The ideal evaluation of diagnostic test performance requires a reference test that is free of errors. However, for many diseases, obtaining such a "gold standard" reference is either impossible or prohibitively expensive. Estimating test accuracy in the absence of a gold standard is therefore a significant challenge. In this article, we introduce and categorize existing methods for evaluating diagnostic tests without a gold standard, considering factors such as the type and number of tests, as well as the structure of the observed data. For each method, we provide a comprehensive introduction and analysis of its underlying assumptions, model architecture, identifiability, estimation techniques, and inference procedures. We use R to conduct simulations for widely applicable models, validating assumptions, comparing models, and assessing their reliability. Additionally, we present real-world examples along with the corresponding R code for these models, enabling readers to better understand how to apply them effectively. Beyond diagnostic medicine, we underscore that the issue of imperfect gold standards affects other fields, drawing parallels to the noisy label problem in machine learning. By highlighting similarities and differences across these domains, we open pathways for further research. The primary aim of this article is to consolidate existing methods for assessing test accuracy in the absence of a gold standard and to provide practical guidance for researchers seeking to apply these methods effectively.

Hepatoscope® is an ultraportable ultrasound system with 50 Hz two-dimensional transient elastography (2DTE) for liver stiffness measurement (LSM). It provides a quality index (QI) for individual stiffness values that is based on imaging features. This study evaluated the 2DTE intra- and inter-user repeatability in patients with chronic liver diseases (CLD) for novice and expert operators across various QI conditions. We compared the performances with other imaging and non-imaging elastography techniques.

This investigation was a prospective cross-sectional single-center study. One hundred CLD patients underwent LSMs with vibration-controlled transient elastography (VCTE™), two-dimensional shear wave elastography (2DSWE) and 2DTE. Expert and novice operators each performed two consecutive exams with 2DTE, blinded to any output. Intra-class correlation coefficient for intra-, and inter-user repeatability were calculated as well as applicability for various QI conditions, and Spearman's correlations against VCTE and 2DSWE were assessed.

Computing LSM as the median of 10 stiffness values with a QI>85 % yielded the best compromise between reliability and applicability. In this setting, expert and inter-operator repeatability showed significant improvement over the condition with no QI threshold (ICC = 0.81 and 0.79, respectively) and 95 % applicability. Novice repeatability was excellent with a more restrictive QI (ICC = 0.80). LSM with 2DTE demonstrated strong and moderate correlation with VCTE and 2DSWE (r = 0.63 and 0.55, respectively).

Hepatoscope 2DTE provides a promising and reliable alternative for non-invasive liver stiffness assessment in patients with CLD. The application of the image-based QI enhances LSM reliability and consistency across novice and expert operators.

To explore the correlation between serum Golgi protein 73 (GP73) levels and the degree of fibrosis in Metabolic dysfunction associated steatotic liver disease (MASLD); to establish a non-invasive diagnostic algorithm based on serum GP73 and liver elasticity.

This is a prospective cross-sectional study, including 228 patients diagnosed with MASLD from May 2018 to January 2024 at two tertiary hospitals. Clinical data and hepatic pathological features and the correlation between serum GP73 and liver fibrosis were assessed. A new algorithm was conducted after logistic regression. Receiver Operating Characteristic (ROC) curve was used to compare its diagnostic performance with traditional models.

Significant fibrosis was diagnosed in 37.2% (85/228) patients. Serum GP73 levels were markedly higher in patients with significant fibrosis than in those without (128 ng/mL v.s 46 ng/mL, p< 0.001). Serum GP73 levels independently predicted significant liver fibrosis (adjusted odds ratio, aOR 1.028, p< 0.001). A new algorithm based on GP73 was developed with a higher area under ROC (AUC) of 0.840 than that of Fibrosis index-4 (p< 0.001).

Serum GP73 is an independent risk factor for significant liver fibrosis in MASLD, and the GFA (GP73-Fibroscan-Age) model has good diagnostic efficacy for significant liver fibrosis.

Accurate and reliable diagnosis and monitoring of hepatic fibrosis is increasingly important given the variable natural history in chronic liver disease (CLD) and expanding antifibrotic therapeutic options targeting reversibility of early-stage cirrhosis. This highlights the need to develop more refined and effective noninvasive techniques for the dynamic assessment of fibrogenesis and fibrolysis.

We conducted a literature review on PubMed, from 1 December 1970, to 1 November 2024, to evaluate and compare available blood-based and imaging-based noninvasive tools for hepatic fibrosis diagnosis and monitoring. Simple scores such as FIB-4 and NAFLD fibrosis score are suitable for excluding significant or advanced fibrosis, while tertiary centers should adopt complex scores and liver stiffness measurement as part of a secondary diagnostic and more comprehensive evaluation. Moreover, the advent of multiomics for high-resolution molecular profiling, and integration of artificial intelligence for noninvasive diagnostics holds promise for revolutionizing fibrosis monitoring and treatment through novel biomarker discovery and predictive omics-based algorithms.

The increased shift toward noninvasive diagnostics for liver fibrosis needs to align with personalized medicine, enabling more effective, tailored management strategies for patients with liver disease in the future.

This study aims to assess how T2 heterogeneity biases IMPULSED-derived metrics of tissue microstructure in solid tumors and evaluate the potential of estimating multi-compartmental T2 and microstructural parameters simultaneously.

This study quantifies the impact of T2 relaxation on IMPULSED-derived microstructural parameters using computer simulations and in vivo multi-TE IMPULSED MRI in five tumor models, including brain, breast, prostate, melanoma, and colon cancer. A comprehensive T2 + IMPULSED method was developed to fit multi-compartmental T2 and microstructural parameters simultaneously. A Bayesian model selection approach was carried out voxel-wisely to determine if the T2 heterogeneity needs to be included in IMPULSED MRI in cancer.

Simulations suggest that T2 heterogeneity has a minor effect on the estimation of d in tissues with intermediate or high cell density, but significantly biases the estimation ofv in $$ {v}_{in} $$ with low cell density. For the in vivo animal experiments, all IMPULSED metrics exceptv in $$ {v}_{in} $$ are statistically independent on TE. For B16 tumors, the IMPULSED-derivedv in $$ {v}_{in} $$ exhibited a notable increase with longer TEs. For MDA-MB-231 tumors, IMPULSED-derivedv in $$ {v}_{in} $$ showed a significant increase with increasing TEs. The T2 + IMPULSED-derivedT 2 in $$ {T}_2^{in} $$ of all five tumor models are consistently smaller thanT 2 ex $$ {T}_2^{ex} $$ .

The findings from this study highlight two key observations: (i) TE has a negligible impact on IMPULSED-derived cell sizes, and (ii) the TE-dependence of IMPULSED-derived intracellular volume fractions used in T2 + IMPULSED modeling to estimateT 2 in $$ {T}_2^{in} $$ andT 2 ex $$ {T}_2^{ex} $$ . These insights contribute to the ongoing development and refinement of non-invasive MRI techniques for measuring cell sizes.

Background: Contrast-enhanced ultrasound (CEUS) has become the preferred method for many clinicians in evaluating focal liver lesions (FLLs) initially identified through standard ultrasound. However, in clinical practice, certain lesions may deviate from the typical enhancement patterns outlined in EFSUMB guidelines. Methods: This study aims to assess FLLs that remained inconclusive or misdiagnosed after CEUS evaluation, spanning eight years of single-center experience. Following CEUS, all FLLs underwent secondary imaging (CT, MRI) or histopathological analysis for diagnostic confirmation. Results: From the initial 979 FLLs, 350 lesions (35.7%) were either inconclusive or misdiagnosed by CEUS, with hepatocellular carcinoma (HCC) and liver metastases constituting the majority of these cases. The most frequent enhancement pattern in inconclusive lesions at CEUS was hyper-iso-iso. Factors such as advanced liver fibrosis, adenomas, and cholangiocarcinoma were significantly associated with higher rates of diagnostic inaccuracies. Conclusions: Advanced liver fibrosis, adenomas, and cholangiocarcinoma were significantly associated with increased diagnostic challenges, emphasizing the need for supplementary imaging techniques.

Aim of the Study: HBV-infected individuals are also presenting with MASLD. However, the value of VCTE for detecting hepatic fibrosis and steatosis in CHB patients concurrent with MASLD is unclear. In patients with combined CHB and MASLD, we intend to assess the diagnostic efficacy of VCTE in determining the extent of fibrosis and steatosis. Methods: This retrospective study involved 368 patients diagnosed with chronic HBV infection combined with MASLD who received liver biopsy and VCTE at Xiamen City Traditional Chinese Medicine Hospital from June 2018 to June 2023. The cutoff values for liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) were determined via the use of the cross-validated area under the receiver operating characteristic (AUROC) curve analyses to identify pairwise fibrosis stage and grade, respectively. The diagnostic statistics were calculated with a 90% fixed sensitivity and 90% specificity. Results: An AUROC of 0.86 (95% CI: 0.76-0.95) was determined by a LSM cutoff value of 11.25 to identify patients with cirrhosis. Patients have the following values: sensitivity, 0.79; specificity, 0.90; PPV, 0.89; and NPV, 0.81. An AUROC of 0.84 (95% CI: 0.76-0.95) was determined by a CAP cutoff value of 313 to identify patients with severe steatotic liver. Patients have the following values: sensitivity, 0.86; specificity, 0.82; PPV, 0.82; and NPV, 0.85. Conclusion:In this investigation of adult patients diagnosed with CHB with MASLD, VCTE demonstrated a robust capability to differentiate cirrhosis and severe steatotic liver.

This study aimed to explore the key genes involved in the pathophysiological process of liver fibrosis and develop a novel predictive model for noninvasive assessment of significant liver fibrosis patients.

Differentially expressed genes (DEGs) were identified using the Limma package. The hub genes were explored using the CytoHubba plugin app and validated in GEO datasets and cell models. Furthermore, serum LTBP2 was measured in liver fibrosis (LF) patients with biopsy-proven by ELISA. All patients' clinical characteristics and laboratory results were analyzed. Finally, multivariate logistic regression analysis was used to construct the model for visualization by nomogram. Area under the receiver operating characteristic curve (AUROC) analysis, calibration curves, and decision curve analysis (DCA) certify the accuracy of the nomogram.

RNA sequencing was performed on the liver tissues of 66 biopsy-proven HBV-LF patients. After multiple analyses and in vitro simulation of HSC activation, LTBP2 was found to be the most associated with HSC activation regardless of the causes. Serum LTBP2 expression was measured in 151 patients with biopsy, and LTBP2 was found to increase in parallel with the fibrosis stage. Multivariate logistic regression analysis showed that LTBP2, PLT and AST levels were demonstrated as the independent prediction factors. A nomogram that included the three factors was tabled to evaluate the probability of significant fibrosis occurrence. The AUROC of the nomogram model was 0.8690 in significant fibrosis diagnosis.

LTBP2 may be a new biomarker for liver fibrosis patients. The nomogram showed better diagnostic performance in patients.

In nonalcoholic fatty liver disease (NAFLD), liver fibrosis is the strongest predictor of adverse outcomes. We sought to investigate the relationship between liver fibrosis and cardiac remodeling in participants from the general population using magnetic resonance imaging (MRI), as well as explore potential mechanistic pathways by analyzing circulating cardiovascular biomarkers.

In this cross-sectional study, we prospectively included participants with type 2 diabetes and individually matched controls from the SCAPIS (Swedish CArdioPulmonary bioImage Study) cohort in Linköping, Sweden. Between November 2017 and July 2018, participants underwent MRI at 1.5 Tesla for quantification of liver proton density fat fraction (spectroscopy), liver fibrosis (stiffness from elastography), left ventricular (LV) structure and function, as well as myocardial native T1 mapping. We analyzed 278 circulating cardiovascular biomarkers using a Bayesian statistical approach.

In total, 92 participants were enrolled (mean age 59.5 ± 4.6 years, 32 women). The mean liver stiffness was 2.1 ± 0.4 kPa. 53 participants displayed hepatic steatosis. LV concentricity increased across quartiles of liver stiffness. Neither liver fat nor liver stiffness displayed any relationships to myocardial tissue characteristics (native T1). In a regression analysis, liver stiffness was related to increased LV concentricity. This association was independent of diabetes and liver fat (Beta = 0.26, p = 0.0053), but was attenuated (Beta = 0.17, p = 0.077) when also adjusting for circulating levels of interleukin-1 receptor type 2.

MRI reveals that liver fibrosis is associated to structural LV remodeling, in terms of increased concentricity, in participants from the general population. This relationship could involve the interleukin-1 signaling.

Liver fibrosis may be considered a cardiovascular risk factor in patients without cirrhosis. Further research on the mechanisms that link liver fibrosis to left ventricular concentricity may reveal potential therapeutic targets in patients with non-alcoholic fatty liver disease (NAFLD).

Previously, studies on liver fibrosis and cardiac remodeling have focused on advanced stages of liver fibrosis. Liver fibrosis is associated with left ventricular (LV) concentricity and may relate to interleukin-1 receptor type 2. Interleukin-1 signaling is a potential mechanistic interlink between early liver fibrosis and LV remodeling.

Chronic hepatitis B virus (HBV) infection remains a serious health issue, and determining the optimal time for antiviral therapy is challenging. We aimed to assess liver histological changes in patients with HBeAg-positive chronic hepatitis B (CHB) and those with HBeAg-negative CHB who had persistently normal alanine aminotransferase and to determine the association between significant liver injury and various clinical parameters.

We retrospectively included, in this study, 339 treatment-naïve patients with chronic HBV infections who had persistently normal alanine aminotransferase and underwent liver biopsy from 2013 to 2023. Histologic assessment was based on the Metavir scoring system to evaluate the association between clinical characteristics and the severity of liver inflammation and fibrosis.

Among the included participants, 138 were HBeAg-positive and 201 were HBeAg-negative. Lower hepatitis B surface antigen (HBsAg) (P = 0.003) and higher aspartate aminotransferase (AST) (P = 0.002) levels were associated with significant necroinflammation, whereas increasing age (P = 0.004) and lower HBV DNA (P < 0.001) levels were associated with significant fibrosis in HBeAg-positive patients with normal ALT levels. Higher HBV-DNA (P = 0.001) and AST levels(P < 0.001) were associated with significant necroinflammation, and higher AST(P < 0.001) levels were associated with significant fibrosis in HBeAg-negative patients.

A substantial proportion of patients with HBV infection who had normal ALT presented significant liver injury. HBsAg and AST were independent predictive factors for evaluating inflammation, while HBV DNA load and age were independent predictive factors for evaluating fibrosis in the HBeAg-positive group. HBV DNA load and AST were independent predictive factors for evaluating inflammation, while AST were independent predictive factors for evaluating fibrosis in the HBeAg-negative group.

There is an unmet clinical need for non-invasive imaging biomarkers that could replace liver biopsy in the management of patients with autoimmune hepatitis (AIH). In this study, we sought to evaluate the diagnostic accuracy of a simple uncorrected, non-contrast T1 mapping for detecting fibrosis and inflammation in AIH patients using histopathology as a reference standard.

Over 3 years, 33 patients with AIH were prospectively studied using a multiparametric liver MRI protocol which included T1 mapping. Biopsies were performed up to 3 months before imaging, and a standardized histopathological score for fibrosis (F0-F4) and inflammatory activity (PPA0-4) was used as a reference. Statistical analysis included independent t test, Mann-Whitney U-test, and ROC (receiver operating characteristic) analysis.

T1 mapping values were significantly higher in patients with advanced fibrosis (F0-2 vs. F3-4; p < 0.015), significant fibrosis (F0-1 vs. F2-4; p < 0.005), and significant inflammatory activity (PPA 0-1 vs. PPA 2-4 p = 0.048). Moreover, the technique demonstrated a good diagnostic performance in detecting significant (AUC 0.856) and advanced fibrosis (AUC 0.835), as well as significant inflammatory activity (AUC 0.763).

A rapid, simple, uncorrected, non-contrast T1 mapping sequence showed satisfactory diagnostic performance in comparison with histopathology for detecting significant tissue inflammation and fibrosis in AIH patients, being a potential non-invasive imaging biomarker for monitoring disease activity in such individuals.

Liver biopsy remains the gold standard for fibrosis staging in patients with chronic hepatitis delta (CHD). Here, we comparatively evaluated the performance of transient elastography (TE) and biomarkers for the diagnosis of liver fibrosis in patients with CHD.

A total of 230 HDV-infected RNA-positive patients from various centers who underwent liver biopsy and liver stiffness measurements (LSMs) using Fibroscan, within a period of 6 months maximum, were investigated retrospectively. Area under the receiver operating characteristic curve and Youden index were used to establish cutoff values of LSM. TE was compared with other noninvasive tests: aspartate aminotransferase to platelet ratio index, Fibrosis-4, and Delta-4 fibrosis scores.

Histologic fibrosis stage distribution was: 20.4% for F0-F1; 27.0% for F2; 18.7% for F3; and 33.9% for F4. TE demonstrated good diagnostic performance for detecting cirrhosis and advanced fibrosis with an Area under the receiver operating characteristic curve of 0.88 and 0.86, which were significantly higher than those obtained with the other noninvasive tests (P = .004 and P < .001). With a cutoff value of >12 kPa for cirrhosis, the sensitivity was 70.5%, specificity was 86.2%, positive predictive value was 72.4%, negative predictive value was 85.1%, and accuracy was 80.9%. Using 10.4 kPa as the cutoff value for F3, the sensitivity was 70.2%, specificity was 83.5%, positive predictive value was 82.5%, negative predictive value was 71.7%, and accuracy was 76.5%. In 89% of patients with LSM ≤6.2 kPa, liver biopsy disclosed only absent or minimal fibrosis.

TE demonstrated good diagnostic performance for advanced fibrosis and cirrhosis in patients with CHD. Advanced fibrosis is highly probable for LSM values ≥10 kPa. LSM values <6 kPa almost totally exclude significant fibrosis. Between 6 and 10 kPa, liver biopsy should be discussed.

Liver fibrosis poses a significant public health challenge given its elevated incidence and associated mortality rates. Diffusion-Weighted Imaging (DWI) serves as a non-invasive diagnostic tool for supporting the identification of liver fibrosis. Deep learning, as a computer-aided diagnostic technology, can assist in recognizing the stage of liver fibrosis by extracting abstract features from DWI images. However, gathering samples is often challenging, posing a common dilemma in previous research. Moreover, previous studies frequently overlooked the cross-comparison information and latent connections among different DWI parameters. Thus, it is becoming a challenge to identify effective DWI parameters and dig potential features from multiple categories in a dataset with limited samples.

A self-defined Multi-view Contrastive Learning Network is developed to automatically classify multi-parameter DWI images and explore synergies between different DWI parameters.

A Dense-fusion Attention Contrastive Learning Network (DACLN) is designed and used to recognize DWI images. Concretely, a multi-view contrastive learning framework is constructed to train and extract features from raw multi-parameter DWI. Besides, a Dense-fusion module is designed to integrate feature and output predicted labels.

We evaluated the performance of the proposed model on a set of real clinical data and analyzed the interpretability by Grad-CAM and annotation analysis, achieving average scores of 0.8825, 0.8702, 0.8933, 0.8727, and 0.8779 for accuracy, precision, recall, specificity and F-1 score. Of note, the experimental results revealed that IVIM-f, CTRW-β, and MONO-ADC exhibited significant recognition ability and complementarity.

Our method achieves competitive accuracy in liver fibrosis diagnosis using the limited multi-parameter DWI dataset and finds three types of DWI parameters with high sensitivity for diagnosing liver fibrosis, which suggests potential directions for future research.

The evaluation of Fontan-associated liver disease is often challenging. Diffusion-weighted magnetic resonance imaging can detect hepatic fibrosis from capillary perfusion and diffusion abnormalities from extracellular matrix accumulation. This study investigated its role in the evaluation of liver disease in Fontan patients and explored possible diagnostic methods for early detection of advanced liver fibrosis.

Stable adult Fontan patients who could safely be examined with magnetic resonance imaging were enrolled, and blood biomarkers, transient elastography were also examined.

Forty-six patients received diffusion-weighted imaging; and 58.7% were diagnosed with advanced liver fibrosis (severe liver fibrosis, 37.0%, and cirrhosis 21.7%). Two parameters of hepatic dysfunction, platelet counts (Spearman's ρ: -0.456, P = 0.001) and cholesterol levels (Spearman's ρ: -0.383, P = 0.009), decreased with increasing severity of fibrosis. Using transient elastography, a cut-off value of 14.2 kPa predicted the presence of advanced liver fibrosis, but with a low positive predictive value. When we included platelet count, cholesterol, post-Fontan years and transient elastography values as a composite, the capability of predicting advanced liver fibrosis was the most satisfactory (C statistic 0.817 ± 0.071, P < 0.001). A cut-off value of 5.0 revealed a sensitivity of 78% and a specificity of 82%.

In Fontan patients, diffusion-weighted imaging was helpful in detecting liver fibrosis that was correlated with hepatic dysfunction. A simple score was proposed for long-term surveillance and early detection of advanced liver disease in adult Fontan patients. For adult Fontan patients with a calculated score > 5.0, we may consider timely diffusion-weight imaging and early management for liver complications.

Liver histology has prognostic relevance and is used in surveillance and therapeutic strategies. This longitudinal study was designed to evaluate the prognostic relevance of ARFI elastography in comparison to liver histology and to the FIB-4 score in a 5-year observation interval.

Based on the hospital database, patients with an elastography examination of the liver between 2010-2012, a liver biopsy, and a follow-up of 5 years were included in the study. The AUROCs of the events liver-related death, HCC, and liver decompensation/variceal bleeding were calculated for ARFI elastography, liver histology, and FIB-4 and compared using the DeLong test.

In the final analysis 113 patients were included with 30 (26.5 %) patients having high-grade fibrosis and 19 (16.8 %) having liver cirrhosis in histology. The AUROC for liver-related death in the 5-year interval (9.7 %, n=11) was 0.80 [0.68-0.92] for ARFI elastography, 0.79 [0.66-0.92] for liver histology, and 0.66 [0.53-0.79] for FIB-4 with a p-value of 0.83 comparing ARFI to histology and a p-value of 0.02 comparing ARFI to FIB-4. The AUROC for liver decompensation/variceal bleeding (13.3 %, n=15) was 0.86 [0.76-0.94] for ARFI, which is significantly higher than the AUROC of liver histology with 0.71 [0.56-0.86] (p=0.02) and FIB-4 with 0.67 [0.54-0.80] (p=0.003). There was no significant difference for the event HCC when comparing ARFI to histology (p=0.33) or FIB-4 (p=0.14).

The prognostic value of ARFI elastography seems to not be inferior to liver histology regarding liver-related survival and might even outperform histology and the FIB-4 score for predicting some liver-related complications.

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.

Despite good hepatitis B virus (HBV) inhibition by nucleoside analogs (NAs), cases of hepatocellular carcinoma (HCC) still occur. This study proposed a non-invasive predictive model to assess HCC risk in patients with chronic hepatitis B (CHB) receiving NAs treatment. Data were obtained from a hospital-based retrospective cohort registered on the Platform of Medical Data Science Academy of Chongqing Medical University, from 2013 to 2019. A total of 501 patients under NAs treatment had their FIB-4 index updated semiannually by recalculation based on laboratory values. Patients were divided into three groups based on FIB-4 index values: < 1.45, 1.45-3.25, and ≥ 3.25. Subsequently, HCC incidence was reassessed every six months using Kaplan-Meier curves based on the updated FIB-4 index. The median follow-up time of CHB patients after receiving NAs treatment was 2.5 years. HCC incidences with FIB-4 index < 1.45, 1.45-3.25, and ≥ 3.25 were 1.18%, 1.32%, and 9.09%, respectively. Dynamic assessment showed that the percentage of patients with FIB-4 index < 1.45 significantly increased semiannually (P < 0.001), and of patients with FIB-4 index ≥ 3.25 significantly decreased (P < 0.001). HCC incidence was the highest among patients with FIB-4 index ≥ 3.25. The FIB-4 index effectively predicted HCC incidence, and its dynamic assessment could be used for regular surveillance to implement early intervention and reduce HCC risk.

With a drastic increase in the number of chronic hepatitis B (CHB) patients with coexisting nonalcoholic fatty liver disease (NAFLD), there is an urgent need to evaluate antiviral treatment effects in this special population.

CHB patients with hepatic steatosis (CHB + HS) were prospectively recruited with followed-up of 3 years. HS and liver fibrosis were assessed by transient elastography. HS was defined as controlled attenuation parameter (CAP) ≥248 dB/m, and fibrosis progression was defined with ≥1-stage fibrosis increment. Multivariate and propensity score matching (PSM) analysis were used to evaluate antiviral therapy effects on fibrosis progression.

In total 212 recruited CHB + HS patients (median age 36 years, median ALT 59 U/L), 49.1% (104/212) received antiviral therapy and 50.9% (108/212) did not. Among patients with antiviral therapy, rates of serum HBV DNA undetectable, HBeAg and HBsAg loss, and ALT normalization at year 3 were 88.5%, 31.0%, 8.7% and 70.2%, respectively. Patients with mild-moderate HS didn't differ patients with severe HS regarding biochemical and virological responses. Antiviral therapy was independently associated with a lower risk of fibrosis progression among the entire cohort (odds ratio 0.473, 95% CI 0.245-0.911, P = 0.025). This finding was further verified by PSM analysis. When stratified by the severity of HS, the antiviral therapy benefits in reducing fibrosis progression were mainly seen in patients with mild-moderate HS.

Among CHB + HS patients, long-term antiviral treatment effectively inhibits HBV replication and reduces fibrosis progression. Our findings have implications for the optimal management of this population.

This study is to explore the proportion of significant liver histopathology in hepatitis B e antigen (HBeAg)-negative chronic hepatitis B virus (HBV)-infected patients with normal alanine aminotransferase (ALT) and investigate noninvasive indicators for predicting significant liver histopathology. A total of 201 HBeAg-negative chronic HBV-infected patients with normal ALT who underwent liver biopsy were involved in this study. Significant liver histological changes were defined as necroinflammation grade ≥2 (G ≥ 2) and/or fibrosis stage ≥2 (S ≥ 2). The results showed that 42.3% (85/201) and 45.8% (92/201) of the HBeAg-negative patients with normal ALT have significant liver necroinflammation (G ≥ 2) and fibrosis (S ≥ 2), respectively. High normal ALT (>22 U/L), high level of serum HBV DNA (>3.42 log IU/mL), and low level of prealbumin (PA) (<170 mg/L) were independent predictors for significant liver necroinflammation, and the predictive value of the combined indicators was 0.750 (P < 0.001), while high normal ALT (>24 U/L) and high level of FIB-4 (>1.53) were independent predictors for significant liver fibrosis, and the predictive value of the combined indicators was 0.740 (P < 0.001). In conclusion, more than 40% of HBeAg-negative patients with normal ALT have significant liver histopathology and require immediate antiviral treatment. ALT, PA, HBV DNA, and FIB-4 can independently predict significant liver inflammation and fibrosis for HBeAg-negative patients with normal ALT. Lowering the treatment threshold of ALT may benefit the HBeAg-negative chronic HBV-infected patients.

Hepatitis B e antigen (HBeAg)-negative chronic hepatitis B virus (HBV)-infected patients with normal alanine aminotransferase (ALT) were supposed to have a low risk of progression to cirrhosis or hepatocellular carcinoma, and it was recommended to regularly follow up or undergo liver biopsy to assess liver histopathology according to the major international guidelines. However, this study indicates that a considerable number of HBeAg-negative chronic HBV-infected patients with normal ALT have significant liver histopathology and require immediate antiviral treatment. Besides, several clinical commonly used noninvasive indicators were found that can be used to predict significant liver histopathology; thereby liver biopsy might be avoided for HBeAg-negative chronic HBV-infected patients with normal ALT.

Liver disease accounts for approximately 2 million deaths per year worldwide. All chronic liver diseases (CLDs), whether of toxic, genetic, autoimmune, or infectious origin, undergo typical histological changes in the structure of the tissue. These changes may include the accumulation of extracellular matrix material, fats, triglycerides, or tissue scarring. Noninvasive methods for diagnosing CLD, such as conventional B-mode ultrasound (US), play a significant role in diagnosis. Doppler US, when coupled with B-mode US, can be helpful in evaluating the hemodynamics of hepatic vessels and detecting US findings associated with hepatic decompensation. US elastography can assess liver stiffness, serving as a surrogate marker for liver fibrosis. It is important to note that interpreting these values should not rely solely on a histological classification. Contrast-enhanced US (CEUS) provides valuable information on tissue perfusion and enables excellent differentiation between benign and malignant focal liver lesions. Clinical evaluation, the etiology of liver disease, and the patient current comorbidities all influence the interpretation of liver stiffness measurements. These measurements are most clinically relevant when interpreted as a probability of compensated advanced CLD. B-mode US offers a subjective estimation of fatty infiltration and has limited sensitivity for mild steatosis. The controlled attenuation parameter requires a dedicated device, and cutoff values are not clearly defined. Quan-titative US parameters for liver fat estimation include the attenuation coefficient, backscatter coefficient, and speed of sound. These parameters offer the advantage of providing fat quantification alongside B-mode evaluation and other US parameters. Multiparametric US (MPUS) of the liver introduces a new concept for complete noninvasive diagnosis. It encourages examiners to utilize the latest features of an US machine, including conventional B-mode, liver stiffness evaluation, fat quantification, dispersion imaging, Doppler US, and CEUS for focal liver lesion characterization. This comprehensive approach allows for diagnosis in a single examination, providing clinicians worldwide with a broader perspective and becoming a cornerstone in their diagnostic arsenal. MPUS, in the hands of skilled clinicians, becomes an invaluable predictive tool for diagnosing, staging, and monitoring CLD.

Chronic liver disease is highly prevalent and often leads to fibrosis or cirrhosis and complications such as liver failure and hepatocellular carcinoma. The diagnosis and staging of liver fibrosis is crucial to determine management and mitigate complications. Liver biopsy for histologic assessment has limitations such as sampling bias and high interreader variability that reduce precision, which is particularly challenging in longitudinal monitoring. MR elastography (MRE) is considered the most accurate noninvasive technique for diagnosing and staging liver fibrosis. In MRE, low-frequency vibrations are applied to the abdomen, and the propagation of shear waves through the liver is analyzed to measure liver stiffness, a biomarker for the detection and staging of liver fibrosis. As MRE has become more widely used in clinical care and research, different contexts of use have emerged. This review focuses on the latest developments in the use of MRE for the assessment of liver fibrosis; provides guidance for image acquisition and interpretation; summarizes diagnostic performance, along with thresholds for diagnosis and staging of liver fibrosis; discusses current and emerging clinical applications; and describes the latest technical developments.

With the increase in patients at risk of advanced liver disease due to the obesity epidemic, there will be a need for simple screening tools for advanced liver fibrosis. Soluble suppression of tumorigenicity 2 (sST2) is a serum biomarker for fibrotic processes. The aim of this study was to evaluate sST2 as marker for liver fibrosis in patients successfully treated for chronic hepatitis C.

424 patients from the Swiss Hepatitis C Cohort Study were screened for inclusion in this post-hoc cohort study. Inclusion criteria were sustained virological response (SVR), available elastography (VCTE) and serum samples for biomarker analysis before and after treatment. For the validation of sST2, values were compared to VCTE, FIB-4 and APRI using Spearman's correlation and AUROC analyses.

Data of 164 subjects were finally analyzed. Median sST2 values slightly increased with VCTE-derived fibrosis stages and remained stable after reaching SVR within the respective fibrosis stage, suggesting that sST2 is not influenced by liver inflammation. However, correlation of sST2 pre- and post-treatment with VCTE was fair (Spearman's rho = 0.39 and rho = 0.36). The area under the curve (AUROC) for sST2 in detecting VCTE-defined F4 fibrosis (vs. F0-F3) before therapy was 0.74 (95%CI 0.65-0.83), and 0.67(95%CI 0.56-0.78) for the discrimination of F3/F4 fibrosis vs. F0-F2. Adding sST2 to either APRI or FIB-4, respectively, increased diagnostic performance of both tests.

sST2 can potentially identify patients with advanced fibrosis as a single serum marker and in combination with APRI and FIB-4.

Hepatitis C virus (HCV) remains a significant public health problem as it can cause acute and chronic hepatitis. Chronic HCV infection is a major cause of liver fibrosis, and evaluation of liver fibrosis is essential because the prognosis of patients with chronic HCV infection is closely related to the stage of fibrosis. Liver fibrosis is traditionally evaluated based on pathological analysis of biopsy specimens, which is considered the gold standard. Nevertheless, liver biopsy is invasive and susceptible to sampling error and inter- and intraobserver variation in pathological interpretation; it is also costly. Therefore, noninvasive diagnostic investigations have been developed, including the use of fibrotic markers, scoring systems based on routine blood tests, and transient elastography with magnetic resonance imaging or ultrasonography. Recently, metabolomics, an emerging technology, has been used to detect the fibrosis stage. In this editorial, I comment on the article titled "Metabolomics in chronic hepatitis C: Decoding fibrosis grading and underlying pathways" by Ferrasi et al published in the recent issue of the World Journal of Hepatology. I discuss previous studies on the use of metabolome analysis for the diagnosis of HCV-related liver fibrosis and the potential development of biopsy-free diagnostic techniques.

Synaptophysin is expressed on fibrogenic hepatic myofibroblasts. C1-3 is a single chain human antibody (scAb) that binds specifically to synaptophysin on hepatic myofibroblasts, providing a targeting vector for novel in vivo imaging agents of chronic liver disease. C1-3 and a negative control scAb, CSBD9, were radiolabelled with zirconium-89 via desferrioxamine chelation to enable non-invasive molecular imaging with positron emission tomography (PET). DFO-scAb conjugates were characterised by gel electrophoresis (SDS-PAGE) and MALDI-TOF spectrometry, and 89Zr-labelled with high radiolabelling efficiency (99%). [89Zr]Zr-DFO-C1-3 exhibited high in vitro stability (> 99%) in mouse and human sera over 3 days at 25 and 37 °C. Activated hepatic myofibroblasts incubated with [89Zr]Zr-DFO-C1-3 displayed significantly higher internalised activity (59.46%, P = 0.001) compared to the [89Zr]Zr-DFO-CSBD9 control, indicating synaptophysin-mediated uptake and high binding specificity of [89Zr]Zr-DFO-C1-3. Mice with CCl4-induced acute liver damage exhibited significantly higher liver uptake of [89Zr]Zr-DFO-C1-3, compared to controls, confirmed by both Cerenkov imaging and ex vivo gamma counting (4.41 ± 0.19%ID/g, P < 0.0001). CCl4-induced liver damage and the number of hepatic myofibroblasts was confirmed by αSMA staining of liver sections. These findings indicate that [89Zr]Zr-DFO-C1-3 has promising utility as a PET imaging agent for non-invasive detection of hepatic myofibroblasts following acute liver injury.

The gold standard to diagnose fatty liver is pathology. Recently, image-based artificial intelligence (AI) has been found to have high diagnostic performance. We systematically reviewed studies of image-based AI in the diagnosis of fatty liver.

We searched the Cochrane Library, Pubmed, Embase and assessed the quality of included studies by QUADAS-AI. The pooled sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were calculated using a random effects model. Summary receiver operating characteristic curves (SROC) were generated to identify the diagnostic accuracy of AI models.

15 studies were selected in our meta-analysis. Pooled sensitivity and specificity were 92% (95% CI: 90-93%) and 94% (95% CI: 93-96%), PLR and NLR were 12.67 (95% CI: 7.65-20.98) and 0.09 (95% CI: 0.06-0.13), DOR was 182.36 (95% CI: 94.85-350.61). After subgroup analysis by AI algorithm (conventional machine learning/deep learning), region, reference (US, MRI or pathology), imaging techniques (MRI or US) and transfer learning, the model also demonstrated acceptable diagnostic efficacy.

AI has satisfactory performance in the diagnosis of fatty liver by medical imaging. The integration of AI into imaging devices may produce effective diagnostic tools, but more high-quality studies are needed for further evaluation.

Liver biopsy remains the gold standard for the histological assessment of the liver. With clear disadvantages and the rise in the incidences of liver disease, the role of neoadjuvant chemotherapy in colorectal liver metastasis (CRLM) and an explosion of surgical management options available, non-invasive serological and imaging markers of liver histopathology have never been more pertinent in order to assess liver health and stratify patients considered for surgical intervention. Liver MRI is a leading modality in the assessment of hepatic malignancy. Recent technological advancements in multiparametric MRI software such as the LiverMultiScanTM offers an attractive non-invasive assay of anatomy and histopathology in the pre-operative setting, especially in the context of CRLM. This narrative review examines the evidence for the LiverMultiScanTM in the assessment of hepatic fibrosis, steatosis/steatohepatitis, and potential applications for chemotherapy-associated hepatic changes. We postulate its future role and the hurdles it must surpass in order to be implemented in the pre-operative management of patients undergoing hepatic resection for colorectal liver metastasis. Such a role likely extends to other hepatic malignancies planned for resection.

This study evaluated ElastQ, a two-dimensional shear wave elastography (2D-SWE) technique, for the non-invasive assessment of liver fibrosis risk using liver stiffness measurement (LSM). The aim was to determine its diagnostic accuracy and establish LSM cutoffs for clinical risk stratification.

A prospective multicenter study was conducted, employing vibration-controlled transient elastography (VCTE) as a reference standard. The statistical analysis utilized Pearson correlations and Lin concordance correlation coefficients, diagnostic areas under the curve (AUCs), and 90%-specific rule-in and 90%-sensitive rule-out ElastQ cutoffs.

The study included 875 patients at risk for liver disease, of whom 816 (376 women, 46.1%; median age, 57.0 years [interquartile range, 19.0]) had successful and reliable VCTE- and ElastQ-LSMs. The median LSM was 13.0 kPa (range, 2.0 to 75.0 kPa) for VCTE and 6.6 kPa (range, 2.9 to 26.5 kPa) for ElastQ. The correlation between VCTE-LSM and ElastQ-LSM was adequate for VCTE-LSM <15 kPa (Pearson r=0.63) but lower for VCTE-LSM ≥15.0 kPa (Pearson r=0.27). VCTE-LSM indicated no fibrosis risk (<5.0 kPa) in 178 cases (21.8%), gray zone (5.0-9.9 kPa) in 347 cases (42.5%), and advanced chronic liver disease (ACLD; ≥10.0 kPa) in 291 cases (35.7%). The diagnostic AUC for ElastQ-LSM was 0.82 for fibrosis risk and 0.90 for ACLD. The clinically relevant ElastQ cutoffs for ruling out fibrosis risk and ruling in compensated ACLD (cACLD) were <5.0 kPa and ≥9.0 kPa, respectively.

ElastQ 2D-SWE enables accurate, non-invasive assessments of liver fibrosis and cACLD risk. In clinical practice, ElastQ-LSM <5.0 kPa rules out fibrosis, while ElastQ-LSM ≥9.0 kPa rules in cACLD.

Background: Pretreatment and post-treatment performances of noninvasive fibrosis indices were determined in patients with chronic hepatitis B. Method: This was a retrospective, single-center study. Results: The best area under the receiver operating characteristic curve values were detected for aspartate aminotransferase-to-alanine aminotransferase ratio (0.685) for ≥F2, Fibrosis Index (FI; 0.703) for ≥F3; FI (0.872) for ≥F4 and FI (0.864) for cirrhosis. After antiviral treatment, the best area under the receiver operating characteristic curve values were detected in aspartate aminotransferase-to-alanine aminotransferase ratio (0.615) for ≥F2; in FI based on four factors (FIB-4; 0.634) for ≥F3; in FIB-4 (0.678) for ≥F4 and in FIB-4 (0.814) for cirrhosis. Conclusion: FIB-4 and FI showed better performance in defining advanced fibrosis (≥F4) and cirrhosis.

The controlled attenuation parameter (CAP) measurement obtained from FibroScan® is a low-risk method of assessing fatty liver. This study investigated the association between the FibroScan® CAP values and nine anthropometric indicators, including the abdominal volume index (AVI), body fat percentage (BFP), body mass index (BMI), conicity index (CI), ponderal index (PI), relative fat mass (RFM), waist circumference (WC), waist-hip ratio (WHR), and waist-to-height ratio (WHtR), and risk of non-alcoholic fatty liver disease (fatty liver). We analyzed the medical records of adult patients who had FibroScan® CAP results. CAP values <238 dB/m were coded as 0 (non- fatty liver) and ≥238 dB/m as 1 (fatty liver). An individual is considered to have class 1 obesity when their body mass index (BMI) ranges from 30 kg/m2 to 34.9 kg/m2. Class 2 obesity is defined by a BMI ranging from 35 kg/m2 to 39.9 kg/m2, while class 3 obesity is designated by a BMI of 40 kg/m2 or higher. Out of 1763 subjects, 908 (51.5%) had fatty liver. The BMI, WHtR, and PI were found to be more strongly correlated with the CAP by the cluster dendrogram with correlation coefficients of 0.58, 0.54, and 0.54, respectively (all p < 0.0001). We found that 28.3% of the individuals without obesity had fatty liver, and 28.2% of the individuals with obesity did not have fatty liver. The BMI, CI, and PI were significant predictors of fatty liver. The BMI, PI, and WHtR demonstrated better predictive ability, indicated by AUC values of 0.72, 0.68, and 0.68, respectively, a finding that was echoed in our cluster group analysis that showed interconnected clustering with the CAP. Therefore, of the nine anthropometric indicators we studied, the BMI, CI, PI, and WHtR were found to be more effective in predicting the CAP score, i.e., fatty liver.

Abdominal ultrasound is the method of first choice in many clinical situations. Gray scale imaging (B-mode) and conventional Doppler techniques are nowadays complemented by contrast-enhanced ultrasound (CEUS), elastography, fat quantification and further technologies which allow multimodal characterization of organs and tissue structure using panoramic imaging, 3D-techniques and image fusion. The development of small portable devices augments the spectrum for sonographic diagnostics. In this review, we describe the current status of ultrasound technology based on published evidence. In addition, we provide guidance for quality assurance.

Regression of liver fibrosis during antiviral therapy in chronic hepatitis B (CHB) patients has been demonstrated, but data on the influence of long-term treatment with tenofovir disoproxil fumarate (TDF) on liver stiffness (LS) measured by transient elastography are scarce. We aimed to investigate the changes in LS values during the 144-week TDF therapy in treatment-naïve CHB patients.

This prospective observational study was conducted from April 2015 to July 2020 at CHA Bundang Medical Center. Laboratory tests and LS measurements were performed at baseline and repeated at weeks 12, 24, 48, 96, and 144. A significant decline in LS was defined as ≥ 30% decrease in LS value at week 96 from baseline.

A total of 48 treatment-naïve CHB patients initiating TDF therapy were screened, and 36 patients were included in the final analysis (median age, 46 [interquartile range, 34.5-55.8] years; 19 men [52.8%]). During TDF therapy, the median LS values decreased from 13.8 kPa at baseline to 8.7 kPa, 6.5 kPa, and 6.4 kPa at weeks 48, 96, and 144, respectively (all P < 0.001). At week 96, virological and biochemical responses were achieved in 34 (94.4%) patients and 20 (76.9%) patients, respectively. Moreover, 21 of 36 (58.3%) patients showed a significant decline in LS value. A higher baseline LS value was a single independent predictor for the reduction in LS value at week 96 from baseline (P < 0.001).

During the 144-week TDF therapy, LS values declined significantly in treatment-naïve CHB patients.

Hepatic steatosis without specific causes (e.g., viral infection, alcohol abuse, etc.) is called non-alcoholic fatty liver disease (NAFLD), which ranges from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), fibrosis, and NASH-related cirrhosis. Despite the usefulness of the standard grading system, liver biopsy has several limitations. In addition, patient acceptability and intra- and inter-observer reproducibility are also concerns. Due to the prevalence of NAFLD and limitations of liver biopsies, non-invasive imaging methods such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) that can reliably diagnose hepatic steatosis have developed rapidly. US is widely available and radiation-free but cannot examine the entire liver. CT is readily available and helpful for detection and risk classification, significantly when analyzed using artificial intelligence; however, it exposes users to radiation. Although expensive and time-consuming, MRI can measure liver fat percentage with magnetic resonance imaging proton density fat fraction (MRI-PDFF). Specifically, chemical shift-encoded (CSE)-MRI is the best imaging indicator for early liver fat detection. The purpose of this review is to provide an overview of each imaging modality with an emphasis on the recent progress and current status of liver fat quantification.

Transient elastography (TE) has largely replaced liver biopsy to evaluate fibrosis stage and cirrhosis in chronic hepatitis C. Previous studies have reported excellent reliability of TE but agreement metrics have not been reported. This study aimed to assess interrater agreement and reliability of repeated TE measurements.

Two operators performed TE independently, directly after each other. The primary outcome was disagreement, defined as a difference in TE results between operators of ≥33%, as well as the smallest detectable change, SDC95 (i.e., the difference between measurements needed to state with 95% certainty that there is a difference in underlying stiffness). Secondary outcomes included reliability, measured as intraclass correlation (ICC), and patient and examination characteristics associated with the agreement.

In total, 65 patients were included, with a mean liver stiffness of 9.7 kPa. Of these, 21 (32%) had a disagreement in TE results of ≥33% between the two operators. The SDC95 on the log scale was 1.97, indicating that an almost twofold increase or decrease in liver stiffness would be required to confidently represent a change in the underlying fibrosis. Reliability, estimated using the ICC, was acceptable at 0.86. In a post hoc analysis, fasting less than 5 h before TE was associated with a higher degree of disagreement (48% vs. 19%, p = 0.03).

In our clinical setting, interrater agreement in directly repeated TE measurements was surprisingly low. It is essential to further investigate the reliability and agreement of TE to determine its validity and usefulness.

Patients with liver disease can be stratified for risk of liver-related ill health by degree of hepatic fibrosis. The Enhanced liver fibrosis (ELF) test was developed to quantify hepatic fibrosis non-invasively and is widely used. The objective of this review was to identify and synthesise the evidence on the diagnostic accuracy of the ELF test for staging of hepatic fibrosis.

Searches of PubMed and EMBASE were conducted between October 2020 and November 2021 to identify studies reporting the diagnostic accuracy of the ELF test compared to histology in liver disease patients. QUADAS-2 was used to assess risk of bias in each study. Meta-analysis using the multiple thresholds model described by Steinhauser S, Schumacher M, Rücker G. Modelling multiple thresholds in meta-analysis of diagnostic test accuracy studies. BMC Med. Res. Methodol. 2016;16. 10.1186/s12874-016-0196-1 allowed synthesis of 2 × 2 data at different cut-offs. Sixty-three studies were included in this review. These studies included 19,285 patients with or at risk of liver disease from viral hepatitis, Non-Alcoholic Fatty Liver Disease, Alcohol-related Liver Disease and other mixed chronic liver diseases. The prevalence of significant fibrosis, advanced fibrosis and cirrhosis was 47.5%, 39.2% and 4.4%, respectively. Cut-offs with maximal Youden index were generated with AUROC = 0.811 (95% CI: 0.736-0.870), 0.812 (95% CI: 0.758-0.856) and 0.810 (95% CI: 0.694-0.888) to detect significant fibrosis, advanced fibrosis or cirrhosis, respectively. Diagnostic accuracy of the ELF test varied between different liver diseases and cut-offs to detect each stage with 95% sensitivity or specificity were also generated.

Meta-analysis revealed considerable variability in the ability of ELF to stage fibrosis across disease aetiologies. Research has mostly focused on viral hepatitis and NAFLD. There is currently a lack of data on the value of the ELF test in Alcohol-related liver disease and patients in primary care settings.

to evaluate the performance of magnetic resonance elastography (MRE) to stage liver fibrosis in patients with histologically confirmed nonalcoholic fatty liver disease (NAFLD) and to assess the impact of potential confounding factors in MRE diagnostic accuracy. The secondary objective was to compare MRE with other non-invasive methods for staging fibrosis such as transient elastography (TE) and non-invasive scores (APRI and FIB-4).

sixty-five histologically confirmed NAFLD patients were prospectively enrolled at the Hospital Universitario Virgen del Rocío (Seville, Spain). Liver stiffness was measured by MRE, TE and non-invasive scores (APRI and FIB-4). Fibrosis was assessed by liver biopsy using the steatosis, activity and fibrosis (SAF) score. Patients were classified into three groups according to the consistency between MRE and histopathological findings: underestimation, concordance and overestimation groups. Areas under the ROC curve (AUROC) and diagnostic performance were evaluated.

the area under the ROC curve (AUROC) of MRE in advanced fibrosis (≥ F3) was 0.90 (0.82-0.97), while TE AUROC was 0.82 (0.72-0.93) (p = 0.22) and lower for the non-invasive test (FIB-4 0.67 and APRI 0.62). Inflammatory activity, steatosis grade and higher levels of liver biochemistry appeared to overestimate MRE results in the univariate analysis, but only gamma-glutamyl transferase (GGT) was statistically significant in the multivariate analysis (p < 0.01). Age, sex, body mass index (BMI), weight, diabetes mellitus (DM), high blood pressure (HBP), platelets or lipidic profile did not affect MRE accuracy.

MRE is an effective and non-invasive method for detecting and staging liver fibrosis in NAFLD patients. MRE is more accurate than TE and allows the study of liver anatomy. Histological inflammation and surrogate biomarkers of inflammation can overestimate liver stiffness, but only GGT was statistically significant in the multivariate analysis. Important features of NAFLD patients such as obesity, DM, or lipidic profile did not affect MRE accuracy.

We aimed to evaluate the diagnostic accuracy of the measurement of serum type IV collagen 7S (T4C7S) concentration for the staging of liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD).

A systematic search or published works was carried out using the PubMed, Cochrane Library, and Web of Science Core Collection databases for studies of the accuracy of serum T4C7S concentration for the staging of fibrosis using Fibrosis stage (F)0-4 in patients with NAFLD diagnosed by liver biopsy.

Nine articles describing 1475 participants with NAFLD were included. For fibrosis ≥F1, with n = 849, summary estimates of sensitivity of 0.79, specificity of 0.69, and area under the curve (AUC) of 0.80 were obtained using a median T7C4S cut-off value of 4.6 ng/ml. For fibrosis ≥F2, with n = 1,090, summary estimates of sensitivity of 0.78, specificity of 0.78, and AUC of 0.84 were obtained using a median cut-off value of 4.9 ng/ml. For fibrosis ≥F3, with n = 1311 participants and a median cut-off value of 5.4 ng/ml, a pooled sensitivity of 0.82, specificity of 0.81, and AUC of 0.83 were obtained. For fibrosis ≥F4, with n = 753 and a median cut-off value of 6.6 ng/ml, a pooled sensitivity of 0.85, specificity of 0.81, and AUC of 0.85 were obtained.

Serum T4C7S concentration was found to be an accurate method of staging liver fibrosis in patients with NAFLD.

To assess trans-regional differences, reproducibility across different MRI scanners, and interobserver agreement of liver surface nodularity (LSN) score from routine liver MRI and to evaluate the correlation between LSN score and liver stiffness (LS) value on MR elastography.

Ninety patients who underwent gadoxetic acid-enhanced liver MRI twice using different MRI scanners within a year were evaluated. On axial hepatobiliary phase images, right anterior (LSN_{RT_ANT}), right posterior (LSN_{RT_POST}), and left anterior hepatic surface (LSN_LT) were chosen for the quantification of LSN score. Repeated-measures ANOVA, paired t test, Pearson's correlation coefficient analysis, and intraclass correlation coefficient (ICC) were used for statistical analysis.

LSN scores from high to low were LSN_{RT_POST}, LSN_{RT_ANT}, and LSN_LT, representing trans-regional differences (p < 0.001). Reproducibility of LSN measurement across different MRI scanners was high to excellent (ICC = 0.838-0.921). The mean difference between first and second examinations in LSN_{RT_ANT}, LSN_{RT_POST}, and LSN_LT were 0.032 (p = 0.013), 0.002 (p = 0.910), and 0.010 (p = 0.285) for reader 1 and 0.051 (p = 0.004), 0.061 (p = 0.002), and 0.023 (p = 0.005) for reader 2. The first and second examinations were highly correlated in all hepatic regions (r = 0.712-0.839, p < 0.001). There was a low to moderate correlation between LSN score and LS value (r = 0.364-0.592, p ≤ 0.001), which was higher in the chronic hepatitis B (CHB) group than in the non-CHB group in all hepatic regions.

In our study, LSN measurement on liver MRI showed trans-regional differences and excellent reproducibility across different MRI scanners. To use LSN score more widely, standardization of quantification software and selected hepatic regions is needed.

Liver fibrosis plays an important role in the development of hepatocellular carcinoma (HCC) and determining its prognosis. Although many staging systems and liver reserve models have been developed without the intention of predicting prognosis of HCC, some studies have investigated their prognostic values in HCC after curative liver resection (LR). The aim of this study is to evaluate prognostic value of non-invasive biomarkers after curative LR.

Between 2006 and 2013, HCC patients underwent LR were included and total 962 patients were enrolled. All non-invasive biomarkers (fibrosis 4 index (FIB-4), aspartate aminotransferase-to-platelet ratio index (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), AAR-to-platelet ratio index (AARPRI), and albumin-bilirubin (ALBI) score) were measured at the time of HCC diagnosis. To binarize each biomarker, an optimal cut-off value for fibrosis stage was selected using the value of minimum distance from the left-upper corner of the receiver operating characteristic curve with a specificity >60%. We performed Cox regression analysis on 2-year recurrence-free survival (RFS) and overall survival (OS).

The area under curve values for FIB-4 and APRI were the largest for fibrosis stage compared to other biomarkers, 0.669 (95% confidential interval (CI), 0.610-0.719) and 0.748 (95% CI, 0.692-0.800), respectively. Between those two indices, FIB-4 is considered a statistically significant prognostic factor of RFS in HCC patients after LR. The HR for 2-year RFS and OS were 1.81 (95% CI, 1.18-2.77; P = 0.007) and 2.36 (95% CI, 0.99-5.65; P = 0.054), respectively.

FIB-4 is identified as a statistically significant predictor of HCC prognosis after curative LR even in HBV dominant populations.

This study compared two different two-dimensional shear wave elastography techniques-plane wave imaging (PWI) and multi-beam (MB) imaging-from the same vendor to evaluate liver fibrosis.

In this prospective study, 42 patients with chronic liver disease who had recently undergone magnetic resonance elastography (<3 months) were enrolled, and their liver stiffness (LS) values were measured using PWI or MB. The LS values (kPa) were compared using the Wilcoxon rank-sum test. Inter-technique reproducibility and intra-observer repeatability were assessed using Bland-Altman analysis with 95% limits of agreement (LOA) and coefficients of variation (CVs). The cutoff values for predicting severe fibrosis (≥F3) were estimated using receiver operating characteristic curve (ROC) analysis, with magnetic resonance elastography as the reference standard.

PWI exhibited technical failure in four patients. Therefore, 38 patients underwent both examinations. The LS values showed moderate agreement between PWI and MB (CV, 22.5%) and 95% LOA of -3.71 to 7.44 kPa. The MB technique showed good intra-observer agreement (CV, 8.1%), while PWI showed moderate agreement (CV, 11.0%). The cutoff values of PWI and MB for diagnosing ≥F3 were 12.3 kPa and 13.8 kPa, respectively, with areas under the ROC curve of 0.89 and 0.95 (sensitivity, 100% and 100%; specificity, 65.6% and 85.7%).

The LS values significantly differed between PWI and MB, hindering their interchangeable use in longitudinal follow-up. Considering its low technical failure rate and better repeatability, the MB technique may be preferable for evaluating liver fibrosis in chronic liver disease patients.