Background/Objectives: To date, no studies have examined radiologic findings by histologic patterns of primary hepatic angiosarcoma; this study clarified radiologic findings of primary hepatic angiosarcoma according to distinct histologic patterns. Methods: From January 2010 to October 2024, 17 individuals (mean age, 69 years ± 11; 11 men) with pathologically confirmed primary hepatic angiosarcoma underwent computed tomography (CT) with or without magnetic resonance imaging (MRI). Histologic patterns were classified as mass-forming, subdivided into vasoformative and non-vasoformative (epithelioid and spindled) patterns, or non-mass-forming, subdivided into sinusoidal and peliotic patterns. Two radiologists independently reviewed CT and MRI images, classifying lesions as non-mass-forming or mass-forming. Hypervascular portions and targetoid patterns were also assessed. Associations between histologic patterns and radiologic findings were evaluated using Fisher’s exact test. Results: Mass-forming tumors were observed in 13 individuals (76.5%), and non-mass-forming tumors in 4 individuals (23.5%). Significant correlation (p < 0.05) was found between radiologic classification (non-mass-forming or mass-forming) and corresponding pathologic patterns. Pathologic subdivision into vasoformative and non-vasoformative patterns did not correlate with hypervascular portions on imaging. Conclusions: Pathological classification into mass-forming and non-mass-forming patterns corresponds closely to radiologic classification of mass-forming and non-mass-forming lesions, indicative of strong pathologic features in imaging.

Purpose: This review presents a practical approach to diagnosing and evaluating metabolic dysfunction-associated steatotic liver disease (MASLD) in primary care, emphasizing identification of patients at risk of advanced fibrosis who require further assessment or specialist referral.Current concepts: MASLD has replaced the term nonalcoholic fatty liver disease by incorporating cardiometabolic risk factors as positive diagnostic criteria, while still requiring assessment of alcohol consumption and alternative causes of steatosis. MASLD is often detected incidentally during health examinations or evaluation of mildly elevated aminotransferases. Normal aspartate aminotransferase (AST) or alanine aminotransferase (ALT) levels do not exclude clinically significant disease. Because liver fibrosis, rather than steatosis severity, is the principal determinant of long-term liver-related outcomes, risk stratification with noninvasive tests is essential. The fibrosis-4 index (FIB-4), calculated from age, AST, ALT, and platelet count, is the most accessible first-line tool in primary care. A FIB-4 value <1.3 in adults aged 35–64 years, or <2.0 in those 65 or older, generally indicates a low risk of advanced fibrosis, whereas ≥2.67 indicates high risk. Patients with intermediate- or high-risk FIB-4 should undergo vibration-controlled transient elastography (VCTE). A liver stiffness measurement <8 kPa suggests low probability of advanced fibrosis, whereas ≥8 kPa warrants further evaluation, and >15 kPa suggests a high probability of compensated advanced chronic liver disease and warrants specialist evaluation.Discussion and conclusion: Evaluation of MASLD should prioritize detection of advanced fibrosis rather than merely confirming steatosis. A stepwise strategy using FIB-4 followed, when indicated, by VCTE provides a practical means of identifying patients requiring specialist referral.

Background and aims The evolution of non-invasive tests of liver fibrosis during follow-up of patients with metabolic dysfunction-associated steatotic liver disease (MASLD) remains difficult to interpret in clinical practice. We aimed to translate the dynamics of non-invasive tests into a personalized prediction of liver-related events (LRE) in MASLD. Methods We used the international multicentre VCTE-Prognosis cohort including adult patients with MASLD who underwent liver stiffness measurements (LSM) by vibration-controlled transient elastography. The study outcome was LRE, a composite endpoint including cirrhosis decompensation or hepatocellular carcinoma. A joint latent class model (JLCM) was used to compute dynamic predictions resulting in a personalized estimation of the risk of LRE (0-100% at chosen time horizons). Results 13,627 patients were included, with 238 LRE occurring during the median follow-up of 4.0 years (IQR: 2.1-5.9). LSM trajectory adjusted on FIB-4 and sex (longitudinal part) and age with platelets (survival part) were selected by the JLCM for LRE prediction. Calibration plots showed very good agreement between the predicted and the observed risk of LRE. The JLCM provided excellent discrimination for LRE with integrated AUROCs increasing from 88.2% at baseline to 92.2% at the 5-year follow-up visit. At the different study visits, 61-80% of the patients who experienced LRE were identified as high risk by the JLCM, versus 39-56% with LSM and 32-60% with FIB-4. Conclusion By automatically integrating and interpreting the dynamics of non-invasive tests of liver fibrosis, JLCM enables the personalised prediction of the risk of hard outcomes, rather than the imperfect evaluation of histological surrogates.

Computed tomography (CT)–ultrasound (US) fusion imaging is widely used for hepatic interventions in human medicine, but its technical performance has not been evaluated in dogs. This study assessed the spatial accuracy, fusion time, and image quality of CT/US fusion imaging in the canine liver. In this prospective experimental study, ten healthy Beagle dogs underwent contrast-enhanced abdominal CT followed immediately by CT/US fusion imaging under the same general anesthesia without repositioning. Fusion was performed at three scan sites (midline subcostal, right intercostal, and left intercostal) using plane registration and three-point manual landmark registration with the gallbladder (GB) as the target structure. Spatial accuracy was quantified as the positional discrepancy between the CT and US GB margins in transverse (left–right, ventral–dorsal) and sagittal (cranial–caudal) planes. Fusion quality was scored on a 5-point scale for the GB center, GB border, vessel alignment, and liver surface alignment. Statistical analyses were performed using nonparametric tests with a significance threshold. Fusion was successful in 58/60 planned image sets; two subcostal studies failed due to intragastric gas. The mean fusion time was 72.7 ± 30.2 s and did not differ significantly among scan sites. Across all sites and planes, the mean CT/US discrepancies were ≤ 2 mm. Qualitative scores were uniformly high (median 5 for all criteria) without relevant site- and plane-dependent degradation. CT/US fusion imaging provided rapid, accurate, and visually reliable co-registration of canine liver anatomy, supporting its potential clinical use for image-guided hepatic interventions in dogs.

PURPOSE:Recently, the steatosis-associated fibrosis estimator (SAFE) score was developed to predict significant fibrosis in primary care. We externally validated the SAFE score in Asian patients with metabolic dysfunction-associated steatotic liver disease (MASLD). MATERIALS AND METHODS:We validated the SAFE score in 6229 patients who underwent transient elastography (TE) from 2012 to 2022. The sensitivities, specificities, negative predictive values, and positive predictive values of SAFE scores (two cutoffs: <0 and ≥100) for predicting fibrosis stage ≥2 were calculated. RESULTS:Based on TE results, the SAFE score had an area under the receiver operating characteristic curve of 0.753 (95% confidence interval 0.737-0.769), outperforming the Fibrosis-4 index (0.672) and the nonalcoholic fatty liver disease fibrosis score (0.663). Non-obese and obese patients had similar sensitivities (77.0% vs. 78.4%) and specificities (61.5% vs. 51.8%) for SAFE score <0, and similar sensitivities (50.0% vs. 50.0%) and specificities (90.1% vs. 85.4%) for SAFE score ≥100. Sensitivity of the SAFE score for ≥100 increased with age, from 16.1% (age 19-30) to 79.7% (age ≥61), whereas specificity for ≥100 decreased. CONCLUSION:We externally validated the good performance of the SAFE score in Asian patients. The SAFE score has potential as an initial assessment to identify a low-risk population in a primary care setting.

The role of liver biopsy in hepatocellular carcinoma (HCC) is being re-evaluated in the era of precision oncology and biomarker-driven systemic therapy. Although histopathological examination remains the diagnostic gold standard, HCC is unique among solid tumors in that accurate non-invasive imaging criteria allow diagnosis without routine biopsy in selected clinical settings. However, increasing biological heterogeneity, expanding therapeutic options, and the growing need for molecular stratification have renewed interest in tissue-based evaluation. Recent international guidelines have gradually broadened the indications for liver biopsy, particularly in selected diagnostic scenarios, prior to systemic therapy, and for molecular profiling. Beyond diagnostic confirmation, liver biopsy provides important information for histological subtyping, prognostic stratification, and biomarker discovery. Advances in immunohistochemistry, next-generation sequencing, and artificial intelligence-assisted pathology have further enhanced the clinical value of tumor tissue. In parallel, contemporary cohort studies indicate that liver biopsy is associated with low complication rates when modern techniques and standardized peri-procedural management are applied. Despite these advances, the integration of liver biopsy into routine clinical practice remains limited. To contextualize this gap, the Korean Liver Cancer Association conducted a nationwide survey of HCC specialists. The survey showed that liver biopsy is infrequently performed in current practice due to perceived procedural risks and limited immediate impact on therapeutic decision-making. Taken together, accumulating evidence supports a reappraisal of the clinical role of liver biopsy in HCC. Optimizing procedural safety, standardizing indications, and integrating tissue-based molecular insights into therapeutic decision-making may help bridge the gap between emerging evidence and real-world practice.

BACKGROUND Transarterial chemoembolization (TACE) is a cornerstone treatment for hepatocellular carcinoma (HCC), yet the hepatitis B virus (HBV) reactivation risk, particularly among patients with prior infection, remains incompletely characterized, with international guidelines providing discordant risk classifications. We hypothesized that patients with resolved HBV infection undergoing TACE face a higher reactivation risk than currently estimated by international guidelines. AIM To determine the incidence and risk factors of HBV reactivation in patients undergoing TACE for HBV-related HCC. METHODS We retrospectively analyzed patients who underwent TACE for HBV-related HCC at a tertiary hospital during 2007-2025. Patients receiving baseline antiviral therapy were excluded. Patients with definitive serostatus (n = 774) were stratified into chronic-infection [hepatitis B surface antigen (HBsAg)-positive, n = 727] and resolved-infection (HBsAg-negative/anti-hepatitis B core antibody-positive, n = 47) groups. Cumulative incidences and risk factors were assessed using Kaplan-Meier analysis and Cox regression, with robustness evaluated through multiple imputation, competing-risks, and antiviral-naive sensitivity analyses. RESULTS During a median follow-up of 16.7 months, HBV reactivation occurred in 60 patients (6.1% overall). Patients with resolved HBV status had a higher reactivation rate (21.3% vs 6.9%; P < 0.001). Resolved HBV status (adjusted hazard ratio: 3.98, 95% confidence interval: 1.99-7.97; P < 0.001) and elevated alpha-fetoprotein level (1.33 per log10 ng/mL, 1.04-1.69; P = 0.024) were independent predictors. Median time to reactivation was 12 months. CONCLUSION HBV reactivation occurred in approximately 6% of patients undergoing TACE, with resolved infection status conferring > 3-fold higher risk and reactivation incidence exceeding 20%. These findings support prophylactic antiviral therapy rather than monitoring alone for HBsAg-negative/anti-hepatitis B core antibody-positive patients undergoing TACE.

BACKGROUND & AIMS:The availability of new drugs for the treatment of patients with metabolic dysfunction-associated steatotic liver disease (MASLD) underlines the need of early predictors of response to such therapies. This study evaluated the impact of 1-year changes in liver stiffness measurement (LSM) by vibration-controlled transient elastography (VCTE), controlled attenuation parameters (CAP), and serum alanine aminotransferase (ALT) on liver outcomes in patients with MASLD. METHODS:A large multicenter cohort of MASLD patients with LSM ≥8 kPa and prospective follow-up was enrolled. Liver-related events (LREs), including hepatocellular carcinoma (HCC) and liver decompensation (LD), were evaluated during follow-up. LSM, CAP, ALT, and Fibrosis-4 Index (FIB-4) were assessed at baseline and at 1-year follow-up. Cause-specific Cox regression analyses were performed to correlate 1-year variation in LSM, CAP, ALT, and FIB-4 with the risk of developing LRE, LD, and HCC, in terms of cause-specific hazard ratios (csHRs). RESULTS:We included 1744 patients with LSM ≥8 kPa (median age, 55 years; 52.1% male; 58.3% obese; 55.8% with diabetes) and 989 with LSM ≥10 kPa (median age, 56 years; 50.2% male; 54.7% obese; 51% with diabetes), followed for a median of 28.2 and 32 months, respectively. LREs occurred in 39 patients with LSM ≥8 kPa (26 LD, 22 HCC) and in 35 with LSM ≥10 kPa (25 LD, 19 HCC). A 1-year variation in LSM, but not in CAP, ALT, or FIB-4, was independently associated with LRE in patients with MASLD and LSM ≥8 kPa (csHR, 1.007; 95% confidence interval [CI], 1.001-1.014). Likewise, 1-year LSM variation (csHR, 1.009; 95% CI, 1.000-1.018) independently predicted LD in this population, whereas no 1-year changes in CAP, ALT, or FIB-4 were associated with LD risk. No independent associations were observed between 1-year changes in LSM, CAP, ALT, or FIB-4 and the risk of HCC. All findings were confirmed in patients with LSM ≥10 kPa and in those at high risk of progression with type 2 diabetes. CONCLUSIONS:In patients with MASLD and LSM ≥8 or ≥10 kPa, the % LSM reduction at 1 year was independently associated with lower risk of LRE and LD.

BACKGROUND & AIMS Metabolic dysfunction-associated steatohepatitis (MASH), a chronic liver disease, is characterized by persistent low-grade inflammation, partially driven by gut-derived lipopolysaccharide (LPS). Although repeated LPS exposure can induce endotoxin tolerance in innate immune cells, its role in chronic liver diseases remains unclear. Acyloxyacyl hydrolase (AOAH) is an endogenous enzyme that inactivates LPS, potentially modulating this process. We aimed to investigate how AOAH regulates endotoxin tolerance in Kupffer cells (KCs) and how this affects hepatic inflammation and fibrosis during MASH progression. METHODS AOAH-deficient (AOAH-/-) mice and wild-type controls were subjected to multiple dietary MASH models. Inflammatory responses, fibrosis, and transcriptomic changes in liver tissues and isolated KCs were analyzed. Endotoxin tolerance was modulated through β-glucan administration or LPS preconditioning. LPS bioactivity was assessed using TLR4-reporter cell assays. RESULTS LPS-preconditioned KCs exhibited reduced pro-inflammatory cytokine production and transcriptional suppression of inflammatory pathways, indicating tolerance. Despite slight elevation of plasma LPS levels in MASH, upregulation of hepatic AOAH positively correlated with disease severity, suggesting enhanced LPS inactivation but impaired establishment of tolerance. In contrast, AOAH-deficient KCs displayed reinforced endotoxin tolerance, leading to diminished hepatic inflammation and fibrosis. Reversal of tolerance using β-glucan reactivated inflammatory and fibrogenic responses in AOAH-deficient mice, whereas tolerance induction by low-dose LPS preconditioning mitigated MASH pathology, supporting the protective role of macrophage tolerance in chronic liver injury. CONCLUSIONS Endotoxin tolerance in KCs represents a protective mechanism against chronic liver inflammation and fibrosis. AOAH regulates this state by limiting bioactive LPS, thereby modulating the establishment of endotoxin tolerance and downstream inflammatory and fibrotic responses. Enhancing macrophage tolerance by utilizing LPS may offer a novel therapeutic avenue to control the progression of MASH.

Background & Aims The comparative outcomes of entecavir (ETV), tenofovir disoproxil fumarate (TDF), and tenofovir alafenamide (TAF) in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after curative resection remain unclear. This study aimed to evaluate the survival benefits of these antiviral regimens in a large real-world cohort.Methods We analysed 902 patients with BCLC stage 0 or A HBV-related HCC who underwent curative resection between September 2001 and August 2025. Patients received ETV (n = 474), TDF (n = 363), or TAF (n = 65) as first-line therapy within 3 months post-resection. Inverse probability of treatment weighting (IPTW) was implemented to balance baseline covariates. The primary and secondary endpoints were overall survival (OS) and recurrence-free survival (RFS).Results The IPTW-adjusted 5-year OS rates for ETV, TDF, and TAF were 90.7%, 95.2%, and 97.1%, respectively (global p = 0.079). The 5-year RFS rates were comparable for ETV, TDF, and TAF (57.4% vs. 61.0% vs. 69.4%; global p = 0.533). In multivariable Cox regression analysis, however, TDF was independently associated with a significantly lower risk of death compared with ETV (aHR 0.48; 95% CI, 0.26-0.89; p = 0.021). TAF showed higher survival rates compared to ETV, although the difference did not reach statistical significance (aHR 0.34; 95% CI, 0.04-2.55; p = 0.292).Conclusion The choice of antiviral regimen was not associated with RFS after curative resection for HBV-related HCC, whereas TDF was independently associated with improved OS compared with ETV. Further large-scale studies are warranted to validate the long-term prognostic impact of TAF.

BACKGROUND & AIMS:Accurate staging of liver fibrosis is crucial for risk stratification in patients with metabolic dysfunction-associated steatotic liver disease. We aimed to develop and validate artificial intelligence-based models capable of distinguishing fibrosis stages. METHODS:We developed and validated machine learning models to predict fibrosis stages in more than 3600 biopsy-confirmed patients with metabolic dysfunction-associated steatotic liver disease using 22 clinical features, liver stiffness measurement, and controlled attenuation parameter. Models included Feature Tokenizer Transformer, TabNet variants with distance-aware losses, ordinal Multilayer Perceptron with the COnditional RAnk Logits framework. Three centers were prespecified for geographic external validation. In the remaining centers, we used a stratified 75/25 split into a training pool and an internal random test set, tuned hyperparameters by stratified 10-fold cross-validation on the training pool, and trained 1 model per imputed dataset (M = 5) with an internal 80/20 train-validation split for early stopping and operating-point selection. Performance was pooled across imputations using Rubin's rules and reported for the internal random test set and the held-out centers. RESULTS:Feature Tokenizer Transformer and TabNet achieved the highest performance in binary tasks: area under the receiver operating characteristic curve = 0.860 and 0.855 (F ≥3 vs 0-F2) and area under the receiver operating characteristic curve = 0.800 and 0.788 (F ≥2 vs 0-F1), significantly outperforming the Fibrosis-4 index. For F ≥3, Feature Tokenizer Transformer had significantly higher area under the receiver operating characteristic curve than liver stiffness measurement (P = .014) but only marginally higher than AGILE3+, and, together with TabNet, the highest accuracy and the lowest gray zone (8.2% and 8.4%, respectively). For multiclass staging, ordinal models performed best with Multilayer Perceptron with the Consistent Rank Logits achieving quadratic weighted kappa = 0.616. CONCLUSIONS:Deep learning models with ordinal-aware architectures can accurately predict liver fibrosis stages using routinely available clinical data, offering a scalable alternative to biopsy without requiring specialized biomarkers.

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is an increasingly important contributor to hepatocellular carcinoma (HCC). Many MASLD-related HCC cases occur in individuals without cirrhosis, yet scalable approaches to identify heterogeneous HCC risk in this large population remain limited. Methods: We developed and externally validated an HCC risk stratification framework for individuals with MASLD without cirrhosis at baseline using three cohorts. The derivation cohort included 66,577 participants from a Taiwanese health examination program (1997–2013), with external validation in Taiwan’s government-led Adult Health Examination program (n=198,453) and the UK Biobank (n=124,866). Candidate predictors were prespecified based on routine availability in screening settings. Five independent predictors were incorporated into a point-based score. Findings: Median follow-up durations were 15.6, 10.1, and 11.0 years, respectively. The final framework included age, alanine aminotransferase, central obesity, diabetes, and high-density lipoprotein cholesterol. Time-dependent AUROCs in internal validation were 0.786, 0.813, and 0.824 at 3, 5, and 10 years, respectively; corresponding AUROCs were 0.785, 0.805, and 0.784 in the Taiwanese external validation cohort, and 0.648, 0.700, and 0.784 in the UK Biobank. Risk stratification consistently separated participants into five groups with different cumulative HCC incidence across cohorts (all log-rank p<0.001). Approximately 40% of incident HCC cases occurred without a recorded diagnosis of cirrhosis. Interpretation: This pragmatic framework, based on routine clinical variables and validated across Asian and Western populations, may support precision public health strategies by identifying heterogeneous HCC risk among individuals with MASLD not currently targeted by routine surveillance.