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BackgroundStatins have multiple benefits in patients with metabolic-associated steatotic liver disease (MASLD).AimTo explore the effects of statins on the long-term risk of all-cause mortality, liver-related clinical events (LREs) and liver stiffness progression in patients with MASLD.MethodsThis cohort study collected data on patients with MASLD undergoing at least two vibration-controlled transient elastography examinations at 16 tertiary referral centres. Cox regression analysis was performed to examine the association between statin usage and long-term risk of all-cause mortality and LREs stratified by compensated advanced chronic liver disease (cACLD): baseline liver stiffness measurement (LSM) of ≥10 kPa. Liver stiffness progression was defined as an LSM increase of ≥20% for cACLD and from <10 kPa to ≥10 or LSM for non-cACLD. Liver stiffness regression was defined as LSM reduction from ≥10 kPa to <10 or LSM decrease of ≥20% for cACLD.ResultsWe followed up 7988 patients with baseline LSM 5.9 kPa (IQR 4.6–8.2) for a median of 4.6 years. At baseline, 40.5% of patients used statins, and cACLD was present in 17%. Statin usage was significantly associated with a lower risk of all-cause mortality (adjusted HR=0.233; 95% CI 0.127 to 0.426) and LREs (adjusted HR=0.380; 95% CI 0.268 to 0.539). Statin usage was also associated with lower liver stiffness progression rates in cACLD (HR=0.542; 95% CI 0.389 to 0.755) and non-cACLD (adjusted HR=0.450; 95% CI 0.342 to 0.592), but not with liver stiffness regression (adjusted HR=0.914; 95% CI 0.778 to 1.074).ConclusionsStatin usage was associated with a relatively lower long-term risk of all-cause mortality, LREs and liver stiffness progression in patients with MASLD.

BackgroundDynamic changes in non-invasive tests, such as changes in alanine aminotransferase (ALT) and MRI proton-density-fat-fraction (MRI-PDFF), may help to detect metabolic dysfunction-associated steatohepatitis (MASH) resolution, but a combination of non-invasive tests may be more accurate than either alone. We developed a novel non-invasive score, the MASH Resolution Index, to detect the histological resolution of MASH.MethodsThis study included a derivation cohort of 95 well-characterised adult participants (67% female) with biopsy-confirmed MASH who underwent contemporaneous laboratory testing, MRI-PDFF and liver biopsy at two time points. The primary objective was to develop a non-invasive score to detect MASH resolution with no worsening of fibrosis. The most predictive logistic regression model was selected based on the highest area under the receiver operating curve (AUC), and the lowest Akaike information criterion and Bayesian information criterion. The model was then externally validated in a distinct cohort of 163 participants with MASH from a clinical trial.ResultsThe median (IQR) age and body mass index were 55 (45–62) years and 32.0 (30–37) kg/m2, respectively, in the derivation cohort. The most accurate model (MASH Resolution Index) included MRI-PDFF, ALT and aspartate aminotransferase. The index had an AUC of 0.81 (95% CI 0.69 to 0.93) for detecting MASH resolution in the derivation cohort. The score calibrated well and performed robustly in a distinct external validation cohort (AUC 0.83, 95% CI 0.76 to 0.91), and outperformed changes in ALT and MRI-PDFF.ConclusionThe MASH Resolution Index may be a useful score to non-invasively identify MASH resolution.

BackgroundSeveral preliminary reports have suggested the utility of ultrasound attenuation coefficient measurements based on B-mode ultrasound, such as iATT, for diagnosing steatotic liver disease. Nonetheless, evidence supporting such utility is lacking. This prospective study aimed to investigate whether iATT is highly concordant with magnetic resonance imaging (MRI)-based proton density fat fraction (MRI-PDFF) and could well distinguish between steatosis grades.MethodsA cohort of 846 individuals underwent both iATT and MRI-PDFF assessments. Steatosis grade was defined as grade 0 with MRI-PDFF < 5.2%, grade 1 with 5.2% MRI-PDFF < 11.3%, grade 2 with 11.3% MRI-PDFF < 17.1%, and grade 3 with MRI-PDFF of 17.1%. The reproducibility of iATT and MRI-PDFF was evaluated using the Bland–Altman analysis and intraclass correlation coefficients, whereas the diagnostic performance of each steatosis grade was examined using receiver operating characteristic analysis.ResultsThe Bland–Altman analysis indicated excellent reproducibility with minimal fixed bias between iATT and MRI-PDFF. The area under the curve for distinguishing steatosis grades 1, 2, and 3 were 0.887, 0.882, and 0.867, respectively. A skin-to-capsula distance of ≥ 25 mm was identified as the only significant factor causing the discrepancy. No interaction between MRI-logPDFF and MRE-LSM on iATT values was observed.ConclusionsCompared to MRI-PDFF, iATT showed excellent diagnostic accuracy in grading steatosis. iATT could be used as a diagnostic tool instead of MRI in clinical practice and trials.Trial registration This study was registered in the UMIN Clinical Trials Registry (UMIN000047411).

The utility of CT-derived parameters for hepatic steatosis assessment has primarily focused on non-alcoholic fatty liver disease. This study aimed to evaluate their applicability in chronic hepatitis B (CHB) through a retrospective analysis of 243 CHB patients. Using deep-learning-based 3D organ segmentation on abdominal CT scans at 100 kVp, the mean volumetric CT attenuation of the liver and spleen was automatically measured on pre-contrast (liver (L)_pre and spleen (S)_pre) and post-contrast (L_post and S_post) portal venous phase images. To identify mild, moderate, and severe steatosis (S1, S2, and S3 based on the controlled attenuation parameter), L_pre showed areas under the receiver operating characteristic curve (AUROCs) of 0.695, 0.779, and 0.795, significantly higher than L-S_pre (0.633, 0.691, and 0.732; Ps = 0.02, 0.003, and 0.03). Post-contrast parameters demonstrated slightly lower AUROCs than their pre-contrast counterparts (Ps = 0.15–0.81). Concomitant hepatic fibrosis influenced diagnostic performance, with CT parameters performing better in patients without severe fibrosis than those with (F3-4 on transient elastography), though statistical significance was only observed for L-S_post in severe steatosis ( P  = 0.037). In conclusion, CT attenuation-based parameters extracted through automated 3D analysis show promise as a tool for assessing hepatic steatosis in patients with CHB.

The impact of marijuana on the general population is largely unknown. The present study aimed to assess the association between marijuana use and liver steatosis and fibrosis in the general United States population utilizing data from the National Health and Nutrition Examination Survey (NHANES). This cross-sectional study was performed with data from the 2017-2018 cycle of NHANES. The target population comprised adults in the NHANES database with reliable vibration controlled transient elastography (VCTE) results. The median values of the controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) were used to evaluate liver steatosis and fibrosis, respectively. After adjusting for relevant confounders, a logistic regression analysis was used to assess the association between marijuana use and liver steatosis and fibrosis. A total of 2622 participants were included in this study. The proportions of never marijuana users, past users, and current users were 45.9%, 35.0%, and 19.1%, respectively. Compared to never marijuana users, past and current users had a lower prevalence of liver steatosis (P = 0.184 and P = 0.048, respectively). In the alcohol intake-adjusted model, current marijuana use was an independent predictor of a low prevalence of liver steatosis in people with non-heavy alcohol intake. The association between marijuana use and liver fibrosis was not significant in univariate and multivariate regression. In this nationally representative sample, current marijuana use is inversely associated with steatosis. The pathophysiology is unclear and needs further study. No significant association was established between marijuana use and liver fibrosis, irrespective of past or current use.

The accuracy of noninvasive markers to discriminate nonalcoholic steatohepatitis (NASH) is unsatisfactory. We investigated whether transient elastography (TE) could discriminate patients with NASH from those with nonalcoholic fatty liver disease (NAFLD). The patients suspected of NAFLD who underwent liver biopsy and concomitant TE were recruited from five tertiary centers between November 2011 and December 2013. The study population (n = 183) exhibited a mean age of 40.6 years and male predominance (n = 111, 60.7%). Of the study participants, 89 (48.6%) had non-NASH and 94 (51.4%) had NASH. The controlled attenuation parameter (CAP) and liver stiffness (LS) were significantly correlated with the degrees of steatosis (r = 0.656, P<0.001) and fibrosis (r = 0.714, P<0.001), respectively. The optimal cut-off values for steatosis were 247 dB/m for S1, 280 dB/m for S2, and 300 dB/m for S3. Based on the independent predictors derived from multivariate analysis [P = 0.044, odds ratio (OR) 4.133, 95% confidence interval (CI) 1.037-16.470 for CAP>250 dB/m; P = 0.013, OR 3.399, 95% CI 1.295-8.291 for LS>7.0 kPa; and P<0.001, OR 7.557, 95% CI 2.997-19.059 for Alanine aminotransferase>60 IU/L], we developed a novel CLA model for discriminating patients with NASH. The CLA model showed good discriminatory capability, with an area under the receiver operating characteristic curve (AUROC) of 0.812 (95% CI 0.724-0.880). To assess discriminatory power, the AUROCs, as determined by the bootstrap method, remained largely unchanged between iterations, with an average value of 0.833 (95% CI 0.740-0.893). This novel TE-based CLA model showed acceptable accuracy in discriminating NASH from simple steatosis. However, further studies are required for external validation.

This study aimed to evaluate whether a pericardial fat pad (PFP) detected on chest X-ray can estimate metabolic dysfunction-associated steatotic liver disease (MASLD) and visceral fat accumulation. Sixty-six patients with type 2 diabetes were categorized on the basis of the presence (n = 40) or absence (n = 26) of PFP on chest X-ray. The visceral fat area (VFA) and visceral-to-subcutaneous fat area ratio (V/S) at the umbilical level were assessed using abdominal computed tomography, whereas the controlled attenuation parameter (CAP) was measured using FibroScan. The fatty liver index (FLI) was estimated using clinical parameters, including body mass index (BMI), blood pressure, and biochemical markers. Subjects with PFP had a significantly higher BMI and a higher proportion of males. Subjects with PFP demonstrated significantly higher CAP, FLI, VFA, and V/S than those without PFP (P = 0.018, 0.005, < 0.001, and 0.020, respectively). The cutoff values for detecting PFP on chest X-ray were CAP ≥265.5 dB/m, FLI ≥ 30.6, VFA ≥ 118.7 cm2, and V/S ≥ 0.71. In patients with type 2 diabetes, PFP detected on chest X-ray may serve as an indicator of MASLD and visceral fat accumulation. •Pericardial fat pad detected on chest X-ray may serve as an indicator of MASLD and visceral fat accumulation.

Objective To evaluate the diagnostic efficacy of magnetic resonance imaging proton density fat fraction (MRI-PDFF) in assessing hepatic steatosis among patients with metabolic dysfunction-associated steatotic liver disease (MASLD) through systematic review and meta-analysis approaches. Methods Comprehensive searches were conducted across major public electronic databases, including PubMed, Web of Science, Cochrane Library, and Embase, to identify relevant studies that compared MRI-PDFF with liver biopsy in diagnosing steatosis in MASLD patients. Diagnostic accuracy was assessed using sensitivity, specificity, and the area under the curve (AUC) for differentiating various steatosis grades (S0 vs. S1-3; S0-1 vs. S2-3; S0-2 vs. S3). Results A total of 10 studies involving 939 MASLD patients were included in this meta-analysis. MRI-PDFF demonstrated robust diagnostic performance for steatosis grading, with sensitivity values ranging from 0.77 to 0.92 and specificity from 0.87 to 0.94. The AUC values were 0.98 (95% CI: 0.96–0.99) for S0 vs. S1-3, 0.92 (95% CI: 0.89–0.94) for S0-1 vs. S2-3, and 0.90 (95% CI: 0.87–0.93) for S0-2 vs. S3. Conclusion This meta-analysis suggests that MRI-PDFF is highly effective in grading steatosis in MASLD patients. Further validation through additional high-quality studies is warranted to consolidate these findings. Clinical trial number Not applicable.

PurposeInternational expert panels proposed new nomenclatures, metabolic dysfunction-associated fatty liver disease (MAFLD) in 2020 and metabolic dysfunction-associated steatotic liver disease (MASLD) in 2023, along with revised diagnostic criteria to replace non-alcoholic fatty liver disease (NAFLD). We aimed to investigate the differences in NAFLD, MAFLD, and MASLD prevalence with changing nomenclature in a health check-up using magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) to assess hepatic steatosis. We also examined the prevalence of the sub-classifications of steatotic liver disease (SLD) and the differences in characteristics among the sub-categories.MethodsWe included 844 participants who underwent liver MRI-PDFF at our health check-up clinic between January 2020 and November 2022. Hepatic steatosis was defined as MRI-PDFF ≥ 5%. Participants were categorized according to NAFLD, MAFLD, MASLD, and sub-classifications of SLD.ResultsThe prevalence rates of NAFLD, MAFLD, and MASLD were 25.9%, 29.5%, and 25.2%, respectively. 30.5% of the participants was categorized as SLD. The prevalence rates of the SLD sub-categories were 25.2% for MASLD, 3.7% for MASLD and alcohol-associated liver disease (MetALD), 0.1% for alcohol-associated liver disease, 1.3% for specific etiology SLD, and 0.1% for cryptogenic SLD. Compared with patients in the MASLD group, those in the MetALD group were younger, predominantly male, and exhibited higher levels of serum aspartate aminotransferase, gamma-glutamyl transpeptidase, and triglycerides.ConclusionThe prevalences of NAFLD and MASLD assessed using MRI-PDFF were similar, with MASLD accounting for 97.3% of the patients with NAFLD. The separate MetALD sub-category may have clinical characteristics that differ from those of MASLD.

This study employed machine learning models to quantitatively analyze liver fat content from MRI images for the evaluation of liver fibrosis and disease severity in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). A total of 26 confirmed MAFLD cases, along with MRI image sequences obtained from public repositories, were included to perform a comprehensive assessment. Radiomics features—such as contrast, correlation, homogeneity, energy, and entropy—were extracted and used to construct a random forest classification model with optimized hyperparameters. The model achieved outstanding performance, with an accuracy of 96.8%, sensitivity of 95.7%, specificity of 97.8%, and an F1-score of 96.8%, demonstrating its strong capability in accurately evaluating the degree of liver fibrosis and overall disease severity in MAFLD patients. The integration of machine learning with MRI-based analysis offers a promising approach to enhancing clinical decision-making and guiding treatment strategies, underscoring the potential of advanced technologies to improve diagnostic precision and disease management in MAFLD.