment of chronic liver diseases.
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