ArticleHepatobiliary surgery and nutrition2022
A novel radiomics signature based on T2-weighted imaging accurately predicts hepatic inflammation in individuals with biopsy-proven nonalcoholic fatty liver disease: a derivation and independent validation study.
Article in Hepatobiliary surgery and nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Application of machine learning and deep learning in metabolic dysfunction-associated steatotic liver disease: a systematic review and meta-analysis.Journal of advanced research · 2026Pooled it
- CT-based radiomics-clinical model for risk assessment of parenteral nutrition-associated hepatic steatosis in chronic intestinal failure and its metabolomic interpretation.Frontiers in nutrition · 2026Article
- Multi-model applications and cutting-edge advancements of artificial intelligence in hepatology in the era of precision medicine.World journal of gastroenterology · 2025Review
- Efficient and Specific PDGFRβ-Targeting Dual-Mode TAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Reply to correspondence on "Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients".Clinical and molecular hepatology · 2024Article
- Association between paravertebral muscle radiological parameter alterations and non-alcoholic fatty liver disease.Abdominal radiology (New York) · 2024Article
- [Application of omics in the diagnosis of metabolic dysfunction-associated fatty liver disease].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2023Article
- Clinic-radiomics model using liver magnetic resonance imaging helps predict chronicity of drug-induced liver injury.Hepatology international · 2023Article
- Hepatic inflammation: an important target for biomarker development in nonalcoholic fatty liver disease.Hepatobiliary surgery and nutrition · 2023Article
- Non-invasive tests of non-alcoholic fatty liver disease.Chinese medical journal · 2022Review
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13 authors at 7 institutions in 3 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Currently, there are no effective methods for assessing hepatic inflammation without resorting to histological examination of liver tissue obtained by biopsy. T2-weighted images (T2WI) are routinely obtained from liver magnetic resonance imaging (MRI) scan sequences. We aimed to establish a radiomics signature based on T2WI (T2-RS) for assessment of hepatic inflammation in people with nonalcoholic fatty liver disease (NAFLD). Methods: A total of 203 individuals with biopsy-confirmed NAFLD from two independent Chinese cohorts with liver MRI examination were enrolled in this study. The hepatic inflammatory activity score (IAS) was calculated by the unweighted sum of the histologic scores for lobular inflammation and ballooning. One thousand and thirty-two radiomics features were extracted from the localized region of interest (ROI) in the right liver lobe of T2WI and, subsequently, selected by minimum redundancy maximum relevance and least absolute shrinkage and selection operator (LASSO) methods. The T2-RS was calculated by adding the selected features weighted by their coefficients. Results: Eighteen radiomics features from Laplacian of Gaussian, wavelet, and original images were selected for establishing T2-RS. The T2-RS value differed significantly between groups with increasing grades of hepatic inflammation (P<0.01). The T2-RS yielded an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.80 [95% confidence interval (CI): 0.71-0.89] for predicting hepatic inflammation in the training cohort with excellent calibration. The AUROCs of T2-RS in the internal cohort and external validation cohorts were 0.77 (0.61-0.93) and 0.75 (0.63-0.84), respectively. Conclusions: The T2-RS derived from radiomics analysis of T2WI shows promising utility for predicting hepatic inflammation in individuals with NAFLD.
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